Reiter N, Schäfer AM, Auer S, Paulsen F, Budday S (2023)
Publication Type: Journal article
Publication year: 2023
Continuum-mechanics-based computational models are a valuable tool to advance our understanding of mechanics-related physiological and pathological processes in the brain. Current numerical predictions of brain tissue behavior are mainly based on phenomenological material models. Such models rely on parameters that often lack physical interpretation and only provide adequate estimates for brain regions with a similar microstructure as those used for calibration. These issues can be overcome by establishing advanced constitutive models that are microstructurally motivated and account for regional and temporal changes through microstructural parameters. In a previous study, we have proposed a microstructure-informed finite viscoelastic constitutive model for porcine brain tissue based on experimental insights into the link between macroscopic deformations and cell displacements during compression tests. Here, we test whether the model can be applied to the material response of human brain tissue from different brain regions during compression and tension tests. We calibrate the model using a combination of cyclic loadings in compression and tension as well as stress relaxation experiments in compression. Furthermore, we include cell densities and the percentage area covered by cell nuclei from microstructural analyses of the tested samples into the model. While it was not possible to identify one set of material parameters for all four considered brain regions, we successfully applied the model to tissue from the cerebellar white matter. Our results show that the microstructure-based time constant that we had determined based on experiments on porcine brain tissue is also valid for human tissue. Furthermore, the microstructure-informed material model is capable of capturing the pronounced compression-tension asymmetry of brain tissue.
APA:
Reiter, N., Schäfer, A.-M., Auer, S., Paulsen, F., & Budday, S. (2023). Modeling the finite viscoelasticity of human brain tissue based on microstructural information. Proceedings in Applied Mathematics and Mechanics. https://doi.org/10.1002/pamm.202300234
MLA:
Reiter, Nina, et al. "Modeling the finite viscoelasticity of human brain tissue based on microstructural information." Proceedings in Applied Mathematics and Mechanics (2023).
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