Viscoelasticity of brain corpus callosum in biaxial tension. (November 2016)

• Record Type: Journal Article
• Authors: Labus, Kevin M.; Puttlitz, Christian M.
• Is Part Of: Journal of the mechanics and physics of solids. Volume 96(2016:Nov.)
• Page Start: 591
• Page End: 604
• Publication Date: 2016-11
• Subjects: Stress relaxation -- Anisotropic material -- Biological material -- Constitutive behavior -- Viscoelastic material; Mechanics, Applied -- Periodicals; Solids -- Periodicals; Mechanics -- Periodicals; Mécanique appliquée -- Périodiques; Solides -- Périodiques; Mechanics, Applied; Solids; Periodicals; 531.05
• DOI: 10.1016/j.jmps.2016.08.010
• Languages: English
• ISSNs: 0022-5096

Abstract

Abstract: Computational models of the brain rely on accurate constitutive relationships to model the viscoelastic behavior of brain tissue. Current viscoelastic models have been derived from experiments conducted in a single direction at a time and therefore lack information on the effects of multiaxial loading. It is also unclear if the time-dependent behavior of brain tissue is dependent on either strain magnitude or the direction of loading when subjected to tensile stresses. Therefore, biaxial stress relaxation and cyclic experiments were conducted on corpus callosum tissue isolated from fresh ovine brains. Results demonstrated the relaxation behavior to be independent of strain magnitude, and a quasi-linear viscoelastic (QLV) model was able to accurately fit the experimental data. Also, an isotropic reduced relaxation tensor was sufficient to model the stress-relaxation in both the axonal and transverse directions. The QLV model was fitted to the averaged stress relaxation tests at five strain magnitudes while using the measured strain history from the experiments. The resulting model was able to accurately predict the stresses from cyclic tests at two strain magnitudes. In addition to deriving a constitutive model from the averaged experimental data, each specimen was fitted separately and the resulting distributions of the model parameters were reported and used in a probabilistic analysis to determine the probability distribution of model predictions and the sensitivity of the model to the variance of the parameters. These results can be used to improve the viscoelastic constitutive models used in computational studies of the brain. Highlights: Viscoelastic model of white matter derived from biaxial stress relaxation tests. QLV was sufficient for modeling relaxation at all strain magnitudes tested. Relaxation behavior was nearly isotropic, but elastic behavior was anisotropic. Model accurately predicted stress from cyclic tests at multiple strain magnitudes.