Viscoelastic parameter identification of human brain tissue

Budday, S., Sommer, G., Holzapfel, G.A., Steinmann, P. and Kuhl, E. (2017) Viscoelastic parameter identification of human brain tissue. Journal of the Mechanical Behavior of Biomedical Materials, 74, pp. 463-476. (doi: 10.1016/j.jmbbm.2017.07.014) (PMID:28756040)

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Abstract

Understanding the constitutive behavior of the human brain is critical to interpret the physical environment during neurodevelopment, neurosurgery, and neurodegeneration. A wide variety of constitutive models has been proposed to characterize the brain at different temporal and spatial scales. Yet, their model parameters are typically calibrated with a single loading mode and fail to predict the behavior under arbitrary loading conditions. Here we used a finite viscoelastic Ogden model with six material parameters–an elastic stiffness, two viscoelastic stiffnesses, a nonlinearity parameter, and two viscous time constants–to model the characteristic nonlinearity, conditioning, hysteresis and tension-compression asymmetry of the human brain. We calibrated the model under shear, shear relaxation, compression, compression relaxation, and tension for four different regions of the human brain, the cortex, basal ganglia, corona radiata, and corpus callosum. Strikingly, unconditioned gray matter with 0.36 kPa and white matter with 0.35 kPa were equally stiff, whereas conditioned gray matter with 0.52 kPa was three times stiffer than white matter with 0.18 kPa. While both unconditioned viscous time constants were larger in gray than in white matter, both conditioned constants were smaller. These rheological differences suggest a different porosity between both tissues and explain–at least in part–the ongoing controversy between reported stiffness differences in gray and white matter. Our unconditioned and conditioned parameter sets are readily available for finite element simulations with commercial software packages that feature Ogden type models at finite deformations. As such, our results have direct implications on improving the accuracy of human brain simulations in health and disease.

Item Type:Articles
Additional Information:The authors thank Dr. Johannes Haybaeck for providing the brain tissue samples. This study was supported by the German National Science Foundation grant STE 544/50 to SB and PS, and by the Humboldt Research Award to EK.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Steinmann, Professor Paul
Authors: Budday, S., Sommer, G., Holzapfel, G.A., Steinmann, P., and Kuhl, E.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
Journal Name:Journal of the Mechanical Behavior of Biomedical Materials
Publisher:Elsevier
ISSN:1751-6161
ISSN (Online):1751-6161
Published Online:11 July 2017
Copyright Holders:Copyright © 2017 Elsevier
First Published:First published in Journal of the Mechanical Behavior of Biomedical Materials 74:463-476
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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