An algorithm to estimate anatomical connectivity between brain regions using diffusion MRI

The study of anatomical connectivity is essential for interpreting functional MRI data and for establishing how brain areas are linked together into networks to support higher-order functions. Diffusion-weighted MR images (DWI) and tractography provide a unique noninvasive tool to explore the connectional architecture of the brain. The identification of anatomical circuits associated with a specific function can be better accomplished by the joint application of diffusion and functional MRI. In this article, we propose a simple algorithm to identify the set of pathways between two regions of interest. The method is based upon running deterministic tractography from all possible starting positions in the brain and selecting trajectories that intersect both regions. We compare results from single-fiber tractography using diffusion tensor imaging and from multi-fiber tractography using reduced-encoding persistent angular structure (PAS) MRI on standard DWI datasets from healthy human volunteers. Our results show that, in comparison with single-fiber tractography, the multi-fiber technique reveals additional putative routes of connection. We demonstrate highly consistent results of the proposed technique over a cohort of 16 healthy subjects.