Faculty Bibliography

BACKGROUND: The uncinate fasciculus connects limbic structures, such as the hippocampus and amygdala, with frontal regions. This study utilized diffusion tensor imaging to examine the structural integrity of the uncinate fasciculus in late-life depression. METHOD: 18 elderly depressed and 19 elderly nondepressed subjects were matched for age and sex; 8 subjects had mid- to late-onset of depression while 10 subjects had early-onset depression. 3T diffusion tensor imaging-based fiber tract mapping delineated the uncinate fasciculus in each hemisphere, which guided measurement of the fractional anisotropy of the uncinate fasciculus in the temporal stem. After controlling for age and sex, differences between diagnostic groups were assessed. RESULTS: After controlling for age and sex, individuals with early onset depression exhibited lower anisotropy of the left uncinate fasciculus than did mid- and late-onset or nondepressed subjects (F(2,36) = 4.50, p = 0.02). Analyses of the right uncinate fasciculus were not statistically significant. CONCLUSIONS: This provides preliminary evidence that there is a structural connectivity deficit between left frontal and limbic structures in early-onset depression. Further work is needed to determine if this is seen in younger depressed subjects, and if it influences treatment outcomes.

The emergence of open-source libraries and development tools in the last decade has changed the process of academic software development in many ways. In medical image processing and visualization this change is especially evident, also because open source projects are actively furthered by grant funding institutions. This manuscript presents the use of such development tools and libraries at the UNC Neuro-Image Analysis Laboratory for open source applications and tools. We have also experienced in our research that the development of open source in academics raises the issue of access to unpublished methodology. The strategy at our laboratory is to combine all in-house libraries and applications into a single repository that consists of two parts: a fully open source part that is distributed under a Berkley-style license and a private, closed source part with unpublished tools and methods. Access to the open source part is unrestricted, whereas the private parts can only be downloaded via cvs user login. This setup solved our issues regarding unpublished methodology, as migration from the private to the open source part is very simple. Overall our experience with this development environment within the academic setting is very positive.

Work in progress towards modeling shape statistics of multi-object complexes is presented. Constraints defined by the set of objects such as a compact representation of object shape relationships and correlation of shape changes might have advantages for automatic segmentation and group discrimination. We present a concept for statistical multi-object modeling and discuss the major challenges which are a reduction to a small set of descriptive features, calculation of mean and variability via curved statistics, the choice of aligning sets of multiple objects, and the problem of describing the statistics of object pose and object shape and their interrelationship. Shape modeling and analysis is demonstrated with an application to a longitudinal autism study, with shape modeling of sets of 10 subcortical structures in a population of 20 subjects.

Building of atlases representing average and variability of a population of images or of segmented objects is a key topic in application areas like brain mapping, deformable object segmentation and object classification. Recent developments in image averaging, i.e. constructing an image which is central within the population, focus on unbiased atlas building with nonlinear deformations. Groupwise nonlinear image averaging creates images which appear sharper than linear results. However, volumetric atlases do not explicitely carry a notion of statistics of embedded shapes. This paper compares population-based linear and non-linear image averaging on 3D objects segmented from each image and compares voxel-based versus surface-based representations. Preliminary results suggest improved locality of group average differences for the nonlinear scheme, which might lead to increased significance for hypothesis testing. Results from a clinical MRI study with sets of subcortical structures of children scanned at two years with follow-up at four years are shown.

OBJECTIVE: The corpus callosum is the primary anatomical substrate for interhemispheric communication, which is important for a range of adaptive and cognitive behaviors in early development. Previous studies that have measured the corpus callosum in developmental populations have been limited by the use of rather arbitrary methods of subdividing the corpus callosum. The purpose of this study was to measure the corpus callosum in a clinical group of developmentally delayed children using a subdivision that more accurately reflected the anatomical properties of the corpus callosum. METHOD: The authors applied tractography to subdivide the corpus callosum into regions corresponding to the cortical regions to and from which its fibers travel in a clinical group of very young children with developmental delay, a precursor to general mental retardation, in comparison with typically developing children. RESULTS: The data demonstrate that the midsagittal area of the entire corpus callosum is reduced in children presenting with developmental delay, reflected in the smaller area of each of the fiber-based callosal subdivisions. In addition, while the area of each subdivision was strongly and significantly correlated with the corresponding cortical white matter volume in comparison subjects, this correlation was prominently absent in the developmentally delayed group. CONCLUSIONS: A fiber-based subdivision successfully separates lobar regions of the corpus callosum, and the areas of these regions distinguish a developmentally delayed clinical group from the comparison group. This distinction was evident both in the area measurements themselves and in their correlation to the white matter volumes of the corresponding cortical lobes.