Abbreviations
FE finite element
GM grey matter
TBI traumatic brain injury
WM white matter
Definition
Biomechanical modeling of traumatic brain injury (TBI) refers to the use of a computer model of the human head to simulate brain mechanical responses when the head is subjected to external blunt impact or blast exposure. The resulting tissue responses such as strain, strain rate, and pressure in specific regions of the brain can then be used to predict the occurrence of TBI.
Detailed Description
A computational head injury model is composed of three basic constituents: model geometry, boundary conditions, and tissue material properties. With properly measured impact loading conditions as input for simulation, whole-brain biomechanical responses can then be estimated.
The most widely used method to model the biomechanical responses of TBI is through a finite element (FE) model of the human head (Yang et al. 2006) (illustrated in Fig. 1). This technique discretizes the spatial domain of...
This is a preview of subscription content, log in via an institution to check access.
References
Bayly PV, Clayton EH, Genin GM (2012) Quantitative imaging methods for the development and validation of brain biomechanics models. Annu Rev Biomed Eng 14(1):369–396 Available at: http://www.ncbi.nlm.nih.gov/pubmed/22655600 Accessed 23 July 2012
Cai Y, Wu S, Zhao W, Li Z, Wu Z, Ji S (2018) Concussion classification via deep learning using whole-brain white matter fiber strains. PLoS One 13:e0197992
Chatelin S, Constantinesco A, Willinger R (2010) Fifty years of brain tissue mechanical testing: from in vitro to in vivo investigations. Biorheology 47(5–6):255–276
Cheng S, Clarke EC, Bilston LE (2008) Rheological properties of the tissues of the central nervous system: a review. Med Eng Phys 30(10):1318–1337 Available at: http://www.ncbi.nlm.nih.gov/pubmed/18614386 Accessed 31 Aug 2012
de Rooij R, Kuhl E (2016) Constitutive modeling of brain tissue: current perspectives. Appl Mech Rev 68(1):010801 http://appliedmechanicsreviews.asmedigitalcollection.asme.org/article.aspx?doi=10.1115/1.4032436. Accessed 16 Nov 2017
Di Ieva A et al (2010) Magnetic resonance elastography: a general overview of its current and future applications in brain imaging. Neurosurg Rev 33(2):137–145 Available at: http://www.ncbi.nlm.nih.gov/pubmed/20195674 Accessed 22 Nov 2017
Giordano C, Kleiven S (2014) Evaluation of axonal strain as a predictor for mild traumatic brain injuries using finite element modeling. Stapp Car Crash J, November(October), 58:29–51
Hardy WN et al (2007) A study of the response of the human cadaver head to impact. Stapp Car Crash J 51(October):17–80 Available at: http://www.scopus.com/inward/record.url?eid=2-s2.0-40649100791&partnerID=40&md5=2757831d2296eebdd82689a619f7ff3e
Hrapko M et al (2008) The influence of test conditions on characterization of the mechanical properties of brain tissue. ournal of Biomechanical Engineering 130(June):031003–031001 Available at: http://www.mate.tue.nl/mate/pdfs/8359.pdf Accessed 20 Aug 2013
Ji S et al (2015) Group-wise evaluation and comparison of white matter fiber strain and maximum principal strain in sports-related concussion. J Neurotrauma 32(7):441–454 Available at: http://online.liebertpub.com/doi/10.1089/neu.2013.3268
King AI et al (2003) Is head injury caused by linear or angular acceleration. In: IRCOBI conference, Lisbon, pp 1–12
Lytton, W.W. et al. (2017) Multiscale modeling in the clinic: diseases of the brain and nervous system. Brain Informatics. Available at: http://link.springer.com/10.1007/s40708-017-0067-5
van Dommelen JAW, Hrapko M, Peters GWMWM (2009) Mechanical properties of brain tissue: characterisation and constitutive modelling. In: Kamkim A, Kiseleva I (eds) Mechanosensitivity of the nervous system. Springer, Dordrecht, pp 249–281
Yang KH et al (2006) Development of numerical models for injury biomechanics research: a review of 50 years of publications in the Stapp Car crash conference. Stapp Car Crash J 50:429–490 Available at: http://www.ncbi.nlm.nih.gov/pubmed/17311173
Zhao W, Ji S (2018) White matter anisotropy for impact simulation and response sampling in traumatic brain injury. J. Neurotrauma, p.in press. Available at: https://doi.org/10.1089/neu.2018.5634
Zhao W et al (2016) White matter injury susceptibility via fiber strain evaluation using whole-brain tractography. J Neurotrauma 33(20):1834–1847 Available at: http://online.liebertpub.com/doi/10.1089/neu.2015.4239
Zhao, W. et al. (2017) Injury prediction and vulnerability assessment using strain and susceptibility measures of the deep white matter. Biomechanics and Modeling in Mechanobiology 16(5):1709–1727
Zhao W, Choate B, Ji S (2018) Material properties of the brain in injury-relevant conditions – experiments and computational modeling. J Mech Behav Biomed Mater 80(February):222–234 Available at: http://linkinghub.elsevier.com/retrieve/pii/S1751616118300857
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2022 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Ji, S. (2022). Biomechanical Modeling of Traumatic Brain Injury. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-0716-1006-0_100668
Download citation
DOI: https://doi.org/10.1007/978-1-0716-1006-0_100668
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-0716-1004-6
Online ISBN: 978-1-0716-1006-0
eBook Packages: Biomedical and Life SciencesReference Module Biomedical and Life Sciences