AUTHOR=Giudice J. Sebastian , Alshareef Ahmed , Wu Taotao , Knutsen Andrew K. , Hiscox Lucy V. , Johnson Curtis L. , Panzer Matthew B. TITLE=Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=9 YEAR=2021 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2021.664268 DOI=10.3389/fbioe.2021.664268 ISSN=2296-4185 ABSTRACT=
Central to the investigation of the biomechanics of traumatic brain injury (TBI) and the assessment of injury risk from head impact are finite element (FE) models of the human brain. However, many existing FE human brain models have been developed with simplified representations of the parenchyma, which may limit their applicability as an injury prediction tool. Recent advances in neuroimaging techniques and brain biomechanics provide new and necessary experimental data that can improve the biofidelity of FE brain models. In this study, the CAB-20MSym template model was developed, calibrated, and extensively verified. To implement material heterogeneity, a magnetic resonance elastography (MRE) template image was leveraged to define the relative stiffness gradient of the brain model. A multi-stage inverse FE (iFE) approach was used to calibrate the material parameters that defined the underlying non-linear deviatoric response by minimizing the error between model-predicted brain displacements and experimental displacement data. This process involved calibrating the infinitesimal shear modulus of the material using low-severity, low-deformation impact cases and the material non-linearity using high-severity, high-deformation cases from a dataset of