Structure-specific statistical mapping of white matter tracts.
We present a new model-based framework for the statistical analysis of diffusion imaging data associated with specific white matter tracts. The framework takes advantage of the fact that several of the major white matter tracts are thin sheet-like structures that can be effectively modeled by medial representations. The approach involves segmenting major tracts and fitting them with deformable geometric medial models. The medial representation makes it possible to average and combine tensor-based features along directions locally perpendicular to the tracts, thus reducing data dimensionality and accounting for errors in normalization. The framework enables the analysis of individual white matter structures, and provides a range of possibilities for computing statistics and visualizing differences between cohorts. The framework is demonstrated in a study of white matter differences in pediatric chromosome 22q11.2 deletion syndrome.
Yushkevich
Paul A
PA
Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA. pauly2@mail.med.upenn.edu
Zhang
Hui
H
Simon
Tony J
TJ
Gee
James C
JC
D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D038524:Diffusion Magnetic Resonance Imaging; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008959:Models, Neurological