Mechanical characterization of human brain tissue

Budday, S. et al. (2017) Mechanical characterization of human brain tissue. Acta Biomaterialia, 48, pp. 319-340. (doi: 10.1016/j.actbio.2016.10.036) (PMID:27989920)

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Mechanics are increasingly recognized to play an important role in modulating brain form and function. Computational simulations are a powerful tool to predict the mechanical behavior of the human brain in health and disease. The success of these simulations depends critically on the underlying constitutive model and on the reliable identification of its material parameters. Thus, there is an urgent need to thoroughly characterize the mechanical behavior of brain tissue and to identify mathematical models that capture the tissue response under arbitrary loading conditions. However, most constitutive models have only been calibrated for a single loading mode. Here, we perform a sequence of multiple loading modes on the same human brain specimen – simple shear in two orthogonal directions, compression, and tension – and characterize the loading-mode specific regional and directional behavior. We complement these three individual tests by combined multiaxial compression/tension-shear tests and discuss effects of conditioning and hysteresis. To explore to which extent the macrostructural response is a result of the underlying microstructural architecture, we supplement our biomechanical tests with diffusion tensor imaging and histology. We show that the heterogeneous microstructure leads to a regional but not directional dependence of the mechanical properties. Our experiments confirm that human brain tissue is nonlinear and viscoelastic, with a pronounced compression-tension asymmetry. Using our measurements, we compare the performance of five common constitutive models, neo-Hookean, Mooney-Rivlin, Demiray, Gent, and Ogden, and show that only the isotropic modified one-term Ogden model is capable of representing the hyperelastic behavior under combined shear, compression, and tension loadings: with a shear modulus of 0.4–1.4 kPa and a negative nonlinearity parameter it captures the compression-tension asymmetry and the increase in shear stress under superimposed compression but not tension. Our results demonstrate that material parameters identified for a single loading mode fail to predict the response under arbitrary loading conditions. Our systematic characterization of human brain tissue will lead to more accurate computational simulations, which will allow us to determine criteria for injury, to develop smart protection systems, and to predict brain development and disease progression.

Item Type:Articles
Additional Information:This study was supported by the German National Science Foundation grant STE 544/50 to SB and PS, by the National Institutes of Health grant U54GM072970, and by the Humboldt Research Award to EK. The Austrian Science Fund supported CB and CL (FWF project KLI-523).
Glasgow Author(s) Enlighten ID:Holzapfel, Professor Gerhard and Steinmann, Professor Paul
Authors: Budday, S., Sommer, G., Birkl, C., Langkammer, C., Haybaeck, J., Kohnert, J., Bauer, M., Paulsen, F., Steinmann, P., Kuhl, E., and Holzapfel, G.A.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
Journal Name:Acta Biomaterialia
ISSN (Online):1878-7568
Published Online:27 October 2016

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