Independent component analysis-based multifiber streamline tractography of the human brain

Abstract

An independent component analysis-based approach has been developed to estimate the orientations of two or three crossing fibers in a voxel to conduct human brain streamline tractography from diffusion data acquired along 25 gradient directions at a b-value of 1000 sec/mm(2) . The approach relies on unmixing signals from fibers mixed within, and spread over, a small cluster of 11 voxels. Simulation studies of diffusion data for two or three crossing fibers at signal-to-noise ratios of 15 and 30 suggest the accuracy to determine interfiber angles with independent component analysis is similar to that attained by a gaussian mixture and other multicompartmental models but at two orders of magnitude faster computational speed. Compared to previous multicompartmental models, independent component analysis visually shows good recovery of fiber orientations and tracts in the crossing region of commonly available orthogonal and 60° phantom diffusion datasets. A 3T MRI human studies show that in contrast to conventional streamline tractography and a multicompartment model, independent component analysis shows better recovery of the continuity of fronto-occipital tracts and cingulum from regions where these tracts are mixed with corpus callosum and other pathways.