Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Anastasia Yendiki - , Massachusetts General Hospital (Autor:in)
  • Patricia Panneck - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Priti Srinivasan - , Massachusetts General Hospital (Autor:in)
  • Allison Stevens - , Massachusetts General Hospital (Autor:in)
  • Lilla Zöllei - , Massachusetts General Hospital (Autor:in)
  • Jean Augustinack - , Massachusetts General Hospital (Autor:in)
  • Ruopeng Wang - , Massachusetts General Hospital (Autor:in)
  • David Salat - , Massachusetts General Hospital (Autor:in)
  • Stefan Ehrlich - , Klinik und Poliklinik für Psychiatrie und Psychotherapie, Universitätsklinikum Carl Gustav Carus Dresden, Massachusetts General Hospital, Harvard Medical School (HMS) (Autor:in)
  • Tim Behrens - , University of Oxford (Autor:in)
  • Saad Jbabdi - , University of Oxford (Autor:in)
  • Randy Gollub - , Massachusetts General Hospital (Autor:in)
  • Bruce Fischl - , Massachusetts General Hospital, Massachusetts Institute of Technology (MIT) (Autor:in)

Abstract

We have developed a method for automated probabilistic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images. Our method is called TRACULA (TRActs Constrained by UnderLying Anatomy) and utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual interaction with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. In this paper we illustrate the application of the method on data from a schizophrenia study and investigate whether the inclusion of both patients and healthy subjects in the training set affects our ability to reconstruct the pathways reliably. We show that, since our method does not constrain the exact spatial location or shape of the pathways but only their trajectory relative to the surrounding anatomical structures, a set a of healthy training subjects can be used to reconstruct the pathways accurately in patients as well as in controls.

Details

OriginalspracheEnglisch
Aufsatznummer23
FachzeitschriftFrontiers in neuroinformatics
Jahrgang5
PublikationsstatusVeröffentlicht - 14 Okt. 2011
Peer-Review-StatusJa

Externe IDs

ORCID /0000-0003-2132-4445/work/160950868

Schlagworte

Schlagwörter

  • Diffusion MRI, Tractography, White matter