Inverse identification of region-specific hyperelastic material parameters for human brain tissue.
Finite element method
Finite hyperelasticity
Human brain tissue
Ogden model
Parameter identification
Journal
Biomechanics and modeling in mechanobiology
ISSN: 1617-7940
Titre abrégé: Biomech Model Mechanobiol
Pays: Germany
ID NLM: 101135325
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
31
10
2022
accepted:
13
06
2023
medline:
25
9
2023
pubmed:
7
9
2023
entrez:
7
9
2023
Statut:
ppublish
Résumé
The identification of material parameters accurately describing the region-dependent mechanical behavior of human brain tissue is crucial for computational models used to assist, e.g., the development of safety equipment like helmets or the planning and execution of brain surgery. While the division of the human brain into different anatomical regions is well established, knowledge about regions with distinct mechanical properties remains limited. Here, we establish an inverse parameter identification scheme using a hyperelastic Ogden model and experimental data from multi-modal testing of tissue from 19 anatomical human brain regions to identify mechanically distinct regions and provide the corresponding material parameters. We assign the 19 anatomical regions to nine governing regions based on similar parameters and microstructures. Statistical analyses confirm differences between the regions and indicate that at least the corpus callosum and the corona radiata should be assigned different material parameters in computational models of the human brain. We provide a total of four parameter sets based on the two initial Poisson's ratios of 0.45 and 0.49 as well as the pre- and unconditioned experimental responses, respectively. Our results highlight the close interrelation between the Poisson's ratio and the remaining model parameters. The identified parameters will contribute to more precise computational models enabling spatially resolved predictions of the stress and strain states in human brains under complex mechanical loading conditions.
Identifiants
pubmed: 37676609
doi: 10.1007/s10237-023-01739-w
pii: 10.1007/s10237-023-01739-w
pmc: PMC10511383
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1729-1749Subventions
Organisme : Deutsche Forschungsgemeinschaf
ID : project number 460333672 - CRC 1540 Exploring Brain Mechanics (subprojects A01 and A02)
Organisme : Deutsche Forschungsgemeinschaf
ID : BU 3728/1-1
Informations de copyright
© 2023. The Author(s).
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