STRUCTURE-PROPERTY RELATIONS IN PORCINE BRAIN TISSUE: STRAIN RATE AND STRESS-STATE DEPENDENCE

Begonia, M., & Williams, L. N. (2009). STRUCTURE-PROPERTY RELATIONS IN PORCINE BRAIN TISSUE: STRAIN RATE AND STRESS-STATE DEPENDENCE. Mississippi State University: Mississippi State University.

Abstract

Due to an escalating health issue known as traumatic brain injury (TBI), this vital organ has been the focal point in various studies aimed at comprehensively determining its mechanical properties. This study examined the strain rate dependence of porcine brain tissue under unconfined compression, and the cellular damage was quantified using a confocal microscope and generated user interface (GUI) that outputted various analysis parameters including object count, number density (objects/μm2), area fraction (%), mean area (μm2), and mean nearest neighbor distance (μm). The selected strain rates were 0.10 s-1, 0.025 s-1, and 0.00625 s-1 while the strain levels targeted for representative confocal imaging were 15%, 30%, and 40%. This study also utilized similar techniques for characterizing the stress-state dependence at specific conditions under the following testing modes: unconfined compression, uniaxial tension, and fixed-end shear. The designated strain rate and strain level were 0.10 s-1 and 40%, respectively. The strain rate dependency testing protocol resulted in a structure-property relation that exhibited nonlinear, viscoelastic behavior in the mechanical data, and the corresponding GUI parameters correlated with increasing strain rate and strain level. In the structure-property relation derived from the stress-state dependency testing protocol, the mechanical data exhibited vastly distinct nonlinear behavior between testing modes, and disparities were observed between the compressive GUI parameters and both the tension and shear GUI parameters. With this supplementary data, structure-property relations for brain tissue can be established to introduce additional variables into current FEA procedures to devise more realistic safety models for medical, automotive, sports, and military applications.