Defining a multimodal signature of remote sports concussions

Eur J Neurosci. 2017 Aug;46(4):1956-1967. doi: 10.1111/ejn.13583. Epub 2017 May 16.

Abstract

Sports-related concussions lead to persistent anomalies of the brain structure and function that interact with the effects of normal ageing. Although post-mortem investigations have proposed a bio-signature of remote concussions, there is still no clear in vivo signature. In the current study, we characterized white matter integrity in retired athletes with a history of remote concussions by conducting a full-brain, diffusion-based connectivity analysis. Next, we combined MRI diffusion markers with MR spectroscopic, MRI volumetric, neurobehavioral and genetic markers to identify a multidimensional in vivo signature of remote concussions. Machine learning classifiers trained to detect remote concussions using this signature achieved detection accuracies up to 90% (sensitivity: 93%, specificity: 87%). These automated classifiers identified white matter integrity as the hallmark of remote concussions and could provide, following further validation, a preliminary unbiased detection tool to help medical and legal experts rule out concussion history in patients presenting or complaining about late-life abnormal cognitive decline.

Keywords: ageing; concussion; diagnosis; machine learning; neuroimaging.

MeSH terms

  • Aged
  • Athletic Injuries / diagnostic imaging
  • Athletic Injuries / psychology
  • Brain / diagnostic imaging*
  • Brain Concussion / diagnostic imaging*
  • Brain Concussion / etiology
  • Brain Concussion / psychology
  • Football / injuries*
  • Football / psychology
  • Hockey / injuries*
  • Hockey / psychology
  • Humans
  • Machine Learning* / trends
  • Magnetic Resonance Imaging / trends
  • Male
  • Middle Aged
  • Nerve Net / diagnostic imaging*
  • Sports