Accuracy and efficiency of finite element head models: The role of finite element formulation and material laws.
brain model
finite element
finite element technology
traumatic brain injury
Journal
International journal for numerical methods in biomedical engineering
ISSN: 2040-7947
Titre abrégé: Int J Numer Method Biomed Eng
Pays: England
ID NLM: 101530293
Informations de publication
Date de publication:
24 Jul 2024
24 Jul 2024
Historique:
revised:
10
06
2024
received:
17
02
2024
accepted:
08
07
2024
medline:
24
7
2024
pubmed:
24
7
2024
entrez:
24
7
2024
Statut:
aheadofprint
Résumé
Traumatic brain injury is a significant problem worldwide. In the United States of America, around 1.7 million cases are documented annually, displaying the need for a deeper understanding of the effects on the human brain. The tests required for this assessment are very complex. Tests on cadavers may raise serious ethical questions, and in vivo crash tests are not viable. In this context, there is a great need to developing finite element head models (FEHM) to study the biomechanics of the tissues when submitted to a certain impact or acceleration/deceleration scenario. An excellent compromise between accuracy and CPU efficiency is always desirable for a FEHM, For this reason, this work focuses on the improvement of an existing head model, including the study of the behavior of the brain using distinct finite element types. The finite element type and formulation is of utmost importance for the general accuracy and efficiency of the models. Several validations were performed, comparing the simulation results against experimental data. The simulations with hexahedral elements, under specific conditions, obtained more accurate results with a lower computational cost. Using hexahedrals, a comparison was also performed using two material characterizations with more than 10 years apart, using the latest finite element head model validation experiment. Overall, the newer material model displays a less stiff response, although its implementation must always depend on the overall purpose of the model it is being applied to.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e3851Subventions
Organisme : Portuguese Science Foundation
ID : PTDC/EME-EME/1239/2021
Organisme : Portuguese Science Foundation
ID : UIDB/00481/2020
Organisme : Portuguese Science Foundation
ID : UIDP/00481/2020
Organisme : Portugal Regional Operational Programme (Centro2020)
ID : CENTRO-01-0145-FEDER-022083
Organisme : European Regional Development Fund
Informations de copyright
© 2024 John Wiley & Sons Ltd.
Références
Kenner V, Goldsmith W. Dynamic loading of a fluid‐filled spherical shell. Int. J. Mech. Sci. 1972;14(9):557‐568. doi:10.1016/0020‐7403(72)90056‐2
Fernandes FA, de Sousa RJA. Head injury predictors in sports trauma–a state‐of‐the‐art review. Proc Inst Mech Eng H. 2015;229(8):592‐608. doi:10.1177/0954411915592906
Schroder A, Lawrence T, Voets N, et al. A machine learning enhanced mechanistic simulation framework for functional deficit prediction in tbi. Front Bioeng Biotechnol. 2021;9:587082. doi:10.3389/fbioe.2021.587082
Li X, Zhou Z, Kleiven S. An anatomically detailed and personalizable head injury model: significance of brain and white matter tract morphological variability on strain. Biomech Model Mechanobiol. 2021;20(2):403‐431. doi:10.1007/s10237‐020‐01391‐8
Wu T, Alshareef A, Giudice JS, Panzer MB. Explicit modeling of white matter axonal fiber tracts in a finite element brain model. Ann Biomed Eng. 2019;47(9):1908‐1922. doi:10.1007/s10439‐019‐02239‐8
Brooks T, Choi JE, Garnich M, et al. Finite element models and material data for analysis of infant head impacts. Heliyon. 2018;4(12):e01010. doi:10.1016/j.heliyon.2018
Brooks T, Garnich M, Jermy M. Sensitivity of material model parameters on finite element models of infant head impacts. Biomech Model Mechanobiol. 2021;20:1675‐1688. doi:10.1007/s10237‐021‐01469‐x
Carmo GP, Grigioni J, Fernandes FAO, Alves de Sousa RJ. Biomechanics of traumatic head and neck injuries on women: a state‐of‐the‐art review and future directions. Biology. 2023;12(1):83. doi:10.3390/biology12010083
Miller K, Wittek A, Joldes G, et al. Modelling brain deformations for computer‐integrated neurosurgery. Int. J. Numer. Method. Biomed. Eng. 2010;26(1):117‐138. doi:10.1002/cnm.1260
Miller K, Joldes GR, Bourantas G, et al. Biomechanical modeling and computer simulation of the brain during neurosurgery. Int. J. Numer. Method. Biomed. Eng. 2019;35(10):e3250. doi:10.1002/cnm.3250
Mao H, Yang KH. Investigation of brain contusion mechanism and threshold by combining finite element analysis with in vivo histology data. Int. J. Numer. Method. Biomed. Eng. 2011;27(3):357‐366. doi:10.1002/cnm.1403
Fernandes FA, Tchepel D, de Sousa RJA, Ptak M. Development and validation of a new finite element human head model: yet another head model (YEAHM). Eng. Comput. 2018;35:477‐496. doi:10.1108/EC‐09‐2016‐0321
Barbosa A, Fernandes FAO, Alves de Sousa RJ, Ptak M, Wilhelm J. Computational modeling of skull bone structures and simulation of skull fractures using the yeahm head model. Biology. 2020;9(9). doi:10.3390/biology9090267
Nahum A, Smith RW. Experimental model for closed head impact injury. Proceedings: Stapp Car Crash Conference. Vol 20. Society of Automotive Engineers SAE; 1976:785‐814.
Migueis G, Fernandes F, Ptak M, Ratajczak M, Alves de Sousa R. Detection of bridging veins rupture and subdural haematoma onset using a finite element head model. Clin Biomech. 2019;63:104‐111. doi:10.1016/j.clinbiomech.2019.02.010
Costa JM, Fernandes FA, Alves de Sousa RJ. Prediction of subdural haematoma based on a detailed numerical model of the cerebral bridging veins. J Mech Behav Biomed Mater. 2020;111:103976. doi:10.1016/j.jmbbm.2020.103976
Simo J, Rifai M. A class of mixed assumed strain methods and the method of incompatible modes. Int J Numer Methods Eng. 1990;29:1595‐1638. doi:10.1002/nme.1620290802
Bathe K‐J, Iosilevich A, Chapelle D. An evaluation of the mitc shell elements. Comput. Struct. 2000;75(1):1‐30. doi:10.1016/S0045‐7949(99)00214‐X
Malkus DS, Hughes TJ. Mixed finite element methods—reduced and selective integration techniques: a unification of concepts. Comput Methods Appl Mech Eng. 1978;15(1):63‐81. doi:10.1016/0045‐7825(78)90005‐1
Alves de Sousa R, Yoon J, Cardoso R, Fontes Valente R, Grácio J. On the use of a reduced enhanced solid‐shell (ress) element for sheet forming simulations. Int. J. Plast. 2007;23(3):490‐515. doi:10.1016/j.ijplas.2006.06.004
Wang E, Nelson T, Rauch R. Back to elements‐tetrahedra vs. hexahedra, in: Proceedings of the 2004 International ANSYS Conference. Ansys Pennsylvania 2004.
Rashid B, Destrade M, Gilchrist MD. Mechanical characterization of brain tissue in compression at dynamic strain rates. J Mech Behav Biomed Mater. 2012;10:23‐38. doi:10.1016/j.jmbbm.2012.01.022
Rashid B, Destrade M, Gilchrist M. Hyperelastic and viscoelastic properties of brain tissue in tension. 2 10.1115/IMECE2012‐85675.Biomedical and Biotechnology of ASME International Mechanical Engineering Congress and Exposition
Menichetti A, MacManus DB, Gilchrist MD, Depreitere B, Sloten V, Famaey N. Regional characterization of the dynamic mechanical properties of human brain tissue by microindentation. Int. J. Eng. Sci. 2020;155:103355. doi:10.1016/j.ijengsci.2020.103355
MacManus DB, Ghajari M. Material properties of human brain tissue suitable for modelling traumatic brain injury. Brain Multiphysics. 2022;3:100059. doi:10.1016/j.brain.2022.100059
Slicer D. Image segmentation. https://slicer.readthedocs.io/en/latest/user_guide/image_segmentation.html
I. Altair Engineering. Hypermesh help manual. 2019 https://2019.help.altair.com/2019/hm/
Carmo GP, Dymek M, Ptak M, de Sousa RJA, Fernandes FA. Development, validation and a case study: the female finite element head model (FEFEHM). Comput Methods Programs Biomed. 2023;231:107430. doi:10.1016/j.cmpb.2023.107430
Winkler AM, Kochunov P, Blangero J, et al. Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. NeuroImage. 2010;53(3):1135‐1146. doi:10.1016/j.neuroimage.2009.12.028
Hardy WN, Foster CD, Mason MJ, Yang KH, King AI, Tashman S. Investigation of Head Injury Mechanisms Using Neutral Density Technology and High‐Speed Biplanar x‐Ray. Tech. rep., SAE Technical Paper 2001. doi:10.4271/2001‐22‐0016
Hardy WN, Mason MJ, Foster CD, et al. A study of the response of the human cadaver head to impact. Stapp Car Crash J. 2007;51:17‐80. doi:10.4271/2007‐22‐0002
Alshareef A, Giudice JS, Forman J, Salzar RS, Panzer MB. A novel method for quantifying human in situ whole brain deformation under rotational loading using sonomicrometry. J Neurotrauma. 2018;35(5):780‐789. doi:10.1089/neu.2017.5362
Alshareef A, Giudice JS, Forman J, et al. Biomechanics of the human brain during dynamic rotation of the head. J Neurotrauma. 2020;37(13):1546‐1555. doi:10.1089/neu.2019.6847
Gehre C, Gades H, Wernicke P. Objective rating of signals using test and simulation responses. 21st International Technical Conference on the Enhanced Safety of Vehicles Conference (ESV) 2009 09–0407.
Anderson ED, Giudice JS, Wu T, Panzer MB, Meaney DF. (2020) Predicting Concussion Outcome by Integrating Finite Element Modeling and Network Analysis. Front. Bioeng. Biotechnol. 8:309. doi:10.3389/fbioe.2020.00309
Ogden RW. Large deformation isotropic elasticity–on the correlation of theory and experiment for incompressible rubberlike solids. Proc. R. Soc. A. 1972;326(1567):565‐584.
Puso MA, Weiss JA. Finite element implementation of anisotropic quasi‐linear viscoelasticity using a discrete spectrum approximation. J Biomech Eng. 1998;120(1):62‐70. doi:10.1115/1.2834308
Hasgall P, Di Gennaro F, Baumgartner C, et al. It'is database for thermal and electromagnetic parameters of biological tissues. version 4.0, IT'IS 2022. doi:10.13099/VIP21000‐04‐1
Gilchrist M. Modelling and accident reconstruction of head impact injuries. Key Eng. Mater. 2003;245‐246:417‐430. 10.4028/www.scientific.net/KEM.245‐246.417
Hibbitt H, Karlsson B, Sorensen P. Abaqus Analysis user's Manual Version 6.10. Dassault Systèmes Simulia Corp.: Providence, RI, USA 2011.