Accelerated Changes in Cortical Thickness Measurements with Age in Military Service Members with Traumatic Brain Injury

J Neurotrauma. 2017 Nov 15;34(22):3107-3116. doi: 10.1089/neu.2017.5022. Epub 2017 Aug 4.


Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.

Keywords: ANTs; MRI; OEF/OIF/OND Service Members; TBI; cortical thickness; gray matter; mTBI; mild traumatic brain injury; traumatic brain injury; volumetrics.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Afghan Campaign 2001-
  • Age Factors
  • Brain Concussion / diagnostic imaging
  • Brain Concussion / epidemiology
  • Brain Concussion / pathology
  • Brain Injuries, Traumatic / diagnostic imaging
  • Brain Injuries, Traumatic / epidemiology
  • Brain Injuries, Traumatic / pathology*
  • Cerebral Cortex / diagnostic imaging
  • Cerebral Cortex / pathology*
  • Female
  • Humans
  • Iraq War, 2003-2011
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Military Personnel / statistics & numerical data*
  • Models, Theoretical*
  • Regression Analysis
  • Retrospective Studies
  • Young Adult