Literature DB >> 18278592

Predictors for traumatic brain injuries evaluated through accident reconstructions.

Svein Kleiven1.   

Abstract

The aim of this study is to evaluate all the 58 available NFL cases and compare various predictors for mild traumatic brain injuries using a detailed and extensively validated finite element model of the human head. Global injury measures such as magnitude in angular and translational acceleration, change in angular velocity, head impact power (HIP) and HIC were also investigated with regard to their ability to predict the intracranial pressure and strains associated with injury. The brain material properties were modeled using a hyperelastic and viscoelastic constitutive law. Also, three different stiffness parameters, encompassing a range of published brain tissue properties, were tested. 8 tissue injury predictors were evaluated for 6 different regions, covering the entire cerebrum, as well as for the whole brain. In addition, 10 head kinematics based predictors were evaluated both for correlation with injury as well as with strain and pressure. When evaluating the results, a statistical correlation between strain, strain rate, product of strain and strain rate, Cumulative Strain Damage Measure (CSDM), strain energy density, maximum pressure, magnitude of minimum pressure, as well as von Mises effective stress, with injury was found when looking into specific regions of the brain. However, the maximal pressure in the gray matter showed a higher correlation with injury than other evaluated measures. On the other hand, it was possible, through the reconstruction of a motocross accident, to re-create the injury pattern in the brain of the injured rider using maximal principal strain. It was also found that a simple linear combination of peak change in rotational velocity and HIC showed a high correlation (R=0.98) with the maximum principal strain in the brain, in addition to being a significant predictor of injury. When applying the rotational and translational kinematics separately for one of the cases, it was found that the translational kinematics contribute very little to the intracranial distortional strains while the rotational kinematics contributes insignificantly to the pressure response. This study underlines that the strain based brain tissue injury predictors are very sensitive to the choice of stiffness for the brain tissue.

Entities:  

Mesh:

Year:  2007        PMID: 18278592     DOI: 10.4271/2007-22-0003

Source DB:  PubMed          Journal:  Stapp Car Crash J        ISSN: 1532-8546


  106 in total

Review 1.  The Influence of Head Impact Threshold for Reporting Data in Contact and Collision Sports: Systematic Review and Original Data Analysis.

Authors:  D King; P Hume; C Gissane; M Brughelli; T Clark
Journal:  Sports Med       Date:  2016-02       Impact factor: 11.136

2.  White Matter Injury Susceptibility via Fiber Strain Evaluation Using Whole-Brain Tractography.

Authors:  Wei Zhao; James C Ford; Laura A Flashman; Thomas W McAllister; Songbai Ji
Journal:  J Neurotrauma       Date:  2016-03-30       Impact factor: 5.269

3.  Real-time, whole-brain, temporally resolved pressure responses in translational head impact.

Authors:  Wei Zhao; Songbai Ji
Journal:  Interface Focus       Date:  2016-02-06       Impact factor: 3.906

4.  A network-based response feature matrix as a brain injury metric.

Authors:  Shaoju Wu; Wei Zhao; Bethany Rowson; Steven Rowson; Songbai Ji
Journal:  Biomech Model Mechanobiol       Date:  2019-11-23

5.  Connecting fractional anisotropy from medical images with mechanical anisotropy of a hyperviscoelastic fibre-reinforced constitutive model for brain tissue.

Authors:  Chiara Giordano; Svein Kleiven
Journal:  J R Soc Interface       Date:  2013-11-20       Impact factor: 4.118

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

Authors:  Mazdak Ghajari; Peter J Hellyer; David J Sharp
Journal:  Brain       Date:  2017-01-02       Impact factor: 13.501

7.  Validation performance comparison for finite element models of the human brain.

Authors:  Logan E Miller; Jillian E Urban; Joel D Stitzel
Journal:  Comput Methods Biomech Biomed Engin       Date:  2017-07-12       Impact factor: 1.763

8.  Resonance of human brain under head acceleration.

Authors:  Kaveh Laksari; Lyndia C Wu; Mehmet Kurt; Calvin Kuo; David C Camarillo
Journal:  J R Soc Interface       Date:  2015-07-06       Impact factor: 4.118

9.  Performance Evaluation of a Pre-computed Brain Response Atlas in Dummy Head Impacts.

Authors:  Wei Zhao; Calvin Kuo; Lyndia Wu; David B Camarillo; Songbai Ji
Journal:  Ann Biomed Eng       Date:  2017-07-14       Impact factor: 3.934

10.  Displacement- and Strain-Based Discrimination of Head Injury Models across a Wide Range of Blunt Conditions.

Authors:  Wei Zhao; Songbai Ji
Journal:  Ann Biomed Eng       Date:  2020-04-02       Impact factor: 3.934

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.