Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology

Mazdak Ghajari, Peter J. Hellyer, David Sharp

Brain, 2016

Abstract

Traumatic brain injury can lead to the neurodegenerative disease chronic traumatic encephalopathy. This condition has a clear neuropathological definition but the relationship between the initial head impact and the pattern of progressive brain pathology is poorly understood. We test the hypothesis that mechanical strain and strain rate are greatest in sulci, where neuropathology is prominently seen in chronic traumatic encephalopathy, and whether human neuroimaging observations converge with computational predictions. Three distinct types of injury were simulated. Chronic traumatic encephalopathy can occur after sporting injuries, so we studied a helmet-to-helmet impact in an American football game. In addition, we investigated an occipital head impact due to a fall from ground level and a helmeted head impact in a road traffic accident involving a motorcycle and a car. A high fidelity 3D computational model of brain injury biomechanics was developed and the contours of strain and strain rate at the grey matter-white matter boundary were mapped. Diffusion tensor imaging abnormalities in a cohort of 97 traumatic brain injury patients were also mapped at the grey matter-white…

Cite as (BibTeX)

@article{ghajari-2016-computational-modelling-of-traumatic,
  title={Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology},
  author={Mazdak Ghajari and Peter J. Hellyer and David Sharp},
  journal={Brain},
  year={2016},
  doi={10.1093/brain/aww317}
}