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Computational Biomechanics for Medicine pp 159–173Cite as

Computation of Brain Deformations Due to Violent Impact: Quantitative Analysis of the Importance of the Choice of Boundary Conditions and Brain Tissue Constitutive Model

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Abstract

The objective of this study is to quantify the effects of approach for modelling the brain-skull interface and constitutive model of the brain parenchyma on predicting the brain deformations using a previously validated finite element head-brain model (Total HUman Model for Safety, THUMS, was used). Four approaches for modelling of the brain-skull interface and two constitutive models (linear viscoelastic and Odgen hyperviscoelastic) of the brain tissue were employed in computer simulations of the experiments reported in the literature. Comparison of the predicted and experimentally determined magnitude and shape of trajectories of selected points within the brain as well as the maximum principal and shear strain within the brain was conducted. The comparison indicates that the predicted brain responses were strongly affected by both analysed factors. The results suggest that accurate prediction of brain deformations due to violent impact requires a model of the brain-skull interface that allows for movement between the brain outer surface and skull, while preventing complete separation between the brain and skull, and constitutive model that accounts for non-linear stress-strain relationship of the brain tissues.

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References

  1. Peeters W, van den Brande R, Polinder S, Brazinova A, Steyerberg EW, Lingsma HF, Maas AI (2015) Epidemiology of traumatic brain injury in Europe. Acta Neurochir 157:1683–1696

    Article  Google Scholar 

  2. de Almeida CER, de Sousa Filho JL, Dourado JC, Gontijo PAM, Dellaretti MA, Costa BS (2016) Traumatic brain injury epidemiology in Brazil. World Neurosurg 87:540–547

    Article  Google Scholar 

  3. Yang KH, King AI (2011) Modeling of the brain for injury simulation and prevention. In: Miller K (ed) Biomechanics of the brain. Springer, New York, pp 90–110

    Google Scholar 

  4. Zhang L, Yang KH, Dwarampudi R, Omori K, Li T, Chang K, Hardy WN, Khalil TB, King AI (2001) Recent advances in brain injury research: a new human head model development and validation. Stapp Car Crash J 45:369–394

    Google Scholar 

  5. Yang J, Xu W, Otte D (2008) Brain injury biomechanics in real world vehicle accident using mathematical models. Chin J Mech 32:81–86

    Article  Google Scholar 

  6. Kleiven S, Hardy WN (2002) Correlation of an FE model of the human head with local brain motion: consequences for injury prediction. Stapp Car Crash J 46:123–144

    Google Scholar 

  7. Miller K, Wittek A, Joldes G, Horton A, Dutta-Roy T, Berger J, Morriss L (2010) Modelling brain deformations for computer-integrated neurosurgery. Int J Numer Meth Bio 26:117–138

    Article  MATH  Google Scholar 

  8. Mao H, Zhang L, Jiang B, Genthikatti VV, Jin X, Zhu F, Makwana R, Gill A, Jandir G, Singh A, Yang KH (2013) Development of a finite element human head model partially validated with thirty five experimental cases. J Biomech Eng 135:111002

    Article  Google Scholar 

  9. Miller K (2011) In: Miller K (ed) Biomechanics of the brain. Springer, New York

    Chapter  Google Scholar 

  10. Miller K, Chinzei K, Orssengo G, Bednarz P (2000) Mechanical properties of brain tissue in-vivo: experiment and computer simulation. J Biomech 33:1369–1376

    Article  Google Scholar 

  11. Miller K, Chinzei K (2002) Mechanical properties of brain tissue in tension. J Biomech 35:483–490

    Article  Google Scholar 

  12. Rashid B, Destrade M, Gilchrist MD (2013) Mechanical characterization of brain tissue in simple shear at dynamic strain rates. J Mech Behav Biomed 28:71–85

    Article  Google Scholar 

  13. Bilston LE (2011) In: Bilston LE (ed) Neural tissue biomechanics: studies in mechanobiology, tissue engineering and biomaterials. Spinger-Verlag, Berlin

    Chapter  Google Scholar 

  14. Wittek A, Grosland NM, Joldes GR, Magnotta V, Miller K (2016) From finite element meshes to clouds of points: a review of methods for generation of computational biomechanics models for patient-specific applications. Ann Biomed Eng 44:3–15

    Article  Google Scholar 

  15. Wittek A, Omori K (2003) Parametric study of effects of brain-skull boundary conditions and brain material properties on responses of simplified finite element brain model under angular acceleration in sagittal plane. JSME Int J 46:1388–1398

    Article  Google Scholar 

  16. Bayly PV, Clayton EH, Genin GM (2012) Quantitative imaging methods for the development and validation of brain biomechanics models. Annu Rev Biomed Eng 14:369–396

    Article  Google Scholar 

  17. Jin X, Mao H, Yang KH, King AI (2014) Constitutive modeling of pia–arachnoid complex. Ann Biomed Eng 42:812–821

    Article  Google Scholar 

  18. Jin X (2009) Biomechanical response and constitutive modeling of bovine pia-arachnoid complex. Dissertation, Wayne State University

    Google Scholar 

  19. Jin X, Yang KH, King AI (2011) Mechanical properties of bovine pia–arachnoid complex in shear. J Biomech 44:467–474

    Article  Google Scholar 

  20. Al-Bsharat AS, Hardy WN, Yang KH, Khalil TB, Tashman S, King AI (1999) Brain/skull relative displacement magnitude due to blunt head impact, In: Proceedings of the 1999 43rd Stapp Car Crash Conference, San Diego, CA, USA

    Google Scholar 

  21. Miller RT, Margulies SS, Leoni M, Nonaka M, Chen X, Smith DH, D.F. Meaney (1998) Finite element modeling approaches for predicting injury in an experimental model of severe diffuse axonal injury. SAE Technical Paper, No. 983154

    Google Scholar 

  22. Agrawal S, Wittek A, Joldes G, Bunt S, Miller K (2015) Mechanical properties of brain-skull Interface in compression. In: Doyle B, Miller K, Wittek A, Nielsen PMF (eds) Computational biomechanics for medicine. Springer International Publishing, New York, pp 83–91

    Google Scholar 

  23. Claessens M, Sauren F, Wismans J (1997) Modeling of the human head under impact conditions: a parametric study. SAE Technical Paper, No. 973338, Washington, DC

    Google Scholar 

  24. Yang J (2011) Investigation of brain trauma biomechanics in vehicle traffic accidents using human body computational models. In: Wittek A, Nielsen PMF, Miller K (eds) Computational biomechanics for medicine. Springer, New York, pp 5–14

    Chapter  Google Scholar 

  25. Shigeta K, Kitagawa Y, Yasuki T (2009) Development of next generation human FE model capable of organ injury prediction, In: International technical conference on the enhanced safety of vehicles (ESV), Stuttgart, Germany

    Google Scholar 

  26. Watanabe R, Miyazaki H, Kitagawa Y, Yasuki T (2011) Research of collision speed dependency of pedestrian head and chest injuries using human FE model (THUMS version 4), In: Proceedings of the 22nd Enhanced Safety of Vehicles (ESV) co nference, Washington DC, USA

    Google Scholar 

  27. Mao H, Zhang L, Yang KH, King AI (2006) Application of a finite element model of the brain to study traumatic brain injury mechanisms in the rat. Stapp Car Crash J 50:583

    Google Scholar 

  28. Takhounts EG, Craig MJ, Moorhouse K, McFadden J, Hasija V (2013) Development of brain injury criteria (BrIC). Stapp Car Crash J 57:243

    Google Scholar 

  29. Haines DE, Harkey HL, Al-Mefty O (1993) The “subdural” space: a new look at an outdated concept. Neurosurgery 32:111–120

    Article  Google Scholar 

  30. Hardy WN, Foster CD, Mason MJ, Yang KH, King AI, Tashman S (2001) Investigation of head injury mechanisms using neutral density technology and high-speed biplanar X-ray. Stapp Car Crash J 45:337–368

    Google Scholar 

  31. Hardy WN (2007) Response of the human cadaver head to impact. Dissertation, Wayne State Univesity

    Google Scholar 

  32. Garlapati R, Roy A, Joldes G, Wittek A, Mostayed A, Doyle B, Warfield S, Kikinis R, Knuckey N, Bunt S, Miller K (2014) More accurate neuronavigation data provided by biomechanical modeling instead of rigid registration. J Neurosurg 120:1477–1483

    Article  Google Scholar 

  33. Miller K, Chinzei K (1997) Constitutive modelling of brain tissue: experiment and theory. J Biomech 30:1115–1121

    Article  Google Scholar 

  34. Wittek A, Dutta-Roy T, Taylor Z, Horton A, Washio T, Chinzei K, Miller K (2008) Subject-specific non-linear biomechanical model of needle insertion into brain. Comput Method Biomech 11:135–146

    Article  Google Scholar 

  35. Wittek A, Miller K, Kikinis R, Warfield SK (2007) Patient-specific model of brain deformation: application to medical image registration. J Biomech 40:919–929

    Article  Google Scholar 

  36. Antona-Makoshi J (2013) Reanalysis of primate head impact experiments to clarify mild traumatic brain injury kinematics and thresholds. Dissertation, Chalmers University of Technology

    Google Scholar 

  37. Hu J, Jin X, Lee JB, Zhang L, Chaudhary V, Guthikonda M, Yang KH, King AI (2007) Intraoperative brain shift prediction using a 3D inhomogeneous patient-specific finite element model. J Neurosurg 106:164–169

    Article  Google Scholar 

  38. Wittek A, Joldes G, Couton M, Warfield SK, Miller K (2010) Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time; application to non-rigid neuroimage registration. Prog Biophys Mol Biol 103:292–303

    Article  Google Scholar 

  39. Mazumder MMG, Miller K, Bunt S, Mostayed A, Joldes G, Day R, Hart R, Wittek A (2013) Mechanical properties of the brain–skull interface. Acta Bioengin Biomech 15:3–11

    Google Scholar 

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Acknowledgements

This work is financially supported by Xiamen University of Technology (Grant No. YKJ15006R) and Fujian Administration of Foreign (Overseas) Experts Affairs (Grant No. 2015-79). Sudip Agrawal was supported by Australian Postgraduate Award programme and The University of Western Australia Safety-Net Top-Up Scholarship. All simulations using Toyota Total HUman Model for Safety THUMS Version 4.0 in this study 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, Zhengyang Geng & Yong Han

  2. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, WA, Australia

    Sudip Agrawal, Karol Miller & Adam Wittek

  3. Institute of Mechanics and Advanced Materials, Cardiff University, Cardiff, UK

    Karol Miller

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  1. Fang Wang
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  2. Zhengyang Geng
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  3. Sudip Agrawal
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  4. Yong Han
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  5. Karol Miller
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  6. Adam Wittek
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Correspondence to Fang Wang .

Editor information

Editors and Affiliations

  1. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Adam Wittek

  2. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Grand Joldes

  3. Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand

    Poul M.F. Nielsen

  4. School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Barry J. Doyle

  5. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Karol Miller

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Wang, F., Geng, Z., Agrawal, S., Han, Y., Miller, K., Wittek, A. (2017). Computation of Brain Deformations Due to Violent Impact: Quantitative Analysis of the Importance of the Choice of Boundary Conditions and Brain Tissue Constitutive Model. In: Wittek, A., Joldes, G., Nielsen, P., Doyle, B., Miller, K. (eds) Computational Biomechanics for Medicine. Springer, Cham. https://doi.org/10.1007/978-3-319-54481-6_14

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  • DOI: https://doi.org/10.1007/978-3-319-54481-6_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54480-9

  • Online ISBN: 978-3-319-54481-6

  • eBook Packages: EngineeringEngineering (R0)

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