Meeting Banner
Abstract #4530

A probabilistic method for unbiased longitudinal tractography with application to Huntington's disease

Anastasia Yendiki 1 , Martin Reuter 1 , Paul Wilkens 1 , Herminia Diana Rosas 1 , and Bruce Fischl 1,2

1 HMS/MGH/MIT Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 2 MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, United States

We propose a probabilistic method for reconstructing white-matter pathways from longitudinal diffusion MRI data. We model the posterior probability of a pathway given a subject's full longitudinal data set, including diffusion and structural images from all time points. Our method is unbiased, making no assumptions on the direction of longitudinal change. By design, it allows longitudinal analysis of anisotropy and diffusivity measures to be performed as a function of position along the trajectory of a tract. We demonstrate that our longitudinal tractography improves both specificity and sensitivity compared to the conventional approach of performing tractography in each time point independently.

This abstract and the presentation materials are available to members only; a login is required.

Join Here