Mechanical characterization of brain tissue in simple shear at dynamic strain rates

TL;DR

This study experimentally characterizes brain tissue's shear response at high strain rates, providing data and models crucial for injury prediction in impact scenarios.

Contribution

It introduces a new experimental setup for shear testing of brain tissue at high strain rates and validates theoretical models with experimental data.

Findings

Maximum shear stress increases with strain rate.

Theoretical models agree well with experimental results.

No significant effect of specimen thickness on shear stress.

Abstract

During severe impact conditions, brain tissue experiences a rapid and complex deformation, which can be seen as a mixture of compression, tension and shear. Moreover, diffuse axonal injury (DAI) occurs in animals and humans when both the strains and strain rates exceed 10% and 10/s, respectively. Knowing the mechanical properties of brain tissue in shear at these strains and strain rates is thus of particular importance, as they can be used in finite element simulations to predict the occurrence of brain injuries under different impact conditions. In this research, an experimental setup was developed to perform simple shear tests on porcine brain tissue at strain rates < 120/s. The maximum measured shear stress at strain rates of 30, 60, 90 and 120/s was 1.15 +/- 0.25 kPa, 1.34 +/- 0.19 kPa, 2.19 +/- 0.225 kPa and 2.52 +/- 0.27 kPa, (mean +/- SD), respectively, at the maximum amount of shear, K = 1. Good agreement of experimental, theoretical (Ogden and MooneyRivlin models) and numerical shear stresses was achieved (p = 0.7866 - 0.9935). Specimen thickness effects (2.0 - 10.0 mm thick specimens) were also analyzed numerically and we found that there is no significant difference (p = 0.9954) in the shear stress magnitudes, indicating a homogeneous deformation of the specimens during simple shear tests. Stress relaxation tests in simple shear were also conducted at different strain magnitudes (10% - 60% strain) with the average rise time of 14 ms. This allowed us to estimate elastic and viscoelastic parameters (mu = 4942.0 Pa and Prony parameters: g1 = 0.520, g2 = 0.3057, tau1 = 0.0264 s, tau2 = 0.011 s) that can be used in FE software to analyze the hyperviscoelastic behavior of brain tissue.