1. B Scherrer, A Gholipour, S K Warfield. Super-resolution reconstruction to increase the spatial resolution of diffusion weighted images from orthogonal anisotropic acquisitions. Med Image Anal., 2012, in press. [WWW] [doi: 10.1016/j.media.2012.05.003]

    Absstract:
    Diffusion-weighted imaging (DWI) enables non-invasive investigation and characterization of the white matter but suffers from a relatively poor spatial resolution. Increasing the spatial resolution in DWI is challenging with a single-shot EPI acquisition due to the decreased signal-to-noise ratio and T2(*) relaxation effect amplified with increased echo time. In this work we propose a super-resolution reconstruction (SRR) technique based on the acquisition of multiple anisotropic orthogonal DWI scans. DWI scans acquired in different planes are not typically closely aligned due to the geometric distortion introduced by magnetic susceptibility differences in each phase-encoding direction. We compensate each scan for geometric distortion by acquisition of a dual echo gradient echo field map, providing an estimate of the field inhomogeneity. We address the problem of patient motion by aligning the volumes in both space and q-space. The SRR is formulated as a maximum a posteriori problem. It relies on a volume acquisition model which describes how the acquired scans are observations of an unknown high-resolution image which we aim to recover. Our model enables the introduction of image priors that exploit spatial homogeneity and enables regularized solutions. We detail our SRR optimization procedure and report experiments including numerical simulations, synthetic SRR and real world SRR. In particular, we demonstrate that combining distortion compensation and SRR provides better results than acquisition of a single isotropic scan for the same acquisition duration time. Importantly, SRR enables DWI with resolution beyond the scanner hardware limitations. This work provides the first evidence that SRR, which employs conventional single shot EPI techniques, enables resolution enhancement in DWI, and may dramatically impact the role of DWI in both neuroscience and clinical applications.
    [bibtex-key = Scherrer:2012:Med-Image-Anal:22770597]

  2. WW Lewis, M Sahin, B Scherrer, J M Peters, R O Suarez, V K Vogel-Farley, S S Jeste, M C Gregas, S P Prabhu, C A Nelson, S K Warfield. Impaired Language Pathways in Tuberous Sclerosis Complex Patients with Autism Spectrum Disorders. Cereb Cortex. 2012, in press. [WWW] [doi: 10.1093/cercor/bhs135]

    Abstract:
    The purpose of this study was to examine the relationship between language pathways and autism spectrum disorders (ASDs) in patients with tuberous sclerosis complex (TSC). An advanced diffusion-weighted magnetic resonance imaging (MRI) was performed on 42 patients with TSC and 42 age-matched controls. Using a validated automatic method, white matter language pathways were identified and microstructural characteristics were extracted, including fractional anisotropy (FA) and mean diffusivity (MD). Among 42 patients with TSC, 12 had ASD (29%). After controlling for age, TSC patients without ASD had a lower FA than controls in the arcuate fasciculus (AF); TSC patients with ASD had even a smaller FA, lower than the FA for those without ASD. Similarly, TSC patients without ASD had a greater MD than controls in the AF; TSC patients with ASD had even a higher MD, greater than the MD in those without ASD. It remains unclear why some patients with TSC develop ASD, while others have better language and socio-behavioral outcomes. Our results suggest that language pathway microstructure may serve as a marker of the risk of ASD in TSC patients. Impaired microstructure in language pathways of TSC patients may indicate the development of ASD, although prospective studies of language pathway development and ASD diagnosis in TSC remain essential.
    [bibtex-key = Lewis:2012:Cereb-Cortex:22661408]

  3. M J Callahan, M Bittman, R V Mulkern, A Bousvaros, S K Warfield. Characterization of fast and slow diffusion from diffusion-weighted MRI of pediatric Crohn’s disease. Journal of Magnetic Resonance Imaging, 25012, in press. [PDF]

    Abstract:
    Purpose: To characterize fast and slow diffusion components in Diffusion-weighted MRI(DW-MRI) of pediatric Crohn’s disease (CD). Overall diffusivity reduction as measured by the apparent diffusion coefficient (ADC) in patients with CD has been previously demonstrated. However, the ADC reduction may be due to changes in either fast or slow diffusion components. In this study we distinguished between the fast and slow diffusion components in the DW-MRI signal decay of pediatric CD. Materials and Methods: We acquired MRI from 24 patients, including MR enterography (MRE) and DW-MRI with 8 b-values [0-800 s/mm2]. We characterized fast and slow diffusivity by intra-voxel incoherent motion (IVIM) model parameters (f, D*, D), and overall diffusivity by ADC values. We determined which model best described the DW-MRI signal decay. We assessed the influence of the IVIM model parameters on the ADC. We evaluated differences in model parameter values between the enhancing and non-enhancing groups. Results: The IVIM model described the observed data significantly better than the ADC model (p=0.0088). The ADC was correlated with f (r=0.67, p=0.0003), but not with D (r=0.39, p=0.062) and D* (r=-0.39, p=0.057). f values were significantly lower (p<0.003) and D* values were significantly higher (p=0.03) in the enhancing segments, while D values were not significantly different between the groups (p=0.14). Conclusion: For this study population, the IVIM model provides a better description of the DW-MRI signal decay than the ADC model. The reduced ADC is related to changes in the fast diffusion rather than to changes in the slow diffusion.


  4. M Freiman, S D Voss, R V Mulkern, J M Perez-Rossello, M J Callahan, S K Warfield. In-vivo assessment of optimal b-value range for perfusion-insensitive apparent diffusion coefficient imaging. Medical Physics, 39(8):4832-4839, 2012. [WWW] [doi: 10.1118/1.4736516] [PDF]

    Abstract:
    Purpose: To assess the optimal b-values range for perfusion-insensitive apparent diffusion coefficient (ADC) imaging of abdominal organs using short-duration DW-MRI acquisitions with currently available ADC estimation methods. Materials and methods: DW-MRI data of 15 subjects was acquired with 8 b-values in the range of 5-800 s/mm2. The reference-standard, a perfusion insensitive, ADC value (ADCIVIM), was computed using an intra-voxel incoherent motion (IVIM) model with all acquired diffusion-weighted images. Simulated DW-MRI data was generated using an IVIM model with b-values in the range of 0-1,200 s/mm2. Mono-exponential ADC estimates were calculated using: 1) 2-point estimator (ADC2); 2) least squares 3-point (ADC3<) estimator and; 3) Rician noise model estimator (ADCR). We found the optimal b-values for perfusion-insensitive ADC calculations by minimizing the relative root mean square error (RRMS) between the ADCIVIM and the mono-exponential ADC values for each estimation method and organ. Results: Low b-value=300 s/mm2 and high b-value=1,200 s/mm2 minimized the RRMS between the estimated ADC and the reference-standard ADCIVIM to less than 5% using the ADC3 estimator. By considering only the in-vivo DW-MRI data, the combination of low b-value=270 s/mm2 and high b-value of 800 s/mm2 minimized the RRMS between the estimated ADC and the reference-standard ADCIVIM to <7 using the ADC3 estimator. For all estimators, the RRMS between the estimated ADC and the reference standard ADC correlated strongly with the perfusion-fraction parameter of the IVIM model (r=[0.78-0.83], p less than or equal to 0.003). Conclusion: The perfusion compartment in DW-MRI signal decay correlates strongly with the RRMS in ADC estimates from short-duration DW-MRI. The impact of the perfusion compartment on ADC estimations depends, however on the choice of bvalues and estimation method utilized. Likewise, perfusion-related errors can be reduced to <7 by carefully selecting the b-values used for ADC calculations and method of estimation.


  5. D E Hyde, F H Duffy and S K Warfield. Anisotropic partial volume CSF modeling for EEG source localization. Neuroimage. 62(3): 2161-2170, 2012. [WWW] [doi: 10.1016/j.neuroimage.2012.05.055]

    Abstract:
    Electromagnetic source localization (ESL) provides non-invasive evaluation of brain electrical activity for neurology research and clinical evaluation of neurological disorders such as epilepsy. Accurate ESL results are dependent upon the use of patient specific models of bioelectric conductivity. While the effects of anisotropic conductivities in the skull and white matter have been previously studied, little attention has been paid to the accurate modeling of the highly conductive cerebrospinal fluid (CSF) region. This study examines the effect that partial volume errors in CSF segmentations have upon the ESL bioelectric model. These errors arise when segmenting sulcal channels whose widths are similar to the resolution of the magnetic resonance (MR) images used for segmentation, as some voxels containing both CSF and gray matter cannot be definitively assigned a single label. These problems, particularly prevalent in pediatric populations, make voxelwise segmentation of CSF compartments a difficult problem. Given the high conductivity of CSF, errors in modeling this region may result in large errors in the bioelectric model. We introduce here a new approach for using estimates of partial volume fractions in the construction of patient specific bioelectric models. In regions where partial volume errors are expected, we use a layered gray matter-CSF model to construct equivalent anisotropic conductivity tensors. This allows us to account for the inhomogeneity of the tissue within each voxel. Using this approach, we are able to reduce the error in the resulting bioelectric models, as evaluated against a known high resolution model. Additionally, this model permits us to evaluate the effects of sulci modeling errors and quantify the mean error as a function of the change in sulci width. Our results suggest that both under and over-estimation of the CSF region leads to significant errors in the bioelectric model. While a model with fixed partial volume fraction is able to reduce this error, we see the largest improvement when using voxel specific partial volume estimates. Our cross-model analyses suggest that an approximately linear relationship exists between sulci error and the error in the resulting bioelectric model. Given the difficulty of accurately segmenting narrow sulcal channels, this suggests that our approach may be capable of improving the accuracy of patient specific bioelectric models by several percent, while introducing only minimal additional computational requirements.
    [bibtex-key = Hyde:2012:Neuroimage:22652021]

  6. M Freiman, S D Voss, R V Mulkern, J M Perez-Rossello, M J Callahan, S K Warfield. Reliable assessment of perfusivity and diffusivity from diffusion imaging of the body. Med Image Comput Comput Assist Interv., 2012, in press. [PDF]
    Abstract:
    Diffusion-weighted MRI of the body has the potential to provide important new insights into physiological and microstructural properties. The Intra-Voxel Incoherent Motion (IVIM) model relates the observed DW-MRI signal decay to parameters that reflect perfusivity(D*) and its volume fraction (f), and diffusivity (D). However, the commonly used voxel-wise fitting of the IVIM model leads to parameter estimates with poor precision, which has hampered their practical usage. In this work, we increase the estimates’ precision by introducing a model of spatial homogeneity, through which we obtain estimates of model parameters for all of the voxels at once, instead of solving for each voxel independently. Furthermore, we introduce an efficient iterative solver which utilizes a model-based bootstrap estimate of the distribution of residuals and a binary graph cut to generate optimal model parameter updates. Simulation experiments show that our approach reduces the relative root mean square error of the estimated parameters by 80% for the D* parameter and by 50% for the f and D parameters. We demonstrated the clinical impact of our model in distinguishing between enhancing and nonenhancing ileum segments in 24 Crohn’s disease patients. Our model detected the enhanced segments with 91%/92% sensitivity/specificity which is better than the 81%/85% obtained by the voxel-independent approach.


  7. O Commowick, A Akhondi-Asl, S K Warfield. Estimating A Reference Standard Segmentation with Spatially Varying Performance Parameters: Local MAP STAPLE. IEEE Trans Med Imaging, 2012, in press. [PDF]
    Abstract:
    We present a new algorithm, called local MAP STAPLE, to estimate from a set of multi-label segmentations both a reference standard segmentation and spatially varying performance parameters. It is based on a sliding window technique to estimate the segmentation and the segmentation performance parameters for each input segmentation. In order to allow for optimal fusion from the small amount of data in each local region and to account for the possibility of labels not being observed in a local region of some (or all) input segmentations, we introduce prior probabilities for the local performance parameters through a new Maximum A Posteriori formulation of STAPLE. Further, we propose an expression to compute confidence intervals in the estimated local performance parameters.


  8. A Gholipour, A Akhondi-Asl, J A Estroff, S K Warfield. Multi-atlas multi-shape segmentation of fetal brain MRI for volumetric and morphometric analysis of ventriculomegaly. Neuroimage, 60(3):1819-31, 2012. [WWW] [doi: 10.1016/j.neuroimage.2012.01.128]
    Abstract:
    The recent development of motion robust super-resolution fetal brain MRI holds out the potential for dramatic new advances in volumetric and morphometric analysis. Volumetric analysis based on volumetric and morphometric biomarkers of the developing fetal brain must include segmentation. Automatic segmentation of fetal brain MRI is challenging, however, due to the highly variable size and shape of the developing brain; possible structural abnormalities; and the relatively poor resolution of fetal MRI scans. To overcome these limitations, we present a novel, constrained, multi-atlas, multi-shape automatic segmentation method that specifically addresses the challenge of segmenting multiple structures with similar intensity values in subjects with strong anatomic variability. Accordingly, we have applied this method to shape segmentation of normal, dilated, or fused lateral ventricles for quantitative analysis of ventriculomegaly (VM), which is a pivotal finding in the earliest stages of fetal brain development, and warrants further investigation. Utilizing these innovative techniques, we introduce novel volumetric and morphometric biomarkers of VM comparing these values to those that are generated by standard methods of VM analysis, i.e., by measuring the ventricular atrial diameter (AD) on manually selected sections of 2D ultrasound or 2D MRI. To this end, we studied 25 normal and abnormal fetuses in the gestation age (GA) range of 19 to 39weeks (mean=28.26, stdev=6.56). This heterogenous dataset was essentially used to 1) validate our segmentation method for normal and abnormal ventricles; and 2) show that the proposed biomarkers may provide improved detection of VM as compared to the AD measurement.
    [bibtex-key = Gholipour:2012:Neuroimage:22500924]

  9. H Als, F H Duffy, G McAnulty, S C Butler, L Lightbody, S Kosta, N I Weisenfeld, R Robertson, R B Parad, S A Ringer, J G Blickman, D Zurakowski, S K Warfield. NIDCAP improves brain function and structure in preterm infants with severe intrauterine growth restriction. J Perinatol., 2012, in press. [WWW] [doi: 10.1038/jp.2011.201] [PDF]
    Abstract:
    Objective:The effect of NIDCAP (Newborn Individualized Developmental Care and Assessment Program) was examined on the neurobehavioral, electrophysiological and neurostructural development of preterm infants with severe intrauterine growth restriction (IUGR).Study Design:A total of 30 infants, 27-33 weeks gestation, were randomized to control (C; N=17) or NIDCAP/experimental (E; N=13) care. Baseline health and demographics were assessed at intake; electroencephalography (EEG) and magnetic resonance imaging (MRI) at 35 and 42?weeks postmenstrual age; and health, growth and neurobehavior at 42 weeks and 9 months corrected age (9 months).Results:C and E infants were comparable in health and demographics at baseline. At follow-up, E infants were healthier, showed significantly improved brain development and better neurobehavior. Neurobehavior, EEG and MRI discriminated between C and E infants. Neurobehavior at 42 weeks correlated with EEG and MRI at 42 weeks and neurobehavior at 9 months.Conclusion:NIDCAP significantly improved IUGR preterm infants' neurobehavior, electrophysiology and brain structure. Longer-term outcome assessment and larger samples are recommended.
    [bibtex-key = Als:2012:J-Perinatol:22301525]

  10. L M Vigneron, L Noels, S K Warfield, J G Verly, P A Robe. Serial FEM/XFEM-Based Update of Preoperative Brain Images Using Intraoperative MRI. Int J Biomed Imaging. 2012:872783, 2012. [WWW] [doi: 10.1155/2012/872783] [PDF]
    Abstract:
    Current neuronavigation systems cannot adapt to changing intraoperative conditions over time. To overcome this limitation, we present an experimental end-to-end system capable of updating 3D preoperative images in the presence of brain shift and successive resections. The heart of our system is a nonrigid registration technique using a biomechanical model, driven by the deformations of key surfaces tracked in successive intraoperative images. The biomechanical model is deformed using FEM or XFEM, depending on the type of deformation under consideration, namely, brain shift or resection. We describe the operation of our system on two patient cases, each comprising five intraoperative MR images, and we demonstrate that our approach significantly improves the alignment of nonrigidly registered images.
    [bibtex-key = Vigneron:2012:Int-J-Biomed-Imaging:22287953]

  11. D K Thompson, Z M Ahmadzai, S J Wood, T E Inder, S K Warfield, L W Doyle, G F Egan. Optimizing Hippocampal Segmentation in Infants Utilizing MRI Post-Acquisition Processing. Neuroinformatics, 10(2):173-80, 2012. [WWW] [doi: 10.1007/s12021-011-9137-7]
    Abstract:
    This study aims to determine the most reliable method for infant hippocampal segmentation by comparing magnetic resonance (MR) imaging post-acquisition processing techniques: contrast to noise ratio (CNR) enhancement, or reformatting to standard orientation. MR scans were performed with a 1.5 T GE scanner to obtain dual echo T2 and proton density (PD) images at term equivalent (38-42 weeks' gestational age). 15 hippocampi were manually traced four times on ten infant images by 2 independent raters on the original T2 image, as well as images processed by: a) combining T2 and PD images (T2-PD) to enhance CNR; then b) reformatting T2-PD images perpendicular to the long axis of the left hippocampus. CNRs and intraclass correlation coefficients (ICC) were calculated. T2-PD images had 17% higher CNR (15.2) than T2 images (12.6). Original T2 volumes' ICC was 0.87 for rater 1 and 0.84 for rater 2, whereas T2-PD images' ICC was 0.95 for rater 1 and 0.87 for rater 2. Reliability of hippocampal segmentation on T2-PD images was not improved by reformatting images (rater 1 ICC?=?0.88, rater 2 ICC?=?0.66). Post-acquisition processing can improve CNR and hence reliability of hippocampal segmentation in neonate MR scans when tissue contrast is poor. These findings may be applied to enhance boundary definition in infant segmentation for various brain structures or in any volumetric study where image contrast is sub-optimal, enabling hippocampal structure-function relationships to be explored.
    [bibtex-key = Thompson:2011:Neuroinformatics:22194186]

  12. D K Thompson, T E Inder, N Faggian, S K Warfield, P J Anderson, L W Doyle, G F Egan. Corpus callosum alterations in very preterm infants: Perinatal correlates and 2-year neurodevelopmental outcomes. Neuroimage, 59(4):3571-81, 2012. [WWW] [doi: 10.1016/j.neuroimage.2011.11.057]
    Abstract:
    The aim of this study was to relate altered corpus callosum (CC) integrity in 106 very preterm (VPT) infants (<30weeks' gestational age or <1250g birth weight) at term equivalent to perinatal predictors and neurodevelopmental outcomes at two years. T1 and diffusion magnetic resonance images were obtained. The CC was traced, and divided into six sub-regions for cross-sectional area and shape analyses. Fractional anisotropy, mean, axial and radial diffusivity were sampled within the CC, and probabilistic tractography was performed. Perinatal predictors were explored. The Bayley Scales of Infant Development (BSID-II) was administered at two years. Intraventricular hemorrhage was associated with a smaller genu and altered diffusion values within the anterior and posterior CC of VPT infants. White matter injury was associated with widespread alterations to callosal diffusion values, especially posteriorly, and radial diffusivity was particularly elevated, indicating altered myelination. Reduced CC tract volume related to lower gestational age, particularly posteriorly. Reduced posterior callosal skew was associated with postnatal corticosteroid exposure. This more circular CC was associated with delayed cognitive development. Higher diffusivity, particularly in splenium tracts, was associated with impaired motor development. This study elucidates perinatal predictors and adverse neurodevelopmental outcomes associated with altered callosal integrity in VPT infants.
    [bibtex-key = Thompson:2011:Neuroimage:22154956]

  13. R O Suarez, O Commowick, S P Prabhu, S K Warfield. Automated delineation of white matter fiber tracts with a multiple region-of-interest approach. Neuroimage, 59(4):3690-700, 2012. [WWW] [doi: 10.1016/j.neuroimage.2011.11.043] [PDF]
    Abstract:
    White matter fiber bundles of the brain can be delineated by tractography utilizing multiple regions-of-interest (MROI) defined by anatomical landmarks. These MROI can be used to specify regions in which to seed, select, or reject tractography fibers. Manual identification of anatomical MROI enables the delineation of white matter fiber bundles, but requires considerable training to develop expertise, considerable time to carry out and suffers from unwanted inter- and intra-rater variability. In a study of 20 healthy volunteers, we compared three methodologies for automated delineation of the white matter fiber bundles. Using these methodologies, fiber bundle MROI for each volunteer was automatically generated. We assessed three strategies for inferring the automatic MROI utilizing nonrigid alignment of reference images and projection of template MROI. We assessed the bundle delineation error associated with alignment utilizing T1-weighted MRI, fractional anisotropy images, and full tensor images. We confirmed the smallest delineation error was achieved using the full tensor images. We then assessed three projection strategies for automatic determination of MROI in each volunteer. Quantitative comparisons were made using the root-mean-squared error observed between streamline density images constructed from fiber bundles identified automatically and by manually drawn MROI in the same subjects. We demonstrate that a multiple template consensus label fusion algorithm generated fiber bundles most consistent with the manual reference standard.
    [bibtex-key = Suarez:2011:Neuroimage:22155046]

  14. J M Peters, M Sahin, V K Vogel-Farley, S S Jeste, C A Nelson 3rd, M C Gregas, S P Prabhu, B Scherrer, S K Warfield. Loss of white matter microstructural integrity is associated with adverse neurological outcome in tuberous sclerosis complex. Acad Radiol. 19(1):17-25, 2012. [WWW] [doi: 10.1016/j.acra.2011.08.016] [PDF]
    Abstract:
    Tuberous sclerosis complex (TSC) is a genetic neurocutaneous syndrome in which cognitive and social-behavioral outcomes for patients vary widely in an unpredictable manner. The cause of adverse neurologic outcome remains unclear. The aim of this study was to investigate the hypothesis that disordered white matter and abnormal neural connectivity are associated with adverse neurologic outcomes.Structural and diffusion magnetic resonance imaging was carried out in 40 subjects with TSC (age range, 0.5-25 years; mean age, 7.2 years; median age, 5 years), 12 of whom had autism spectrum disorders (ASD), and in 29 age-matched controls. Tractography of the corpus callosum was used to define a three-dimensional volume of interest. Regional averages of four diffusion scalar parameters of the callosal projections were calculated for each subject. These were the average fractional anisotropy (AFA) and the average mean, radial, and axial diffusivity.Subjects with TSC had significantly lower AFA and higher average mean, radial, and axial diffusivity values compared to controls. Subjects with TSC and ASD had significantly lower AFA values compared to those without ASD and compared to controls. Subjects with TSC without ASD had similar AFA values compared to controls.Diffusion tensor scalar parameters provided measures of properties of the three-dimensional callosal projections. In TSC, changes in these parameters may reflect microstructural changes in myelination, axonal integrity, or extracellular environment. Alterations in white matter microstructural properties were associated with TSC, and larger changes were associated with TSC and ASD, thus establishing a relationship between altered white matter microstructural integrity and brain function.
    [bibtex-key = Peters:2012:Acad-Radiol:22142677]

  15. C Clouchoux, D Kudelski, A Gholipour, S K Warfield, S Viseur, M Bouyssi-Kobar, J L Mari, A C Evans, A J du Plessis, C Limperopoulos. Quantitative in vivo MRI measurement of cortical development in the fetus. Brain Struct Funct., 217(1):127-39, 2012. [WWW] [doi: 10.1007/s00429-011-0325-x]
    Abstract:
    Normal brain development is associated with expansion and folding of the cerebral cortex following a highly orchestrated sequence of gyral-sulcal formation. Although several studies have described the evolution of cerebral cortical development ex vivo or ex utero, to date, very few studies have characterized and quantified the gyrification process for the in vivo fetal brain. Recent advances in fetal magnetic resonance imaging and post-processing computational methods are providing new insights into fetal brain maturation in vivo. In this study, we investigate the in vivo fetal cortical folding pattern in healthy fetuses between 25 and 35?weeks gestational age using 3-D reconstructed fetal cortical surfaces. We describe the in vivo fetal gyrification process using a robust feature extraction algorithm applied directly on the cortical surface, providing an explicit delineation of the sulcal pattern during fetal brain development. We also delineate cortical surface measures, including surface area and gyrification index. Our data support an exuberant third trimester gyrification process and suggest a non-linear evolution of sulcal development. The availability of normative indices of cerebral cortical developing in the living fetus may provide critical insights on the timing and progression of impaired cerebral development in the high-risk fetus.
    [bibtex-key = Clouchoux:2011:Brain-Struct-Funct:215629]

  16. P Wintermark, A Hansen, M C Gregas, J Soul, M Labrecque, R L Robertson, S K Warfield. Brain perfusion in asphyxiated newborns treated with therapeutic hypothermia. AJNR Am J Neuroradiol. 32(11):2023-9, 2011. [WWW] [doi: 10.3174/ajnr.A2708]
    Abstract:
    Induced hypothermia is thought to work partly by mitigating reperfusion injury in asphyxiated term neonates. The purpose of this study was to assess brain perfusion in the first week of life in these neonates.In this prospective cohort study, MR imaging and ASL-PI were used to assess brain perfusion in these neonates. We measured regional CBF values on 1-2 MR images obtained during the first week of life and compared these with values obtained in control term neonates. The same or later MR imaging scans were obtained to define the extent of brain injury.Eighteen asphyxiated and 4 control term neonates were enrolled; 11 asphyxiated neonates were treated with hypothermia. Those developing brain injury despite being treated with induced hypothermia usually displayed hypoperfusion on DOL 1 and then hyperperfusion on DOL 2-3 in brain areas subsequently exhibiting injury. Asphyxiated neonates not treated with hypothermia who developed brain injury also displayed hyperperfusion on DOL 1-6 in brain areas displaying injury.Our data show that ASL-PI may be useful for identifying asphyxiated neonates at risk of developing brain injury, whether or not hypothermia is administered. Because hypothermia for 72 hours may not prevent brain injury when hyperperfusion is found early in the course of neonatal hypoxic-ischemic encephalopathy, such neonates may be candidates for adjustments in their hypothermia therapy or for adjunctive neuroprotective therapies.
    [bibtex-key = Wintermark:2011:AJNR-Am-J-Neuroradiol:21979494]

  17. L M Vigneron, S K Warfield, P A Robe, J G Verly. 3D XFEM-based modeling of retraction for preoperative image update. Comput Aided Surg., 16(3):121-34, 2011. [WWW] [doi: 10.3109/10929088.2011.570090]
    Abstract:
    Outcomes for neurosurgery patients can be improved by enhancing intraoperative navigation and guidance. Current navigation systems do not accurately account for intraoperative brain deformation. So far, most studies of brain deformation have focused on brain shift, whereas this paper focuses on the brain deformation due to retraction. The heart of our system is a 3D nonrigid registration technique using a biomechanical model driven by the deformations of key surfaces tracked between two intraoperative images. The key surfaces, e.g., the whole-brain region boundary and the lips of the retraction cut, thus deform due to the combination of gravity and retractor deployment. The tissue discontinuity due to retraction is handled via the eXtended Finite Element Method (XFEM), which has the appealing feature of being able to handle arbitrarily shaped discontinuity without any remeshing. Our approach is shown to significantly improve the alignment of intraoperative MRI.
    [bibtex-key = Vigneron:2011:Comput-Aided-Surg:21476788]

  18. A Akselrod-Ballin, D Bock, R C Reid, S K Warfield. Accelerating image registration with the johnson-lindenstrauss lemma: application to imaging 3-d neural ultrastructure with electron microscopy. IEEE Trans Med Imaging, 30(7): 1427-38, 2011. [WWW] [doi: 10.1109/TMI.2011.2125797] [PDF]
    Abstract:
    We present a novel algorithm to accelerate feature based registration, and demonstrate the utility of the algorithm for the alignment of large transmission electron microscopy (TEM) images to create 3-D images of neural ultrastructure. In contrast to the most similar algorithms, which achieve small computation times by truncated search, our algorithm uses a novel randomized projection to accelerate feature comparison and to enable global search. Further, we demonstrate robust estimation of nonrigid transformations with a novel probabilistic correspondence framework, that enables large TEM images to be rapidly brought into alignment, removing characteristic distortions of the tissue fixation and imaging process. We analyze the impact of randomized projections upon correspondence detection, and upon transformation accuracy, and demonstrate that accuracy is maintained. We provide experimental results that demonstrate significant reduction in computation time and successful alignment of TEM images.
    [bibtex-key = AkselrodBallin:2011:IEEE-Trans-Med-Imaging:21402511]

  19. N I Weisenfeld and S K Warfield. Learning Likelihoods for Labeling (L3): A General Multi-Classifier Segmentation Algorithm. Med Image Comput Comput Assist Interv., 14(Pt 3):322-329, 2011. [PDF] [WWW]
    Abstract:
    PURPOSE: To develop an MRI segmentation method for brain tissues, regions, and substructures that yields improved classification accuracy. Current brain segmentation strategies include two complementary strategies. Multi-spectral classification techniques generate excellent segmentations for tissues with clear intensity contrast, but fail to identify structures defined largely by location, such as lobar parcellations and certain subcortical structures. Conversely, multi-template label fusion methods are excellent for structures defined largely by location, but perform poorly when segmenting structures that cannot be accurately identified through a consensus of registered templates. METHODS: We propose here a novel multi-classifier fusion algorithm with the advantages of both types of segmentation strategy. We illustrate and validate this algorithm using a group of 14 expertly hand-labeled images. RESULTS: Our method generated segmentations of cortical and subcortical structures that were more similar to hand-drawn segmentations than majority vote label fusion or a recently published intensity/label fusion method. CONCLUSIONS: We have presented a novel, general segmentation algorithm with the advantages of both statistical classifiers and label fusion techniques.


  20. M Freiman, S D Voss, R V Mulkern, J M Perez-Rossello and S K Warfield. Quantitative Body DW-MRI Biomarkers Uncertainty Estimation Using Unscented Wild-Bootstrap. Med Image Comput Comput Assist Interv., 14(Pt 2):74-81, 2011. [WWW] [PDF]
    Abstract:
    We present a new method for the uncertainty estimation of diffusion parameters for quantitative body DW-MRI assessment. Diffusion parameters uncertainty estimation from DW-MRI is necessary for clinical applications that use these parameters to assess pathology. However, uncertainty estimation using traditional techniques requires repeated acquisitions, which is undesirable in routine clinical use. Model-based bootstrap techniques, for example, assume an underlying linear model for residuals rescaling and cannot be utilized directly for body diffusion parameters uncertainty estimation due to the non-linearity of the body diffusion model. To offset this limitation, our method uses the Unscented transform to compute the residuals rescaling parameters from the non-linear body diffusion model, and then applies the wildbootstrap method to infer the body diffusion parameters uncertainty. Validation through phantom and human subject experiments shows that our method identify the regions with higher uncertainty in body DWI-MRI model parameters correctly with realtive error of ~36% in the uncertainty values.


  21. B Scherrer and S K Warfield. Super resolution in diffusion-weighted imaging. Med Image Comput Comput Assist Interv., 14(Pt 2):124-132, 2011. [WWW] [PDF]
    Abstract:
    Diffusion-weighted imaging (DWI) enables non-invasive investigation and characterization of the white-matter but suffers from a relatively poor resolution. In this work we propose a super-resolution reconstruction (SRR) technique based on the acquisition of multiple anisotropic orthogonal DWI scans. We address the problem of patient motions by aligning the volumes both in space and in q-space. The SRR is formulated as a maximum a posteriori (MAP) problem. It relies on a volume acquisition model which describes the generation of the acquired scans from the unknown high-resolution image. It enables the introduction of image priors that exploit spatial homogeneity and enables regularized solutions. We detail our resulting SRR optimization procedure and report various experiments including numerical simulations, synthetic SRR scenario and real world SRR scenario. Super-resolution reconstruction in DWI may enable DWI to be performed with unprecedented resolution.


  22. M Taquet, B Macq and S K Warfield. Spatially adaptive log-Euclidean polyaffine registration based on sparse matches. Med Image Comput Comput Assist Interv., 14(Pt 2):590-597, 2011. [WWW] [PDF]
    Abstract:
    Log-euclidean polyane transforms have recently been introduced to characterize the local ane behavior of the deformation in principal anatomical structures. The elegant mathematical framework makes them a powerful tool for image registration. However, their application is limited to large structures since they require the pre-definition of affine regions. This paper extends the polyaffine registration to adaptively fit a log-euclidean polyaffine transform that captures deformations at smaller scales. The approach is based on the sparse selection of matching points in the images and the formulation of the problem as an expectationmaximization iterative closest point problem. The efficiency of the algorithm is shown through experiments on inter-subject registration of brain MRI between a healthy subject and patients with multiple sclerosis.


  23. A Gholipour, M Polak, A van der Kouwe, E Nevo, S K Warfield. Motion-robust MRI through real-time motion tracking and retrospective super-resolution volume reconstruction. Conf Proc IEEE Eng Med Biol Soc., 2011:5722-5, 2011. [WWW] [doi: 10.1109/IEMBS.2011.6091385] [PDF]
    Abstract:
    Magnetic Resonance Imaging (MRI) is highly sensitive to motion; hence current practice is based on the prevention of motion during scan. In newborns, young children, and patients with limited cooperation, this commonly requires full sedation or general anesthesia, which is time consuming, costly, and is associated with significant risks. Despite progress in prospective motion correction in MRI, the use of motion compensation techniques is limited by the type and amount of motion that can be compensated for, the dependency on the scanner platform, the need for pulse sequence modifications, and/or difficult setup. In this paper we introduce a novel platform-independent motion-robust MRI technique based on prospective real-time motion tracking through a miniature magnetic field sensor and retrospective super-resolution volume reconstruction. The technique is based on fast 2D scans that maintain high-quality of slices in the presence of motion but are degraded in 3D due to inter-slice motion artifacts. The sensor, conveniently attached to the subject forehead, provides real-time estimation of the motion, which in turn gives the relative location of the slice acquisitions. These location parameters are used to compensate the inter-slice motion to reconstruct an isotropic high-resolution volumetric image from slices in a super-resolution reconstruction framework. The quantitative results obtained for phantom and volunteer subject experiments in this study show the efficacy of the developed technique, which is particularly useful for motion-robust high-resolution T2-weighted imaging of newborns and pediatric subjects.
    [bibtex-key = Gholipour:2011:Conf-Proc-IEEE-Eng-Med-Biol-Soc:22255639]

  24. A Gholipour, N Kehtarnavaz, B Scherrer, S K Warfield. On the accuracy of unwarping techniques for the correction of susceptibility-induced geometric distortion in magnetic resonance Echo-planar images. Conf Proc IEEE Eng Med Biol Soc., 2011:6997-7000, 2011. [WWW] [doi: 10.1109/IEMBS.2011.6091769] [PDF]
    Abstract:
    Rapid and efficient imaging of the brain to monitor brain activity and neural connectivity is performed through functional MRI and diffusion tensor imaging (DTI) using the Echo-planar imaging (EPI) sequence. An entire volume of the brain is imaged by EPI in a few seconds through the measurement of all k-space lines within one repetition time. However, this makes the sequence extremely sensitive to imperfections of magnetic field. In particular, the error caused by susceptibility induced magnetic field inhomogeneity accumulates over the duration of phase encoding, which in turn results in severe geometric distortion (warping) in EPI scans. EPI distortion correction through unwarping can be performed by field map based or image based techniques. However, due to the lack of ground truth it has been difficult to compare and validate different approaches. In this paper we propose a hybrid field map guided constrained deformable registration approach and compare it to field map based and image based unwarping approaches through a novel in-vivo validation framework which is based on the acquisition and alignment of EPI scans with different phase encoding directions. The quantitative evaluation results show that our hybrid approach of field map guided deformable registration to an undistorted T2-weighted image outperforms the other approaches.
    [bibtex-key = Gholipour:2011:Conf-Proc-IEEE-Eng-Med-Biol-Soc:22255949]

  25. A Gholipour, J A Estroff, C E Barnewolt, S A Connolly, S K Warfield. Fetal brain volumetry through MRI volumetric reconstruction and segmentation. Int J Computer Assisted Radiology and Surgery, 6(3): 329-39, 2011. [WWW] [doi: 10.1007/s11548-010-0512-x] [PDF]
    Abstract:
    Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested.The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation.Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses.The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation.
    [bibtex-key = Gholipour:2011:Int-J-Comput-Assist-Radiol-Surg:20625848]

  26. D K Thompson, T E Inder, N Faggian, L Johnston, S K Warfield, P J Anderson, L W Doyle, G F Egan. Characterization of the corpus callosum in very preterm and full-term infants utilizing MRI. Neuroimage, 15; 55(2): 479-90 2011. [WWW] [doi: 10.1016/j.neuroimage.2010.12.025]
    Abstract:
    The corpus callosum is the largest white matter tract, important for interhemispheric communication. The aim of this study was to investigate and compare corpus callosum size, shape and diffusion characteristics in 106 very preterm infants and 22 full-term infants. Structural and diffusion magnetic resonance images were obtained at term equivalent. The corpus callosum was segmented, cross-sectional areas were calculated, and shape was analyzed. Fractional anisotropy, mean, axial and radial diffusivity measures were obtained from within the corpus callosum, with additional probabilistic tractography analysis. Very preterm infants had significantly reduced callosal cross-sectional area compared with term infants (p=0.004), particularly for the mid-body and posterior sub-regions. Very preterm callosi were more circular (p=0.01). Fractional anisotropy was lower (p=0.007) and mean (p=0.006) and radial (p=0.001) diffusivity values were higher in very preterm infants' callosi, particularly at the anterior and posterior ends. The volume of tracts originating from the corpus callosum was reduced in very preterm infants (p=0.001), particularly for anterior mid-body (p=0.01) and isthmus tracts (p=0.04). This study characterizes callosal size, shape and diffusion in typically developing infants at term equivalent age, and reports macrostructural and microstructural abnormalities as a result of prematurity.
    [bibtex-key = Thompson:2011:Neuroimage:21168519]

  27. L Hoyte, W Ye, L Brubaker, J R Fielding, M E Lockhart, M E Heilbrun, M B Brown, S K Warfield, Pelvic Floor Disorders Network. Segmentations of MRI images of the female pelvic floor: a study of inter- and intra-reader reliability. J Magn Reson Imaging, 33(3): 684-91, 2011. [WWW] [doi: 10.1002/jmri.22478]
    Abstract:
    To describe the inter- and intra-operator reliability of segmentations of female pelvic floor structures.Three segmentation specialists were asked to segment out the female pelvic structures in 20 MR datasets on three separate occasions. The STAPLE algorithm was used to compute inter- and intra-segmenter agreement of each organ in each dataset. STAPLE computed the sensitivity, specificity, and positive predictive values (PPV) for inter- and intra-segmenter repeatability. These parameters were analyzed using intra-class correlation analysis. Correlation of organ volume to PPV and sensitivity was also computed.Mean PPV of the segmented organs ranged from 0.82 to 0.99, and sensitivity ranged from 33 to 96%. Intra-class correlation ranged from 0.07 to 0.98 across segmenters. Pearson correlation of volume to sensitivity were significant across organs, ranging from 0.54 to 0.91. Organs with significant correlation of PPV to volume were bladder (-0.69), levator ani (-0.68), and coccyx (-0.63).Undirected manual segmentation of the pelvic floor organs are adequate for locating the organs, but poor at defining structural boundaries.
    [bibtex-key = Hoyte:2011:J-Magn-Reson-Imaging:21563253]

  28. P Wintermark, A Hansen, J Soul, M Labrecque, R L Robertson, S K Warfield. Early versus late MRI in asphyxiated newborns treated with hypothermia. Arch Dis Child Fetal Neonatal Ed., 96(1): F36-44 2011. [WWW] [doi: 10.1136/adc.2010.184291]
    Abstract:
    The purposes of this feasibility study were to assess: (1) the potential utility of early brain MRI in asphyxiated newborns treated with hypothermia; (2) whether early MRI predicts later brain injury observed in these newborns after hypothermia has been completed; and (3) whether early MRI indicators of brain injury in these newborns represent reversible changes.All consecutive asphyxiated term newborns meeting the criteria for therapeutic hypothermia were enrolled prospectively. Each newborn underwent one or two early MRI scans while receiving hypothermia, on day of life (DOL) 1 and DOL 2-3 and also one or two late MRI scans on DOL 8-13 and at 1 month of age.37 MRI scans were obtained in 12 asphyxiated neonates treated with induced hypothermia. Four newborns developed MRI evidence of brain injury, already visible on early MRI scans. The remaining eight newborns did not develop significant MRI evidence of brain injury on any of the MRI scans. In addition, two patients displayed unexpected findings on early MRIs, leading to early termination of hypothermia treatment.MRI scans obtained on DOL 2-3 during hypothermia seem to predict later brain injuries in asphyxiated newborns. Brain injuries identified during this early time appear to represent irreversible changes. Early MRI scans might also be useful to demonstrate unexpected findings not related to hypoxic-ischaemic encephalopathy, which could potentially be exacerbated by induced hypothermia. Additional studies with larger numbers of patients will be useful to confirm these results.
    [bibtex-key = Wintermark:2011:Arch-Dis-Child-Fetal-Neonatal-Ed:20688865]

  29. P Wintermark, M Labrecque, S K Warfield, S Dehart, A Hansen. Can induced hypothermia be assured during brain MRI in neonates with hypoxic-ischemic encephalopathy? Pediatr Radiol., 40(12):1950-4 2010. [WWW] [doi: 10.1007/s00247-010-1816-2] [PDF]
    Abstract:
    Until now, brain MRIs in asphyxiated neonates who are receiving therapeutic hypothermia have been performed after treatment is complete. However, there is increasing interest in utilizing early brain MRI while hypothermia is still being provided to rapidly understand the degree of brain injury and possibly refine neuroprotective strategies. This study was designed to assess whether therapeutic hypothermia can be maintained while performing a brain MRI. Twenty MRI scans were obtained in 12 asphyxiated neonates while they were treated with hypothermia. The median difference between esophageal temperature on NICU departure and return was 0.1 degrees C (range: -0.8 to 0.8 degrees C). We found that therapeutic hypothermia can be safely and reproducibly maintained during a brain MRI. Hypothermia treatment should not prevent obtaining an early brain MRI if clinically indicated.
    [bibtex-key = Wintermark:2010:Pediatr-Radiol:20737144]

  30. A Wittek, G Joldes, M Couton, S K Warfield, K Miller.Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration. Prog Biophys Mol Biol, 103(2-3):292-303 2010. [WWW]doi: 10.1016/j.pbiomolbio.2010.09.001]
    Abstract:
    Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4?s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer.
    [bibtex-key = Wittek:2010:Prog-Biophys-Mol-Biol:20868706]

  31. A Gholipour, J A Estroff, M Sahin, S P Prabhu, S K War?eld. Maximum A Posteriori Estimation of Isotropic High-Resolution Volumetric MRI from Orthogonal Thick-Slice Scans. Med Image Comput Comput Assist Interv., 13(Pt 2):109-16 2010. [WWW] [PDF]
    Abstract:
    Thick-slice image acquisitions are sometimes inevitable in magnetic resonance imaging due to limitations posed by pulse sequence timing and signal-to-noise-ratio. The estimation of an isotropic high-resolution volume from thick-slice MRI scans is desired for improved image analysis and evaluation. In this article we formulate a maximum a posteriori (MAP) estimation algorithm for high-resolution volumetric MRI reconstruction. As compared to the previous techniques, this probabilistic formulation relies on a slice acquisition model and allows the incorporation of image priors. We focus on image priors based on image gradients and compare the developed MAP estimation approach to scattered data interpolation (SDI) and maximum likelihood reconstruction. The results indicate that the developed MAP estimation approach outperforms the SDI techniques and appropriate image priors may improve the volume estimation when the acquired thick-slice scans do not sufficiently sample the imaged volume. We also report applications in pediatric and fetal imaging.
    [bibtex-key = Gholipour:2010:Med-Image-Comput-Comput-Assist-Interv:20879305]

  32. O Commowick and S K Warfield. Incorporating priors on expert performance parameters for segmentation validation and label fusion: a maximum a posteriori STAPLE. Med Image Comput Comput Assist Interv., 13(Pt 3):25-32 2010. [WWW] [PDF]
    Abstract:
    In order to evaluate the quality of segmentations of an image and assess intra- and inter-expert variability in segmentation performance, an Expectation Maximization (EM) algorithm for Simultaneous Truth And Performance Level Estimation (STAPLE) was recently developed. This algorithm, originally presented for segmentation validation, has since been used for many applications, such as atlas construction and decision fusion. However, the manual delineation of structures of interest is a very time consuming and burdensome task. Further, as the time required and burden of manual delineation increase, the accuracy of the delineation is decreased. Therefore, it may be desirable to ask the experts to delineate only a reduced number of structures or the segmentation of all structures by all experts may simply not be achieved. Fusion from data with some structures not segmented by each expert should be carried out in a manner that accounts for the missing information. In other applications, locally inconsistent segmentations may drive the STAPLE algorithm into an undesirable local optimum, leading to misclassifications or misleading experts performance parameters. We present a new algorithm that allows fusion with partial delineation and which can avoid convergence to undesirable local optima in the presence of strongly inconsistent segmentations. The algorithm extends STAPLE by incorporating prior probabilities for the expert performance parameters. This is achieved through a Maximum A Posteriori formulation, where the prior probabilities for the performance parameters are modeled by a beta distribution. We demonstrate that this new algorithm enables dramatically improved fusion from data with partial delineation by each expert in comparison to fusion with STAPLE.
    [bibtex-key = Commowick:2010:Med-Image-Comput-Comput-Assist-Interv:20879379]
  33. A Gholipour, J A Estroff, and S K Warfield. Robust Super-resolution Volume Reconstruction from Slice Acquisitions: Application to Fetal Brain MRI. IEEE Trans Med Imaging., 29(10):1739-58 2010. [WWW] [doi: 10.1109/TMI.2010.2051680] [PDF]
    Abstract:
    Fast magnetic resonance imaging slice acquisition techniques such as single shot fast spin echo are routinely used in the presence of uncontrollable motion. These techniques are widely used for fetal MRI and MRI of moving subjects and organs. Although high-quality slices are frequently acquired by these techniques, inter-slice motion leads to severe motion artifacts that are apparent in out-of-plane views. Slice sequential acquisitions do not enable 3D volume representation. In this study, we have developed a novel technique based on a slice acquisition model, which enables the reconstruction of a volumetric image from multiple-scan slice acquisitions. The superresolution volume reconstruction is formulated as an inverse problem of finding the underlying structure generating the acquired slices. We have developed a robust M-estimation solution which minimizes a robust error norm function between the model-generated slices and the acquired slices. The accuracy and robustness of this novel technique has been quantitatively assessed through simulations with digital brain phantom images as well as high-resolution newborn images. We also report here successful application of our new technique for the reconstruction of volumetric fetal brain MRI from clinically acquired data.
    [bibtex-key = GholipourBaboli:2010:IEEE-Trans-Med-Imaging:20529730]

  34. A Gholipour, J A Estroff, C E Barnewolt, S A Connolly, S K Warfield. Fetal brain volumetry through MRI volumetric reconstruction and segmentation. Int J Computer Assisted Radiology and Surgery, 2010, in press. [WWW] [doi: 10.1007/s11548-010-0512-x] [PDF]
    Abstradt
    PURPOSE: Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. MATERIALS AND METHODS: The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. RESULTS: Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. CONCLUSION: The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation.
    [bibtex-key = Gholipour:2010:Int-J-Comput-Assist-Radiol-Surg:20625848]

  35. O Commowick and S K Warfield. Estimation of Inferential Uncertainty in Assessing Expert Segmentation Performance from STAPLE. IEEE Trans Med Imaging, 29(3):771-80 2010. [WWW] [doi: 10.1109/TMI.2009.2036011] [PDF]
    Abstract:
    The evaluation of the quality of segmentations of an image, and the assessment of intra- and inter-expert variability in segmentation performance, has long been recognized as a difficult task. For a segmentation validation task, it may be effective to compare the results of an automatic segmentation algorithm to multiple expert segmentations. Recently an Expectation Maximization (EM) algorithm for Simultaneous Truth and Performance Level Estimation (STAPLE) was developed to this end to compute both an estimate of the reference standard segmentation and performance parameters from a set of segmentations of an image. The performance is characterized by the rate of detection of each segmentation label by each expert in comparison to the estimated reference standard. This previous work provides estimates of performance parameters, but does not provide any information regarding the uncertainty of the estimated values. An estimate of this inferential uncertainty, if available, would allow the estimation of confidence intervals for the values of the parameters. This would facilitate the interpretation of the performance of segmentation generators, and help determine if sufficient data size and number of segmentations have been obtained to precisely characterize the performance parameters. We present a new algorithm to estimate the inferential uncertainty of the performance parameters for binary and multicategory segmentations. It is derived for the special case of the STAPLE algorithm based on established theory for general purpose covariance matrix estimation for EM algorithms. The bounds on the performance parameters are estimated by the computation of the observed Information Matrix. We use this algorithm to study the bounds on performance parameters estimates from simulated images with specified performance parameters, and from interactive segmentations of neonatal brain MRIs. We demonstrate that confidence intervals for expert segmentation performance parameters can be estimated with our algorithm. We investigate the influence of the number of experts and of the segmented data size on these bounds, showing that it is possible to determine the number of image segmentations and the size of images necessary to achieve a chosen level of accuracy in segmentation performance assessment.
    [bibtex-key = Commowick:2010:IEEE-Trans-Med-Imaging:20199913 >

  36. J W Lee, P Y Wen, S Hurwitz, P Black, S Kesari, J Drappatz, A J Golby, W M Wells, S K Warfield, R Kikinis, E B Bromfield. Morphological characteristics of brain tumors causing seizures. Arch Neurol., 67(3):336-42 2010. [WWW] [doi: 10.1001/archneurol.2010.2]
    Abstract:
    OBJECTIVE: To quantify size and localization differences between tumors presenting with seizures vs nonseizure neurological symptoms. DESIGN: Retrospective imaging survey. We performed magnetic resonance imaging-based morphometric analysis and nonparametric mapping in patients with brain tumors. SETTING: University-affiliated teaching hospital. PATIENTS OR OTHER PARTICIPANTS: One hundred twenty-four patients with newly diagnosed supratentorial glial tumors. MAIN OUTCOME MEASURES: Volumetric and mapping methods were used to evaluate differences in size and location of the tumors in patients who presented with seizures as compared with patients who presented with other symptoms. RESULTS: In high-grade gliomas, tumors presenting with seizures were smaller than tumors presenting with other neurological symptoms, whereas in low-grade gliomas, tumors presenting with seizures were larger. Tumor location maps revealed that in high-grade gliomas, deep-seated tumors in the pericallosal regions were more likely to present with nonseizure neurological symptoms. In low-grade gliomas, tumors of the temporal lobe as well as the insular region were more likely to present with seizures. CONCLUSIONS: The influence of size and location of the tumors on their propensity to cause seizures varies with the grade of the tumor. In high-grade gliomas, rapidly growing tumors, particularly those situated in deeper structures, present with non-seizure-related symptoms. In low-grade gliomas, lesions in the temporal lobe or the insula grow large without other symptoms and eventually cause seizures. Quantitative image analysis allows for the mapping of regions in each group that are more or less susceptible to seizures.
    [bibtex-key = Lee:2010:Arch-Neurol:20212231]

  37. M Krishnan, O Commowick, S S Jeste, N Weisenfeld, A Hans, M Gregas, M Sahin, and S K Warfield. Diffusion features of white matter in Tuberous Sclerosis Complex assessed with tractography. Pediatric Neurology, 42(2):101-6 2010. [WWW] [doi: 10.1016/j.pediatrneurol.2009.08.001] [PDF]
    Abstract:
    Normal-appearing white matter has been shown via diffusion tensor imaging to be affected in tuberous sclerosis complex. Under the hypothesis that some systems might be differentially affected, including the visual pathways and systems of social cognition, diffusion properties of various regions of white matter were compared. For 10 patients and 6 age-matched control subjects, 3 T magnetic resonance imaging was assessed using diffusion tensor imaging obtained in 35 directions. Three-dimensional volumes corresponding to the geniculocalcarine tracts were extracted via tractography, and two-dimensional regions of interest were used to sample other regions. Regression analysis indicated lower fractional anisotropy in the splenium of corpus callosum and geniculocalcarine tracts in tuberous sclerosis complex group, as well as lower axial diffusivity in the internal capsule, superior temporal gyrus, and geniculocalcarine tracts. Mean and radial diffusivity of the splenium of corpus callosum were higher in the tuberous sclerosis complex group. The differences in diffusion properties of white matter between tuberous sclerosis complex patients and control subjects suggest disorganized and structurally compromised axons with poor myelination.The visual and social cognition systems appear to be differentially involved, which might in part explain the behavioral and cognitive characteristics of the tuberous sclerosis complex population.
    [bibtex-key = Krishnan:2010:Pediatr-Neurol:20117745]

  38. J Fripp, S Crozier, S K Warfield, and S Ourselin. Automatic segmentation and quantitative analysis of the articular cartilages from magnetic resonance images of the knee. Pediatr Res., 29(1): 55-64 2010. [WWW] [doi: 10.1109/TMI.2009.2024743]
    Abstract:
    In this paper, we present a segmentation scheme that automatically and accurately segments all the cartilages from magnetic resonance (MR) images of nonpathological knees. Our scheme involves the automatic segmentation of the bones using a three-dimensional active shape model, the extraction of the expected bone-cartilage interface (BCI), and cartilage segmentation from the BCI using a deformable model that utilizes localization, patient specific tissue estimation and a model of the thickness variation. The accuracy of this scheme was experimentally validated using leave one out experiments on a database of fat suppressed spoiled gradient recall MR images. The scheme was compared to three state of the art approaches, tissue classification, a modified semi-automatic watershed algorithm and nonrigid registration (B-spline based free form deformation). Our scheme obtained an average Dice similarity coefficient (DSC) of (0.83, 0.83, 0.85) for the (patellar, tibial, femoral) cartilages, while (0.82, 0.81, 0.86) was obtained with a tissue classifier and (0.73, 0.79, 0.76) was obtained with nonrigid registration. The average DSC obtained for all the cartilages using a semi-automatic watershed algorithm (0.90) was slightly higher than our approach (0.89), however unlike this approach we segment each cartilage as a separate object. The effectiveness of our approach for quantitative analysis was evaluated using volume and thickness measures with a median volume difference error of (5.92, 4.65, 5.69) and absolute Laplacian thickness difference of (0.13, 0.24, 0.12) mm.
    [bibtex-key = Fripp:2010:IEEE-Trans-Med-Imaging:19520633]

  39. R O Suarez, A Golby, S Whalen, S Sato, W H Theodore, C V Kufta, O Devinsky, M Balish and E B Bromfield. Contributions to singing ability by the posterior portion of the superior temporal gyrus of the non-language-dominant hemisphere: First evidence from subdural cortical stimulation, Wada testing, and fMRI. Cortex 46(3):343-53 2010. [WWW] [doi: 10.1016/j.cortex.2009.04.010]
    Abstract:
    INTRODUCTION: Although the substrates that mediate singing abilities in the human brain are not well understood, invasive brain mapping techniques used for clinical decision making such as intracranial electro-cortical testing and Wada testing offer a rare opportunity to examine music-related function in a select group of subjects, affording exceptional spatial and temporal specificity. METHODS: We studied eight patients with medically refractory epilepsy undergoing indwelling subdural electrode seizure focus localization. All patients underwent Wada testing for language lateralization. Functional assessment of language and music tasks was done by electrode grid cortical stimulation. One patient was also tested non-invasively with functional magnetic resonance imaging (fMRI). Functional organization of singing ability compared to language ability was determined based on four regions-of-interest (ROIs): left and right inferior frontal gyrus (IFG), and left and right posterior superior temporal gyrus (pSTG). RESULTS: In some subjects, electrical stimulation of dominant pSTG can interfere with speech and not singing, whereas stimulation of non-dominant pSTG area can interfere with singing and not speech. Stimulation of the dominant IFG tends to interfere with both musical and language expression, while non-dominant IFG stimulation was often observed to cause no interference with either task; and finally, that stimulation of areas adjacent to but not within non-dominant pSTG typically does not affect either ability. Functional fMRI mappings of one subject revealed similar music/language dissociation with respect to activation asymmetry within the ROIs. CONCLUSION: Despite inherent limitations with respect to strictly research objectives, invasive clinical techniques offer a rare opportunity to probe musical and language cognitive processes of the brain in a select group of patients.
    [bibtex-key = Suarez:2009:Cortex:19570530]

  40. D Hyde, E Miller, D Brooks, and V Ntziachristos. Data specific Spatially Varying Regularization for Multi-Model Fluoresence Molecular Tomography. IEEE Trans Med Imaging, 29(2):365-74 2010. [WWW] [doi: 10.1109/TMI.2009.2031112]
    Abstract:
    Fluorescence molecular tomography (FMT) allows in-vivo localization and quantification of fluorescence biodistributions in whole animals. The ill-posed nature of the tomographic reconstruction problem, however, limits the attainable resolution. Improvements in resolution and overall imaging performance can be achieved by forming image priors from geometric information obtained by a secondary anatomical or functional high-resolution imaging modality such as X-ray CT or MRI. A particular challenge in using image priors is to avoid the use of assumptions that may bias the solution and reduced the accuracy of the inverse problem. This is particularly relevant in FMT inversions where there is not an evident link between secondary geometric information and the underlying fluorescence biodistribution. We present here a new, two step approach to incorporating structural priors into the FMT inverse problem. By using the anatomic information to define a low dimensional inverse problem, we obtain a solution which we then use to determine the parameters defining a spatially varying regularization matrix for the full resolution problem. The regularization term is thus customized for each data set and is guided by the data rather than depending only on user defined a priori assumptions. Results are presented for both simulated and experimental data sets, and show significant improvements in image quality as compared to traditional regularization techniques.
    [bibtex-key = Hyde:2009:IEEE-Trans-Med-Imaging:19758858]

  41. A Reshef, A Shirvan, A Akselrod-Ballin, A Wall, and I Ziv. Small Molecular Biomarkers for Clinical PET imaging of Apoptosis. The Journal of Nuclear Medicine, 51(6):837-40 2010. [WWW] [doi: 10.2967/jnumed.109.063917] [PDF]
    Abstract:
    Apoptosis is a fundamental biologic process. Molecular imaging of apoptosis in vivo may have important implications for clinical practice, assisting in early detection of disease, monitoring of disease course, assessment of treatment efficacy, or development of new therapies. Although a PET probe for clinical imaging of apoptosis would be highly desirable, this is yet an unachieved goal, mainly because of the required challenging integration of various features, including sensitive and selective detection of the apoptotic cells, clinical aspects such as favorable biodistribution and safety profiles, and compatibility with the radiochemistry and imaging routines of clinical PET centers. Several approaches are being developed to address this challenge, all based on novel small-molecule structures targeting various steps of the apoptotic cascade. This novel concept of small-molecule PET probes for apoptosis is the focus of this review.
    [bibtex-key = Reshef:2010:J-Nucl-Med:20484422]

  42. P Wintermark, T Boyd, M M Parast, L J Van Marter, S K Warfield, R L Robertson, and S A Ringer. Fetal Placental Thrombosis and Neonatal Implications. Am J Perinatol., 27(3):251-6 2010. [WWW] [doi : 10.1055/s-0029-1239486] [PDF]
    Abstract:
    We present the neonatal complications of two premature newborn infants whose placentas demonstrated placental thrombosis in the fetal circulation. Both mothers presented with a 3-day history of decreased fetal movements before delivery. The first infant presented with thrombocytopenia and disseminated intravascular coagulation. The second infant had extended bilateral extended hemorrhagic venous infarctions. Severe fetal placental vascular lesions seem to be a predisposing factor for some adverse neonatal outcomes. We present these two cases with a brief review of the literature.
    [bibtex-key = Wintermark:2009:Am-J-Perinatol:19806531]

  43. L M Vigneron, R C Boman, J-P Ponthot, P A Robe, S K Warfield and J G Verly. Enhanced FEM-based modeling of brain shift deformation in Image-Guided Neurosurgery. Journal of Computational and Applied Mathematics. 2009, in press.
    Abstract:
    We consider the problem of improving outcomes for neurosurgery patients by enhancing intraoperative navigation and guidance. Current navigation systems do not accurately account for intraoperative brain deformation. We focus on the brain shift deformation that occurs just after the opening of the skull and dura. The heart of our system is a nonrigid registration technique using a biomechanical model. We specifically work on two axes: the representation of the structures in the biomechanical model and the evaluation of the surface landmark displacement fields between intraoperative MR images. Using the modified Hausdorff distance as an image similarity measure, we demonstrate that our approach significantly improves the alignment of the intraoperative images.


  44. A Akselrod-Ballin, D Bock, R C Reid, and S K Warfield. Improved registration for large electron microscopy images. In: Biomedical Imaging: From Nano to Macro, 2009 (ISBI 2009), pages 434-437 2009. [PDF]
    Abstract:
    In this paper we introduce a novel algorithm for alignment of Electron Microscopy images for 3D reconstruction. The algorithm extends the Expectation Maximization - Iterative Closest Points (EM-ICP) registration algorithm to go from point matching to patch matching. We utilize local patch characteristics to achieve improved registration. The method is applied to enable 3D reconstruction of Transmission Electron Microscopy (TEM) images. We demonstrate results on large TEM images and show the increased alignment accuracy of our approach.


  45. N I Weisenfeld and S K Warfield. A data-driven approach to discovering common brain anatomy. In: Biomedical Imaging: From Nano to Macro, 2009 (ISBI 2009), pages 217-220 2009. [PDF]
    Abstract:
    An atlas defines a common coordinate system to enable the comparison of data from different subjects. Key in the development of a brain atlas are the identification of a common coordinate system and the definition of a procedure for aligning an individual brain to the common coordinate system. The algorithms used for atlas construction to date have not sought to characterize residual anatomical variability after registration, and have sought to assign equal weight to each subject, rather than assessing their degree of commonality. Our new algorithm defines a common coordinate system by estimating the typical anatomical distribution of brain structures and characterizes the quality of alignment of each subject within the common coordinate system. Residual anatomical variability is quantitatively described by the extent to which the brain structures of an individual fail to match the typical anatomy. We have applied this to cohorts of 14 adult and 11 newborn brain segmentations and demonstrated the ability of the algorithm to distinguish groups of subjects in a clinically relevant application.


  46. A Akselrod-Ballin, D Bock, R C Reid and S K Warfield. Accelerating Feature Based Registration Using the Johnson-Lindenstrauss Lemma. Med Image Comput Comput Assist Interv., 12(Pt 1):632-9 2009. [PDF]
    Abstract:
    We introduce an efficient search strategy to substantially accelerate feature based registration. Previous feature based registration algorithms often use truncated search strategies in order to achieve small computation times. Our new accelerated search strategy is based on the realization that the search for corresponding features can be dramatically accelerated by utilizing Johnson-Lindenstrauss dimension reduction. Order of magnitude calculations for the search strategy we propose here indicate that the algorithm proposed is more than a million times faster than previously utilized naive search strategies, and this advantage in speed is directly translated into an advantage in accuracy as the fast speed enables more comparisons to be made in the same amount of time. We describe the accelerated scheme together with a full complexity analysis. The registration algorithm was applied to large transmission electron microscopy (TEM) images of neural ultrastructure. Our experiments demonstrate that our algorithm enables alignment of TEM images with increased accuracy and efficiency compared to previous algorithms.


  47. O Commowick, S K Warfield and G Malandain. Using Frankenstein's Creature Paradigm to Build a Patient Specific Atlas. Med Image Comput Comput Assist Interv., 12(Pt 2):993-1000 2009. [PDF]
    Abstract:
    In this article, we focus on the parameterization of non-rigid geometrical deformations with a small number of flexible degrees of freedom . In previous work, we proposed a general framework called polyaffine to parameterize deformations with a small number of rigid or affine components, while guaranteeing the invertibility of global deformations. However, this framework lacks some important properties: the inverse of a polyaffine transformation is not polyaffine in general, and the polyaffine fusion of affine components is not invariant with respect to a change of coordinate system. We present here a novel general framework, called Log-Euclidean polyaffine, which overcomes these defects. We also detail a simple algorithm, the Fast Polyaffine Transform, which allows to compute very efficiently Log-Euclidean polyaffine transformations and their inverses on a regular grid. The results presented here on real 3D locally affine registration suggest that our novel framework provides a general and efficient way of fusing local rigid or affine deformations into a global invertible transformation without introducing artifacts, independently of the way local deformations are first estimated.


  48. G R Joldes, A Wittek, M Couton, S K Warfield and K Miller. Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms. Med Image Comput Comput Assist Interv., 12(Pt 2):300-7 2009. [PDF]
    Abstract:
    Patient-specific biomechanical models implemented using specialized nonlinear (i.e. taking into account material and geometric nonlinearities) finite element procedures were applied to predict the deformation field within the brain for five cases of craniotomy-induced brain shift. The procedures utilize the Total Lagrangian formulation with explicit time stepping. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register the preoperative images with the intraoperative ones indicated that the models very accurately predict the intraoperative positions and deformations of the brain anatomical structures for limited information about the brain surface deformations. For each case, it took less than 40 s to compute the deformation field using a standard personal computer, and less than 4 s using a Graphics Processing Unit (GPU). The results suggest that nonlinear biomechanical models can be regarded as one possible method of complementing medical image processing techniques when conducting non-rigid registration within the real-time constraints of neurosurgery.


  49. A Gholipour and S K Warfield. Super-resolution reconstruction of fetal brain MRI. In:MICCAI Workshop on Image Analysis for the Developing Brain (IADB'2009), C. Studholme and F. Rousseau, Eds., London, UK, 24 Sept. 2009, pp. 45-52. [PDF]
    Abstract:
    Current fetal MRI practice involves fast 2D slice acquisitions. The reconstruction of volumetric fetal brain MRI from these acquisitions and its post-processing is greatly desired for studying in-utero brain development. The previously developed reconstruction techniques rely on iterations of slice-to-volume registration and scattered data interpolation. In contrast, the technique introduced here is based on a slice acquisition model, and refines the reconstructed volumetric image through a maximum likelihood error minimization approach. Qualitative and quantitative evaluation results show improved sharpness of the reconstructed images using the developed technique. The increased image sharpness measures and lower registration error metrics both indicate more accurate slice motion correction. This in-turn indicates that better volumetric images were reconstructed and used in registration iterations.


  50. O Commowick and S K Warfield. Estimation of inferential uncertainty in assessing expert segmentation performance from STAPLE. Inf Process Med Imaging., 21:701-12 2009. [WWW]
    Abstract:
    The evaluation of the quality of segmentations of an image, and the assessment of intra- and inter-expert variability in segmentation performance, has long been recognized as a difficult task. Recently an Expectation Maximization (EM) algorithm for Simultaneous Truth and Performance Level Estimation (STAPLE), Was developed to compute both an estimate of the reference standard segmentation and performance parameters from a set of segmentations of an image. The performance is characterized by the rate of detection of each segmentation label by each expert in comparison to the estimated reference standard. This previous work provides estimates of performance parameters, but does not provide any information regarding their uncertainty. An estimate of this inferential uncertainty, if available, would allow estimation of confidence intervals for the values of the parameters, aid in the interpretation of the performance of segmentation generators, and help determine if sufficient data size and number of segmentations have been obtained to accurately characterize the performance parameters. We present a new algorithm to estimate the inferential uncertainty of the performance parameters for binary segmentations. It is derived for the special case of the STAPLE algorithm based on established theory for general purpose covariance matrix estimation for EM algorithms. The bounds on performance estimates are estimated by the computation of the observed Information Matrix. We use this algorithm to study the bounds on performance estimates from simulated images with specified performance parameters, and from interactive segmentations of neonatal brain MRIs. We demonstrate that confidence intervals for expert segmentation performance parameters can be estimated with our algorithm. We investigate the influence of the number of experts and of the image size on these bounds, showing that it is possible to determine the number of image segmentations and the size of images necessary to achieve a chosen level of accuracy in segmentation performance assessment.


  51. M Schaap, C T Metz, T van Walsum, A G van der Giessen, A C Weustink, N R Mollet, C Bauer, H Bogunovic, C Castro, X Deng, E Dikici, T O'Donnell, M Frenay, O Friman, M Hernández Hoyos, P H Kitslaar, K Krissian, C Kühnel, M A Luengo-Oroz, M Orkisz, O Smedby, M Styner, A Szymczak, H Tek, C Wang, S K Warfield, S Zambal, Y Zhang, G P Krestin, and W J Niessen. Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms. Med Image Anal., 13(5):701-14 2009. [WWW] [doi: 10.1016/j.media.2009.06.003]
    Abstract:
    Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.
    [bibtex-key = Schaap:2009:Med-Image-Anal:19632885]

  52. L M Vigneron, M P Duflot, P A Robe, S K Warfield, and J G Verly . 2D XFEM-based modeling of retraction and successive resections for preoperative image update. Comput Aided Surg., Jul 27:1-20 2009. [WWW] [doi: 10.1080/10929080903052677]
    Abstract:
    This paper considers an approach to improving outcomes for neurosurgery patients by enhancing intraoperative navigation and guidance. Currently, intraoperative navigation systems do not accurately account for brain shift or tissue resection. We describe how preoperative images can be incrementally updated to take into account any type of brain tissue deformation that may occur during surgery, and thus to improve the accuracy of image-guided navigation systems. For this purpose, we have developed a non-rigid image registration technique using a biomechanical model, which deforms based on the Finite Element Method (FEM). While the FEM has been used successfully for dealing with deformations such as brain shift, it has difficulty with tissue discontinuities. Here, we describe a novel application of the eXtended Finite Element Method (XFEM) in the field of image-guided surgery in order to model brain deformations that imply tissue discontinuities. In particular, this paper presents a detailed account of the use of XFEM for dealing with retraction and successive resections, and demonstrates the feasibility of the approach by considering 2D examples based on intraoperative MR images. To evaluate our results, we compute the modified Hausdorff distance between Canny edges extracted from images before and after registration. We show that this distance decreases after registration, and thus demonstrate that our approach improves alignment of intraoperative images.
    [bibtex-key = Vigneron:2009:Comput-Aided-Surg:19634040]

  53. M J N L Benders, F Groenendaal, F van Bel, R Ha Vinh, J Dubois, J F Lazeyras, S K Warfield, P S Huppi, and L S de Vries. Brain development of the preterm neonate after neonatal hydrocortisone treatment for chronic lung disease Pediatric Research 66(5):555-9 2009. [WWW] [doi : 10.1203/PDR.0b013e3181b3aec5]
    Abstract:
    Previous studies reported impaired cerebral cortical grey matter development and neurodevelopmental impairment following neonatal dexamethasone treatment for chronic lung disease in preterm newborns. No long term effects on neurocognitive outcome have yet been shown for hydrocortisone treatment. A prospective study was performed to evaluate brain growth at term in preterm infants who did receive neonatal hydrocortisone for chronic lung disease. Thirty-eight preterm infants (n=19 hydrocortisone, n=19 controls) were matched for gestational age at birth. Gestational age and birth weight were 27.0+1.4 vs. 27.6+1.1 weeks (p=ns), and 826+173 vs. 1017+202 gram respectively (p<0.05). Infants were studied at term equivalent age . Hydrocortisone was started with a dose of 5 mg/kg/day for 1 week, followed by a tapering course over 3 weeks. A 3D-MRI technique was used to quantify cerebral tissue volumes: cortical grey matter, basal ganglia/thalami, unmyelinated white matter, myelinated white matter, cerebellum and cerebrospinal fluid. Infants who were treated with hydrocortisone had more severe respiratory distress. There were no differences in cerebral tissue volumes between the 2 groups at term equivalent age. In conclusion, no effect on brain growth, measured at term equivalent age, was shown following treatment with hydrocortisone for chronic lung disease.
    [bibtex-key = Benders:2009:Pediatr-Res:19581837]

  54. N I Weisenfeld and S K Warfield. Automatic Segmentation of Newborn Brain MRI. Neuroimage, 47(2):564-72 2009. [WWW] [doi: 10.1016/j.neuroimage.2009.04.068] [PDF]
    Abstract:
    Quantitative brain tissue segmentation from newborn MRI offers the possibility of improved clinical decision making and diagnosis, new insight into the mechanisms of disease, and new methods for the evaluation of treatment protocols for preterm newborns. Such segmentation is challenging, however, due to the imaging characteristics of the developing brain. Existing techniques for newborn segmentation either achieve automation by ignoring critical distinctions between different tissue types or require extensive expert interaction. Because manual interaction is time consuming and introduces both bias and variability, we have developed a novel automatic segmentation algorithm for brain MRI of newborn infants. The key algorithmic contribution of this work is a new approach for automatically learning patient-specific class conditional probability density functions. The algorithm achieves performance comparable to expert segmentations while automatically identifying cortical gray matter, subcortical gray matter, cerebrospinal fluid, myelinated white matter and unmyelinated white matter. We compared the performance of our algorithm with a previously published semi-automated algorithm and with expert-drawn images. Our algorithm achieved an accuracy comparable with methods that require undesirable manual interaction.
    [bibtex-key = Weisenfeld:2009:Neuroimage:19409502]

  55. O Commowick and S K Warfield. A Continuous STAPLE for Scalar, Vector and Tensor Images: An Application to DTI Analysis. IEEE TMI, 28(6):838-846 2009. [WWW] [doi: 10.1109/TMI.2008.2010438] [PDF]


    Abstract:
    The comparison of images of a patient to a reference standard may enable the identification of structural brain changes. These comparisons may involve the use of vector or tensor images (i.e. 3D images for which each voxel can be represented as an RN vector) such as Diffusion Tensor Images (DTI) or transformations. The recent introduction of the Log-Euclidean framework for diffeomorphisms and tensors has greatly simplified the use of these images by allowing all the computations to be performed on a vector-space. However, many sources can result in a bias in the images, including disease or imaging artifacts. In order to estimate and compensate for these sources of variability, we developed a new algorithm, called continuous STAPLE, that estimates the reference standard underlying a set of vector images. This method, based on an Expectation-Maximization method similar in principle to the validation method STAPLE, also estimates for each image a set of parameters characterizing their bias and variance with respect to the reference standard. We demonstrate how to use these parameters for the detection of atypical images or outliers in the population under study. We identified significant differences between the tensors of diffusion images of multiple sclerosis patients and those of control subjects in the vicinity of lesions.
    [bibtex-key = Commowick:2009:IEEE-Trans-Med-Imaging:19272988]

  56. M Rullmann, A Anwander, M Dannhauer, S K Warfield, F H Duffy, and CH Wolters. EEG source analysis of epileptiform activity using a 1 mm anisotropic hexahedra finite element head model. Neuroimage, 44(2):399-410 2009. [WWW] [doi:10.1016/j.neuroimage.2008.09.009] [PDF]
    Abstract:
    The major goal of the evaluation in presurgical epilepsy diagnosis for medically intractable patients is the precise reconstruction of the epileptogenic foci, preferably with non-invasive methods. This paper evaluates whether surface electroencephalography (EEG) source analysis based on a 1 mm anisotropic finite element (FE) head model can provide additional guidance for presurgical epilepsy diagnosis and whether it is practically feasible in daily routine. A 1 mm hexahedra FE volume conductor model of the patient's head with special focus on accurately modeling the compartments skull, cerebrospinal fluid (CSF) and the anisotropic conducting brain tissues was constructed using non-linearly co-registered T1-, T2- and diffusion-tensor-magnetic resonance imaging data. The electrodes of intra-cranial EEG (iEEG) measurements were extracted from a co-registered computed tomography image. Goal function scan (GFS), minimum norm least squares (MNLS), standardized low resolution electromagnetic tomography (sLORETA) and spatio-temporal current dipole modeling inverse methods were then applied to the peak of the averaged ictal discharges EEG data. MNLS and sLORETA pointed to a single center of activity. Moving and rotating single dipole fits resulted in an explained variance of more than 97%. The non-invasive EEG source analysis methods localized at the border of the lesion and at the border of the iEEG electrodes which mainly received ictal discharges. Source orientation was towards the epileptogenic tissue. For the reconstructed superficial source, brain conductivity anisotropy and the lesion conductivity had only a minor influence, whereas a correct modeling of the highly conducting CSF compartment and the anisotropic skull was found to be important. The proposed FE forward modeling approach strongly simplifies meshing and reduces run-time (37 ms for one forward computation in the model with 3.1 million unknowns), corroborating the practical feasibility of the approach.
    [bibtex-key = Wisco:2008:Neurobiol-Aging:17459528]

  57. D K Thompson, S J Wood, L W Doyle, S K Warfield, G F Egan, and T E Inder MR-determined hippocampal asymmetry in full-term and preterm neonates Hippocampus 19(2):118-23 2009. [WWW] [doi:10.1002/hipo.20492 ] [PDF]
    Abstract:
    Hippocampi are asymmetrical in children and adults, where the right hippocampus is larger. To date, no literature has confirmed that hippocampal asymmetry is evident at birth. Furthermore, gender differences have been observed in normal hippocampal asymmetry, but this has not been examined in neonates. Stress, injury, and lower IQ have been associated with alterations to hippocampal asymmetry. These same factors often accompany preterm birth. Therefore, prematurity is possibly associated with altered hippocampal asymmetry. There were three aims of this study: First, we assessed whether hippocampi were asymmetrical at birth, second whether there was a gender effect on hippocampal asymmetry, and third whether the stress of preterm birth altered hippocampal asymmetry. This study utilized volumetric magnetic resonance imaging to compare left and right hippocampal volumes in 32 full-term and 184 preterm infants at term. Full-term infants demonstrated rightward hippocampal asymmetry, as did preterm infants. In the case of preterm infants, hippocampal asymmetry was proportional to total hemispheric asymmetry. This study is the first to demonstrate that the normal pattern of hippocampal asymmetry is present this early in development. We did not find gender differences in hippocampal asymmetry at term. Preterm infants tended to have less asymmetrical hippocampi than full-term infants, a difference which became significant after correcting for hemispheric brain tissue volumes. This study may suggest that hippocampal asymmetry develops in utero and is maintained into adulthood in infants with a normal neurological course.
    [bibtex-key = Thompson:2008:Hippocampus:18767066]

  58. I Zelman, M Galun, A Akselrod-Ballin, Y Yekutieli, B Hochner and T Flash. Nearly-automatic motion capture system for tracking octopus arm movements in 3D space. Journal of Neuroscience Methods, 182(1):97-109 2009. [WWW] [doi: 10.1016/j.jneumeth.2009.05.022]
    Abstract:
    Tracking animal movements in 3D space is an essential part of many biomechanical studies. The most popular technique for human motion capture uses markers placed on the skin which are tracked by a dedicated system. However, this technique may be inadequate for tracking animal movements, especially when it is impossible to attach markers to the animal's body either because of its size or shape or because of the environment in which the animal performs its movements. Attaching markers to an animal's body may also alter its behavior. Here we present a nearly automatic markerless motion capture system that overcomes these problems and successfully tracks octopus arm movements in 3D space. The system is based on three successive tracking and processing stages. The first stage uses a recently presented segmentation algorithm to detect the movement in a pair of video sequences recorded by two calibrated cameras. In the second stage, the results of the first stage are processed to produce 2D skeletal representations of the moving arm. Finally, the 2D skeletons are used to reconstruct the octopus arm movement as a sequence of 3D curves varying in time. Motion tracking, segmentation and reconstruction are especially difficult problems in the case of octopus arm movements because of the deformable, non-rigid structure of the octopus arm and the underwater environment in which it moves. Our successful results suggest that the motion-tracking system presented here may be used for tracking other elongated objects.
    [bibtex-key = Zelman:2009:J-Neurosci-Methods:19505502]

  59. A Akselrod-Ballin, M Galun, J M Gomori, M Filippi, P Valsasina, R Basri and A Brandt. Automatic segmentation and classification of multiple sclerosis in multi-channel MRI., IEEE Trans Biomed Eng, 56(10):2461-9 2009. [WWW] [doi: 10.1109/TBME.2008.926671]
    Abstract:
    We introduce a multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility in automatically detecting multiple sclerosis (MS) lesions in 3-D multichannel magnetic resonance (MR) images. Our method uses segmentation to obtain a hierarchical decomposition of a multichannel, anisotropic MR scans. It then produces a rich set of features describing the segments in terms of intensity, shape, location, neighborhood relations, and anatomical context. These features are then fed into a decision forest classifier, trained with data labeled by experts, enabling the detection of lesions at all scales. Unlike common approaches that use voxel-by-voxel analysis, our system can utilize regional properties that are often important for characterizing abnormal brain structures. We provide experiments on two types of real MR images: a multichannel proton-density-, T2-, and T1-weighted dataset of 25 MS patients and a single-channel fluid attenuated inversion recovery (FLAIR) dataset of 16 MS patients. Comparing our results with lesion delineation by a human expert and with previously extensively validated results shows the promise of the approach.
    [bibtex-key = AkselrodBallin:2009:IEEE-Trans-Biomed-Eng:19758850]

  60. D Hyde, R Schulz, E Miller, D Brooks, and V Ntziachristos. Performance Dependence of Hybrid X-ray CT-FMT on the Optical Forward Problem. J Opt Soc Am A Opt Image Sci Vis., 26(4):919-23 2009. [WWW]
    Abstract:
    Hybrid imaging systems combining x-ray computed tomography (CT) and fluorescence tomography can improve fluorescence imaging performance by incorporating anatomical x-ray CT information into the optical inversion problem. While the use of image priors has been investigated in the past, little is known about the optimal use of forward photon propagation models in hybrid optical systems. In this paper, we explore the impact on reconstruction accuracy of the use of propagation models of varying complexity, specifically in the context of these hybrid imaging systems where significant structural information is known a priori. Our results demonstrate that the use of generically known parameters provides near optimal performance, even when parameter mismatch remains.
    [bibtex-key = Hyde:2009:J-Opt-Soc-Am-A-Opt-Image-Sci-Vis:19340266]

  61. D Hyde, R DeKleine, S MacLaurin, E Miller, D Brooks, T Krucker, and V Ntziachristos. Hybrid FMT-CT Method for In Vivo Imaging of Amyloid-B Plaques in a Murine Model for Alzheimer's Disease. NeuroImage, 44(4):1304-11 2009. [WWW] [doi: 10.1016/j.neuroimage.2008.10.038]
    Abstract:
    The need to study molecular and functional parameters of Alzheimer's disease progression in animal models has led to the development of disease-specific fluorescent markers. However, curved optical interfaces and a highly heterogeneous internal structure make quantitative fluorescence imaging of the murine brain a particularly challenging tomographic problem. We investigated the integration of X-ray computed tomography (CT) information into a state-of-the-art fluorescence molecular tomography (FMT) scheme and establish that the dual-modality approach is essential for high fidelity reconstructions of distributed fluorescence within the murine brain, as compared to conventional fluorescence tomography. We employ this method in vivo using a fluorescent oxazine dye to quantify amyloid-beta plaque burden in transgenic APP23 mice modeling Alzheimer's disease. Multi-modal imaging allows for accurate signal localization and correlation of in vivo findings to ex vivo studies. The results point to FMT-CT as an essential tool for in vivo study of neurodegenerative disease in animal models and potentially humans.
    [bibtex-key = Hyde:2009:Neuroimage:19041402]

  62. B Scherrer, F Forbes, C Garbay, and M Dojat. Distributed Local MRF Models for Tissue and Structure Brain Segmentation. IEEE TMI, 28(8):1278-95. [WWW] [doi: 10.1109/TMI.2009.2014459]
    Abstract:
    Accurate tissue and structure segmentation of magnetic resonance (MR) brain scans is critical in several applications. In most approaches this task is handled through two sequential steps. We propose to carry out cooperatively both tissue and subcortical structure segmentation by distributing a set of local and cooperative Markov random field (MRF) models Tissue segmentation is performed by partitioning the volume into subvolumes where local MRFs are estimated in cooperation with their neighbors to ensure consistency. Local estimation fits precisely to the local intensity distribution and thus handles nonuniformity of intensity without any bias field modelization. Similarly, subcortical structure segmentation is performed via local MRF models that integrate localization constraints provided by a priori fuzzy description of brain anatomy. Subcortical structure segmentation is not reduced to a subsequent processing step but joined with tissue segmentation: the two procedures cooperate to gradually and conjointly improve model accuracy. We propose a framework to implement this distributed modeling integrating cooperation, coordination, and local model checking in an efficient way. Its evaluation was performed using both phantoms and real 3 T brain scans, showing good results and in particular robustness to nonuniformity and noise with a low computational cost. This original combination of local MRF models, including anatomical knowledge, appears as a powerful and promising approach for MR brain scan segmentation.
    [bibtex-key = Scherrer:2009:IEEE-Trans-Med-Imaging:19228553]

  63. B Scherrer, M Dojat, F Forbes, and C Garbay. Agentification of Markov model-based segmentation: Application to magnetic resonance brain scans. Artif Intell Med., 46(1):81-95 2009. [WWW] [doi: 10.1016/j.artmed.2008.08.012]
    Abstract:
    OBJECTIVE: Markov random field (MRF) models have been traditionally applied to the task of robust-to-noise image segmentation. Most approaches estimate MRF parameters on the whole image via a global expectation-maximization (EM) procedure. The resulting estimated parameters are likely to be uncharacteristic of local image features. Instead, we propose to distribute a set of local MRF models within a multiagent framework. MATERIALS AND METHODS: Local segmentation agents estimate local MRF models via local EM procedures and cooperate to ensure a global consistency of local models. We demonstrate different types of cooperations between agents that lead to additional levels of regularization compared to the standard label regularization provided by MRF. Embedding Markovian EM procedures into a multiagent paradigm shows interesting properties that are illustrated on magnetic resonance (MR) brain scan segmentation. RESULTS: A cooperative tissue and subcortical structure segmentation approach is designed with such a framework, where both models mutually improve. Several experiments are reported and illustrate the working of Markovian EM agents. The evaluation of MR brain scan segmentation was performed using both phantoms and real 3T brain scans. It showed a robustness to intensity non-uniformity and noise, together with a low computational time. CONCLUSION: Based on these experiments MRF agent-based approach appears to be a very promising new tool for complex image segmentation.
    [bibtex-key = Scherrer:2009:Artif-Intell-Med:18929472]

  64. S Peled, S Whalen, F A Jolesz, and A J Golby. High b-value apparent diffusion-weighted images from CURVE-ball DTI. J Magn Reson., 30(1):243-8 2009. [WWW] [doi: 10.1002/jmri.21808]
    Abstract:
    PURPOSE: To investigate the utility of a proposed clinical diffusion imaging scheme for rapidly generating multiple b-value diffusion contrast in brain magnetic resonance imaging (MRI) with high signal-to-noise ratio (SNR). MATERIALS AND METHODS: Our strategy for efficient image acquisition relies on the invariance property of the diffusion tensor eigenvectors to b-value. A simple addition to the conventional diffusion tensor MR imaging (DTI) data acquisition scheme used for tractography yields diffusion-weighted images at twice and three times the conventional b-value. An example from a neurosurgical brain tumor is shown. Apparent diffusion-weighted (ADW) images were calculated for b-values 800, 1600, and 2400 s/mm(2), and a map of excess diffusive kurtosis was computed from the three ADWs. RESULTS: High b-value ADW images demonstrated decreased contrast between normal gray and white matter, while the heterogeneity and contrast of the lesion was emphasized relative to conventional b-value data. Kurtosis maps indicated the deviation from Gaussian diffusive behavior. CONCLUSION: DTI data with multiple b-values and good SNR can be acquired in clinically reasonable times. High b-value ADW images show increased contrast and add information to conventional DWI. Ambiguity in conventional b-value images over whether hyperintense signal results from abnormally low diffusion, or abnormally long T(2), is better resolved in high b-value images.
    [bibtex-key = Peled:2009:J-Magn-Reson-Imaging:19557743]

  65. P J White, S Whalen, S C Tang, G T Clement, and A J Golby. An interoperative brain-shift monitor using shear-mode transcranial ultrasound: Preliminary results. J Ultrasound Med., 28(2):191-203. [WWW]
    Abstract:
    OBJECTIVE: Various methods of intraoperative structural monitoring during neurosurgery are used to localize lesions after brain shift and to guide surgically introduced probes such as biopsy needles or stimulation electrodes. With its high temporal resolution, portability, and nonionizing mode of radiation, ultrasound has potential advantages over other existing imaging modalities for intraoperative monitoring, yet ultrasound is rarely used during neurosurgery largely because of the craniotomy requirement to achieve sufficiently useful signals. METHODS: Prompted by results from recent studies on transcranial ultrasound, a prototype device that aims to use the shear mode of transcranial ultrasound transmission for intraoperative monitoring was designed, constructed, and tested with 10 human participants. Magnetic resonance images were then obtained with the device spatially registered to the magnetic resonance imaging (MRI) reference coordinates. Peaks in both the ultrasound and MRI signals were identified and analyzed for both spatial localization and signal-to-noise ratio (SNR). RESULTS: The first results aimed toward validating the prototype device with MRI showed an excellent correlation (n = 38; R(2) = 0.9962) between the structural localization abilities of the two modalities. In addition, the overall SNR of the ultrasound backscatter signals (n = 38; SNR = 25.4 +/- 5.2 dB, mean +/- SD) was statistically equivalent to that of the MRI data (n = 38; SNR = 22.5 +/- 4.8 dB). CONCLUSIONS: A statistically significant correlation of localized intracranial structures between intraoperative transcranial ultrasound monitoring and MRI data was achieved with 10 human participants. We have shown and validated a prototype device incorporating transcranial shear mode ultrasound for clinical monitoring applications.
    [bibtex-key = White:2009:J-Ultrasound-Med:19168769]

  66. A A Qazi, A Radmanesh, L O'Donnell, G Kindlmann, S Peled, S Whalen, C F Westin, and A J Golby. Resolving crossings in the corticospinal tract by two-tensor streamline tractography: Method and clinical assessment using fMRI. NeuroImage, 47(Suppl 2):T98-106 2009. [WWW] [doi: 10.1016/j.neuroimage.2008.06.034]
    Abstract:
    An inherent drawback of the traditional diffusion tensor model is its limited ability to provide detailed information about multidirectional fiber architecture within a voxel. This leads to erroneous fiber tractography results in locations where fiber bundles cross each other. This may lead to the inability to visualize clinically important tracts such as the lateral projections of the corticospinal tract. In this report, we present a deterministic two-tensor eXtended Streamline Tractography (XST) technique, which successfully traces through regions of crossing fibers. We evaluated the method on simulated and in vivo human brain data, comparing the results with the traditional single-tensor and with a probabilistic tractography technique. By tracing the corticospinal tract and correlating with fMRI-determined motor cortex in both healthy subjects and patients with brain tumors, we demonstrate that two-tensor deterministic streamline tractography can accurately identify fiber bundles consistent with anatomy and previously not detected by conventional single-tensor tractography. When compared to the dense connectivity maps generated by probabilistic tractography, the method is computationally efficient and generates discrete geometric pathways that are simple to visualize and clinically useful. Detection of crossing white matter pathways can improve neurosurgical visualization of functionally relevant white matter areas.
    [bibtex-key = Qazi:2009:Neuroimage:18657622]

  67. P Wintermark, E Roulet-Perez, M Maeder-Ingvar, A C Moessinger, F Gudinchet, and R Meuli. Perfusion abnormalities in hemimegalencephaly. Neuropedatrics, 40(2):92-6 2009. [WWW] [doi: 10.1055/s-0029-1237721]
    Abstract:
    INTRODUCTION: Cerebrovascular changes are rarely discussed in patients with hemimegalencephaly. These alterations have previously been associated with epileptical activity. CASE: We report the case of a 36-week gestation neonate presenting with total right hemimegalencephaly, as demonstrated by a magnetic resonance imaging (MRI) performed in the first days of life. Perfusion-weighted imaging displayed a clear hypervascularization of the right hemisphere. Diffusion-tensor imaging showed an arrangement of white matter fibers concentrically around the ventricle on the right hemisphere. AngioMRI showed an obvious asymmetry in the size of the middle cerebral arteries, with the right middle cerebral artery being prominent. The baby was free of clinical seizures during his first week of life. An electroencephalogram at that time displayed an asymmetric background activity, but no electrical seizures. CONCLUSION: Perfusion anomalies in hemimegalencephaly may not necessarily be related to epileptical activity, but may be related to vessel alterations.
    [bibtex-key = Wintermark:2009:Neuropediatrics:19809940]

  68. R O Suarez, S Whalen, A P Nelson, Y Tie, M E Meadows, A Radmanesh and A J Golby. Threshold-independent functional MRI determination of language dominance: a validation study against clinical gold standards. Epilepsy Behav., 16(2):288-97 2009. [WWW] [doi: 10.1016/j.yebeh.2009.07.034]
    Abstract:
    Functional MRI (fMRI) is often used for presurgical language lateralization. In the most common approach, a laterality index (LI) is calculated on the basis of suprathreshold voxels. However, strong dependencies between LI and threshold can diminish the effectiveness of this technique; in this study we investigated an original methodology that is independent of threshold. We compared this threshold-independent method against the common threshold-dependent method in 14 patients with epilepsy who underwent Wada testing. In addition, clinical results from electrocortical language mapping and postoperative language findings were used to assess the validity of the fMRI lateralization method. The threshold-dependent methodology yielded ambiguous or incongruent lateralization outcomes in 4 of 14 patients in the inferior frontal gyrus (IFG) and in 6 of 14 patients in the supramarginal gyrus (SMG). Conversely, the threshold-independent method yielded unambiguous lateralization in all the patients tested, and demonstrated lateralization outcomes incongruent with clinical standards in 2 of 14 patients in IFG and in 1 of 14 patients in SMG. This validation study demonstrates that the threshold-dependent LI calculation is prone to significant within-patient variability that could render results unreliable; the threshold-independent method can generate distinct LIs that are more concordant with gold standard clinical findings.
    [bibtex-key = Suarez:2009:Epilepsy-Behav:19733509]

  69. Y Tie, R O Suarez, S Whalen, A Radmanesh, I H Norton and A J Golby. Comparison of blocked and event-related fMRI related designs for pre-surgical language mapping. NeuroImage, 47(Suppl 2):T107-15 2009. [WWW] [doi: 10.1016/j.neuroimage.2008.11.020]
    Abstract:
    Language functional magnetic resonance imaging (fMRI) is a promising non-invasive technique for pre-surgical planning in patients whose lesions are adjacent to or within critical language areas. Most language fMRI studies in patients use blocked experimental design. In this study, we compared a blocked design and a rapid event-related design with a jittered inter-stimulus-interval (ISI) (or stochastic design) for language fMRI in six healthy controls, and eight brain tumor patients, using a vocalized antonym generation task. Comparisons were based on visual inspection of fMRI activation maps and degree of language lateralization, both of which were assessed at a constant statistical threshold for each design. The results indicated a relatively high degree of discordance between the two task designs. In general, the event-related design provided maps with more robust activations in the putative language areas than the blocked design, especially for brain tumor patients. Our results suggest that the rapid event-related design has potential for providing comparable or even higher detection power over the blocked design for localizing language function in brain tumor patients, and therefore may be able to generate more sensitive language maps. More patient studies, and further investigation and optimization of language fMRI paradigms will be needed to determine the utility and validity of this approach for pre-surgical planning.
    [bibtex-key = Tie:2009:Neuroimage:19101639]

  70. T Laswad, P Wintermark, L Alamo, A Moessinger, R Meuli, and F Gudinchet. Method for performing cerebral perfusion-weighted MRI in neonates. Pediatr. Radiol., 39(3):260-4 2009. [WWW] [doi: 10.1007/s00247-008-1081-9]
    Abstract:
    Cerebral perfusion-weighted imaging (PWI) in neonates is known to be technically difficult and there are very few published studies on its use in preterm infants. In this paper, we describe one convenient method to perform PWI in neonates, a method only recently used in newborns. A device was used to manually inject gadolinium contrast material intravenously in an easy, quick and reproducible way. We studied 28 newborn infants, with various gestational ages and weights, including both normal infants and those suffering from different brain pathologies. A signal intensity-time curve was obtained for each infant, allowing us to build perfusion maps. This technique offered a fast and easy method to manually inject a bolus gadolinium contrast material, which is essential in performing PWI in neonates. Cerebral PWI is technically feasible and reproducible in neonates of various gestational age and with various pathologies.
    [bibtex-key = Laswad:2009:Pediatr-Radiol:19104796]

  71. M S De Craene, B Macq, F Marques, P Salembier, and S K Warfield Unbiased Group-wise Alignment by Iterative Central Tendency Estimation. Math. Model. Nat. Phenom., 3(6):2-32 2008. [PDF]
    Abstract:
    This paper introduces a new approach for the joint alignment of a large collection of segmented images into the same system of coordinates while estimating at the same time an optimal common coordinate system. The atlas resulting from our group-wise alignment algorithm is obtained as the hidden variable of an Expectation-Maximization (EM) estimation. This is achieved by identifying the most consistent label across the collection of images at each voxel in the common frame of coordinates. In an iterative process, each subject is iteratively aligned with the current probabilistic atlas until convergence of the estimated atlas is reached. Two different transformation models are successively applied in the alignment process: an affine transformation model and a dense non-rigid deformation field. The metric for both transformation models is the mutual information that is computed between the probabilistic atlas and each subject. This metric is optimized in the affine alignment step using a gradient based stochastic optimization (SPSA) and with a variational approach to estimate the non-rigid atlas to subject transformations. A first advantage of our method is that the computational cost increases linearly with the number of subjects in the database. This method is therefore particularly suited for a large number of subjects. Another advantage is that, when computing the common coordinate system, the estimation algorithm identifies weights for each subject on the basis of the typicality of the segmentation. This makes the common coordinate system robust to outliers in the population. Several experiments are presented in this paper to validate our atlas construction method on a population of 80 brain images segmented into 4 labels (background, white and gray matters and ventricles). First, the 80 subjects were aligned using affine and dense non-rigid deformation models. The results are visually assessed by examining how the population converges closer to a central tendency when the deformation model allows more degrees of freedom (from affine to dense non-rigid field). Second, the stability of the atlas construction procedure for various sizes of population was investigated by starting from a subset of the total population which was incrementally augmented until the total population of 80 subjects was reached. Third, the consistency of our group-wise reference (hidden variable of the EM algorithm) was also compared to the choice of an arbitrary subject for a subset of 10 subjects. According to William’s index, our reference choice performed favorably. Finally, the performance of our algorithm was quantified on a synthetic population of 10 subjects (generated using random B-Spline transformations) using a global overlap measure for each label. We also measured the robustness of this measure to the introduction of noisy subjects in the population.


  72. Ž Špiclin, A Hans, F H Duffy, S K Warfield, B Likar, and F Pernus. EEG to MRI registration based on global and local similarities of MRI intensity distributions. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 11(Pt 1): 762-70 2008. [WWW] [PDF]
    Abstract:
    In this paper, a novel method for EEG to MRI registration is proposed. Initial registration is achieved by extracting and matching symmetry planes of MRI and EEG data, followed by iterative registration based on minimizing a cost function. Comparison of the intensity distributionsof the whole MR image and MRI voxels around a head surface point yields global similarities, while the comparison of intensity distributions of MRI voxels around corresponding EEG points, which reflects the head’s sagittal symmetry, yields local similarities. Therefore, when the EEG points are registered to the MR image, maximal global and local similarities should be obtained. The cost function, incorporating global and local similarities, was the sum of Kullback-Leibler divergences between corresponding intensity distributions. The proposed method was evaluated on clinical MRI data with simulated EEG data, yielding mean registration error of 0.48±0.33 mm, while with real EEG data an average root-mean-square point-to-surface error of 2.27±0.02 mm was obtained.


  73. O Commowick. P Fillard, O Clatz, and S K Warfield Detection of DTI White Matter Abnormalities in Multiple Sclerosis Pateints. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 11(Pt 1):975-982 2008 [WWW] [PDF]
    Abstract:
    The emergence of new modalities such as Diffusion Tensor Imaging (DTI) is of great interest for the characterization and the temporal study of Multiple Sclerosis (MS). DTI indeed gives information on water diffusion within tissues and could therefore reveal alterations in white matter fibers before being visible in conventional MRI. However, recent studies generally rely on scalar measures derived from the tensors such as FA or MD instead of using the full tensor itself. Therefore, a certain amount of information is left unused. In this article, we present a framework to study the benefits of using the whole diffusion tensor information to detect statistically significant differences between each individual MS patient and a database of control subjects. This framework, based on the comparison of the MS patient DTI and a mean DTI atlas built from the control subjects, allows us to look for differences both in normally appearing white matter but also in and around the lesions of each patient. We present a study on a database of 11 MS patients, showing the ability of the DTI to detect not only significant differences on the lesions but also in regions around them, enabling an early detection of an extension of the MS disease.


  74. S K Warfield, K H Zou, and W M Wells. Validation of image segmentation by estimating rater bias and variance. Phil. Trans. R. Soc. A, 366(1874):2361-75, April 2008 [WWW] [doi: 10.1098/rsta.2008.0040] [PDF]
    Abstract:
    The accuracy and precision of segmentations of medical images has been difficult to quantify in the absence of a 'ground truth' or reference standard segmentation for clinical data. Although physical or digital phantoms can help by providing a reference standard, they do not allow the reproduction of the full range of imaging and anatomical characteristics observed in clinical data.An alternative assessment approach is to compare with segmentations generated by domain experts. Segmentations may be generated by raters who are trained experts or by automated image analysis algorithms. Typically, these segmentations differ due to intra-rater and inter-rater variability. The most appropriate way to compare such segmentations has been unclear.We present here a new algorithm to enable the estimation of performance characteristics, and a true labelling, from observations of segmentations of imaging data where segmentation labels may be ordered or continuous measures. This approach may be used with, among others, surface, distance transform or level-set representations of segmentations, and can be used to assess whether or not a rater consistently overestimates or underestimates the position of a boundary.
    [bibtex-key = Warfield:2008:Philos-Transact-A-Math-Phys-Eng-Sci:18407896]

  75. D K Thompson, S J Wood, L W Doyle, S K Warfield, G A Lodygensky, P J Anderson, G F Egan, and T E Inder. Neonate Hippocampal Volumes: Prematurity, Perinatal Predictors, and 2-Year Outcome. Annals of Neurology, 63(5):642-51, April 2008 [WWW] [doi: 10.1002/ana.21367] [PDF]
    Abstract:
    OBJECTIVE: To compare preterm (PT) and full-term (FT) infant hippocampal volumes and to investigate the relations among PT hippocampal volume, perinatal risk factors, and neurodevelopmental outcome. METHODS: A total of 184 PTand 32 full-term infants underwent magnetic resonance imaging at term equivalent age with manual segmentation of the hippocampi on coronal slices. Perinatal data were collected and 2-year neurodevelopment was evaluated with the Mental Development Index and Psychomotor Development Index on the Bayley Scales of Infant Development. RESULTS: PT and FT infant hippocampi did not significantly differ after controlling for head size, and percentage reductions in PT hippocampi (3.4%) were less than for cortical (7%) and deep nuclear gray matter (13%), and total brain tissue volume (4.7%). PT hippocampal volumes were significantly lower in infants with moderate-to-severe white matter injury (p < 0.001), exposure to postnatal steroids (right, p = 0.001; left, p = 0.008), and indomethacin treatment (right, p = 0.01; left, p = 0.03). PT infant hippocampal volumes correlated with the Mental (p < 0.001) and Psychomotor Development Indices (right, p = 0.001; left, p = 0.002) after correcting for head size and sex, but remained significant only for the Mental Development Index and left hippocampi (p = 0.04) after additionally adjusting for white matter injury and steroids. INTERPRETATION: Hippocampal volumes were reduced in PT infants exposed to several perinatal events but were preserved in PT infants without these exposures. SmallerPT hippocampal volumes were indirectly associated with delayed development at 2 years.
    [bibtex-key = Thompson:2008:Ann-Neurol:18384167]

  76. G A Lodygensky, M L Seghier, S K Warfield, C B Tolsa, S Sizonenko, F Lazeyras, and P S Hueppi. Intrauterine Growth Restriction Affects the Preterm Infant's Hippocampus. Pediatr Res., 63(4): 438-443 April 2008 [WWW] [doi: 10.1203/PDR.0b013e318165c005] [PDF]
    Abstract:
    The hippocampus is known to be vulnerable to hypoxia, stress, and undernutrition, all likely to be present in fetal intrauterine growth restriction (IUGR). The effect of IUGR in preterm infants on the hippocampus was studied using 3D magnetic resonance imaging at term-equivalent age Thirteen preterm infants born with IUGR after placental insufficiency were compared with 13 infants with normal intrauterine growth age matched for gestational age. The hippocampal structural differences were defined using voxel-based morphometry and manual segmentation. The specific neurobehavioral function was evaluated by the Assessment of Preterm Infants' Behavior at term and at 24 mo of corrected age by a Bayley Scales of Infant and Toddler Development. Voxel-based morphometry detected significant gray matter volume differences in the hippocampus between the two groups. This finding was confirmed by manual segmentation of the hippocampus with a reduction of hippocampal volume after IUGR. The hippocampal volume reduction was further associated with functional behavioral differences at term-equivalent age in all six subdomains of the Assessment of Preterm Infants' Behavior but not at 24 mo of corrected age. We conclude that hippocampal development in IUGR is altered and might result from a combination of maternal corticosteroid hormone exposure, hypoxemia, and micronutrient deficiency.
    [bibtex-key = Lodygensky:2008:Pediatr-Res:18356754]


  77. M J Rivkin, P E Davis, J L Lemaster, H J Cabral, S K Warfield, R V Mulkern, C D Robson, R Rose-Jacobs, and D A Frank Volumetric MRI study of brain in children with intrauterine exposure to cocaine, alcohol, tobacco, and marijuana. Pediatrics 121(4): 741-50 April 2008 [WWW] [doi: 10.1542/peds.2007-1399] [PDF]
    Abstract:
    OBJECTIVE: The objective of this study was to use volumetric MRI to study brain volumes in 10- to 14-year-old children with and without intrauterine exposure to cocaine, alcohol, cigarettes, or marijuana. METHODS: Volumetric MRI was performed on 35 children (mean age: 12.3 years; 14 with intrauterine exposure to cocaine, 21 with no intrauterine exposure to cocaine) to determine the effect of prenatal drug exposure on volumes of cortical gray matter; white matter; subcortical gray matter; cerebrospinal fluid; and total parenchymal volume. Head circumference was also obtained. Analyses of each individual substance were adjusted for demographic characteristics and the remaining 3 prenatal substance exposures. RESULTS: Regression analyses adjusted for demographic characteristics showed that children with intrauterine exposure to cocaine had lower mean cortical gray matter and total parenchymal volumes and smaller mean head circumference than comparison children. After adjustment for other prenatal exposures, these volumes remained smaller but lost statistical significance. Similar analyses conducted forprenatal ethanol exposure adjusted for demographics showed significant reduction in mean cortical gray matter; total parenchymal volumes; and head circumference, which remained smaller but lost statistical significance after adjustment for the remaining 3 exposures. Notably, prenatal cigarette exposure was associated with significant reductions in cortical gray matter and total parenchymal volumes and head circumference after adjustment for demographics that retained marginal significance after adjustment for the other 3 exposures. Finally, as the number of exposures to prenatal substances grew, cortical gray matter and total parenchymal volumes and head circumference declined significantly with smallest measures found among children exposed to all 4. CONCLUSIONS; These data suggest that intrauterine exposures to cocaine, alcohol, and cigarettes are individually related to reduced head circumference; cortical gray matter; and total parenchymal volumes as measured by MRI at school age. Adjustment for other substance exposures precludes determination of statistically significant individual substance effect on brain volume in this small sample; however, these substances may act cumulatively during gestation to exert lasting effects on brain size and volume.
    [bibtex-key = Rivkin:2008:Pediatrics:18381539]


  78. J J Wisco, D L Rosene, R J Killiany, M B Moss, S K Warfield, S Egorova, Y Wu, Z Liptak, J Warner, and C R Guttmann. A rhesus monkey reference label atlas for template driven segmentation. J Med Primatol., 37(5):250-60, October 2008 [WWW] [doi:10.1111/j.1600-0684.2008.00288.x] [PDF]
    Abstract:
    Background: We have acquired dual-echo spin-echo (DE SE) MRI data of the rhesus monkey brain since 1994 as part of an ongoing study of normal aging. To analyze these legacy data for regional volume changes, we have created a reference label atlas for the Template Driven Segmentation (TDS) algorithm. Methods The atlas was manually created from DE SE legacy MRI data of one behaviorally normal, young, male rhesus monkey and consisted of 14 regions of interest (ROI's). We analyzed the reproducibility and validity of the TDS algorithm using the atlas relative to manual segmentation. Results ROI volumes were comparable between the two segmentation methodologies, except TDS overestimated the volume of basal ganglia regions. Both methodologies were highly reproducible, but TDS had lower sensitivity and comparable specificity. Conclusions TDS segmentation calculates accurate volumes for most ROI's. Sensitivity will be improved in future studies through the acquisition of higher quality data.
    [bibtex-key = Wisco:2008:J-Med-Primatol:18466282]


  79. J J Wisco, R J Killiany, C R Guttmann, S K Warfield, M B Moss, and D L Rosene. An MRI study of age-related white and gray matter volume changes in the rhesus monkey. Neurobiol Aging, 29(10):1563-75 October 2008 [WWW] [doi: 10.1016/j.neurobiolaging.2007.03.022] [PDF]
    Abstract:
    We applied the automated MRI segmentation technique Template Driven Segmentation (TDS) to dual-echo spin echo (DE SE) images of eight young (5-12 years), six middle-aged (16-19 years) and eight old (24-30 years) rhesus monkeys. We analyzed standardized mean volumes for 18 anatomically defined regions of interest (ROI's) and found an overall decrease from young to old age in the total forebrain (5.01%), forebrain parenchyma (5.24%), forebrain white matter (11.53%), forebrain gray matter (2.08%), caudate nucleus (11.79%) and globus pallidus (18.26%). Corresponding behavioral data for five of the young, five of the middle-aged and seven of the old subjectson the Delayed Non-matching to Sample (DNMS) task, the Delayed-recognition Span Task (DRST) and the Cognitive Impairment Index (CII) were also analyzed. We found that none of the cognitive measures were related to ROI volume changes in our sample size of monkeys.
    [bibtex-key = Wisco:2007:Neurobiol-Aging:17459528]

  80. J Dubois, M Benders, C Borradori-Tolsa, A Cachia, F Lazeyras, R Ha-Vinh Leuchter, S V Sizonenko, S K Warfield, J F Mangin, and P S Huppi. Primary cortical folding in the human newborn: an early marker of later functional development. Brain, 131:2028-2041, August 2008 [WWW] [doi: 10.1093/brain/awn137] [PDF]
    Abstract:
    In the human brain, the morphology of cortical gyri and sulci is complex and variable among individuals, and it may reflect pathological functioning with specific abnormalities observed in certain developmental and neuropsychiatric disorders. Since cortical folding occurs early during brain development, these structural abnormalities might be present long before the appearance of functional symptoms. So far, the precise mechanisms responsible for such alteration in the convolution pattern during intra-uterine or post-natal development are still poorly understood. Here we compared anatomical and functional brain development in vivo among 45 premature newborns who experienced different intra-uterine environments: 22 normal singletons, 12 twins and 11 newborns with intrauterine growth restriction (IUGR). Using magnetic resonance imaging (MRI) and dedicated post-processing tools, we investigated early disturbances in cortical formation at birth, over the developmental period critical for the emergence of convolutions (26-36 weeks of gestational age), and defined early 'endophenotypes' of sulcal development. We demonstrated that twins have a delayed but harmonious maturation, with reduced surface and sulcation index compared to singletons, whereas the gyrification of IUGR newborns is discordant to the normal developmental trajectory, with a more pronounced reduction of surface in relation to the sulcation index compared to normal newborns. Furthermore, we showed that these structural measurements of the brain at birth are predictors of infants' outcome at term equivalent age, for MRI-based cerebral volumes and neurobehavioural development evaluated with the assessment of preterm infant's behaviour (APIB).
    [bibtex-key = Dubois:2008:Brain:18587151]


  81. N Archip, O Clatz, S Whalen, S P Dimaio, P M Black, F A Jolesz, A Golby, and S K Warfield. Compensation of geometric distortion effects on intraoperative magnetic resonance imaging for enhanced visualization in image-guided neurosurgery. Neurosurgery, 62(3 Suppl 1): 209-15; discussion 215-6 March 2008 [WWW] [doi: 10.1227/01.neu.0000317395.08466.e6] [PDF]
    Abstract:
    OBJECTIVE: Preoperative magnetic resonance imaging (MRI), functional MRI, diffusion tensor MRI, magnetic resonance spectroscopy, and positron-emission tomographic scans may be aligned to intraoperative MRI to enhance visualization and navigation during image-guided neurosurgery. However, several effects (both machine- and patient-induced distortions) lead to significant geometric distortion of intraoperative MRI. Therefore, a precise alignment of these image modalities requires correction of the geometric distortion. We propose and evaluate a novel method to compensate for the geometric distortion of intraoperative 0.5-T MRI in image-guided neurosurgery. METHODS: In this initial pilot study, 11 neurosurgical procedures were prospectively enrolled. The scheme used to correct the geometric distortion is based on a nonrigid registration algorithm introduced by our group. This registration scheme uses image features to establish correspondence between images. It estimates a smooth geometric distortion compensation field by regularizing the displacements estimated at the correspondences. A patient-specific linear elastic material model is used to achieve the regularization. The geometry of intraoperative images (0.5 T) is changed so that the images match the preoperative MRI scans (3 T). RESULTS: We compared the alignment between preoperative and intraoperative imaging using 1) only rigid registration without correction of the geometric distortion, and 2) rigid registration and compensation for the geometric distortion. We evaluated the success of the geometric distortion correction algorithm by measuring the Hausdorff distance between boundaries in the 3-T and 0.5-T MRIs after rigid registration alone and with the addition of geometric distortion correction of the 0.5-T MRI. Overall, the mean magnitude of the geometric distortion measured on the intraoperative images is 10.3 mm with a minimum of 2.91 mm and a maximum of 21.5 mm. The measured accuracy of the geometric distortion compensation algorithm is 1.93 mm. There is a statistically significant difference between the accuracy of the alignment of preoperative and intraoperative images, both with and without the correction of geometric distortion (P < 0.001). CONCLUSION: The major contributions of this study are 1) identification of geometric distortion of intraoperative images relative to preoperative images, 2) measurement of the geometric distortion, 3) application of nonrigid registration to compensate for geometric distortion during neurosurgery, 4) measurement of residual distortion after geometric distortion correction, and 5) phantom study to quantify geometric distortion.
    [bibtex-key = Archip:2008:Neurosurgery:18424988]


  82. L Hoyte, M S Damaser, S K Warfield, G Chukkapalli, A Majumdar, D J Choi, A Trivedi, and P Krysl. Quantity and distribution of levator ani stretch during simulated vaginal childbirth. Am J Obstet Gynecol., 199(2):198.e1-198.e5, August 2008 [WWW] [doi: 10.1016/j.ajog.2008.04.027] [PDF]
    Abstract:
    OBJECTIVE: The objective of the study was to develop a model of the female pelvic floor to study levator stretch during simulated childbirth. STUDY DESIGN: Magnetic resonance data from an asymptomatic nulligravida were segmented into pelvic muscles and bones to create a simulation model. Stiffness estimates of lateral and anteroposterior levator attachments were varied to estimate the impact on levator stretch. A 9 cm sphere was passed through the pelvis, along the path of the vagina, simulating childbirth. Levator response was interpreted at 4 positions of the sphere, simulating fetal head descent. The levator was color mapped to display the stretch experienced. RESULTS: A maximum stretch ratio of 3.5 to 1 was seen in the posteriomedial puborectalis. Maximum stretch increased with increasing stiffness of lateral levator attachments. CONCLUSION: Although preliminary, this work may help explain epidemiologic data regarding the pelvic floor impact of a first delivery. The models and simulation technique need refinement, but they may help study the effect of labor parameters on the pelvic floor.
    [bibtex-key = Hoyte:2008:Am-J-Obstet-Gynecol:18513684]


  83. P Wintermark, A C Moessinger, F Gudinchet, and R Meuli. Perfusion-weighted magnetic resonance imaging patterns of hypoxic-ischemic encephalopathy in term neonates. J Magn Reson Imaging, 28(4):1019-25 2008. [WWW] [doi: 10.1002/jmri.21525]
    Abstract:
    PURPOSE: To determine whether an early magnetic resonance imaging (MRI) study using perfusion-weighted imaging (PWI) may define the pattern of brain injury in term neonatal hypoxic-ischemic (HI) encephalopathy. MATERIALS AND METHODS: Five newborns with HI encephalopathy or a marker of perinatal depression, and 2 controls underwent an early MRI (at 2 to 4 days), including PWI. Relative cerebral blood flow (rCBF) values were measured. RESULTS: On early PWI-MRI, marked hyperperfusion was seen in areas of HI brain damage, allowing the classification of the children into different patterns according to the predominant site of injury: 1 with a "normal pattern"; 1 with a "watershed pattern" with increased rCBF ratios in white matter; 1 with a "basal ganglia pattern" with increased rCBF ratios in basal ganglia; and 2 with a "total cortical pattern" with increased rCBF ratios in cortical gray matter, white matter, and basal ganglia. These patterns were confirmed in all infants on late (9 to 11 days) conventional MRI (T2-weighted images) (4 of 5 patients) or on postmortem examination (1 of 5 patients). CONCLUSION: PWI is technically feasible in neonates with HI encephalopathy in a reproducible way, permitting comparisons between children. It provides a practical means to identify early after birth the future definitive ischemic areas that may be shown on conventional MRI only later.
    [bibtex-key = Wintermark:2008:J-Magn-Reson-Imaging:18821602]

  84. R O Suarez, S Whalen, J P O'Shea, and A J Golby. A surgical planning method for functional MRI assessment of language dominance: Influences from threshold, region-of-interest, and stimulus mode. Brain Imaging and Behavior, 2(2):59-73 2008.
    Abstract:
    Presurgical determination of language laterality is an important step for assessing potential risk of dysfunction resulting from brain resection within or near suspected language areas. Image-based functional MRI (fMRI) methods seek to address limitations to the clinical gold-standard technique by offering a safer, less costly, and non-invasive alternative. In this study we outline a set of protocols for objective determination of langue-specific asymmetry from fMRI activation maps. We studied 13 healthy, right-handed volunteers using a vocalized antonym-generation task. Initially, using the standard threshold-dependent laterality index (LI) procedure, we demonstrated an undesirably high degree of intra-subject variability and indeterminacy in LI value. We addressed this issue by implementing a novel threshold-independent method, resulting in a single, unambiguous LI for each subject. These LIs were then averaged across the group and used to compare functional laterality within the whole hemispheric volumes and six intra-hemispheric regions-of-interest (ROIs). We noted that as a result of increased bilateral activation from vocalizations, laterality assessment calculated from the whole hemisphere resulted in insignificant asymmetry. However, by focusing the LI exclusively on the inferior frontal (IFG) and supramarginal gyri (SMG), robust leftward asymmetries were observed. We also examined the influence of stimulus mode on the group mean ROI LI, and observed an increase in IFG asymmetry using visual mode, and in SMG using the auditory mode. Based on these findings, we make recommendations for optimized presurgical protocols.


  85. P Wintermark, A C Moessinger, F Gudinchet, and R Meuli. Temporal evolution of MR perfusion in neonatal hypoxic-ischemic encephalopathy. J Magn Reson Imaging, 27(6):1229-34 2008. [WWW] [doi: 10.1002/jmri.21379]
    Abstract:
    PURPOSE: To illustrate the evolution of brain perfusion-weighted magnetic resonance imaging (PWI-MRI) in severe neonatal hypoxic-ischemic (HI) encephalopathy, and its possible relation to further neurodevelopmental outcome. MATERIALS AND METHODS: Two term neonates with HI encephalopathy underwent an early and a late MRI, including PWI. They were followed until eight months of age. A total of three "normal controls" were also included. Perfusion maps were obtained, and relative cerebral blood flow (rCBF) and cerebral blood volume (rCBV) values were measured. RESULTS: Compared to normal neonates, a hyperperfusion (increased rCBF and rCBV) was present on early scans in the whole brain. On late scans, hyperperfusion persisted in cortical gray matter (normalization of rCBF and rCBV ratios in white matter and basal ganglia, but not in cortical gray matter). Diffusion-weighted imaging (DWI) was normalized, and extensive lesions became visible on T2-weighted images. Both patients displayed very abnormal outcome: Patient 2 with the more abnormal early and late hyperperfusion being the worst. CONCLUSION: PWI in HI encephalopathy did not have the same temporal evolution as DWI, and remained abnormal for more than one week after injury. This could be a marker of an ongoing mechanism underlying severe neonatal HI encephalopathy. Evolution of PWI might help to predict further neurodevelopmental outcome.
    [bibtex-key = Wintermark:2008:J-Magn-Reson-Imaging:18504740]

  86. N Archip, F A Jolesz, and S K Warfield. A validation framework for brain tumor segmentation. Acad Radiol., 14(10): 1242-51 October 2007 [WWW] [doi: 10.1016/j.acra.2007.05.025] [PDF]
    Abstract:
    RATIONALE AND OBJECTIVES: We introduce a validation framework for the segmentation of brain tumors from magnetic resonance (MR) images. A novel unsupervised semiautomatic brain tumor segmentation algorithm is also presented. MATERIALS AND METHODS: The proposed framework consists of 1) T1-weighted MR images of patients with brain tumors, 2) segmentation of brain tumors performed by four independent experts, 3) segmentation of brain tumors generated by a semiautomatic algorithm, and 4) a software tool that estimates the performance of segmentation algorithms. RESULTS: We demonstrate the validation of the novel segmentation algorithm within the proposed framework. We show its performance and compare it with existent segmentation. The image datasets and software are available at http://www.brain-tumor-repository.org/. CONCLUSIONS: We present an Internet resource that providesaccess to MR brain tumor image data and segmentation that can be openly used by the research community. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image dahuman expert segmentation results, and methods for comparing segmentation results.
    [bibtex-key = Archip:2007:Acad-Radiol:17889341]


  87. J Dauguet, S Peled, V Berezovskii, T Delzescaux, S K Warfield, R Born, and C F Westin. Comparison of fiber tracts derived from in-vivo DTI tractography with 3D histological neural tract tracer reconstruction on a macaque brain. Neuroimage., 37(2): 530-8 August 2007 [WWW] [doi: 10.1016/j.neuroimage.2007.04.067]
    Abstract:
    Since the introduction of diffusion weighted imaging (DWI) as a method for examining neural connectivity, its accuracy has not been formally evaluated. In this study, we directly compared connections that were visualized using injected neural tract tracers (WGA-HRP) with those obtained using in-vivo diffusion tensor imaging (DTI) tractography. First, we injected the tracer at multiple sites in the brain of a macaque monkey; second, we reconstructed the histological sections of the labeled fiber tracts in 3D; third, we segmented and registered the fibers (somatosensory and motor tracts) with the anatomical in-vivo MRI from the same animal; and last, we conducted fiber tracing along the same pathways on the DTI data using a classical diffusion tracing technique with the injection sites as seeds. To evaluate the performance of DTI fiber tracing, we compared the fibers derivedfrom the DTI tractography with those segmented from the histology. We also studied the influence of the parameters controlling the tractography by comparing Dice superimposition coefficients between histology and DTI segmentations. While there was generally good visual agreement between the two methods, our quantitative comparisons reveal certain limitations of DTI tractography, particularly for regions at remote locations from seeds. We have thus demonstrated the importance of appropriate settings for realistic tractography results.
    [bibtex-key = Dauguet:2007:Neuroimage:17604650]


  88. A U Mewes, L Zoellei, P S Hueppi, H Als, G B McAnulty, T E Inder, W M Wells, and S K Warfield. Displacement of brain regions in preterm infants with non-synostotic dolichocephaly investigated by MRI. Neuroimage., 36(4): 1074-85 July 2007 [WWW] [doi: 10.1016/j.neuroimage.2007.04.011]
    Abstract:
    Regional investigations of newborn MRI are important to understand the appearance and consequences of early brain injury. Previously, regionalization in neonates has been achieved with a Talairach parcellation, using internallandmarks of the brain. Non-synostotic dolichocephaly defines a bi-temporal narrowing of the preterm infant's head caused by pressure on the immature skull. The impact of dolichocephaly on brain shape and regional brain shift, which may compromise the validity of the parcellation scheme, has not yet been investigated. Twenty-four preterm and 20 fullterm infants were scanned at term equivalent. Skull shapes were investigated by cephalometric measurements and population registration. Brain tissue volumes were calculated to rule out brain injury underlying skull shape differences. The position of Talairach landmarks was evaluated. Cortical structures were segmentedto determine a positional shift between both groups. The preterm group displayed dolichocephalic head shapes and had similar brain volumes compared to the mesocephalic fullterm group. In preterm infants, Talairach landmarks were consistently positioned relative to each other and to the skull base, but were displaced with regard to the calvarium. The frontal and superior region was enlarged; central and temporal gyri and sulciwere shifted comparing preterm and fullterm infants. We found that, in healthy preterm infants, dolichocephaly led to a shift of cortical structures, but did not influence deep brain structures. We concluded that the validityof a Talairach parcellation scheme is compromised and may lead to a miscalculation of regional brain volumes and inconsistent parcel contents when comparing infant populations with divergent head shapes.
    [bibtex-key = Mewes:2007:Neuroimage:17513129]


  89. S Alayon, R Robertson, S K Warfield, and J Ruiz-Alzola. A fuzzy system for helping medical diagnosis of malformations of cortical development. J Biomed Inform., 40(3): 221-35 June 2007 [WWW] [doi: 10.1016/j.jbi.2006.11.002]
    Abstract:
    Malformations of the cerebral cortex are recognized as a common cause of developmental delay, neurological deficits, mental retardation and epilepsy. Currently, the diagnosis of cerebral cortical malformations is based on a subjective interpretation of neuroimaging characteristics of the cerebral gray matter and underlying white matter. There is no automated system for aiding the observer in making the diagnosis of a cortical malformation. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available expert knowledge about cortical malformations and assists the medical observer in arriving at a correct diagnosis. Moreover, the system allows the study of the influence of the various factors that take part in the decision. The evaluation of the system has been carried out by comparing the automated diagnostic algorithm with known case examples of various malformations due to abnormal cortical organization. An exhaustive evaluation of the system by comparison with published cases and a ROC analysis is presented in the paper.
    [bibtex-key = Alayon:2007:J-Biomed-Inform:17197247]


  90. N Archip, O Clatz, S Whalen, D Kacher, A Fedorov, A Kot, N Chrisochoides, J Jolesz, A Golby, P M Black, and S K Warfield. Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage., 35(2): 609-24 April 2007 [WWW] [doi: 10.1016/j.neuroimage.2006.11.060] [PDF]
    Abstract:
    OBJECTIVE: The usefulness of neurosurgical navigation with current visualizations is seriously compromised by brain shift, which inevitably occurs during the course of the operation, significantly degrading the precise alignment between the pre-operative MR data and the intra-operative shape of the brain. Our objectives were (i) to evaluate the feasibility of non-rigid registration that compensates for the brain deformations within the timeconstraints imposed by neurosurgery, and (ii) to create augmented reality visualizations of critical structural and functional brain regions during neurosurgery using pre-operatively acquired fMRI and DT-MRI. MATERIALS AND METHODS: Eleven consecutive patients with supratentorial gliomas were included in our study. All underwent surgery at our intra-operative MR imaging-guided therapy facility and have tumors in eloquent brain areas (e.g. precentral gyrus and cortico-spinal tract). Functional MRI and DT-MRI, together with MPRAGE and T2w structural MRI were acquired at 3 T prior to surgery. SPGR and T2w images were acquired with a 0.5 T magnet during each procedure. Quantitative assessment of the alignment accuracy was carried out and compared with current state-of-the-art systems based only on rigid registration. RESULTS: Alignment between pre-operative and intra-operative datasets was successfully carried out during surgery for all patients. Overall, the mean residual displacement remaining after non-rigid registration was 1.82 mm. There is a statistically significant improvement in alignment accuracy utilizing our non-rigid registration in comparison to the currently used technology (p<0.001). CONCLUSIONS: We were able to achieve intra-operative rigid and non-rigid registration of (1) pre-operative structural MRI with intra-operative T1w MRI; (2) pre-operative fMRI with intra-operative T1w MRI, and (3) pre-operative DT-MRI with intra-operative T1w MRI. The registration algorithms as implemented were sufficiently robust and rapid to meet the hard real-time constraints of intra-operative surgical decision making. The validation experiments demonstrate that we can accurately compensate for the deformation of the brain and thus can construct an augmentedreality visualization to aid the surgeon.
    [bibtex-key = Archip:2007:Neuroimage:17289403]


  91. J Fripp, S Crozier, S K Warfield, and S Ourselin. Automatic segmentation of the bone and extraction of the bone-cartilage interface from magnetic resonance images of the knee. Phys Med Biol., 52(6): 1617-31 March 2007 [WWW] [doi: 10.1088/0031-9155/52/6/005]
    Abstract:
    The accurate segmentation of the articular cartilages from magnetic resonance (MR) images of the knee is important for clinical studies and drug trials into conditions like osteoarthritis. Currently, segmentations are obtained using time-consuming manual or semi-automatic algorithms which have high inter- and intra-observer variabilities. This paper presents an important step towards obtaining automatic and accurate segmentations of the cartilages, namely an approach to automatically segment the bones and extract the bone-cartilage interfaces (BCI) in the knee. The segmentation is performed using three-dimensional active shape models, which are initialized using an affine registration to an atlas. The BCI are then extracted using image information and prior knowledge about the likelihood of each point belonging to the interface. The accuracy and robustness of the approach was experimentally validated using an MR database of fat suppressed spoiled gradient recall images. The (femur, tibia, patella) bone segmentation had a median Dice similarity coefficient of (0.96, 0.96, 0.89) and an average point-to-surface error of 0.16 mm on the BCI. The extracted BCI had a median surface overlap of 0.94 with the real interface, demonstrating its usefulness for subsequent cartilage segmentation or quantitative analysis.
    [bibtex-key = Fripp:2007:Phys-Med-Biol:17327652]


  92. K T Downing, L P Hoyte, S K Warfield, and A C Weidner. Racial differences in pelvic floor muscle thickness in asymptomatic nulliparas as seen on magnetic resonance imaging-based three-dimensional color thickness mapping Am J Obstet Gynecol., 197(6): 625.e1-4 December 2007 [WWW] [doi: 10.1016/j.ajog.2007.08.015]
    Abstract:
    OBJECTIVE: The objective of the study was to compare levator and obturator thickness between asymptomatic black and white nulliparas using three-dimensional (3D) magnetic resonance imaging (MRI) color mapping. STUDY DESIGN: 3D color-mapped MRI of pelvic muscles were evaluated in 22 similar nulliparas (12 black, 10 white). Levator and obturator (OI) were divided into right and left. Levator was subdivided into puborectalis (PR) and ileococcygeus (IC) portions. Maximal thickness of each muscle was recorded and compared between groups. Nonparametric testing was applied, with significance at P = .05. RESULTS: Levator thickness was significantly greater in blacks bilaterally (median right PR, 8.5 vs 6.0 mm; P = .001; right IC, 6.5 vs 4.5 mm; P = .002; left PR, 9.5 vs 5.75 mm; P = .0002; left IC, 6.5 vs 5.75 mm; P = .02). Obturator thicknesses were similar (right OI, 20.0 vs 19.5 mm; left OI, 19.25 vs 19.25 mm; P = NS). CONCLUSION: Significantly thicker levators but similar obturators were seen in black nulliparas, compared with white nulliparas. These levator differences may influence pelvic floor dysfunction risk. The clinical significance of these findings is under study.
    [bibtex-key = Downing:2007:Am-J-Obstet-Gynecol:18060955]


  93. M Maddah, W E Grimson, S K Warfield, and W M Wells. A unified framework for clustering and quantitative analysis of white matter fiber tracts. Med Image Anal, October 2007 [WWW] [doi: 10.1016/j.media.2007.10.003] [PDF]
    Abstract:
    We present a novel approach for joint clustering and point-by-point mapping of white matter fiber pathways. Knowledge of the point correspondence along the fiber pathways is not only necessary for accurate clustering of the trajectories into fiber bundles, but also crucial for any tract-oriented quantitative analysis. We employ an expectation-maximization (EM) algorithm to cluster the trajectories in a gamma mixture model context. The result of clustering is the probabilistic assignment of the fiber trajectories to each cluster, an estimate of the cluster parameters, i.e. spatial mean and variance, and point correspondences. The fiber bundles are modeled by the meantrajectory and its spatial variation. Point-by-point correspondence of the trajectories within a bundle is obtained by constructing a distance map and a label map from each cluster center at every iteration of the EM algorithm. This offers a time-efficient alternative to pairwise curve matching of all trajectories with respect to each cluster center. The proposed method has the potential to benefit from an anatomical atlas of fiber tractsby incorporating it as prior information in the EM algorithm. The algorithm is also capable of handling outliers in a principled way. The presented results confirm the efficiency and effectiveness of the proposed framework for quantitative analysis of diffusion tensor MRI.
    [bibtex-key= Maddah:2007:Med-Image-Anal:18180197]

  94. D K Thompson, S K Warfield, J B Carlin, M Pavlovic, H X Wang, M Bear, M J Kean, L W Doyle, G F Egan, and T E Inder. Perinatal risk factors altering regional brain structure in the preterm infant. Brain, 130(Pt 3): 667-77 March 2007. [WWW] [doi:10.1093/brain/awl277]
    Abstract:
    Neuroanatomical structure appears to be altered in preterm infants, but there has been little insight into the major perinatal risk factors associated with regional cerebral structural alterations. MR images were taken to quantitatively compare regional brain tissue volumes between term and preterm infants and to investigate associations between perinatal risk factors and regional neuroanatomical alterations in a large cohort of preterm infants. In a large prospective longitudinal cohort study of 202 preterm and 36 term infants, MR scans at term equivalent were undertaken for volumetric estimates of cortical and deep nuclear grey matter, unmyelinated and myelinated white matter (WM) and CSF within 8 parcellated regions for each hemisphere of the brain. Perinatal correlates analysed in relation to regional brain structure included gender, gestational age, intrauterine growth restriction, bronchopulmonary dysplasia, white matter injury (WMI) and intraventricular haemorrhage. Results revealed region-specific reductions in brain volumes in preterm infants compared with term controls in the parieto-occipital (preterm mean difference: -8.1%; 95% CI = -13.8 to -2.3%), sensorimotor (-11.6%; -18.2 to -5.0%), orbitofrontal (-30.6%; -49.8 to -11.3%) and premotor (-7.6%; -14.2 to -0.9%) regions. Within the sensorimotor and orbitofrontal regions cortical grey matter and unmyelinated WM were most clearly reduced in preterm infants, whereas deep nuclear grey matter was reduced mainly within the parieto-occipital and subgenual regions. CSF (ventricular and extracerebral) was doubled in volume within the superior regions in preterm infants compared with term controls. Cerebral WMI and intrauterine growth restriction were both associated with a more posterior reduction in brain volumes, whereas bronchopulmonary dysplasia was associated with a more global reduction across all regions. In contrast degree of immaturity was not related to regional brain structure among preterm infants. In summary, preterm birth is associated with regional cerebral tissue reductions, with the adverse pattern varying between risk factors. These findings add to our understanding of the potential pathways leading to altered brain structure and outcome in the preterm infant.
    [bibtex-key = Thompson:2006:Brain:17008333]


  95. A Wittek, K Miller, R Kikinis, and S K Warfield. Patient-specific model of brain deformation: Application to medical image registration. J Biomech, 40(4): 919-29 2007. [WWW] [doi:10.1016/j.jbiomech.2006.02.021]
    Abstract:
    This contribution presents finite element computation of the deformation field within the brain during craniotomy-induced brain shift. The results were used to illustrate the capabilities of non-linear (i.e. accounting for both geometric and material non-linearities) finite element analysis in non-rigid registration of pre- and intra-operative magnetic resonance images of the brain. We used patient-specific hexahedron-dominant finite element mesh, together with realistic material properties for the brain tissue and appropriate contact conditions at boundaries. The model was loaded by the enforced motion of nodes (i.e. through prescribed motion of a boundary) at the brain surface in the craniotomy area. We suggest using explicit time-integration scheme for discretised equations of motion, as the computational times are much shorter and accuracy, for practical purposes, the same as in the case of implicit integration schemes. Application of the computed deformation field to register (i.e. align) the pre-operative images with the intra-operative ones indicated that the model very accurately predicts the displacements of the tumour and the lateral ventricles even for limited information about the brain surface deformation. The prediction accuracy improves when information about deformation of not only exposed (during craniotomy) but also unexposed parts of the brain surface is used when prescribing loading. However, it appears that the accuracy achieved using information only about the deformation of the exposed surface, that can be determined without intra-operative imaging, is acceptable. The presented results show that non-linear biomechanical models can complement medical image processing techniques when conducting non-rigid registration. Important advantage of such models over the previously used linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain stress-strain relationship is linear.
    [bibtex-key = Wittek:2006:J-Biomech:16678834]


  96. M Maddah, W M Wells, S K Warfield, C F Westin, and W E Grimson. Probabilistic clustering and quantitative analysis of white matter fiber tracts. Inf Process Med Imaging., 20: 372-83 2007 [WWW]
    Abstract:
    A novel framework for joint clustering and point-by-point mapping of white matter fiber pathways is presented. Accurate clustering of the trajectories into fiber bundles requires point correspondence determined along the fiber pathways. This knowledge is also crucial for any tract-oriented quantitative analysis. We employ an expectation-maximization (EM) algorithm to cluster the trajectories in a Gamma mixture model context. The result of clustering is the probabilistic assignment of the fiber trajectories to each cluster, an estimate of the cluster parameters, and point correspondences along the trajectories. Point-by-point correspondence of the trajectories within a bundle is obtained by constructing a distance map and a label map from each cluster center at every iteration of the EM algorithm. This offers a time-efficient alternative to pairwise curve matching of all trajectories with respect to each cluster center. Probabilistic assignment of the trajectories to clusters is controlled by imposing a minimum threshold on the membership probabilities, to remove outliers in a principled way.The presented results confirm the efficiency and effectiveness of the proposed framework for quantitative analysis of diffusion tensor MRI.
    [bibtex-key = Maddah:2007:Inf-Process-Med-Imaging:17633714]


  97. N Archip, S Tatli, P Morrison, F Jolesz, S K Warfield, and S Silverman. Non-rigid registration of pre-procedural MR images with intra-procedural unenhanced CT images for improved targeting of tumors during liver radiofrequency ablations. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 10(Pt 2): 969-77 2007 [WWW]
    Abstract:
    In the United States, unenhanced CT is currently the most common imaging modality used to guide percutaneous biopsy and tumor ablation. The majority of liver tumors such as hepatocellular carcinomas are visible on contrast-enhanced CT or MRI obtained prior to the procedure. Yet, these tumors may not be visible or may have poor margin conspicuity on unenhanced CT images acquired during the procedure. Non-rigid registration has been usedto align images accurately, even in the presence of organ motion. However, to date, it has not been used clinically for radiofrequency ablation (RFA), since it requires significant computational infrastructure and often thes methods are not sufficient robust. We have already introduced a novel finite element based method (FEM) that is demonstrated to achieve good accuracy and robustness for the problem of brain shift in neurosurgery. In this current study, we adapt it to fuse pre-procedural MRI with intra-procedural CT of liver. We also compare its performance with conventional rigid registration and two non-rigid registration methods: b-spline and demons on 13 retrospective datasets from patients that underwent RFA at our institution. FEM non-rigid registration technique was significantly better than rigid (p < 10-5), non-rigid b-spline (p < 10-4) and demons (p < 10-4) registration techniques. The results of our study indicate that this novel technology may be used to optimize placement of RF applicator during CT-guided ablations.
    [bibtex-key = Archip:2007:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:18044662]


  98. J Dauguet, D Bock, R C Reid, and S K Warfield. Alignment of large image series using cubic B-splines tessellation: application to transmission electron microscopy data. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 10(Pt 2): 710-7 2007 [WWW]
    Abstract:
    3D reconstruction from serial 2D microscopy images depends on non-linear alignment of serial sections. For some structures, such as the neuronal circuitry of the brain, very large images at very high resolution are necessary to permit reconstruction. These very large images prevent the direct use of classical registration methods. We propose in this work a method to deal with the non-linear alignment of arbitrarily large 2D images using the finite support properties of cubic B-splines. After initial affine alignment, each large image is split into a grid of smaller overlapping sub-images, which are individually registered using cubic B-splines transformations. Inside the overlapping regions between neighboring sub-images, the coefficients of the knots controlling the B-splines deformations are blended, to create a virtual large grid of knots for the whole image. The sub-images are resampled individually, using the new coefficients, and assembled together into a final large aligned image. We evaluated the method on a series of large transmission electron microscopy images and our results indicate significant improvements compared to both manual and affine alignment.
    [bibtex-key = Dauguet:2007:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:18044631]


  99. J Fripp, S Crozier, S K Warfield, and S Ourselin. Automatic segmentation of articular cartilage in magnetic resonance images of the knee. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 10(Pt 2): 186-94 2007 [WWW]
    Abstract:
    To perform cartilage quantitative analysis requires the accurate segmentation of each individual cartilage. In this paper we present a model based scheme that can automatically and accurately segment each individual cartilagein healthy knees from a clinical MR sequence (fat suppressed spoiled gradient recall). This scheme consists of three stages; the automatic segmentation of the bones, the extraction of the bone-cartilage interfaces (BCI) and segmentation of the cartilages. The bone segmentation is performed using three-dimensional active shape models. The BCI is extracted using image information and prior knowledge about the likelihood of each point belonging to the interface. A cartilage thickness model then provides constraints and regularizes the cartilage segmentation performed from the BCI. The accuracy and robustness of the approach was experimentally validated, with (patellar,tibial and femoral) cartilage segmentations having a median DSC of (0.870, 0.855, 0.870), performing significantly better than non-rigid registration (0.787, 0.814, 0.795). The total cartilage segmentation had an average DSC of (0.891), close to the (0.896) obtained using a semi-automatic watershed algorithm. The error in quantitative volume and thickness measures was (8.29, 4.94, 5.56)% and (0.19, 0.33, 0.10) mm respectively.
    [bibtex-key = Fripp:2007:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:18044568]


  100. S K Warfield, K H Zou, and W M Wells. Validation of image segmentation by estimating rater bias and variance. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 9(Pt 2): 839-47 2006 [WWW] [PDF]
    Abstract:
    The accuracy and precision of segmentations of medical images has been difficult to quantify in the absence of a "ground truth" or reference standard segmentation for clinical data. Although physical or digital phantoms can help by providing a reference standard, they do not allow the reproduction of the full range of imaging and anatomical characteristics observed in clinical data. An alternative assessment approach is to compare to segmentations generated by domain experts. Segmentations may be generated by raters who are trained experts or by automated image analysis algorithms. Typically these segmentations differ due to intra-rater and inter-rater variability. The most appropriate way to compare such segmentations has been unclear. We present here a new algorithm to enable the estimation of performance characteristics, and a true labeling, from observations of segmentations of imaging data where segmentation labels may be ordered or continuous measures. This approach may be used with, amongst others, surface, distance transform or level set representations of segmentations, and canbe used to assess whether or not a rater consistently over-estimates or under-estimates the position of a boundary.
    [bibtex-key = Warfield:2006:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:17354851]


  101. J Dauguet, S Peled, V Berezovskii, T Delzescaux, S K Warfield, R Born, and C F Westin. 3D histological reconstruction of fiber tracts and direct comparison with diffusion tensor MRI tractography. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 9(Pt 1): 109-16 2006. [WWW]
    Abstract:
    A classical neural tract tracer, WGA-HRP, was injected at multiple sites within the brain of a macaque monkey. Histological sections of the labeled fiber tracts were reconstructed in 3D, and the fibers were segmented and registered with the anatomical post-mortem MRI from the same animal. Fiber tracing along the same pathways was performed on the DTI data using a classical diffusion tracing technique. The fibers derived from the DTI were compared with those segmented from the histology in order to evaluate the performance of DTI fiber tracing. While there was generally good agreement between the two methods, our results reveal certain limitations of DTI tractography, particularly at regions of fiber tract crossing or bifurcation.
    [bibtex-key = Dauguet:2006:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:17354880]


  102. S P Dimaio, N Archip, N Hata, I F Talos, S K Warfield, A Majumdar, N Mcdannold, K Hynynen, P R Morrison, W M Wells, D F Kacher, R E Ellis, A J Golby, P M Black, F A Jolesz, and R Kikinis. Image-guided neurosurgery at Brigham and Women's Hospital. IEEE Eng Med Biol Mag, 25(5):67-73, Sep-Oct 2006. [WWW] [bibtex-key = Dimaio:2006:IEEE-Eng-Med-Biol-Mag:17020201]


  103. A Fedorov, N Chrisochoides, R Kikinis, and S K Warfield. An evaluation of three approaches to tetrahedral mesh generation for deformable registration of brain MR images. Proceedings of the 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2006, 1:658-661, 2006. [PDF]
    Abstract:
    In this paper we evaluate three conceptually different approaches to mesh generation for deformable Finite Element Method (FEM) registration of Magnetic Resonance (MR) images of brain volume. Precise approximation of brain volume segmentations and good shape of the mesh tetrahedra are the main requirements imposed by the application. Our contributions are (1) application-motivated comparison and analysis of practical mesh generation implementations and (2) open source implementation of a mesh generation algorithm, which we show delivers mesh quality comparable with the best commercial software products available. The preliminary results indicate, that our implementation provides a solid foundation for further development of application-specific mesh generation tools.


  104. D Goldberg-Zimring and S K Warfield. Novel image processing techniques to better understand white matter disruption in multiple sclerosis. Autoimmun Rev, 5(8):544-548, October 2006. [WWW] [doi:10.1016/j.autrev.2006.06.003]
    Abstract:
    In Multiple Sclerosis (MS) patients, conventional magnetic resonance imaging (MRI) shows a pattern of white matter (WM) disruption but may also overlook some WM damage. Diffusion tensor MRI (DT-MRI) can provide important in-vivo information about fiber direction that is not provided by conventional MRI. The geometry of diffusion tensors can quantitatively characterize the local structure in tissues. The integration of both conventional MRI and DT-MRI measures together with connectivity-based regional assessment provide a better understanding of the nature and the location of WM abnormalities. Image processing and visualization techniques have been developed and applied to study conventional MRI and DT-MRI of MS patients. These include methods of: Image Segmentation for identifying the different areas of the brain as well as to discriminate normal from abnormal WM, Computerized Atlases, which include structural information obtained from a set of subjects, and Tractographies which can aid in the delineation of WM fiber tracts by tracking connected diffusion tensors. These new techniques hold out the promise of improving our understanding of WM architecture and its disruption in diseases such as MS. In the present study, we review the work that has been done in the development of these techniques and illustrate their applications.
    [bibtex-key = GoldbergZimring:2006:Autoimmun-Rev:17027890]


  105. P Jannin, E Krupinski, and S K Warfield. Validation in medical image processing. IEEE Trans Med Imaging, 25(11):1405-1409, November 2006. [WWW] [bibtex-key = Jannin:2006:IEEE-Trans-Med-Imaging:17117769]


  106. A U Mewes, P S Hüppi, H Als, F J Rybicki, T E Inder, G B McAnulty, R V Mulkern, R L Robertson, M J Rivkin, and S K Warfield. Regional brain development in serial magnetic resonance imaging of low-risk preterm infants. Pediatrics, 118(1):23-33, July 2006. [WWW] [doi:10.1542/peds.2005-2675]
    Abstract:
    OBJECTIVE: MRI studies have shown that preterm infants with brain injury have altered brain tissue volumes. Investigation of preterm infants without brain injury offers the opportunity to define the influence of early birth on brain development and provide normative data to assess effects of adverse conditions on the preterm brain. In this study, we investigated serial MRI of low-risk preterm infants with the aim to identify regions of altered brain development. METHODS: Twenty-three preterm infants appropriate for gestational age without magnetic resonance-visible brain injury underwent MRI twice at 32 and at 42 weeks' postmenstrual age. Fifteen term infants were scanned 2 weeks after birth. Brain tissue classification and parcellation were conducted to allow comparison of regional brain tissue volumes. Longitudinal brain growth was assessed from preterm infants' serial scans. RESULTS: At 42 weeks' postmenstrual age, gray matter volumes were not different between preterm and term infants. Myelinated white matter was decreased, as were unmyelinated white matter volumes in the region including the central gyri. The gray matter proportion of the brain parenchyma constituted 30% and 37% at 32 and 42 weeks' postmenstrual age, respectively. CONCLUSIONS: This MRI study of preterm infants appropriate for gestational age and without brain injury establishes the influence of early birth on brain development. No decreased cortical gray matter volumes were found, which is in contrast to findings in preterm infants with brain injury. Moderately decreased white matter volumes suggest an adverse influence of early birth on white matter development. We identified a sharp increase in cortical gray matter volume in preterm infants' serial data, which may correspond to a critical period for cortical development.
    [bibtex-key = Mewes:2006:Pediatrics:16818545]


  107. D K Shah, P J Anderson, J B Carlin, M Pavlovic, K Howard, D K Thompson, S K Warfield, and T E Inder. Reduction in cerebellar volumes in preterm infants: relationship to white matter injury and neurodevelopment at two years of age. Pediatr Res, 60(1):97-102, July 2006. [WWW] [doi:10.1203/01.pdr.0000220324.27597.f0]
    Abstract:
    A substantial number of prematurely born infants will experience later neurodevelopmental challenges. Abnormal development of the cerebellum may be related to some of the impairments exhibited by preterm children. To test the hypothesis that cerebellar development is structurally impaired in preterm infants and associated with adverse outcomes, we studied 83 preterm infants and 13 term controls using volumetric magnetic resonance imaging techniques to obtain cerebellar volumes (CV) at term corrected and subsequent neurodevelopmental assessment at 2 y of age. The preterm group had smaller mean CV at term compared with the term control infants [mean (SD) CV, 22.0 (5.0) versus 23.5 (5.0) cc; mean difference (95% confidence interval), 1.5 (-1.5, 4.4)] although this did not reach statistical significance. Within the preterm group, there was evidence of a reduction in CV related to the presence of white matter injury (WMI) after adjusting for intracranial volume (ICV) [WMI grade 1 versus grade 2: mean (SD) CV, 23.6 (5.0) versus 21.6 (4.5); p = 0.01; WMI grade 1 versus grade 3 and 4: 23.6 (5.0) versus 20.8 (5.6); p = 0.07]. Within the preterm infants, there was no apparent relationship between CV at term and gestational age at birth after adjusting for ICV. At 2 y of age, CV showed a weak correlation with cognitive and motor development, although this was principally mediated by WMI. In conclusion, we found no evidence for a primary impairment in cerebellar development in relation to prematurity, although there was evidence for a secondary effect of cerebral WMI on cerebellar development independent of immaturity.
    [bibtex-key = Shah:2006:Pediatr-Res:16690952]


  108. D K Shah, C Guinane, P August, N C Austin, L J Woodward, D K Thompson, S K Warfield, R Clemett, and T E Inder. Reduced occipital regional volumes at term predict impaired visual function in early childhood in very low birth weight infants. Invest Ophthalmol Vis Sci, 47(8):3366-3373, August 2006. [WWW] [doi:10.1167/iovs.05-0811]
    Abstract:
    PURPOSE: Premature infants are at increased risk of impaired visual performance related to both cortical and subcortical pathways for oculomotor control. The hypothesis for the current study was that preterm infants with impaired saccades, smooth pursuit, and binocular eye alignment at age 2 years would have smaller occipital brain volumes at term equivalent, as measured by volumetric magnetic resonance (MR) techniques, than would preterm infants without such abnormalities. METHODS: Study participants consisted of 68 infants from a representative regional cohort of 100 preterm infants born between 23 and 33 weeks' gestation. At term equivalent, all infants underwent MR imaging, and the images were coregistered, tissue segmented into five cerebral tissue subtypes, and further subdivided into eight regions for each hemisphere. At 2 years corrected, all infants completed a comprehensive orthoptic evaluation performed by a single examiner. RESULTS: Twenty-four (35%) of the 68 infants had abnormal oculomotor control at 2 years, including abnormalities in saccadic movements (n = 7), smooth pursuit (n = 14), or strabismus (n = 9, four with esotropia and five with exotropia). When compared with preterm infants without visuomotor impairment, these infants had significantly smaller inferior occipital region brain tissue volumes bilaterally (n = 24 vs. n = 44; total tissue, mean +/- SD, left, 37.9 +/- 7.4 cm(3) vs. 43.7 +/- 7.4 cm(3); mean difference [95% CI] -5.7 [-9.4 to -2.0] cm(3), P = 0.003; right, 36.8 +/- 7.1 cm(3) vs. 41.4 +/- 6.2 cm(3), mean difference -4.6 [-7.9 to -1.3] cm(3), P = 0.007). This difference remained significant after adjusting for intracranial volume (ICV; left, mean difference -3.5 [-6.7 to -0.2] cm(3), P = 0.04; right, mean difference -2.4 [-5.2 to -0.4] cm(3), P = 0.09). Within this region, the cortical gray matter volume was the most significantly reduced (left, 20.4 +/- 6.2 cm(3) vs. 25.4 +/- 5.6 cm(3), mean difference -3.1 [-5.7 to -0.5] cm(3), P = 0.02; right 21.0 +/- 5.4 cm(3) vs. 24.9 +/- 5.0 cm(3), mean difference -2.2 [-4.4 to 0.0] cm(3), P = 0.05, ICV adjusted). Abnormalities in saccadic eye movements accounted for the largest effect on inferior occipital regional brain volumes (left side, P = 0.02). CONCLUSIONS: Volumetric MR imaging techniques demonstrated an overall reduction in the inferior occipital regional brain volumes in preterm infants at term corrected who later exhibit impaired oculomotor function control. These findings assist in understanding the neuroanatomic correlates of later visual difficulties experienced by infants born prematurely.
    [bibtex-key = Shah:2006:Invest-Ophthalmol-Vis-Sci:16877404]


  109. Y Wu, S K Warfield, I L Tan, W M Wells, D S Meier, R A van Schijndel, F Barkhof, and C R Guttmann. Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI. Neuroimage, 32(3):1205-1215, September 2006. [WWW] [doi:10.1016/j.neuroimage.2006.04.211]
    Abstract:
    PURPOSE: To automatically segment multiple sclerosis (MS) lesions into three subtypes (i.e., enhancing lesions, T1 "black holes", T2 hyperintense lesions). MATERIALS AND METHODS: Proton density-, T2- and contrast-enhanced T1-weighted brain images of 12 MR scans were pre-processed through intracranial cavity (IC) extraction, inhomogeneity correction and intensity normalization. Intensity-based statistical k-nearest neighbor (k-NN) classification was combined with template-driven segmentation and partial volume artifact correction (TDS+) for segmentation of MS lesions subtypes and brain tissue compartments. Operator-supervised tissue sampling and parameter calibration were performed on 2 randomly selected scans and were applied automatically to the remaining 10 scans. Results from this three-channel TDS+ (3ch-TDS+) were compared to those from a previously validated two-channel TDS+ (2ch-TDS+) method. The results of both the 3ch-TDS+ and 2ch-TDS+ were also compared to manual segmentation performed by experts. RESULTS: Intra-class correlation coefficients (ICC) of 3ch-TDS+ for all three subtypes of lesions were higher (ICC between 0.95 and 0.96) than that of 2ch-TDS+ for T2 lesions (ICC = 0.82). The 3ch-TDS+ also identified the three lesion subtypes with high specificity (98.7-99.9%) and accuracy (98.5-99.9%). Sensitivity of 3ch-TDS+ for T2 lesions was 16% higher than with 2ch-TDS+. Enhancing lesions were segmented with the best sensitivity (81.9%). "Black holes" were segmented with the least sensitivity (62.3%). CONCLUSION: 3ch-TDS+ is a promising method for automated segmentation of MS lesion subtypes.
    [bibtex-key = Wu:2006:Neuroimage:16797188]


  110. N I Weisenfeld, A U Mewes, and S K Warfield. Highly accurate segmentation of brain tissue and subcortical gray matter from newborn MRI. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv., 9(Pt 1): 199-206 2006. [WWW] [PDF]
    Abstract:
    The segmentation of newborn brain MRI is important for assessing and directing treatment options for premature infants at risk for developmental disorders, abnormalities, or even death. Segmentation of infant brain MRI is particularly challenging when compared with the segmentation of images acquired from older children and adults. We sought to develop a fully automated segmentation strategy and present here a Bayesian approach utilizing an atlas of priors derived from previous segmentations and a new scheme for automatically selecting and iteratively refining classifier training data using the STAPLE algorithm. Results have been validated by comparison to hand-drawn segmentations.
    [bibtex-key = Weisenfeld:2006:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:17354891]


  111. N Archip, R Rohling, P Cooperberg, H Tahmasebpour, and S K Warfield. Spectral clustering algorithms for ultrasound image segmentation. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, 8(Pt 2):862-869, 2005. [WWW]
    Abstract:
    Image segmentation algorithms derived from spectral clustering analysis rely on the eigenvectors of the Laplacian of a weighted graph obtained from the image. The NCut criterion was previously used for image segmentation in supervised manner. We derive a new strategy for unsupervised image segmentation. This article describes an initial investigation to determine the suitability of such segmentation techniques for ultrasound images. The extension of the NCut technique to the unsupervised clustering is first described. The novel segmentation algorithm is then performed on simulated ultrasound images. Tests are also performed on abdominal and fetal images with the segmentation results compared to manual segmentation. Comparisons with the classical NCut algorithm are also presented. Finally, segmentation results on other types of medical images are shown.
    [bibtex-key = Archip:2005:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:16686041]


  112. O Clatz, H Delingette, I F Talos, A J Golby, R Kikinis, F A Jolesz, N Ayache, and S K Warfield. Hybrid formulation of the model-based non-rigid registration problem to improve accuracy and robustness. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, 8(Pt 2):295-302, 2005. [WWW]
    Abstract:
    We present a new algorithm to register 3D pre-operative Magnetic Resonance (MR) images with intra-operative MR images of the brain. This algorithm relies on a robust estimation of the deformation from a sparse set of measured displacements. We propose a new framework to compute iteratively the displacement field starting from an approximation formulation (minimizing the sum of a regularization term and a data error term) and converging toward an interpolation formulation (least square minimization of the data error term). The robustness of the algorithm is achieved through the introduction of an outliers rejection step in this gradual registration process. We ensure the validity of the deformation by the use of a biomechanical model of the brain specific to the patient, discretized with the finite element method. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift up to 13 mm.
    [bibtex-key = Clatz:2005:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:16685972]


  113. O Clatz, H Delingette, I F Talos, A J Golby, R Kikinis, F A Jolesz, N Ayache, and S K Warfield. Robust nonrigid registration to capture brain shift from intraoperative MRI. IEEE Trans Med Imaging, 24(11):1417-1427, November 2005. [WWW] [PDF]
    Abstract:
    We present a new algorithm to register 3-D preoperative magnetic resonance (MR) images to intraoperative MR images of the brain which have undergone brain shift. This algorithm relies on a robust estimation of the deformation from a sparse noisy set of measured displacements. We propose a new framework to compute the displacement field in an iterative process, allowing the solution to gradually move from an approximation formulation (minimizing the sum of a regularization term and a data error term) to an interpolation formulation (least square minimization of the data error term). An outlier rejection step is introduced in this gradual registration process using a weighted least trimmed squares approach, aiming at improving the robustness of the algorithm. We use a patient-specific model discretized with the finite element method in order to ensure a realistic mechanical behavior of the brain tissue. To meet the clinical time constraint, we parallelized the slowest step of the algorithm so that we can perform a full 3-D image registration in 35 s (including the image update time) on a heterogeneous cluster of 15 personal computers. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift of up to 14 mm. The results show a good ability to recover large displacements, and a limited decrease of accuracy near the tumor resection cavity.
    [bibtex-key = Clatz:2005:IEEE-Trans-Med-Imaging:16279079]


  114. O Clatz, M Sermesant, P Y Bondiau, H Delingette, S K Warfield, G Malandain, and N Ayache. Realistic simulation of the 3-D growth of brain tumors in MR images coupling diffusion with biomechanical deformation. IEEE Trans Med Imaging, 24(10):1334-1346, October 2005. [WWW]
    Abstract:
    We propose a new model to simulate the three-dimensional (3-D) growth of glioblastomas multiforma (GBMs), the most aggressive glial tumors. The GBM speed of growth depends on the invaded tissue: faster in white than in gray matter, it is stopped by the dura or the ventricles. These different structures are introduced into the model using an atlas matching technique. The atlas includes both the segmentations of anatomical structures and diffusion information in white matter fibers. We use the finite element method (FEM) to simulate the invasion of the GBM in the brain parenchyma and its mechanical interaction with the invaded structures (mass effect). Depending on the considered tissue, the former effect is modeled with a reaction-diffusion or a Gompertz equation, while the latter is based on a linear elastic brain constitutive equation. In addition, we propose a new coupling equation taking into account the mechanical influence of the tumor cells on the invaded tissues. The tumor growth simulation is assessed by comparing the in-silico GBM growth with the real growth observed on two magnetic resonance images (MRIs) of a patient acquired with 6 mo difference. Results show the feasibility of this new conceptual approach and justifies its further evaluation.
    [bibtex-key = Clatz:2005:IEEE-Trans-Med-Imaging:16229419]


  115. D Goldberg-Zimring, A U Mewes, M Maddah, and S K Warfield. Diffusion tensor magnetic resonance imaging in multiple sclerosis. J Neuroimaging, 15(4 Suppl):-81, 2005. [WWW] [doi:10.1177/1051228405283363] [PDF]
    Abstract:
    Multiple sclerosis (MS), a demyelinating disease, occurs principally in the white matter (WM) of the central nervous system. Conventional magnetic resonance imaging (MRI) is sensitive to some, but not all, brain changes associated with MS. Diffusion-weighted imaging (DWI) provides information about water diffusion in tissue and diffusion tensor MRI (DT-MRI) about fiber direction, allowing for the identification of WM abnormalities that are not apparent on conventional MRI images. These techniques can quantitatively characterize the local microstructure of tissues. MS-associated disease processes lead to regions characterized by an increased amount of water diffusion and a decrease in the anisotropy of diffusion direction. These changes have been found to produce different patterns in MS patients presenting different courses of the disease. Changes in water diffusion may allow examination of the type, appearance, enhancement, and location of lesions not readily visible by other means. Ongoing studies of MS are integrating conventional MRI and DT-MRI measures with connectivity-based regional assessment, aiming to provide a better understanding of the nature and the location of WM lesions. This integration and the development of novel image-processing and visualization techniques may improve the understanding of WM architecture and its disruption in MS. This article presents a brief history of DWI, its basic principles and applications in the study of MS, a review of the properties and applications of DT-MRI, and their use in the study of MS. In addition, this article illustrates the methodology for the analysis of DT-MRI in ongoing studies of MS.
    [bibtex-key = GoldbergZimring:2005:J-Neuroimaging:16385020]


  116. H Haidar, S K Warfield, and J S Soul. Talairach-based parcellation of neonatal brain magnetic resonance imaging data: validation of a new approach. J Neuroimaging, 15(4):305-314, October 2005. [WWW] [doi:10.1177/1051228405279041]
    Abstract:
    BACKGROUND AND PURPOSE: Talairach-based parcellation (TP) of human brain magnetic resonance imaging (MRI) data has been used increasingly in clinical research to make regional measurements of brain structures in vivo. Recently, TP has been applied to pediatric research to elucidate the changes in regional brain volumes related to several neurological disorders. However, all freely available tools have been designed to parcellate adult brain MRI data. Parcellation of neonatal MRI data is very challenging owing to the lack of strong signal contrast, variability in signal intensity within tissues, and the small size and thus difficulty in identifying small structures used as landmarks for TP. Hence the authors designed and validated a new interactive tool to parcellate brain MRI data from newborns and young infants. METHODS: The authors' tool was developed as part of a postprocessing pipeline, which includes registration of multichannel MR images, segmentation, and parcellation of the segmented data. The tool employs user-friendly interactive software to visualize and assign the anatomic landmarks required for parcellation, after which the planes and parcels are generated automatically by the algorithm. The authors then performed 3 sets of validation experiments to test the precision and reliability of their tool. RESULTS: Validation experiments of intra-and interrater reliability on data obtained from newborn and 1-year-old children showed a very high sensitivity of >95% and specificity >99.9%. The authors also showed that rotating and reformatting the original MRI data results in a statistically significant difference in parcel volumes, demonstrating the importance of using a tool such as theirs that does not require realignment of the data prior to parcellation. CONCLUSIONS: To the authors' knowledge, the presented approach is the first TP method that has been developed and validated specifically for neonatal brain MRI data. Their approach would also be valuable for the analysis of brain MRI data from older children and adults.
    [bibtex-key = Haidar:2005:J-Neuroimaging:16254393]


  117. S Haker, W M Wells, S K Warfield, I F Talos, J G Bhagwat, D Goldberg-Zimring, A Mian, L Ohno-Machado, and K H Zou. Combining classifiers using their receiver operating characteristics and maximum likelihood estimation. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, 8(Pt 1):506-514, 2005. [WWW]
    Abstract:
    In any medical domain, it is common to have more than one test (classifier) to diagnose a disease. In image analysis, for example, there is often more than one reader or more than one algorithm applied to a certain data set. Combining of classifiers is often helpful, but determining the way in which classifiers should be combined is not trivial. Standard strategies are based on learning classifier combination functions from data. We describe a simple strategy to combine results from classifiers that have not been applied to a common data set, and therefore can not undergo this type of joint training. The strategy, which assumes conditional independence of classifiers, is based on the calculation of a combined Receiver Operating Characteristic (ROC) curve, using maximum likelihood analysis to determine a combination rule for each ROC operating point. We offer some insights into the use of ROC analysis in the field of medical imaging.
    [bibtex-key = Haker:2005:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:16685884]


  118. T E Inder, S K Warfield, H Wang, P S Hüppi, and J J Volpe. Abnormal cerebral structure is present at term in premature infants. Pediatrics, 115(2):286-294, February 2005. [WWW] [doi:10.1542/peds.2004-0326]
    Abstract:
    BACKGROUND: Long-term studies of the outcome of very prematurely born infants have clearly documented that the majority of such infants have significant motor, cognitive, and behavioral deficits. However, there is a limited understanding of the nature of the cerebral abnormality underlying these adverse neurologic outcomes. AIM: The overall aim of this study was to define quantitatively the alterations in cerebral tissue volumes at term equivalent in a large longitudinal cohort study of very low birth weight premature infants in comparison to term-born infants by using advanced volumetric 3-dimensional magnetic resonance imaging (MRI) techniques. We also aimed to define any relationship of such perinatal lesions as white matter (WM) injury or other potentially adverse factors to the quantitative structural alterations. Additionally, we wished to identify the relationship of the structural alterations to short-term neurodevelopmental outcome. METHODS: From November 1998 to December 2000, 119 consecutive premature infants admitted to the neonatal intensive care units at Christchurch Women's Hospital (Christchurch, New Zealand) and the Royal Women's Hospital (Melbourne, Australia) were recruited (88% of eligible) after informed parental consent to undergo an MRI scan at term equivalent. Twenty-one term-born infants across both sites were recruited also. Postacquisition advanced 3-dimensional tissue segmentation with 3-dimensional reconstruction was undertaken to estimate volumes of cerebral tissues: gray matter (GM; cortical and deep nuclear structures), WM (myelinated and unmyelinated), and cerebrospinal fluid (CSF). RESULTS: In comparison to the term-born infants, the premature infants at term demonstrated prominent reductions in cerebral cortical GM volume (premature infants [mean +/- SD]: 178 +/- 41 mL; term infants: 227 +/- 26 mL) and in deep nuclear GM volume (premature infants: 10.8 +/- 4.1 mL; term infants: 13.8 +/- 5.2 mL) and an increase in CSF volume (premature infants: 45.6 +/- 22.1 mL; term infants: 28.9 +/- 16 mL). The major predictors of altered cerebral volumes were gestational age at birth and the presence of cerebral WM injury. Infants with significantly reduced cortical GM and deep nuclear GM volumes and increased CSF volume volumes exhibited moderate to severe neurodevelopmental disability at 1 year of age. CONCLUSIONS: This MRI study of prematurely born infants further defines the nature of quantitative cerebral structural abnormalities present as early as term equivalent. The abnormalities particularly involve cerebral neuronal regions including both cortex and deep nuclear structures. The pattern of cerebral alterations is related most significantly to the degree of immaturity at birth and to concomitant WM injury. The alterations are followed by abnormal short-term neurodevelopmental outcome.
    [bibtex-key = Inder:2005:Pediatrics:15687434]


  119. C Limperopoulos, J S Soul, K Gauvreau, P S Huppi, S K Warfield, H Bassan, R L Robertson, J J Volpe, and A J du Plessis. Late gestation cerebellar growth is rapid and impeded by premature birth. Pediatrics, 115(3):688-695, March 2005. [WWW] [doi:10.1542/peds.2004-1169]
    Abstract:
    OBJECTIVE: Cognitive impairments and academic failure are commonly reported in survivors of preterm birth. Recent studies suggest an important role for the cerebellum in the development of cognitive and social functions. The objective of this study was to examine the impact of prematurity itself, as well as prematurity-related brain injuries, on early postnatal cerebellar growth with quantitative MRI. METHODS: Advanced 3-dimensional volumetric MRI was performed and cerebellar volumes were obtained by manual outlining in preterm (<37 weeks) and healthy term-born infants. Intracranial and total brain volumes were also calculated. RESULTS: A total of 169 preterm and 20 healthy full-term infants were studied; 145 had preterm MRI (pMRI), 75 had term MRI (tMRI), and 51 underwent both pMRI and tMRI. From 28 weeks' postconceptional age to term, mean cerebellar volume (177%) in preterm infants increased at a much faster rate than did mean intracranial (110%) or mean brain (107%) volumes. Smaller cerebellar volume was significantly related to lower gestational age at birth and to intracranial and total brain volumes. Mean cerebellar volume of preterm infants at tMRI was significantly smaller than the volumes of term-born infants. Cerebellar growth impairment was correlated strongly with associated brain injuries, even in the absence of direct cerebellar injury. CONCLUSIONS: Our data suggest that the growth of the immature cerebellum is particularly rapid during late gestation. However, this accelerated growth seems to be impeded by premature birth and associated brain injury. The long-term neurodevelopmental disabilities seen in survivors of premature birth may be attributable in part to impaired cerebellar development.
    [bibtex-key = Limperopoulos:2005:Pediatrics:15741373]


  120. C Limperopoulos, J S Soul, H Haidar, P S Huppi, H Bassan, S K Warfield, R L Robertson, M Moore, P Akins, J J Volpe, and A J du Plessis. Impaired trophic interactions between the cerebellum and the cerebrum among preterm infants. Pediatrics, 116(4):844-850, October 2005. [WWW] [doi:10.1542/peds.2004-2282]
    Abstract:
    BACKGROUND: Advanced neuroimaging techniques have brought increasing recognition of cerebellar injury among premature infants. The developmental relationship between early brain injury and effects on the cerebrum and cerebellum remains unclear. OBJECTIVES: To examine whether cerebral parenchymal brain lesions among preterm infants are associated with subsequent decreases in cerebellar volume and, conversely, whether primary cerebellar injury is associated with decreased cerebral brain volumes, with advanced, 3-dimensional, volumetric MRI at term gestational age equivalent. METHODS: Total cerebellar volumes and cerebellar gray and myelinated white matter volumes were determined through manual outlining for 74 preterm infants with unilateral periventricular hemorrhagic infarction (14 infants), bilateral diffuse periventricular leukomalacia (20 infants), cerebellar hemorrhage (10 infants), or normal term gestational age equivalent MRI findings (30 infants). Total brain and right/left cerebral and cerebellar hemispheric volumes were calculated. RESULTS: Unilateral cerebral brain injury was associated with significantly decreased volume of the contralateral cerebellar hemisphere. Conversely, unilateral primary cerebellar injury was associated with a contralateral decrease in supratentorial brain volume. Cerebellar gray matter and myelinated white matter volumes were reduced significantly not only among preterm infants with primary cerebellar hemorrhage but also among infants with cerebral parenchymal brain injury. CONCLUSIONS: These data suggest strongly that both reduction in contralateral cerebellar volume with unilateral cerebral parenchymal injury and reduction in total cerebellar volume with bilateral cerebral lesions are related to trophic transsynaptic effects. Early-life cerebellar injury may contribute importantly to the high rates of cognitive, behavioral, and motor deficits reported for premature infants.
    [bibtex-key = Limperopoulos:2005:Pediatrics:16199692]


  121. M Maddah, A U Mewes, S Haker, W E Grimson, and S K Warfield. Automated atlas-based clustering of white matter fiber tracts from DTMRI. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, 8(Pt 1):188-195, 2005. [WWW]
    Abstract:
    A new framework is presented for clustering fiber tracts into anatomically known bundles. This work is motivated by medical applications in which variation analysis of known bundles of fiber tracts in the human brain is desired. To include the anatomical knowledge in the clustering, we invoke an atlas of fiber tracts, labeled by the number of bundles of interest. In this work, we construct such an atlas and use it to cluster all fiber tracts in the white matter. To build the atlas, we start with a set of labeled ROIs specified by an expert and extract the fiber tracts initiating from each ROI. Affine registration is used to project the extracted fiber tracts of each subject to the atlas, whereas their B-spline representation is used to efficiently compare them to the fiber tracts in the atlas and assign cluster labels. Expert visual inspection of the result confirms that the proposed method is very promising and efficient in clustering of the known bundles of fiber tracts.
    [bibtex-key = Maddah:2005:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:16685845]


  122. A Tsai, W M Wells, S K Warfield, and A S Willsky. An EM algorithm for shape classification based on level sets. Med Image Anal, 9(5):491-502, October 2005. [WWW] [doi:10.1016/j.media.2005.05.001]
    Abstract:
    In this paper, we propose an expectation-maximization (EM) approach to separate a shape database into different shape classes, while simultaneously estimating the shape contours that best exemplify each of the different shape classes. We begin our formulation by employing the level set function as the shape descriptor. Next, for each shape class we assume that there exists an unknown underlying level set function whose zero level set describes the contour that best represents the shapes within that shape class. The level set function for each example shape in the database is modeled as a noisy measurement of the appropriate shape class's unknown underlying level set function. Based on this measurement model and the judicious introduction of the class labels as the hidden data, our EM formulation calculates the labels for shape classification and estimates the shape contours that best typify the different shape classes. This resulting iterative algorithm is computationally efficient, simple, and accurate. We demonstrate the utility and performance of this algorithm by applying it to two medical applications.
    [bibtex-key = Tsai:2005:Med-Image-Anal:16046181]


  123. J F Verhey, J Wisser, S K Warfield, J Rexilius, and R Kikinis. Non-rigid registration of a 3D ultrasound and a MR image data set of the female pelvic floor using a biomechanical model. Biomed Eng Online, 4(1):19-19, 2005. [WWW] [doi:10.1186/1475-925X-4-19]
    Abstract:
    BACKGROUND: The visual combination of different modalities is essential for many medical imaging applications in the field of Computer-Assisted medical Diagnosis (CAD) to enhance the clinical information content. Clinically, incontinence is a diagnosis with high clinical prevalence and morbidity rate. The search for a method to identify risk patients and to control the success of operations is still a challenging task. The conjunction of magnetic resonance (MR) and 3D ultrasound (US) image data sets could lead to a new clinical visual representation of the morphology as we show with corresponding data sets of the female anal canal with this paper. METHODS: We present a feasibility study for a non-rigid registration technique based on a biomechanical model for MR and US image data sets of the female anal canal as a base for a new innovative clinical visual representation. RESULTS: It is shown in this case study that the internal and external sphincter region could be registered elastically and the registration partially corrects the compression induced by the ultrasound transducer, so the MR data set showing the native anatomy is used as a frame for the US data set showing the same region with higher resolution but distorted by the transducer CONCLUSION: The morphology is of special interest in the assessment of anal incontinence and the non-rigid registration of normal clinical MR and US image data sets is a new field of the adaptation of this method incorporating the advantages of both technologies.
    [bibtex-key = Verhey:2005:Biomed-Eng-Online:15777475]


  124. S K Warfield, S J Haker, I F Talos, C A Kemper, N Weisenfeld, A U Mewes, D Goldberg-Zimring, K H Zou, C F Westin, W M Wells, C M Tempany, A Golby, P M Black, F A Jolesz, and R Kikinis. Capturing intraoperative deformations: research experience at Brigham and Women's Hospital. Med Image Anal, 9(2):145-162, April 2005. [WWW] [doi:10.1016/j.media.2004.11.005]
    Abstract:
    During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patient's brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and Women's Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy.
    [bibtex-key = Warfield:2005:Med-Image-Anal:15721230]


  125. L C Wiegand, S K Warfield, J J Levitt, Y Hirayasu, D F Salisbury, S Heckers, S Bouix, D Schwartz, M Spencer, C C Dickey, R Kikinis, F A Jolesz, R W McCarley, and M E Shenton. An in vivo MRI study of prefrontal cortical complexity in first-episode psychosis. Am J Psychiatry, 162(1):65-70, January 2005. [WWW] [doi:10.1176/appi.ajp.162.1.65]
    Abstract:
    OBJECTIVE: The purpose of this study was to investigate abnormalities in the surface complexity of the prefrontal cortex and in the hemispheric asymmetry of cortical complexity in first-episode patients with schizophrenia. METHOD: An estimate of the surface complexity of the prefrontal cortex was derived from the number of voxels along the boundary between gray matter and CSF. Magnetic resonance imaging scans were acquired from patients with a first episode of schizophrenia (N=17), patients with a first episode of affective psychosis (N=17), and normal comparison subjects (N=17), age-matched within a narrow age range (18-29 years). This study group was the focus of a previous study that showed lower prefrontal cortical volume in patients with schizophrenia. RESULTS: Prefrontal cortical complexity was not significantly different among the groups. However, the schizophrenia patients differed significantly from the normal comparison subjects in asymmetry, with the schizophrenia patients showing less left-greater-than-right asymmetry in cortical complexity than the comparison subjects. CONCLUSIONS: An abnormal pattern of asymmetry in the prefrontal cortex of first-episode patients with schizophrenia provides evidence for a neurodevelopmental mechanism in the etiology of schizophrenia.
    [bibtex-key = Wiegand:2005:Am-J-Psychiatry:15625203]


  126. A Wittek, R Kikinis, S K Warfield, and K Miller. Brain shift computation using a fully nonlinear biomechanical model. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv, 8(Pt 2):583-590, 2005. [WWW]
    Abstract:
    In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict deformation field within the brain during the craniotomy-induced brain shift. Deformation of brain surface was used as displacement boundary conditions. Application of the computed deformation field to align (i.e. register) the preoperative images with the intraoperative ones indicated that the model very accurately predicts the displacements of gravity centers of the lateral ventricles and tumor even for very limited information about the brain surface deformation. These results are sufficient to suggest that nonlinear biomechanical models can be regarded as one possible way of complementing medical image processing techniques when conducting nonrigid registration. Important advantage of such models over the linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain tissue stress-strain relationship is linear.
    [bibtex-key = Wittek:2005:Med-Image-Comput-Comput-Assist-Interv-Int-Conf-Med-Image-Comput-Comput-Assist-Interv:16686007]


  127. L Wolfson, X Wei, C B Hall, V Panzer, D Wakefield, R R Benson, J A Schmidt, S K Warfield, and C R Guttmann. Accrual of MRI white matter abnormalities in elderly with normal and impaired mobility. J Neurol Sci, 232(1-2):23-27, May 2005. [WWW] [doi:10.1016/j.jns.2004.12.017]
    Abstract:
    White matter signal abnormality (WMSA) is often present in the MRIs of older persons with mobility impairment. We examined the relationship between impaired mobility and the progressive accrual of WMSA. Mobility was assessed with the Short Physical Performance Battery (SPPB) and quantitative measures of gait and balance. Fourteen subjects had baseline and follow-up MRI scans performed 20 months apart. WMSA was detected and quantified using automated computer algorithms. In the control subjects, WMSA volume increased by 0.02+/-0.05% ICCV (percent intracranial cavity volume)/year while the WMSA of mobility impaired subjects increased five-times faster (0.10+/-0.10 ICCV/year, p=0.03). WMSA volume was related to some of the mobility measures and was sensitive to change which was not true of the other MRI variables. The study demonstrates the sensitivity of longitudinal automated volumetric analysis of WMSA to differentiate differences in the accrual rate of WMSA in groups selected on the basis of mobility. Based on these results, we propose that a subset of subjects with mobility impairment have accelerated, disease related WMSA accrual, thus explaining the rapid progression of mobility impairment in some older persons without apparent cause. This study demonstrates that quantitative MRI and performance measures can provide valuable insight into the rate of progression and pathophysiologic abnormalities underlying mobility impairment.
    [bibtex-key = Wolfson:2005:J-Neurol-Sci:15850578]


  128. K H Zou, D N Greve, M Wang, S D Pieper, S K Warfield, N S White, S Manandhar, G G Brown, M G Vangel, R Kikinis, and W M Wells. Reproducibility of functional MR imaging: preliminary results of prospective multi-institutional study performed by Biomedical Informatics Research Network. Radiology, 237(3):781-789, December 2005. [WWW] [doi:10.1148/radiol.2373041630]
    Abstract:
    PURPOSE: To prospectively investigate the factors--including subject, brain hemisphere, study site, field strength, imaging unit vendor, imaging run, and examination visit--affecting the reproducibility of functional magnetic resonance (MR) imaging activations based on a repeated sensory-motor (SM) task. MATERIALS AND METHODS: The institutional review boards of all participating sites approved this HIPAA-compliant study. All subjects gave informed consent. Functional MR imaging data were repeatedly acquired from five healthy men aged 20-29 years who performed the same SM task at 10 sites. Five 1.5-T MR imaging units, four 3.0-T units, and one 4.0-T unit were used. The subjects performed bilateral finger tapping on button boxes with a 3-Hz audio cue and a reversing checkerboard. In a block design, 15-second epochs of alternating baseline and tasks yielded 85 acquisitions per run. Functional MR images were acquired with block-design echo-planar or spiral gradient-echo sequences. Brain activation maps standardized in a unit-sphere for the left and right hemispheres of each subject were constructed. Areas under the receiver operating characteristic curve, intraclass correlation coefficients, multiple regression analysis, and paired Student t tests were used for statistical analyses. RESULTS: Significant factors were subject (P < .005), k-space (P < .005), and field strength (P = .02) for sensitivity and subject (P = .03) and k-space (P = .05) for specificity. At 1.5-T MR imaging, mean sensitivities ranged from 7% to 32% and mean specificities were higher than 99%. At 3.0 T, mean sensitivities and specificities ranged from 42% to 85% and from 96% to 99%, respectively. At 4.0 T, mean sensitivities and specificities ranged from 41% to 73% and from 95% to 99%, respectively. Mean areas under the receiver operating characteristic curve (+/- their standard errors) were 0.77 +/- 0.05 at 1.5 T, 0.90 +/- 0.09 at 3.0 T, and 0.95 +/- 0.02 at 4.0 T, with significant differences between the 1.5- and 3.0-T examinations and between the 1.5- and 4.0-T examinations (P < .01 for both comparisons). Intraclass correlation coefficients ranged from 0.49 to 0.71. CONCLUSION: MR imaging at 3.0- and 4.0-T yielded higher reproducibility across sites and significantly better results than 1.5-T imaging. The effects of subject, k-space, and field strength on examination reproducibility were significant.
    [bibtex-key = Zou:2005:Radiology:16304101]


  129. K H Zou, K Tuncali, S K Warfield, C P Zentai, D Worku, P R Morrison, and S G Silverman. Three-dimensional assessment of MR imaging-guided percutaneous cryotherapy using multi-performer repeated segmentations: the value of supervised learning. Acad Radiol, 12(4):444-450, April 2005. [WWW] [doi:10.1016/j.acra.2004.11.029]
    Abstract:
    RATIONALE AND OBJECTIVES: Accurate and reproducible segmentations of two-dimensional images are an important prerequisite for assessing tumor ablations three dimensionally (3D). We evaluated whether supervised learning methods would improve multiperformer repeated segmentations of magnetic resonance images (MRI) obtained before and after MRI-guided cryotherapy of renal cell carcinoma. MATERIALS AND METHODS: Three medical students independently performed five manual segmentations of a biopsy-proven renal cell carcinoma that was treated with percutaneous MRI-guided cryotherapy. Using pretreatment (T2-weighted fast recovery fast spin echo [FRFSE]) and posttreatment (T1-weighted, fat-suppressed, dynamically enhanced) MRIs, regions of tumor cryonecrosis were segmented. The same tasks were repeated after an experienced abdominal radiologist provided supervised learning. Segmentation sensitivity was compared with an estimated 3D-ground truth via voxel counts for regions of tumor, both before and after treatment, and for the regions of cryonecrosis. The sensitivity of each repeated segmentation was compared against the estimated ground truth using sensitivity, overlap index, and volume (mL). RESULTS: Supervised learning significantly improved posttreatment segmentation sensitivity (P = .03). With supervised learning, the ranges of the performance metrics over the segmentation performers were: pretreated tumor, sensitivity 0.902-0.999, overlap index 0.935-0.961, and volume 19.15-23.71 mL; posttreated tumor, sensitivity 0.923-0.991, overlap index 0.952-0.981, and volume 20.67-22.70 mL; in the ablation zone, sensitivity 0.938-0.969, overlap index 0.940-0.962, and volume 31.79-32.36 mL. CONCLUSIONS: Supervised learning improved multiperformer repeated segmentations of MRIs obtained before and after MRI-guided percutaneous cryotherapy of renal cell carcinoma. These methods may prove useful in aiding the 3D assessment of percutaneous tumor ablations.
    [bibtex-key = Zou:2005:Acad-Radiol:15831417]


  130. A du Bois d'Aische, M D Craene, X Geets, V Gregoire, B Macq, and S K Warfield. Efficient multi-modal dense field non-rigid registration: alignment of histological and section images. Med Image Anal, 9(6):538-546, December 2005. [WWW] [doi:10.1016/j.media.2005.04.003]
    Abstract:
    We describe a new algorithm for non-rigid registration capable of estimating a constrained dense displacement field from multi-modal image data. We applied this algorithm to capture non-rigid deformation between digital images of histological slides and digital flat-bed scanned images of cryotomed sections of the larynx, and carried out validation experiments to measure the effectiveness of the algorithm. The implementation was carried out by extending the open-source Insight ToolKit software. In diagnostic imaging of cancer of the larynx, imaging modalities sensitive to both anatomy (such as MRI and CT) and function (PET) are valuable. However, these modalities differ in their capability to discriminate the margins of tumor. Gold standard tumor margins can be obtained from histological images from cryotomed sections of the larynx. Unfortunately, the process of freezing, fixation, cryotoming and staining the tissue to create histological images introduces non-rigid deformations and significant contrast changes. We demonstrate that the non-rigid registration algorithm we present is able to capture these deformations and the algorithm allows us to align histological images with scanned images of the larynx. Our non-rigid registration algorithm constructs a deformation field to warp one image onto another. The algorithm measures image similarity using a mutual information similarity criterion, and avoids spurious deformations due to noise by constraining the estimated deformation field with a linear elastic regularization term. The finite element method is used to represent the deformation field, and our implementation enables us to assign inhomogeneous material characteristics so that hard regions resist internal deformation whereas soft regions are more pliant. A gradient descent optimization strategy is used and this has enabled rapid and accurate convergence to the desired estimate of the deformation field. A further acceleration in speed without cost of accuracy is achieved by using an adaptive mesh refinement strategy.
    [bibtex-key = duBoisdAische:2005:Med-Image-Anal:15897000]


  131. H Als, F H Duffy, G B McAnulty, M J Rivkin, S Vajapeyam, R V Mulkern, S K Warfield, P S Huppi, S C Butler, N Conneman, C Fischer, and E C Eichenwald. Early experience alters brain function and structure. Pediatrics, 113(4):846-857, April 2004. [WWW]
    Abstract:
    OBJECTIVE: To investigate the effects of early experience on brain function and structure. METHODS: A randomized clinical trial tested the neurodevelopmental effectiveness of the Newborn Individualized Developmental Care and Assessment Program (NIDCAP). Thirty preterm infants, 28 to 33 weeks' gestational age (GA) at birth and free of known developmental risk factors, participated in the trial. NIDCAP was initiated within 72 hours of intensive care unit admission and continued to the age of 2 weeks, corrected for prematurity. Control (14) and experimental (16) infants were assessed at 2 weeks' and 9 months' corrected age on health status, growth, and neurobehavior, and at 2 weeks' corrected age additionally on electroencephalogram spectral coherence, magnetic resonance diffusion tensor imaging, and measurements of transverse relaxation time. RESULTS: The groups were medically and demographically comparable before as well as after the treatment. However, the experimental group showed significantly better neurobehavioral functioning, increased coherence between frontal and a broad spectrum of mainly occipital brain regions, and higher relative anisotropy in left internal capsule, with a trend for right internal capsule and frontal white matter. Transverse relaxation time showed no difference. Behavioral function was improved also at 9 months' corrected age. The relationship among the 3 neurodevelopmental domains was significant. The results indicated consistently better function and more mature fiber structure for experimental infants compared with their controls. CONCLUSIONS: This is the first in vivo evidence of enhanced brain function and structure due to the NIDCAP. The study demonstrates that quality of experience before term may influence brain development significantly.
    [bibtex-key = Als:2004:Pediatrics:15060237]


  132. N G Anderson, S K Warfield, S Wells, C Spencer, A Balasingham, J J Volpe, and T E Inder. A limited range of measures of 2-D ultrasound correlate with 3-D MRI cerebral volumes in the premature infant at term. Ultrasound Med Biol, 30(1):11-18, January 2004. [WWW] [doi:10.1016/j.ultrasmedbio.2003.10.001]
    Abstract:
    Two-dimensional (2-D) cranial ultrasound (US) is the principal method for the detection of cerebral injury in the newborn. The aim of this study was to compare 2-D sonographic methods with more advanced 3-D magnetic resonance imaging (MRI) for assessing brain structure. From July 1998 to November 2000, we conducted a prospective methodological study comparing 2-D cranial sonographic measurements with volumes of cerebrospinal fluid (CSF), white matter, grey matter and total volume of brain obtained using 3-D MRI. The study group comprised 63 infants (33 boys), mean gestational age 28 weeks (range 23 to 33 weeks), with imaging studies within 15 days of term equivalent. The highest correlations were between the occipital horn length and total brain volume (R2 = 0.30), the subarachnoid space and both CSF volume (R2 = 0.46) and relative intracranial space occupied by brain tissue (R2 = 0.48). Only 8 (30%) of the 2-D cranial US measures demonstrated good reproducibility. 2-D sonographic measures are limited in reflecting variations in overall cerebral structure, although certain measures, such as subarachnoid space and occipital lobe measures, may be useful in better defining cerebral parenchymal and CSF volumes.
    [bibtex-key = Anderson:2004:Ultrasound-Med-Biol:14962603]


  133. D Goldberg-Zimring, A Achiron, S K Warfield, C R Guttmann, and H Azhari. Application of spherical harmonics derived space rotation invariant indices to the analysis of multiple sclerosis lesions' geometry by MRI. Magn Reson Imaging, 22(6):815-825, July 2004. [WWW] [doi:10.1016/j.mri.2004.01.053]
    Abstract:
    In the longitudinal study of multiple sclerosis (MS) lesions, varying position of the patient inside the MRI scanner is one of the major sources of assessment errors. We propose to use analytical indices that are invariant to spatial orientation to describe the lesions, rather than focus on patient repositioning or image realignment. Studies were made on simulated lesions systematically rotated, from in vitro MS lesions scanned on different days, and from in vivo MS lesions from a patient that was scanned five times the same day with short intervals of time between scans. Each of the lesions' 3D surfaces was approximated using spherical harmonics, from which indices that are invariant to space rotation were derived. From these indices, an accurate and highly reproducible volume estimate can be derived, which is superior to the common approach of 2D slice stacking. The results indicate that the suggested approach is useful in reducing part of the errors that affect the analysis of changes of MS lesions during follow-up studies. In conclusion, our proposed method circumvents the need for precise patient repositioning and can be advantageous in MRI longitudinal studies of MS patients.
    [bibtex-key = GoldbergZimring:2004:Magn-Reson-Imaging:15234450]


  134. L Hoyte, M Jakab, S K Warfield, S Shott, G Flesh, and J R Fielding. Levator ani thickness variations in symptomatic and asymptomatic women using magnetic resonance-based 3-dimensional color mapping. Am J Obstet Gynecol, 191(3):856-861, September 2004. [WWW] [doi:10.1016/j.ajog.2004.06.067]
    Abstract:
    OBJECTIVE: This study was undertaken to develop and test a 3-dimensional (3D) color thickness mapping technique on levator ani imaged with magnetic resonance imaging (MRI). METHODS: Supine MRI datasets from 30 women were studied: 10 asymptomatic, 10 with urodynamic stress incontinence, and 10 with pelvic organ prolapse. Levators were manually outlined, and thickness mapping applied. Three-dimensional models were colored topographically, reflecting levator thickness. Thickness and occurrences of absent levator substance (gaps) were compared across the 3 groups, using nonparametric statistical tests. RESULTS: Color thickness mapping was successful in all subjects. There were statistically significant differences in thickness and gap percentages among the 3 groups of women, with thicker, bulkier levators in asymptomatic women, compared with women with prolapse or urodynamic stress incontinence. CONCLUSION: Color thickness mapping is feasible. It may be used to compare levators in symptomatic and asymptomatic women, to study relationships between levator thickness and pelvic floor dysfunction. This technique can be used in larger studies for hypothesis testing.
    [bibtex-key = Hoyte:2004:Am-J-Obstet-Gynecol:15467553]


  135. S G Silverman, M R Sun, K Tuncali, P R Morrison, E vanSonnenberg, S Shankar, K H Zou, and S K Warfield. Three-dimensional assessment of MRI-guided percutaneous cryotherapy of liver metastases. AJR Am J Roentgenol, 183(3):707-712, September 2004. [WWW]
    Abstract:
    OBJECTIVE: We report our initial investigation of the use of a 3D method for assessing percutaneous tumor ablations. We hypothesized that these 3D techniques could be used to assess the technical success of ablations and that 3D metrics would be predictive of treatment response. CONCLUSION: Three-dimensional assessment of percutaneous tumor ablations provides a quantitative evaluation of the technical success of the procedure. Three-dimensional computer-based techniques can both quantify coverage of a tumor and create a virtual ablation margin for percutaneous procedures, akin to a surgical margin. Although results are preliminary, 3D metrics were useful in predicting treatment response.
    [bibtex-key = Silverman:2004:AJR-Am-J-Roentgenol:15333359]


  136. C B Tolsa, S Zimine, S K Warfield, M Freschi, A Sancho Rossignol, F Lazeyras, S Hanquinet, M Pfizenmaier, and P S Huppi. Early alteration of structural and functional brain development in premature infants born with intrauterine growth restriction. Pediatr Res, 56(1):132-138, July 2004. [WWW] [doi:10.1203/01.PDR.0000128983.54614.7E]
    Abstract:
    Placental insufficiency with fetal intrauterine growth restriction (IUGR) is an important cause of perinatal mortality and morbidity and is subsequently associated with significant neurodevelopmental impairment in cognitive function, attention capacity, and school performance. The underlying biologic cause for this association is unclear. Twenty-eight preterm infants (gestational age 32.5 +/- 1.9 wk) were studied by early and term magnetic resonance imaging (MRI). An advanced quantitative volumetric three-dimensional MRI technique was used to measure brain tissue volumes in 14 premature infants with placental insufficiency, defined by abnormal antenatal Doppler measurements and mean birth weights <10(th) percentile (1246 +/- 299 g) (IUGR) and in 14 preterm infants matched for gestational age with normal mean birth weights 1843 +/- 246 g (control). Functional outcome was measured at term in all infants by a specialized assessment scale of preterm infant behavior. Premature infants with IUGR had a significant reduction in intracranial volume (mean +/- SD: 253.7 +/- 29.9 versus 300.5 +/- 43.5 mL, p < 0.01) and in cerebral cortical gray matter (mean +/- SD: 77.2 +/- 16.3 versus 106.8 +/- 24.6 mL, p < 0.01) when measured within the first 2 wk of life compared with control premature infants. These findings persisted at term with intracranial volume (mean +/- SD: 429.3 +/- 47.9 versus 475.9 +/- 53.4 mL, p < 0.05) and cerebral cortical gray matter (mean +/- SD: 149.3 +/- 29.2 versus 189 +/- 34.2 mL, p < 0.01). Behavioral assessment at term showed a significantly less mature score in the subsystem of attention-interaction availability in IUGR infants (p < 0.01). Cerebral cortical gray matter volume at term correlated with attention-interaction capacity measured at term (r = 0.45, p < 0.05). These results suggest that placental insufficiency with IUGR have specific structural and functional consequences on cerebral cortical brain development. These findings may provide insight into the structural-functional correlate for the developmental deficits associated with IUGR.
    [bibtex-key = Tolsa:2004:Pediatr-Res:15128927]


  137. S K Warfield, K H Zou, and W M Wells. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Trans Med Imaging, 23(7):903-921, July 2004. [WWW] [PDF]
    Abstract:
    Characterizing the performance of image segmentation approaches has been a persistent challenge. Performance analysis is important since segmentation algorithms often have limited accuracy and precision. Interactive drawing of the desired segmentation by human raters has often been the only acceptable approach, and yet suffers from intra-rater and inter-rater variability. Automated algorithms have been sought in order to remove the variability introduced by raters, but such algorithms must be assessed to ensure they are suitable for the task. The performance of raters (human or algorithmic) generating segmentations of medical images has been difficult to quantify because of the difficulty of obtaining or estimating a known true segmentation for clinical data. Although physical and digital phantoms can be constructed for which ground truth is known or readily estimated, such phantoms do not fully reflect clinical images due to the difficulty of constructing phantoms which reproduce the full range of imaging characteristics and normal and pathological anatomical variability observed in clinical data. Comparison to a collection of segmentations by raters is an attractive alternative since it can be carried out directly on the relevant clinical imaging data. However, the most appropriate measure or set of measures with which to compare such segmentations has not been clarified and several measures are used in practice. We present here an expectation-maximization algorithm for simultaneous truth and performance level estimation (STAPLE). The algorithm considers a collection of segmentations and computes a probabilistic estimate of the true segmentation and a measure of the performance level represented by each segmentation. The source of each segmentation in the collection may be an appropriately trained human rater or raters, or may be an automated segmentation algorithm. The probabilistic estimate of the true segmentation is formed by estimating an optimal combination of the segmentations, weighting each segmentation depending upon the estimated performance level, and incorporating a prior model for the spatial distribution of structures being segmented as well as spatial homogeneity constraints. STAPLE is straightforward to apply to clinical imaging data, it readily enables assessment of the performance of an automated image segmentation algorithm, and enables direct comparison of human rater and algorithm performance.
    [bibtex-key = Warfield:2004:IEEE-Trans-Med-Imaging:15250643]


  138. X Wei, C R Guttmann, S K Warfield, M Eliasziw, and J R Mitchell. Has your patient's multiple sclerosis lesion burden or brain atrophy actually changed?. Mult Scler, 10(4):402-406, August 2004. [WWW] [PDF]
    Abstract:
    Changes in mean magnetic resonance imaging (MRI)-derived measurements between patient groups are often used to determine outcomes in therapeutic trials and other longitudinal studies of multiple sclerosis (MS). However, in day-to-day clinical practice the changes within individual patients may also be of interest In this paper, we estimated the measurement error of an automated brain tissue quantification algorithm and determined the thresholds for statistically significant change of MRI-derived T2 lesion volume and brain atrophy in individual patients. Twenty patients with MS were scanned twice within 30 min. Brain tissue volumes were measured using the computer algorithm. Brain atrophy was estimated by calculation of brain parenchymal fraction. The threshold of change between repeated scans that represented statistically significant change beyond measurement error with 95% certainty was 0.65 mL for T2 lesion burden and 0.0056 for brain parenchymal fraction. Changes in lesion burden and brain atrophy below these thresholds can be safely (with 95% certainty) explained by measurement variability alone. These values provide clinical neurologists with a useful reference to interpret MRI-derived measures in individual patients.
    [bibtex-key = Wei:2004:Mult-Scler:15327037]


  139. L C Wiegand, S K Warfield, J J Levitt, Y Hirayasu, D F Salisbury, S Heckers, C C Dickey, R Kikinis, F A Jolesz, R W McCarley, and M E Shenton. Prefrontal cortical thickness in first-episode psychosis: a magnetic resonance imaging study. Biol Psychiatry, 55(2):131-140, January 2004. [WWW] [PDF]
    Abstract:
    BACKGROUND: Findings from postmortem studies suggest reduced prefrontal cortical thickness in schizophrenia; however, cortical thickness in first-episode schizophrenia has not been evaluated using magnetic resonance imaging (MRI). METHODS: Prefrontal cortical thickness was measured using MRI in first-episode schizophrenia patients (n = 17), first-episode affective psychosis patients (n = 17), and normal control subjects (n = 17); subjects were age-matched within 2 years and within a narrow age range (18-29 years). A previous study using the same subjects reported reduced prefrontal gray matter volume in first-episode schizophrenia. Manual editing was performed on those prefrontal segmentations before cortical thickness was measured. RESULTS: Prefrontal cortical thickness was not significantly different among groups. Prefrontal gray matter volume and thickness were, however, positively correlated in both schizophrenia and control subjects. The product of boundary complexity and thickness, an alternative measure of volume, was positively correlated with volume for all three groups. Finally, age and age at first medication were negatively correlated with prefrontal cortical thickness only in first-episode schizophrenia. CONCLUSIONS: This study demonstrates the potential usefulness of MRI for the study of cortical thickness abnormalities in schizophrenia. Correlations between cortical thickness and age and between cortical thickness and age at first medication suggest that the longer the schizophrenic process has been operative, the thinner the prefrontal cortex, although this needs confirmation in a longitudinal study.
    [bibtex-key = Wiegand:2004:Biol-Psychiatry:14732592]


  140. K H Zou, S K Warfield, A Bharatha, C M Tempany, M R Kaus, S J Haker, W M Wells, F A Jolesz, and R Kikinis. Statistical validation of image segmentation quality based on a spatial overlap index. Acad Radiol, 11(2):178-189, February 2004. [WWW]
    Abstract:
    RATIONALE AND OBJECTIVES: To examine a statistical validation method based on the spatial overlap between two sets of segmentations of the same anatomy. MATERIALS AND METHODS: The Dice similarity coefficient (DSC) was used as a statistical validation metric to evaluate the performance of both the reproducibility of manual segmentations and the spatial overlap accuracy of automated probabilistic fractional segmentation of MR images, illustrated on two clinical examples. Example 1: 10 consecutive cases of prostate brachytherapy patients underwent both preoperative 1.5T and intraoperative 0.5T MR imaging. For each case, 5 repeated manual segmentations of the prostate peripheral zone were performed separately on preoperative and on intraoperative images. Example 2: A semi-automated probabilistic fractional segmentation algorithm was applied to MR imaging of 9 cases with 3 types of brain tumors. DSC values were computed and logit-transformed values were compared in the mean with the analysis of variance (ANOVA). RESULTS: Example 1: The mean DSCs of 0.883 (range, 0.876-0.893) with 1.5T preoperative MRI and 0.838 (range, 0.819-0.852) with 0.5T intraoperative MRI (P < .001) were within and at the margin of the range of good reproducibility, respectively. Example 2: Wide ranges of DSC were observed in brain tumor segmentations: Meningiomas (0.519-0.893), astrocytomas (0.487-0.972), and other mixed gliomas (0.490-0.899). CONCLUSION: The DSC value is a simple and useful summary measure of spatial overlap, which can be applied to studies of reproducibility and accuracy in image segmentation. We observed generally satisfactory but variable validation results in two clinical applications. This metric may be adapted for similar validation tasks.
    [bibtex-key = Zou:2004:Acad-Radiol:14974593]


  141. K H Zou, W M Wells, R Kikinis, and S K Warfield. Three validation metrics for automated probabilistic image segmentation of brain tumours. Stat Med, 23(8):1259-1282, April 2004. [WWW] [doi:10.1002/sim.1723]
    Abstract:
    The validity of brain tumour segmentation is an important issue in image processing because it has a direct impact on surgical planning. We examined the segmentation accuracy based on three two-sample validation metrics against the estimated composite latent gold standard, which was derived from several experts' manual segmentations by an EM algorithm. The distribution functions of the tumour and control pixel data were parametrically assumed to be a mixture of two beta distributions with different shape parameters. We estimated the corresponding receiver operating characteristic curve, Dice similarity coefficient, and mutual information, over all possible decision thresholds. Based on each validation metric, an optimal threshold was then computed via maximization. We illustrated these methods on MR imaging data from nine brain tumour cases of three different tumour types, each consisting of a large number of pixels. The automated segmentation yielded satisfactory accuracy with varied optimal thresholds. The performances of these validation metrics were also investigated via Monte Carlo simulation. Extensions of incorporating spatial correlation structures using a Markov random field model were considered.
    [bibtex-key = Zou:2004:Stat-Med:15083482]


  142. V Grau, A U Mewes, M Alcaniz, R Kikinis, and S K Warfield Improved watershed transform for medical image segmentation using prior information. IEEE Trans Med Imaging, 23(4): 447-58 April 2004 [WWW] [PDF]
    Abstract:
    The watershed transform has interesting properties that make it useful for many different image segmentation applications: it is simple and intuitive, can be parallelized, and always produces a complete division of the image.However, when applied to medical image analysis, it has important drawbacks (oversegmentation, sensitivity to noise, poor detection of thin or low signal to noise ratio structures). We present an improvement to the watershed transform that enables the introduction of prior information in its calculation. We propose to introduce this information via the use of a previous probability calculation. Furthermore, we introduce a method to combine the watershed transform and atlas registration, through the use of markers. We have applied our new algorithm to two challenging applications: knee cartilage and gray matter/white matter segmentation in MR images. Numerical validation of the results is provided, demonstrating the strength of the algorithm for medical image segmentation.
    [bibtex-key = Grau:2004:IEEE-Trans-Med-Imaging:15084070]


  143. S Jaume, M Ferrant, B Macq, L Hoyte, J R Fielding, A Schreyer, R Kikinis, and S K Warfield. Tumor detection in the bladder wall with a measurement of abnormal thickness in CT scans. IEEE Trans Biomed Eng, 50(3):383-390, March 2003. [WWW] [doi: 10.1109/TBME.2003.808828]
    Abstract:
    Virtual cystoscopy is a developing technique for bladder cancer screening. In a conventional cystoscopy, an optical probe is inserted into the bladder and an expert reviews the appearance of the bladder wall. Physical limitations of the probe place restrictions on the examination of the bladder wall. In virtual cystoscopy, a computed tomography (CT) scan of the bladder is acquired and an expert reviews the appearance of the bladder wall as shown by the CT. The task of identifying tumors in the bladder wall has often been done without extensive computational aid to the expert. We have developed an image processing algorithm that aids the expert in the detection of bladder tumors. Compared with an expert observer reading the CT, our algorithm achieves 89% sensitivity, 88% specificity, 48% positive predictive value, and 98% negative predictive value.
    [bibtex-key = Jaume:2003:IEEE-Trans-Biomed-Eng:12669995]


  144. K H Zou, S K Warfield, J R Fielding, C M Tempany, M W William, M R Kaus, F A Jolesz, and R Kikinis. Statistical validation based on parametric receiver operating characteristic analysis of continuous classification data. Acad Radiol, 10(12):1359-1368, December 2003. [WWW]
    Abstract:
    RATIONALE AND OBJECTIVES: The accuracy of diagnostic test and imaging segmentation is important in clinical practice because it has a direct impact on therapeutic planning. Statistical validations of classification accuracy was conducted based on parametric receiver operating characteristic analysis, illustrated on three radiologic examples, MATERIALS AND METHODS: Two parametric models were developed for diagnostic or imaging data. Example 1: A semi-automated fractional segmentation algorithm was applied to magnetic resonance imaging of nine cases of brain tumors. The tumor and background pixel data were assumed to have bi-beta distributions. Fractional segmentation was validated against an estimated composite pixel-wise gold standard based on multi-reader manual segmentations. Example 2: The predictive value of 100 cases of spiral computed tomography of ureteral stone sizes, distributed as bi-normal after a non-linear transformation, under two treatment options received. Example 3: One hundred eighty cases had prostate-specific antigen levels measured in a prospective clinical trial. Radical prostatectomy was performed in all to provide a binary gold standard of local and advanced cancer stages. Prostate-specific antigen level was transformed and modeled by bi-normal distributions. In all examples, areas under the receiver operating characteristic curves were computed. RESULTS. The areas under the receiver operating characteristic curves were: Example 1: Fractional segmentation of magnetic resonance imaging of brain tumors: meningiomas (0.924-0.984); astrocytomas (0.786-0.986); and other low-grade gliomas (0.896-0.983). Example 3: Ureteral stone size for treatment planning (0.813). Example 2: Prostate-specific antigen for staging prostate cancer (0.768). CONCLUSION: All clinical examples yielded fair to excellent accuracy. The validation metric area under the receiver operating characteristic curves may be generalized to evaluating the performances of several continuous classifiers related to imaging.
    [bibtex-key = Zou:2003:Acad-Radiol:14697004]


  145. R W Hunt, S K Warfield, H Wang, M Kean, J J Volpe, and T E Inder Assessment of the impact of the removal of cerebrospinal fluid on cerebral tissue volumes by advanced volumetric 3D-MRI in posthaemorrhagic hydrocephalus in a premature infant. J Neurol Neurosurg Psychiatry, 74(5): 658-60 May 2003. [WWW]
    Abstract:
    Current clinical practice in the premature infant with posthaemorrhagic ventricular dilatation (PHVD) includes drainage of cerebrospinal fluid (CSF). This case study used advanced volumetric three dimensional magnetic resonance imaging to document the impact of CSF removal on the volume of regional brain tissues in a premature infant with PHVD. The removal of a large volume of CSF was associated with an identical reduction in CSF volume, but more dramatically with a significant increase in the regional volumes of cortical grey matter and myelinated white matter. The alterations in cerebral cortical grey matter and myelinated white matter volumes may provide insight into the established association of PHVD with deficits in cognitive and motor functions.
    [bibtex-key = Hunt:2003:J-Neurol-Neurosurg-Psychiatry:12700314]


  146. M Ferrant, A Nabavi, B Macq, P M Black, F A Jolesz, R Kikinis, and S K Warfield. Serial registration of intraoperative MR images of the brain. Med Image Anal, 6(4):337-359, December 2002. [WWW] [PDF]
    Abstract:
    The increased use of image-guided surgery systems during neurosurgery has brought to prominence the inaccuracies of conventional intraoperative navigation systems caused by shape changes such as those due to brain shift. We propose a method to track the deformation of the brain and update preoperative images using intraoperative MR images acquired at different crucial time points during surgery. We use a deformable surface matching algorithm to capture the deformation of boundaries of key structures (cortical surface, ventricles and tumor) throughout the neurosurgical procedure, and a linear finite element elastic model to infer a volumetric deformation. The boundary data are extracted from intraoperative MR images using a real-time intraoperative segmentation algorithm. The algorithm has been applied to a sequence of intraoperative MR images of the brain exhibiting brain shift and tumor resection. Our results characterize the brain shift after opening of the dura and at the different stages of tumor resection, and brain swelling afterwards. Analysis of the average deformation capture was assessed by comparing landmarks identified manually and the results indicate an accuracy of 0.7+/-0.6 mm (mean+/-S.D.) for boundary surface landmarks, of 0.9+/-0.6 mm for landmarks inside the boundary surfaces, and 1.6+/-0.9 mm for landmarks in the vicinity of the tumor.
    [bibtex-key = Ferrant:2002:Med-Image-Anal:12426109]


  147. J R Fielding, L X Hoyte, S A Okon, A Schreyer, J Lee, K H Zou, S K Warfield, J P Richie, K R Loughlin, M P O'Leary, C J Doyle, and R Kikinis. Tumor detection by virtual cystoscopy with color mapping of bladder wall thickness. J Urol, 167(2 Pt 1):559-562, February 2002. [WWW]
    Abstract:
    PURPOSE: We determine the value of color mapping of bladder wall thickness for detection of tumor as a component of virtual cystoscopy. MATERIALS AND METHODS: A total of 31 subjects with hematuria and/or a history of bladder tumor underwent helical computerized tomography of the pelvis after distention of the bladder with air. Three-dimensional (D) models were constructed, and thickness of the wall was color mapped according to a fixed and validated mm. scale. Axial source images and 3-D models were reviewed and graded for the presence of wall thickening. A comparison was made with findings on conventional cystoscopy in 31 patients and pathological specimen in 13. RESULTS: Compared with conventional cystoscopy, the analysis of axial image yielded a sensitivity of 0.80, specificity 0.90, positive predictive value 0.80 and negative predictive value 0.90 for the presence of tumor. Examination of color mapped 3-D renderings resulted in 0.83, 0.36, 0.42 and 0.71, respectively. CONCLUSIONS: Thin axial computerized tomography of the air distended bladder shows promise as a potential screening tool for bladder cancer. The low specificity of color mapped 3-D renderings makes the technique inappropriate for screening. It may valuable for guiding urologists to additional suspicious sites in a patient with a known tumor.
    [bibtex-key = Fielding:2002:J-Urol:11792918]


  148. M Hirose, A Bharatha, N Hata, K H Zou, S K Warfield, R A Cormack, A D'Amico, R Kikinis, F A Jolesz, and C M Tempany. Quantitative MR imaging assessment of prostate gland deformation before and during MR imaging-guided brachytherapy. Acad Radiol, 9(8):906-912, August 2002. [WWW]
    Abstract:
    RATIONALE AND OBJECTIVES: The authors performed this study to document the deformations that occur between pretreatment magnetic resonance (MR) imaging and intraoperative MR imaging during brachytherapy. MATERIALS AND METHODS: MR images obtained at 1.5 and 0.5 T in 10 patients with prostate cancer were analyzed for changes in the shape and substructure of the prostate. Three-dimensional models of the prostate were obtained. The authors measured anteroposterior dimension; total gland, peripheral zone, and central gland volumes; transverse dimension; and superoinferior height. RESULTS: Gland deformations were seen at visual inspection of the three-dimensional models. The anteroposterior dimension of the total gland, central gland, and peripheral zone increased from 1.5- to 0.5-T imaging (median dimension, 4.9, 1.5, and 1.8 mm, respectively), and the increase was greatest in the peripheral zone (P < .05, all comparisons). There was a decrease in the transverse dimension from 1.5- to 0.5-T imaging (median, 4.5 mm; P < .005). The total gland volume and the superoinferior height did not show a statistically significant change. CONCLUSION: There were significant deformations in the shape of the prostate, especially in the peripheral zone, between the two imaging studies. The likely causes of the shape change are differences in rectal filling (endorectal coil used in 1.5-T studies vs obturator in 0.5-T studies) and/or changes in patient position (supine vs lithotomy). These findings suggest that pretreatment images alone may not be reliable for accurate therapy planning. It may be useful to integrate pre-and intraoperative data.
    [bibtex-key = Hirose:2002:Acad-Radiol:12186439]


  149. X Wei, S K Warfield, K H Zou, Y Wu, X Li, A Guimond, J P Mugler, R R Benson, L Wolfson, H L Weiner, and C R Guttmann. Quantitative analysis of MRI signal abnormalities of brain white matter with high reproducibility and accuracy. J Magn Reson Imaging, 15(2):203-209, February 2002. [WWW]
    Abstract:
    PURPOSE: To assess the reproducibility and accuracy compared to radiologists of three automated segmentation pipelines for quantitative magnetic resonance imaging (MRI) measurement of brain white matter signal abnormalities (WMSA). MATERIALS and METHODS: WMSA segmentation was performed on pairs of whole brain scans from 20 patients with multiple sclerosis (MS) and 10 older subjects who were positioned and imaged twice within 30 minutes. Radiologist outlines of WMSA on 20 sections from 16 patients were compared with the corresponding results of each segmentation method. RESULTS: The segmentation method combining expectation-maximization (EM) tissue segmentation, template-driven segmentation (TDS), and partial volume effect correction (PVEC) demonstrated the highest accuracy (the absolute value of the Z-score was 0.99 for both groups of subjects), as well as high interscan reproducibility (repeatability coefficient was 0.68 mL in MS patients and 1.49 mL in aging subjects). CONCLUSION: The addition of TDS to the EM segmentation and PVEC algorithms significantly improved the accuracy ofWMSA volume measurements, while also improving measurement reproducibility.
    [bibtex-key = Wei:2002:J-Magn-Reson-Imaging:11836778]


  150. J Ruiz-Alzola, C F Westin, S K Warfield, C Alberola, S Maier, and R Kikinis Nonrigid registration of 3D tensor medical data. Med Image Anal., 6(2): 143-61 June 2002. [WWW]
    Abstract:
    New medical imaging modalities offering multi-valued data, such as phase contrast MRA and diffusion tensor MRI, require general representations for the development of automated algorithms. In this paper we propose a unified framework for the registration of medical volumetric multi-valued data using local matching. The paper extends the usual concept of similarity between two pieces of data to be matched, commonly used with scalar (intensity) data, to the general tensor case. Our approach to registration is based on a multiresolution scheme, where the deformation field estimated in a coarser level is propagated to provide an initial deformation in the next finer one. In each level, local matching of areas with a high degree of local structure and subsequent interpolation are performed. Consequently, we provide an algorithm to assess the amount of structure in generic multi-valued data by means of gradient and correlation computations. The interpolation step is carried out by means of the Kriging estimator, which provides a novel framework for the interpolation of sparse vector fields in medical applications. The feasibility of the approach is illustrated by results on synthetic and clinical data.
    [bibtex-key = RuizAlzola:2002:Med-Image-Anal:12045001]


  151. R R Benson, C R Guttmann, X Wei, S K Warfield, C Hall, J A Schmidt, R Kikinis, and L I Wolfson Older people with impaired mobility have specific loci of periventricular abnormality on MRI. Neurology, 58(1): 48-55 January 2002. [WWW]
    Abstract:
    BACKGROUND: Recent investigations using MRI suggest that older persons with mobility impairment have a greater volume of abnormal cerebral white matter compared with persons with normal mobility, thus raising the possibility that those with impairment have lesions in areas critical for the control of mobility. OBJECTIVE: To utilize automated image analysis methods to localize the specific regions of abnormal white matter that distinguish subjectswith lower mobility from subjects with higher mobility. METHODS: Tissue classification was performed on subjects' dual-echo long repetition time spin-echo MRI using computer algorithms operating on intensity criteria integrated with anatomic information. Statistical analysis of group differences was obtained after spatially normalizing each brain to a standard reference brain. RESULTS: Four discrete periventricular regions, including bilaterally symmetric frontal and bilateral occipitoparietal regions, were identified as being sensitive (frontal) or specific (occipitoparietal) in discriminating the subjects with lower mobility from subjects with higher mobility. The symmetry of these lesions in individual subjects suggested pathology other than arteriolar infarction. CONCLUSIONS: These results suggest that damage to discrete frontal and occipitoparietal periventricular white matter locations may be associated with a mobility disorder of aging.
    [bibtex-key = Benson:2002:Neurology:11781405]


  152. M Ferrant, A Nabavi, B Macq, F A Jolesz, R Kikinis, and S K Warfield. Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model. IEEE Trans Med Imaging, 20(12):1384-97, December 2001. [WWW] [doi: 10.1109/42.974933]
    Abstract:
    We present a new algorithm for the nonrigid registration of three-dimensional magnetic resonance (MR) intraoperative image sequences showing brain shift. The algorithm tracks key surfaces of objects (cortical surface and the lateral ventricles) in the image sequence using a deformable surface matching algorithm. The volumetric deformation field of the objects is then inferred from the displacements at the boundary surfaces using a linear elastic biomechanical finite-element model. Two experiments on synthetic image sequences are presented, as well as an initial experiment on intraoperative MR images showing brain shift. The results of the registration algorithm show a good correlation of the internal brain structures after deformation, and a good capability of measuring surface as well as subsurface shift. We measured distances between landmarks in the deformed initial image and the corresponding landmarks in the target scan. Cortical surface shifts of up to 10 mm and subsurface shifts of up to 6 mm were recovered with an accuracy of 1 mm or less and 3 mm or less respectively.
    [bibtex-key = Ferrant:2001:IEEE-Trans-Med-Imaging:11811838]

  153. A Bharatha, M Hirose, N Hata, S K Warfield, M Ferrant, K H Zou, E Suarez-Santana, J Ruiz-Alzola, A D'Amico, R A Cormack, R Kikinis, F A Jolesz, and C M Tempany. Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging. Med Phys., 28(12): 2551-60 , December 2001. [WWW]
    Abstract:
    In this report we evaluate an image registration technique that can improve the information content of intraoperative image data by deformable matching of preoperative images. In this study, pretreatment 1.5 tesla (T) magnetic resonance (MR) images of the prostate are registered with 0.5 T intraoperative images. The method involves rigid and nonrigid registration using biomechanical finite element modeling. Preoperative 1.5 T MR imaging is conducted with the patient supine, using an endorectal coil, while intraoperatively, the patient is in the lithotomy position with a rectal obturator in place. We have previously observed that these changes in patient position and rectal filling produce a shape change in the prostate. The registration of 1.5 T preoperative images depicting the prostate substructure [namely central gland (CG) and peripheral zone (PZ)] to 0.5 T intraoperative MR images using this method can facilitate the segmentation of the substructure of the gland for radiation treatment planning. After creating and validating a dataset of manually segmented glands from images obtained in ten sequential MR-guided brachytherapy cases, we conducted a set of experiments to assess our hypothesis that the proposed registration system can significantly improve the quality of matching of the total gland (TG), CG, and PZ. The results showed that the method statistically-significantly improves the quality of match (compared to rigid registration), raising the Dice similarity coefficient (DSC) from prematched coefficients of 0.81, 0.78, and 0.59 for TG, CG, and PZ, respectively, to 0.94, 0.86, and 0.76. A point-based measure of registration agreement was also improved by the deformable registration. CG and PZ volumes are not changed by the registration, indicating that the method maintains the biomechanical topology of the prostate. Although this strategy was tested for MRI-guided brachytherapy, the preliminary results from these experiments suggest that it may be applied to other settings such as transrectal ultrasound-guided therapy, where the integration of preoperative MRI may have a significant impact upon treatment planning and guidance.
    [bibtex-key = Bharatha:2001:Med-Phys:11797960]

  154. A Nabavi, P M Black, D T Gering, C F Westin, V Mehta, R S Pergolizzi, M Ferrant, S K Warfield, N Hata, R B Schwartz, W M Wells, R Kikinis, and F A Jolesz. Serial intraoperative magnetic resonance imaging of brain shift. Neurosurgery, 48(4): 787-97; discussion 797-8, April 2001. [WWW]
    Abstract:
    OBJECTIVE: A major shortcoming of image-guided navigational systems is the use of preoperatively acquired image data, which does not account for intraoperative changes in brain morphology. The occurrence of these surgically induced volumetric deformations ("brain shift") has been well established. Maximal measurements for surface and midline shifts have been reported. There has been no detailed analysis, however, of the changes that occur during surgery. The use of intraoperative magnetic resonance imaging provides a unique opportunity to obtain serial image data and characterize the time course of brain deformations during surgery. METHODS: The vertically open intraoperative magnetic resonance imaging system (SignaSP, 0.5 T; GE Medical Systems, Milwaukee, WI) permits access to the surgical field and allows multiple intraoperative image updates without the need to move the patient. We developed volumetric display software (the 3D Slicer) that allows quantitative analysis of the degree and direction of brain shift. For 25 patients, four or more intraoperative volumetric image acquisitions were extensively evaluated. RESULTS: Serial acquisitions allow comprehensive sequential descriptions of the direction and magnitude of intraoperative deformations. Brain shift occurs at various surgical stages and in different regions. Surface shift occurs throughout surgery and is mainly attributable to gravity. Subsurface shift occurs during resection and involves collapse of the resection cavity and intraparenchymal changes that are difficult to model. CONCLUSION: Brain shift is a continuous dynamic process that evolves differently in distinct brain regions. Therefore, only serial imaging or continuous data acquisition can provide consistently accurate image guidance. Furthermore, only serial intraoperative magnetic resonance imaging provides an accurate basis for the computational analysis of brain deformations, which might lead to an understanding and eventual simulation of brain shift for intraoperative guidance.
    [bibtex-key = Nabavi:2001:Neurosurgery:11322439]

  155. M R Kaus, S K Warfield, A Nabavi, P M Black, F A Jolesz, and R Kikinis.
  156. Automated segmentation of MR images of brain tumors. Radiology, 218(2): 586-91 February 2001. [WWW]
    Abstract:
    An automated brain tumor segmentation method was developed and validated against manual segmentation with three-dimensional magnetic resonance images in 20 patients with meningiomas and low-grade gliomas. The automated method (operator time, 5-10 minutes) allowed rapid identification of brain and tumor tissue with an accuracy and reproducibility comparable to those of manual segmentation (operator time, 3-5 hours), making automated segmentation practical for low-grade gliomas and meningiomas.
    [bibtex-key = Kaus:2001:Radiology:11161183]

  157. R A Sperling, C R Guttmann, M J Hohol, S K Warfield, M Jakab, M Parente, E L Diamond, K R Daffner, M J Olek, E J Orav, R Kikinis, F A Jolesz, and H L Weiner. Regional magnetic resonance imaging lesion burden and cognitive function in multiple sclerosis: a longitudinal study. Arch Neurol., 58(1): 115-21, January 2001. [WWW]
    Abstract:
    OBJECTIVE: To investigate the relationship between magnetic resonance imaging regional lesion burden and cognitive performance in multiple sclerosis (MS) over a 4-year follow-up period. DESIGN: Twenty-eight patients with MS underwent magnetic resonance imaging and took the Brief, Repeatable Battery of Neuropsychological Tests in Multiple Sclerosis at baseline, 1-year, and 4-year follow-up. An automated 3-dimensional lesion detection method was used to identify MS lesions within anatomical regions on proton density T2-weighted images. The relationship between magnetic resonance imaging regional lesion volumes and the Brief, Repeatable Battery of Neuropsychological Tests in Multiple Sclerosis results was examined using regression analyses. RESULTS: At all time points, frontal lesion volume represented the greatest proportion of total lesion volume, and the percentage of white matter classified as lesion was also highest in frontal and parietal regions. On neuropsychological testing, when compared with age- and educational level-matched control subjects, patients with MS showed significant impairment on tests of sustained attention, processing speed, and verbal memory (P>.001). Performance on these measures was negatively correlated with MS lesion volume in frontal and parietal regions at baseline, 1-year, and 4-year follow-up (R = -0.55 to -0.73, P>.001). CONCLUSIONS: Multiple sclerosis lesions show a propensity for frontal and parietal white matter. Lesion burden in these areas was strongly associated with performance on tasks requiring sustained complex attention and working verbal memory. This relationship was consistent over a 4-year period, suggesting that disruption of frontoparietal subcortical networks may underlie the pattern of neuropsychological impairment seen in many patients with MS.
    [bibtex-key = Kaus:2001:Radiology:11161183]

  158. N Hata, A Nabavi, W M Wells, S K Warfield, R Kikinis, P M Black, and F A Jolesz. Three-dimensional optical flow method for measurement of volumetric brain deformation from intraoperative MR images. J Comput Assist Tomogr., 24(4): 531-8 July - August 2000. [WWW]
    Abstract:
    A three-dimensional optical flow method to measure volumetric brain deformation from sequential intraoperative MR images and preliminary clinical results from five cases are reported. Intraoperative MR images were scanned before and after dura opening, twice during tumor resection, and immediately after dura closure. The maximum cortical surface shift measured was 11 mm and subsurface shift was 4 mm. The computed deformation field was most satisfactory when the skin was segmented and removed from the images before the optical flow computation.
    [bibtex-key = Hata:2000:J-Comput-Assist-Tomogr:10966182]

  159. A G Schreyer, J R Fielding, S K Warfield, J H Lee, K R Loughlin, H Dumanli, F A Jolesz, and R Kikinis R. Virtual CT cystoscopy: color mapping of bladder wall thickness. Invest Radiol., 35(5): 331-4, May 2000. [WWW]
    Abstract:
    RATIONALE AND OBJECTIVES: To improve the conspicuity of bladder tumors in a virtual environment, we developed an algorithm for color mapping the thickness of the bladder wall. The purpose of this study was to demonstrate the feasibility of this algorithm as a component of virtual CT cystoscopy. METHODS: Five subjects with a history of superficial transitional-cell carcinoma of the bladder underwent helical CT scanning after insufflation of the bladder with air. Source images were transformed into three-dimensional models, and the thickness of the bladder wall was demarcated by using a new computer algorithm and a fixed color scale. Results were compared with those obtained by conventional cystoscopy. RESULTS: Three tumors, one site of benign wall thickening, and normal wall thickness were correctly identified by using axial source images and virtual cystoscopy with color mapping. CONCLUSIONS: Color mapping of bladder wall thickness is feasible and demonstrates both normal and thickened urothelium. Its value in identification of small or sessile tumors will require further trials.
    [bibtex-key = Schreyer:2000:Invest-Radiol:10803675]

  160. S K Warfield, R V Mulkern, C S Winalski, F A Jolesz, and R Kikinis. An image processing strategy for the quantification and visualization of exercise-induced muscle MRI signal enhancement. J Magn Reson Imaging, 11(5): 525-31 May 2000. [WWW]
    Abstract:
    Exercise increases the skeletal muscle water signal in T2-weighted images. Potential medical applications of MR studies of exercise-induced muscle signal intensity changes are the assessment of myopathies, sport training regimens, and physical therapy approaches following surgeries. We developed an automated image processing technique that provides volumetric analysis and visualization of exercise-related T2-weighted image intensity changes. The image processing was applied to the segmentation and quantification of activated muscle volumes. Qualitative assessment of muscle activation is demonstrated with three-dimensional surface rendering. Quantitative determination of active muscle volume, signal intensity, and change over time is demonstrated. Visualization of the activated muscles allows functional anatomical assessment of exercise, which in turn allows detection of muscle utilization.
    [bibtex-key = Warfield:2000:J-Magn-Reson-Imaging:10813862]

  161. C R Guttmann, R Benson, S K Warfield, X Wei, M C Anderson, C B Hall, K Abu-Hasaballah, J P Mugler, and L Wolfson. White matter abnormalities in mobility-impaired older persons. Neurology, 54(6): 1277-83, March 2000. [WWW]
    Abstract:
    OBJECTIVE: To investigate the relationship between white matter abnormalities and impairment of gait and balance in older persons. METHODS: Quantitative MRI was used to evaluate the brain tissue compartments of 28 older individuals separated into normal and impaired groups on the basis of mobility performance testing using the Short Physical Performance Battery. In addition, individuals were tested on six indices of gait and balance. For imaging data, segmentation of intracranial volume into four tissue classes was performed using template-driven segmentation, in which signal-intensity-based statistical tissue classification is refined using a digital brain atlas as anatomic template. RESULTS: Both decreased white matter volume, which was age-related, and increased white matter signal abnormalities, which were not age-related, were observed in the mobility-impaired group compared with the control subjects. The average volume of white matter signal abnormalities for impaired individuals was nearly double that of control subjects. CONCLUSIONS: This cross-sectional study suggests that decreased white matter volume is age-related, whereas increased white matter signal abnormalities are most likely to occur as a result of disease. Both of these changes are independently associated with impaired mobility in older persons and therefore likely to be additive factors of motor disability.
    [bibtex-key = Guttmann:2000:Neurology:10746598]

  162. S K Warfield, M Kaus, F A Jolesz, and R Kikinis. Adaptive, template moderated, spatially varying statistical classification. Med Image Anal., 4(1): 43-55, March 2000. [WWW] [PDF]
    Abstract:
    A novel image segmentation algorithm was developed to allow the automatic segmentation of both normal and abnormal anatomy from medical images. The new algorithm is a form of spatially varying statistical classification, in which an explicit anatomical template is used to moderate the segmentation obtained by statistical classification. The algorithm consists of an iterated sequence of spatially varying classification and nonlinear registration, which forms an adaptive, template moderated (ATM), spatially varying statistical classification (SVC). Classification methods and nonlinear registration methods are often complementary, both in the tasks where they succeed and in the tasks where they fail. By integrating these approaches the new algorithm avoids many of the disadvantages of each approach alone while exploiting the combination. The ATM SVC algorithm was applied to several segmentation problems, involving different image contrast mechanisms and different locations in the body. Segmentation and validation experiments were carried out for problems involving the quantification of normal anatomy (MRI of brains of neonates) and pathology of various types (MRI of patients with multiple sclerosis, MRI of patients with brain tumors, MRI of patients with damaged knee cartilage). In each case, the ATM SVC algorithm provided a better segmentation than statistical classification or elastic matching alone.
    [bibtex-key = Warfield:2000:Med-Image-Anal:10972320]

  163. T E Inder, P S Huppi, S Warfield, R Kikinis, G P Zientara, P D Barnes, F Jolesz, and J J Volpe. Periventricular white matter injury in the premature infant is followed by reduced cerebral cortical gray matter volume at term. Ann Neurol., 46(5): 755-60, November 1999. [WWW]
    Abstract:
    Periventricular white matter injury, that is, periventricular leukomalacia (PVL), the dominant form of brain injury in the premature infant, is the major neuropathological substrate associated with the motor and cognitive deficits observed later in such infants. The nature of the relationship of this lesion to the subsequent cognitive deficits is unclear, but such deficits raise the possibility of cerebral cortical neuronal dysfunction. Although cortical neuronal necrosis is not a prominent feature of brain injury in premature infants, the possibility of a deleterious effect of PVL on subsequent cerebral cortical development has not been investigated. An advanced quantitative volumetric three-dimensional magnetic resonance imaging technique was used to measure brain tissue volumes at term in premature infants with earlier ultrasonographic and magnetic resonance imaging evidence of PVL (mean gestational age at birth, 28.7 +/- 2.0 weeks; n = 10), in premature infants with normal imaging studies (mean gestational age at birth, 29.0 +/- 2.1 weeks; n = 10), and in control term infants (n = 14). Premature infants with PVL had a marked reduction in cerebral cortical gray matter at term compared with either premature infants without PVL or normal term infants (mean +/- SD: PVL, 157.5 +/- 41.5 ml; no PVL, 211.7 +/- 25.4 ml; normal term, 218.8 +/- 21.3 ml). As expected, a reduction in the volume of total brain myelinated white matter was also noted (mean +/- SD: PVL, 14.5 +/- 4.6 ml; no PVL, 23.1 +/- 6.9 ml; normal term, 27.6 +/- 10.3 ml). An apparent compensatory increase in total cerebrospinal fluid volume also was found (mean +/- SD: PVL, 64.5 +/- 15.2 ml; no PVL, 52.0 +/- 24.1 ml; normal term, 32.9 +/- 13.5 ml). PVL in the premature infant is shown for the first time to be followed by impaired cerebral cortical development. These findings may provide insight into the anatomical correlate for the intellectual deficits associated with PVL in the premature infant.
    [bibtex-key = Inder:1999:Ann-Neurol:10553993]

  164. C R Guttmann, R Kikinis, M C Anderson, M Jakab, S K Warfield, R J Killiany, H L Weiner, and F A Jolesz. Quantitative follow-up of patients with multiple sclerosis using MRI: reproducibility. J Magn Reson Imaging., 9(4): 509-18, April 1999. [WWW]
    Abstract:
    The reproducibility of an automated method for estimating the volume of white matter abnormalities on brain magnetic resonance (MR) images of multiple sclerosis (MS) patients was evaluated. Twenty MS patients underwent MR imaging twice within 30 minutes. Measurement variability is introduced mainly by MRI acquisition and image registration procedures, which demonstrate significantly worse reproducibility than the image segmentation. The correction of partial volume artifacts is essential for sensitive measurements of overall lesion burden. The average lesion volume difference (bias) between two MR exams of the same MS patient (N = 20) was 0.05 cm3, with a 95% confidence interval between -0.17 and +0.28 cm3, suggesting that the proposed measurement system is suitable for clinical follow-up trials, even in relatively small patient cohorts. The limits of agreement for lesion volume were between -1.3 and +1.5 cm3, implying that in individual patients changes in lesion load need to be at least this large to be detected reliably. This automated method for estimating lesion burden is a reliable tool for the evaluation of MS progression and exacerbation in patient cohorts and potentially also in individual patients.
    [bibtex-key = Guttmann:1999:J-Magn-Reson-Imaging:10232508]

  165. P S Huppi, S Warfield, R Kikinis, P D Barnes, G P Zientara, F A Jolesz, M K Tsuji, and J J Volpe. Quantitative magnetic resonance imaging of brain development in premature and mature newborns. Ann Neurol., 43(2): 224-35, February 1998. [WWW] [doi: 10.1002/ana.410430213]
    Abstract:
    Definition in the living premature infant of the anatomical and temporal characteristics of development of critical brain structures is crucial for insight into the time of greatest vulnerability of such brain structures. We used three-dimensional magnetic resonance imaging (3D MRI) and image-processing algorithms to quantitate total brain volume and total volumes of cerebral gray matter (GM), unmyelinated white matter (WM), myelinated WM, and cerebrospinal fluid (CSF) in 78 premature and mature newborns (postconceptional age, 29-41 weeks). Total brain tissue volume was shown to increase linearly at a rate of 22 ml/wk. Total GM showed a linear increase in relative intracranial volume of approximately 1.4% or 15 ml in absolute volume per week. The pronounced increase in total GM reflected primarily a fourfold increase in cortical GM. Unmyelinated WM was found to be the most prominent brain tissue class in the preterm infant younger than 36 weeks of postconceptional age. Although minimal myelinated WM was present in the preterm infant at 29 weeks, between 35 and 41 weeks an abrupt fivefold increase in absolute volume of myelinated WM was documented. Extracerebral and intraventricular CSF was readily quantitated by this technique and found to change minimally. The application of 3D MRI and tissue segmentation to the study of human infant brain from 29 to 41 weeks of postconceptional age has provided new insights into cerebral cortical development and myelination and has for the first time provided means of quantitative assessment in vivo of early human brain development.
    [bibtex-key = Huppi:1998:Ann-Neurol:9485064]

  166. S K Warfield, F A Jolesz, and R Kikinis. A high performance computing approach to the registration of medical imaging data. Parallel Computing, 24(9-10):1345-1368, October 1998.
    Abstract:
    A novel automatic registration algorithm for the alignment of medical imaging data was developed. The algorithm measures alignment by comparison of dense feature sets (tissue labels) and optimum alignment is found by minimizing the mismatch of tissue segmentations. A parallel implementation that distributes resampling and comparison operations across a cluster of symmetric multiprocessors achieves execution times in a clinically compatible range (5-10 minutes). Each node executes a parallelized resample and compare operation implemented with POSIX threads, and work is dynamically load balanced across the cluster with communication implemented with MPI. The quality of the registration algorithm and the performance characteristics of the parallel implementation were investigated for typical registration problems. The algorithm has been used to successfully achieve intrapatient and interpatient registration of tissue segmentations without any manual intervention for over three hundred scans of the brain.


  167. D V Iosifescu, M E Shenton, S K Warfield, R Kikinis, J Dengler, F A Jolesz, and R W McCarley. An automated registration algorithm for measuring MRI subcortical brain structures. Neuroimage, 6(1): 13-25, July 1997. [WWW] [doi: 10.1006/nimg.1997.0274]
    Abstract:
    An automated registration algorithm was used to elastically match an anatomical magnetic resonance (MR) atlas onto individual brain MR images. Our goal was to evaluate the accuracy of this procedure for measuring the volume of MRI brain structures. We applied two successive algorithms to a series of 28 MR brain images, from 14 schizophrenia patients and 14 normal controls. First, we used an automated segmentation program to differentiate between white matter, cortical and subcortical gray matter, and cerebrospinal fluid. Next, we elastically deformed the atlas segmentation to fit the subject's brain, by matching the white matter and subcortical gray matter surfaces. To assess the accuracy of these measurements, we compared, on all 28 images, 11 brain structures, measured with elastic matching, with the same structures traced manually on MRI scans. The similarity between the measurements (the relative difference between the manual and the automated volume) was 97% for whole white matter, 92% for whole gray matter, and on average 89% for subcortical structures. The relative spatial overlap between the manual and the automated volumes was 97% for whole white matter, 92% for whole gray matter, and on average 75% for subcortical structures. For all pairs of structures rendered with the automated and the manual method, Pearson correlations were between r = 0.78 and r = 0.98 (P < 0.01, N = 28), except for globus pallidus, where r = 0.55 (left) and r = 0. 44 (right) (P < 0.01, N = 28). In the schizophrenia group, compared to the controls, we found a 16.7% increase in MRI volume for the basal ganglia (i.e., caudate nucleus, putamen, and globus pallidus), but no difference in total gray/white matter volume or in thalamic MR volume. This finding reproduces previously reported results, obtained in the same patient population with manually drawn structures, and suggests the utility/efficacy of our automated registration algorithm over more labor-intensive manual tracings.
    [bibtex-key = Iosifescu:1997:Neuroimage:9245652]

  168. S K Warfield. Fast k-NN Classification for multichannel image data. Pattern Recog Lett., 17(7):713-721, 1996.
    Abstract:
    A new fast and exact algorithm for determining the k-NN classification of multichannel image data, and a new distance transform algorithm are described. Complexity analysis and empirical studies with magnetic resonance images (MRI) demonstrate the effectiveness of the new classification algorithm.


  169. S Warfield, J Dengler, J Zaers, C R Guttmann, W M Wells, G J Ettinger, J Hiller, and R Kikinis. Automatic identification of gray matter structures from MRI to improve the segmentation of white matter lesions. J Image Guid Surg., 1(6): 326-38, 1995. [WWW] [doi: 10.1002/(SICI)1522-712X(1995)1:6<326::AID-IGS4>3.0.CO;2-C]
    Abstract:
    The segmentation of MRI scans of patients with white matter lesions (WML) is difficult because the MRI characteristics of WML are similar to those of gray matter. Intensity-based statistical classification techniques misclassify some WML as gray matter and some gray matter as WML. We developed a fast elastic matching algorithm that warps a reference data set containing information about the location of the gray matter into the approximate shape of the patient's brain. The region of white matter was segmented after segmenting the cortex and deep gray matter structures. The cortex was identified by using a three-dimensional, region-growing algorithm that was constrained by anatomical, intensity gradient, and tissue class parameters. White matter and WML were then segmented without interference from gray matter by using a two-class minimum-distance classifier. Analysis of double-echo spin-echo MRI scans of 16 patients with clinically determined multiple sclerosis (MS) was carried out. The segmentation of the cortex and deep gray matter structures provided anatomical context. This was found to improve the segmentation of MS lesions by allowing correct classification of the white matter region despite the overlapping tissue class distributions of gray matter and MS lesion.
    [bibtex-key = Warfield:1995:J-Image-Guid-Surg:9080353]