Model-driven exploration of poro-viscoelasticity in human brain tissue: be careful with the parameters!

The brain is arguably the most complex human organ and modelling its mechanical behaviour has challenged researchers for decades. There is still a lack of understanding on how this multiphase tissue responds to mechanical loading and how material parameters can be reliably calibrated. While previous viscoelastic models with two relaxation times have successfully captured the response of brain tissue, the Theory of Porous Media provides a continuum mechanical framework to explore the underlying physical mechanisms, including interactions between solid matrix and free-flowing interstitial fluid. Following our previously published experimental testing protocol, here we perform finite element simulations of cyclic compression-tension loading and compression-relaxation experiments on human brain white and gray matter specimens. The solid volumetric stress proves to be a crucial factor for the overall biphasic tissue behaviour as it strongly interferes with porous effects controlled by the permeability. An inverse parameter identification reveals that poroelasticity alone is insufficient to capture the time-dependent material behaviour, but a poro-viscoelastic formulation captures the response of brain tissue well. We provide valuable insights into the individual contributions of viscous and porous effects. However, due to the strong coupling between porous, viscous, and volumetric effects, additional experiments are required to reliably determine all material parameters.

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Publication Details

Journal
Interface Focus
Published
2024-12-06
DOI
https://doi.org/10.1098/rsfs.2024.0026
Citations
10
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
1.84

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article

Model-driven exploration of poro-viscoelasticity in human brain tissue: be careful with the parameters!

Jan Hinrichsen, Gerhard A. Holzapfel, Nina Reiter, Manuel P. Kainz et al.
10 citations
Interface Focus
Elasticity and Material Modeling
1.84
article

Model-driven exploration of poro-viscoelasticity in human brain tissue: be careful with the parameters!

Jan Hinrichsen, Gerhard A. Holzapfel, Nina Reiter, Manuel P. Kainz, Gerhard Sommer, Paul Steinmann, Ester Comellas, Alexander Greiner, Silvia Budday
article en
10 citations

Abstract

The brain is arguably the most complex human organ and modelling its mechanical behaviour has challenged researchers for decades. There is still a lack of understanding on how this multiphase tissue responds to mechanical loading and how material parameters can be reliably calibrated. While previous viscoelastic models with two relaxation times have successfully captured the response of brain tissue, the Theory of Porous Media provides a continuum mechanical framework to explore the underlying physical mechanisms, including interactions between solid matrix and free-flowing interstitial fluid. Following our previously published experimental testing protocol, here we perform finite element simulations of cyclic compression-tension loading and compression-relaxation experiments on human brain white and gray matter specimens. The solid volumetric stress proves to be a crucial factor for the overall biphasic tissue behaviour as it strongly interferes with porous effects controlled by the permeability. An inverse parameter identification reveals that poroelasticity alone is insufficient to capture the time-dependent material behaviour, but a poro-viscoelastic formulation captures the response of brain tissue well. We provide valuable insights into the individual contributions of viscous and porous effects. However, due to the strong coupling between porous, viscous, and volumetric effects, additional experiments are required to reliably determine all material parameters.

Interface FocusVol. 14(6)
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Norwegian University of Science and Technology (NO), Graz University of Technology (AT), International Center for Numerical Methods in Engineering (ES), University of Glasgow (GB), Universitat Politècnica de Catalunya (ES)
Deutsche Forschungsgemeinschaft, Austrian Science Fund
Openalex Percentile: Top 15%
Elasticity and Material Modeling
1.84
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