Tissue‐Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models. Issue 4 (5th April 2022)

• Record Type: Journal Article
• Authors: Faber, Jessica; Hinrichsen, Jan; Greiner, Alexander; Reiter, Nina; Budday, Silvia
• Is Part Of: Current protocols. Volume 2:Issue 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-04-05
• Subjects: brain tissue -- constitutive modeling -- indentation -- large strains -- multi‐modal mechanical testing -- parameter identification; Life sciences -- Laboratory manuals -- Periodicals; Biology -- Laboratory manuals -- Periodicals; Life sciences -- Technique -- Periodicals; Biology -- Technique -- Periodicals; 570.028
• DOI: 10.1002/cpz1.381
• Languages: English
• ISSNs: 2691-1299

Abstract

Abstract: Brain tissue is one of the most complex and softest tissues in the human body. Due to its ultrasoft and biphasic nature, it is difficult to control the deformation state during biomechanical testing and to quantify the highly nonlinear, time‐dependent tissue response. In numerous experimental studies that have investigated the mechanical properties of brain tissue over the last decades, stiffness values have varied significantly. One reason for the observed discrepancies is the lack of standardized testing protocols and corresponding data analyses. The tissue properties have been tested on different length and time scales depending on the testing technique, and the corresponding data have been analyzed based on simplifying assumptions. In this review, we highlight the advantage of using nonlinear continuum mechanics based modeling and finite element simulations to carefully design experimental setups and protocols as well as to comprehensively analyze the corresponding experimental data. We review testing techniques and protocols that have been used to calibrate material model parameters and discuss artifacts that might falsify the measured properties. The aim of this work is to provide standardized procedures to reliably quantify the mechanical properties of brain tissue and to more accurately calibrate appropriate constitutive models for computational simulations of brain development, injury and disease. Computational models can not only be used to predictively understand brain tissue behavior, but can also serve as valuable tools to assist diagnosis and treatment of diseases or to plan neurosurgical procedures. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. This article was corrected on 16 April 2022. See the end of the full text for details.