Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology
File(s)CTE-Brain-re-rev-v3-forSymplectic.pdf (3.58 MB)
Accepted version
Author(s)
Ghajari, M
Hellyer, P
Sharp, D
Type
Journal Article
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 matter boundary. Fifty-one healthy subjects served as controls. The computational models predicted large strain most prominent at the depths of sulci. The volume fraction of sulcal regions exceeding brain injury thresholds were significantly larger than that of gyral regions. Strain and strain rates were highest for the road traffic accident and sporting injury. Strain was greater in the sulci for all injury types, but strain rate was greater only in the road traffic and sporting injuries. Diffusion tensor imaging showed converging imaging abnormalities within sulcal regions with a significant decrease in fractional anisotropy in the patient group compared to controls within the sulci. Our results show that brain tissue deformation induced by head impact loading is greatest in sulcal locations, where pathology in cases of chronic traumatic encephalopathy is observed. In addition, the nature of initial head loading can have a significant influence on the magnitude and pattern of injury. Clarifying this relationship is key to understanding the long-term effects of head impacts and improving protective strategies, such as helmet design.
Date Issued
2017-02-01
Date Acceptance
2016-10-25
Citation
Brain, 2017, 140 (2), pp.333-343
ISSN
0006-8950
Publisher
Oxford University Press
Start Page
333
End Page
343
Journal / Book Title
Brain
Volume
140
Issue
2
Copyright Statement
© The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
Sponsor
National Institute for Health Research
Wellcome Trust
Grant Number
NIHR-RP-011-048
106092/Z/14/Z
Subjects
Science & Technology
Life Sciences & Biomedicine
Clinical Neurology
Neurosciences
Neurosciences & Neurology
computational modelling
diffusion imaging
traumatic brain injury
DIFFUSE AXONAL INJURY
DYNAMIC STRETCH INJURY
CENTRAL-NERVOUS-SYSTEM
WHITE-MATTER INJURY
COGNITIVE IMPAIRMENT
HEAD-INJURY
TOLERANCE
CONCUSSION
TISSUE
DEFORMATION
computational modelling
diffusion imaging
traumatic brain injury
Adolescent
Adult
Anisotropy
Chronic Traumatic Encephalopathy
Computer Simulation
Diffusion Tensor Imaging
Female
Football
Head
Humans
Imaging, Three-Dimensional
Male
Middle Aged
Models, Neurological
Neuropsychological Tests
Young Adult
Head
Humans
Imaging, Three-Dimensional
Neuropsychological Tests
Anisotropy
Models, Neurological
Football
Computer Simulation
Adolescent
Adult
Middle Aged
Female
Male
Young Adult
Diffusion Tensor Imaging
Chronic Traumatic Encephalopathy
Neurology & Neurosurgery
11 Medical and Health Sciences
17 Psychology and Cognitive Sciences
Publication Status
Published
Date Publish Online
2016-12-31