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Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model

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Abstract

In this study, we investigate the effects of modelling choices for the brain–skull interface (layers of tissues between the brain and skull that determine boundary conditions for the brain) and the constitutive model of brain parenchyma on the brain responses under violent impact as predicted using computational biomechanics model. We used the head/brain model from Total HUman Model for Safety (THUMS)—extensively validated finite element model of the human body that has been applied in numerous injury biomechanics studies. The computations were conducted using a well-established nonlinear explicit dynamics finite element code LS-DYNA. We employed four approaches for modelling the brain–skull interface and four constitutive models for the brain tissue in the numerical simulations of the experiments on post-mortem human subjects exposed to violent impacts reported in the literature. The brain–skull interface models included direct representation of the brain meninges and cerebrospinal fluid, outer brain surface rigidly attached to the skull, frictionless sliding contact between the brain and skull, and a layer of spring-type cohesive elements between the brain and skull. We considered Ogden hyperviscoelastic, Mooney–Rivlin hyperviscoelastic, neo–Hookean hyperviscoelastic and linear viscoelastic constitutive models of the brain tissue. Our study indicates that the predicted deformations within the brain and related brain injury criteria are strongly affected by both the approach of modelling the brain–skull interface and the constitutive model of the brain parenchyma tissues. The results suggest that accurate prediction of deformations within the brain and risk of brain injury due to violent impact using computational biomechanics models may require representation of the meninges and subarachnoidal space with cerebrospinal fluid in the model and application of hyperviscoelastic (preferably Ogden-type) constitutive model for the brain tissue.

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Based on Hardy et al. (2001) and adapted from our recent paper (Wang et al. 2017)

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Acknowledgements

The authors would like to gratefully acknowledge the support of National Natural Science Foundation of China (Grant Nos. 51605407, 51505403), Fujian Provincial Department of Science and Technology (Grant No. 2017J01652) and State Administration of Foreign Experts Affairs P. R. China (Grant No. GDT20173600566). All simulations using Total HUman Model for Safety (THUMS) Version 4.0 human body model in this research were conducted at Xiamen University of Technology.

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Authors and Affiliations

  1. School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen, 361024, China

    Fang Wang, Yong Han, Bingyu Wang, Qian Peng & Xiaoqun Huang

  2. Fujian Collaborative Innovation Center for R&D of Coach and Special Vehicle, Xiamen, 361024, China

    Fang Wang, Yong Han, Bingyu Wang, Qian Peng & Xiaoqun Huang

  3. Intelligent System for Medicine Laboratory, The University of Western Australia, Perth, WA, 6009, Australia

    Karol Miller & Adam Wittek

  4. Institute of Mechanics and Advanced Materials, Cardiff School of Engineering, Cardiff University, Wales, UK

    Karol Miller

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  1. Fang Wang
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Correspondence to Fang Wang.

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Adam Wittek was employed by Toyota Central Research and Development Laboratories in 2002–2004, where he was involved in development of the brain model for Total HUman Model for Safety (THUMS). He is a co-author of patent (in Japan) 2004-303220 “Method for determining brain damage, and human head finite element model” by Toyota Central and Development Laboratories.

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Wang, F., Han, Y., Wang, B. et al. Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model. Biomech Model Mechanobiol 17, 1165–1185 (2018). https://doi.org/10.1007/s10237-018-1021-z

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