Publications by Year: 2005

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.

We present a statistical framework that combines the registration of an atlas with the segmentation of magnetic resonance images. We use an Expectation Maximization-based algorithm to find a solution within the model, which simultaneously estimates image inhomogeneities, anatomical labelmap, and a mapping from the atlas to the image space. An example of the approach is given for a brain structure-dependent affine mapping approach. The algorithm produces high quality segmentations for brain tissues as well as their substructures. We demonstrate the approach on a set of 22 magnetic resonance images. In addition, we show that the approach performs better than similar methods which separate the registration and segmentation problems.

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.

PURPOSE OF REVIEW: The purpose of this review is to highlight important recent imaging, histological, and genetic findings relevant to white matter abnormalities in schizophrenia. It is cast within the context of research findings conducted over the last 5 years, where we analyze their importance in understanding schizophrenia, as well as discuss future directions for research. RECENT FINDINGS: White matter abnormalities have long been hypothesized in schizophrenia, although only recently has it become possible to investigate them more closely. This has come about as a result of advances in neuroimaging, including new imaging techniques sensitive to white matter structure, as well as advances in computer science, with new analysis techniques making it possible to evaluate several interconnected brain regions at a time. Postmortem studies, with advances such as fluoroscopy and electron microscopy, have also led to quantifying populations of different brain cells, including myelin-forming oligodendrocytes. Moreover, molecular studies enable examination of immunoreactivity of proteins that are responsible for building myelin sheaths. Additionally, microarray genetic studies allow us to investigate myelin-related genes in schizophrenia. Taken together, these technological advances bring us closer to understanding white matter pathology in schizophrenia. SUMMARY: Advances in new imaging techniques likely account for the renewed interest in investigating white matter abnormalities in schizophrenia, with over 30 new articles published on this topic in the last 12 months, compared with 11 the year before. We review recent imaging, histological, and genetic findings that suggest white matter abnormalities in schizophrenia.

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.

We develop a differential geometric framework for regularizing diffusion MRI data. The key idea is to model white matter fibers as 3D space curves and to then extend Parent and Zucker’s 2D curve inference approach [8] by using a notion of co-helicity to indicate compatibility between fibre orientation estimates at each voxel with those in a local neighborhood. We argue that this provides several advantages over earlier regularization methods. We validate the approach quantitatively on a biological phantom and on synthetic data, and qualitatively on data acquired in vivo from a human brain.

OBJECTIVE: Medical classification accuracy studies often yield continuous data based on predictive models for treatment outcomes. A popular method for evaluating the performance of diagnostic tests is the receiver operating characteristic (ROC) curve analysis. The main objective was to develop a global statistical hypothesis test for assessing the goodness-of-fit (GOF) for parametric ROC curves via the bootstrap. DESIGN: A simple log (or logit) and a more flexible Box-Cox normality transformations were applied to untransformed or transformed data from two clinical studies to predict complications following percutaneous coronary interventions (PCIs) and for image-guided neurosurgical resection results predicted by tumor volume, respectively. We compared a non-parametric with a parametric binormal estimate of the underlying ROC curve. To construct such a GOF test, we used the non-parametric and parametric areas under the curve (AUCs) as the metrics, with a resulting p value reported.

OBJECTIVE: Research suggests that the normal left-greater-than-right angular gyrus volume asymmetry is reversed in chronic schizophrenia. The authors examined whether angular gyrus volume and asymmetry were abnormal in patients with first-episode schizophrenia. METHOD: Magnetic resonance imaging scans were obtained from 14 inpatients at their first hospitalization for psychosis and 14 normal comparison subjects. Manual editing was undertaken to delineate postcentral, supramarginal, and angular gyri gray matter volumes. RESULTS: Group comparisons revealed that the left angular gyrus gray matter volume in patients was 14.8% less than that of the normal subjects. None of the other regions measured showed significant group volume or asymmetry differences. CONCLUSIONS: Patients with new-onset schizophrenia showed smaller left angular gyrus volumes than normal subjects, consistent with other studies showing parietal lobe volume abnormalities in schizophrenia. Angular gyrus pathology in first-episode patients suggests that the angular gyrus may be a neuroanatomical substrate for the expression of schizophrenia.

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.

Functional neuroimaging in human subjects and single cell recordings in monkeys show that several extra-striate visual areas are activated by visual motion. However, the extent to which different types of motion are processed in different regions remains unclear, although neuropsychological studies of patients with circumscribed lesions hint at regional specialization. We, therefore, studied four patients with unilateral damage to different regions of extrastriate visual cortex on a series of visual discrimination tasks that required them, to a different extent, to integrate local motion signals in order to correctly perceive the direction of global motion. Performance was assessed psychophysically and compared with that of control subjects and with the patients’ performance with stimuli presented in the visual field ipsilateral to the lesion. The results indicate considerable regional specialization in extra-striate regions for different aspects of motion processing, namely the largest displacement from frame to frame (D-max) that can sustain perception of coherent motion; perception of relative speed; the amount of coherent motion needed to sustain a percept of global motion in a particular direction; the detection of discontinuities within a moving display; the extraction of form from motion. It was also clear that a defect in local motion, i.e. D-max, can be overcome by integrating local motion signals over a longer period of time. Although no patient suffered from only one defect, the overall pattern of results strongly supports the notion of regional specialization for different aspects of motion processing.