Citation

Dennis EL, Rashid F, Villalon-Reina J, Prasad G, Faskowitz J, Babikian T, Mink R, Babbitt CJ, Johnson J, Giza CC, Asarnow RF, Thompson PM. Lect. Notes Comput. Sci. 2016; 10154: 32-42.

Affiliation

Departments of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and Ophthalmology, USC.

Copyright

(Copyright © 2016, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/978-3-319-55524-9_4

PMID

29147687

PMCID

PMC5684889

Abstract

Traumatic brain injury (TBI) can disrupt the white matter (WM) integrity in the brain, leading to functional and cognitive disruptions that may persist for years. There is considerable heterogeneity within the patient group, which complicates group analyses. Here we present improvements to a tract identification workflow, automated multi-atlas tract extraction (autoMATE), evaluating the effects of improved registration. Use of study-specific template improved group classification accuracy over the standard workflow. The addition of a multi-modal registration that includes information from diffusion weighted imaging (DWI), T1-weighted, and Fluid-Attenuated Inversion Recovery (FLAIR) further improved classification accuracy. We also examined whether particular tracts contribute more to group classification than others. Parts of the corpus callosum contributed most, and there were unexpected asymmetries between bilateral tracts.

Language: en