Automated Probabilistic Reconstruction of White-Matter Pathways in Health and Disease Using an Atlas of the Underlying Anatomy

By Anastasia Yendiki, Patricia Panneck, Priti Srinivasan, A. Stevens, Lilla Zöllei, Jean C. Augustinack, Ruopeng Wang, David H. Salat, S. Ehrlich, Timothy Edward John Behrens and 3 more. Front. Neuroinform., 2011

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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.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/4701fd1f7ee07993aac36de54e11440554ef6440

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Citations in the corpus

FreeSurfer (2012, methodology): “Anastasia Yendiki, in collaboration with Tim Behrens and Saad Jbabdi at Oxford, has developed and integrated automated tractography into FreeSurfer (Yendiki et al., 2011), Lilla Zöllei in collaboration with Gheorghe Postelnicu developed a combined volume and surface registration that aligns cortical”
The early development of brain white matter: a review of imaging studies in fetuses, newborns and infants. (2014, neutral): “, 2011, 2012) and probabilistic methods (Yendiki et al., 2011).”
Spurious group differences due to head motion in a diffusion MRI study (2013, methodology): “We used TRActs Constrained by UnderLying Anatomy (TRACULA) to delineate 18majorWMfascicles in each scan (Yendiki et al., 2011).”
Tract Profiles of White Matter Properties: Automating Fiber-Tract Quantification (2012, background): “There is much interest in developing methods that rapidly and reliably identify and measure fiber tracts in an individual’s brain, and there has been recent progress in automating tract identification [19].”
The first step for neuroimaging data analysis: DICOM to NIfTI conversion. (2016, positive): “This has now been adopted by many tools including MedInria (Toussaint et al. 2007), Freesurfer’s Tracula (Yendiki et al., 2011).”
BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods (2016, neutral): “…algorithm T1w [42–45] tracula Automatic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images T1w, DWI [46] https://doi.org/10.1371/journal.pcbi.1005209.t001 platforms as well as efficient execution on computational clusters independently of the…”