Combining quasi-static and high frequency experiments for the viscoelastic characterization of brain tissue
Laura Ruhland, Nina Reiter, Silvia Budday, Kai Willner

TL;DR
This study integrates quasi-static and high-frequency experimental data to develop a unified viscoelastic model of brain tissue, enhancing the accuracy of biomechanical simulations relevant to neurosurgery and brain research.
Contribution
It combines multi-scale experimental findings to calibrate a comprehensive viscoelastic model of brain tissue, addressing inconsistencies in prior literature.
Findings
Consistent regional variations in viscoelastic behavior across scales
Mechanical behavior shifts from elasticity to viscosity with frequency
Unified fractional Kelvin-Voigt model accurately represents tissue mechanics
Abstract
Mechanical models of brain tissue are a beneficial tool to simulate neurosurgical interventions, disease progression, or brain development. However, the accuracy and predictive capacity of such a model relies on a precise experimental characterization of the tissue's mechanical behavior. Such a characterization is yet limited by inconsistent or contradictory experimental responses reported in the literature, particularly when measurements are performed in different time or length scales. Although brain tissue has been extensively investigated in previous studies, the combination of experimental findings from different scales has received limited attention. In this study, we combine ex vivo mechanical responses of porcine brain tissue obtained at different time scales in a mechanical model. We investigated the mechanical behavior of three different brain regions in the quasi-static…
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Taxonomy
TopicsAutomotive and Human Injury Biomechanics · Elasticity and Material Modeling · Ultrasound Imaging and Elastography
