4.7 Article

Joint reconstruction of white-matter pathways from longitudinal diffusion MRI data with anatomical priors

Journal

NEUROIMAGE
Volume 127, Issue -, Pages 277-286

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2015.12.003

Keywords

Diffusion MRI; Tractography; Longitudinal data analysis

Funding

  1. National Institute for Biomedical Imaging and Bioengineering [K99/R00-EB008129, R01-EB006758]
  2. National Cancer Institute [K25-CA181632]
  3. National Center for Research Resources [P41-RR14075, U24-RR021382]
  4. National Institute on Aging [AG022381, 5R01-AG008122-22]
  5. National Center for Alternative Medicine [RC1-AT005728-01]
  6. National Institute for Neurological Disorders and Stroke [R01-NS052585-01, 1R21-NS072652-01, 1R01-NS070963]
  7. Shared Instrumentation Grants [1S10RR023401, 1S10RR019307, 1S10RR023043]
  8. National Institutes of Health Blueprint for Neuroscience Research, part of the multi-institutional Human Connectome Project [5U01-MH093765]

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We consider the problem of reconstructing white-matter pathways in a longitudinal study, where diffusion-weighted and T-1-weighted MR images have been acquired at multiple time points for the same subject. We propose a method for joint reconstruction of a subject's pathways at all time points given the subject's entire set of longitudinal data. We apply a method for unbiased within-subject registration to generate a within-subject template from the T-1-weighted images of the subject at all time points. We follow a global probabilistic tractography approach, where the unknown pathway is represented in the space of this within-subject template and propagated to the native space of the diffusion-weighted images at all time points to compute its posterior probability given the images. This ensures spatial correspondence of the reconstructed pathway among time points, which in turn allows longitudinal changes in diffusion measures to be estimated consistently along the pathway. We evaluate the reliability of the proposed method on data from healthy controls scanned twice within a month, where no changes in white-matter microstructure are expected between scans. We evaluate the sensitivity of the method on data from Huntington's disease patients scanned repeatedly over the course of several months, where changes are expected between scans. We show that reconstructing white-matter pathways jointly using the data from all time points leads to improved reliability and sensitivity, when compared to reconstructing the pathways at each time point independently. (C) 2015 Elsevier Inc. All rights reserved.

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