Publications

In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to create a weighted undirected graph which is partitioned into coherent sets using the normalized cut (N cut) criterion. A simple and yet effective method for pairwise comparison of fiber traces is presented which in combination with the N cut criterion is shown to produce plausible segmentations of both synthetic and real fiber trace data. Segmentations are visualized as colored stream-tubes or transformed to a segmentation of voxel space, revealing structures in a way that looks promising for future explorative studies of diffusion weighted MRI data.

We introduce a method for combining fiber tracking from diffusion-tensor (DT) imaging with cortical gray matter parcellation from structural high-spatial-resolution 3D spoiled gradient-recalled acquisition in the steady state images. We applied this method to a tumor case to determine the impact of the tumor on white matter architecture. We conclude that this new method for combining structural and DT imaging data is useful for understanding cortical connectivity and the localization of fiber tracts and their relationship with cortical anatomy and brain abnormalities.

A novel method for the visual and quantitative analysis of the geometrical relationship between the vascular architecture of the brain and white matter pathology is presented. The cerebro vascular system is implicated in the pathogenesis of many diseases of the cerebral white matter, for example, stroke, microcerebrovascular disease, and multiple sclerosis (MS). In our work, white matter lesions and vessels are depicted using magnetic resonance imaging (MRI) and extracted using image analysis techniques. We focus on measuring distance relationships between white matter lesions and vessels, and distribution of lesions with respect to vessel caliber. Vascular distance maps are generated by computing for each voxel the Euclidean distance to the closest vessel. Analogously, radius maps assign the radius of the closest vessel to each voxel in the image volume. The distance and radius maps are used to analyze the distribution of lesions with respect to the vessels’ locations and their calibers. The method was applied to three MS patients to demonstrate its functionality and feasibility. Preliminary findings indicate that larger MS lesions tend to be farther from detected vessels and that the caliber of the vessels nearest to larger lesions tends to be smaller, suggesting a possible role of relative hypoperfusion or hypoxia in lesion formation.

BACKGROUND: We measured the shape of the head of the caudate nucleus with a new approach based on magnetic resonance imaging (MRI) in schizotypal personality disorder (SPD) subjects in whom we previously reported decreased caudate nucleus volume. We believe MRI shape analysis complements traditional MRI volume measurements. METHODS: Magnetic resonance imaging scans were used to measure the shape of the caudate nucleus in 15 right-handed male subjects with SPD, who had no prior neuroleptic exposure, and in 14 matched normal comparison subjects. With MRI processing tools, we measured the head of the caudate nucleus using a shape index, which measured how much a given shape deviates from a sphere. RESULTS: In relation to comparison subjects, neuroleptic never-medicated SPD subjects had significantly higher (more "edgy") head of the caudate shape index scores, lateralized to the right side. Additionally, for SPD subjects, higher right and left head of the caudate SI scores correlated significantly with poorer neuropsychological performance on tasks of visuospatial memory and auditory/verbal working memory, respectively. CONCLUSIONS: These data confirm the value of measuring shape, as well as volume, of brain regions of interest and support the association of intrinsic pathology in the caudate nucleus, unrelated to neuroleptic medication, with cognitive abnormalities in the schizophrenia spectrum.

The interaction between the nonionic polymer poly(ethylene oxide) (PEO) of molecular weight 20,000 and surfactants of various types [sodium dodecyl sulfate (SDS), dodecyl trimethylammonium bromide, octyl beta-D-glucoside, and potassium laurate] has been investigated in an aqueous solution at 25 degrees C by 1H NMR pulsed-gradient spin-echo self-diffusion techniques. The SDS/PEO study was further complemented by component-resolved 1H NMR-based studies of the electrophoretic mobility of PEO and the alkyl part of SDS under the same measurement conditions. Through such combined studies, a much more complete picture of the binding and aggregation processes becomes accessible.

Several studies have shown that in tissues over an extended range of b-factors, the signal decay deviates significantly from the basic monoexponential model. The true nature of this departure has to date not been identified. For the current study, line scan diffusion images of brain suitable for biexponential diffusion tensor analysis were acquired in normal subjects on a clinical MR system. For each of six noncollinear directions, 32 images with b-factors ranging from 5 to 5000 s/mm2 were collected. Biexponential fits yielded parameter maps for a fast and a slow diffusion component. A subset of the diffusion data, consisting of the images obtained at the conventional range of b-factors between 5 and 972 s/mm2, was used for monoexponential diffusion tensor analysis. Fractional anisotropy (FA) of the fast-diffusion component and the monoexponential fit exhibited no significant difference. FA of the slow-diffusion biexponential component was significantly higher, particularly in areas of lower fiber density. The principal diffusion directions for the two biexponential components and the monoexponential solution were largely the same and in agreement with known fiber tracts. The second and third diffusion eigenvector directions also appeared to be aligned, but they exhibited significant deviations in localized areas.

We demonstrate that classical Business Process Reengineering (BPR) methods can be successfully applied to Computer Aided Surgery while increasing safety and efficiency of the overall procedure through an integrated Workflow Management System. Computer guided Prostate Brachytherapy, as a sophisticated treatment by an interdisciplinary team, is perfectly suited to apply our method. Detailed suggestions for improvement of the whole procedure could be derived by our modified BPR method.

A way to use adiabatic radiofrequency pulses and modulated magnetic-field gradient pulses, together constituting a "shim pulse," for NMR spectroscopy and imaging is demonstrated. These pulses capitalize on phase shifts derived from probe gradient coils to compensate for nonlinear intrinsic main magnetic field homogeneity for spectroscopy, as well as for deviations from linear gradients for imaging. This approach opens up the possibility of exploiting cheaper, less-than-perfect magnets and gradient coils for NMR applications.

In this paper we present a new algorithm for 3D medical image segmentation. The algorithm is versatile, fast, relatively simple to implement, and semi-automatic. It is based on minimizing a global energy defined from a learned non-parametric estimation of the statistics of the region to be segmented. Implementation details are discussed and source code is freely available as part of the 3D Slicer project. In addition, a new unified set of validation metrics is proposed. Results on artificial and real MRI images show that the algorithm performs well on large brain structures both in terms of accuracy and robustness to noise.

This is an application of new longitudinal structural equation modeling techniques to time-dependent associations of memory and brain structure measurements. There were 225 participants aged 30-80 years at baseline who were measured again after a 7-year interval on both the lateral ventricular size and Wechsler memory score. Multiple regression analyses show nonlinear associations with age but no relationships among longitudinal changes. Mixed-effects latent growth curve analyses and analyses based on latent difference scores indicate that longitudinal changes in both variables are reasonably well described by an exponential or dual change model. Bivariate dynamic structural equation modeling analyses indicate age-lagged changes operate in a coupled-over-time fashion, with the brain measure (lateral ventricular size) as a leading indicator in time of memory (Wechsler memory score) declines.