Addressing the Problem of Path-Length Dependency in Probabilistic Tractography the ICE-T Framework

Matthew George Liptrot¹, Karam Sidaros¹, Tim Bjrn Dyrby¹

One of the primary hurdles to the quantitative interpretation of probabilistic tractography results is the path-length dependency problem. Here we present a novel framework, Iterative Confidence Enhancement for Tractography (ICE-T), which addresses the issue and can be implemented with any conventional probabilistic tractography method. Fibre-tracking was performed from a somatosensory seed region, and whereas a traditional approach with 60,000 streamlines failed to penetrate far into the contralateral hemisphere, the ICE-T version succeeded with good agreement with in-vivo tracer results. We hope that ICE-T will allow future comparison of quantitative fibre-tracking results across subjects.