Statistical Analysis of Fiber Bundles using Multi-tensor Tractography: Application to First-episode Schizophrenia
Y. Rathi, M. Kubicki, S. Bouix, C.F. Westin, J. Goldstein, L. Seidman, R. Mesholam-Gately, R. McCarley, M. E. Shenton
Mag Reson Image
Volume 29, Pages 507-515
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This work proposes a new method to detect abnormalities in fiber bundles of first-episode (FE) schizophrenia patients. Existing methods
have either examined a particular region of interest or used voxel-based morphometry or used tracts generated using the single tensor model
for locating statistically different fiber bundles. Further, a two-sample t test, which assumes a Gaussian distribution for each population, is the
most widely used statistical hypothesis testing algorithm.
In this study, we use the unscented Kalman filter based two-tensor tractography algorithm for tracing neural fiber bundles of the brain
that connect 105 different cortical and subcortical regions. Next, fiber bundles with significant connectivity across the entire population
were determined. Several diffusion measures derived from the two-tensor model were computed and used as features in the subsequent
analysis. For each fiber bundle, an affine-invariant descriptor was computed, thus obviating the need for precise registration of patients to an
atlas. A kernel-based statistical hypothesis testing algorithm, which makes no assumption regarding the distribution of the underlying
population, was then used to determine the abnormal diffusion properties of all fiber bundles for 20 FE patients and 20 age-matched healthy
controls. Of the 1254 fiber bundles with significant connectivity, 740 fiber bundles were found to be significantly different in at least one
diffusion measure after correcting for multiple comparisons. Thus, the changes affecting first-episode patients seem to be global in nature
(spread throughout the brain).
Rathi Y, Kubicki M, Bouix S, Westin C, Goldstein J, Seidman L, Mesholam-Gately R, McCarley R, Shenton ME. Statistical analysis of fiber bundles using multi-tensor tractography: Application to first-episode schizophrenia. Mag Reson Image 2011;29:507-515.
VA Merit Award, VA Schizophrenia Center Grant
, NIH grants: 1P50MH080272-01, P41 RR13218, R01 MH 52807, R01 MH 50740, R01MH074794, NA-MIC (NIH) U54 GM072977-01