Synergistic Role of Quantitative Diffusion Magnetic Resonance Imaging and Structural Magnetic Resonance Imaging in Predicting Outcomes after Traumatic Brain Injury

Arman Avesta, Anastasia Yendiki, Vincent Perlbarg, Lionel Velly, Omid Khalilzadeh, Louis Puybasset, Damien Galanaud, Rajiv Gupta

Research output: Contribution to journalArticlepeer-review

Abstract

Objective This study aimed to assess if quantitative diffusion magnetic resonance imaging analysis would improve prognostication of individual patients with severe traumatic brain injury. Methods We analyzed images of 30 healthy controls to extract normal fractional anisotropy ranges along 18 white-matter tracts. Then, we analyzed images of 33 patients, compared their fractional anisotropy values with normal ranges extracted from controls, and computed severity of injury to white-matter tracts. We also asked 2 neuroradiologists to rate severity of injury to different brain regions on fluid-attenuated inversion recovery and susceptibility-weighted imaging. Finally, we built 3 models: (1) fed with neuroradiologists' ratings, (2) fed with white-matter injury measures, and (3) fed with both input types. Results The 3 models respectively predicted survival at 1 year with accuracies of 70%, 73%, and 88%. The accuracy with both input types was significantly better (P < 0.05). Conclusions Quantifying severity of injury to white-matter tracts complements qualitative imaging findings and improves outcome prediction in severe traumatic brain injury.

Original languageEnglish (US)
Pages (from-to)236-243
Number of pages8
JournalJournal of computer assisted tomography
Volume46
Issue number2
DOIs
StatePublished - Mar 1 2022

Keywords

  • TBI
  • TRACULA
  • diffusion tensor imaging
  • fractional anisotropy
  • outcome prediction

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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