ArticleFrontiers in bioengineering and biotechnology2021
Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach.
Article in Frontiers in bioengineering and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 30 citations in OpenAlex.
- Multiecho Fat-Water Spiral MR Elastography With Distributed Encoding for Simultaneously Imaging Brain and Skull Displacement.Magnetic resonance in medicine · 2026Article
- Mechanical deformation explains distinct neuroimaging patterns and etiologies in brain trauma.NeuroImage · 2026Article
- Effect of modeling subject-specific cortical folds on brain injury risk prediction under blunt impact loading.Biomechanics and modeling in mechanobiology · 2026Article
- Multimodal characterization of intracranial biomechanics in a 3D biofidelic head surrogate.Journal of the mechanical behavior of biomedical materials · 2026Article
- Average Responses of Brain Displacement Under Rotational Loading for Computational Model Validation.IEEE transactions on bio-medical engineering · 2025Article
- An MRI-derived head-neck finite element model.Biomechanics and modeling in mechanobiology · 2025Article
- Brain modes of resonance estimated by a biophysical multi-compartment finite elements model.Scientific reports · 2025Article
- Mechanical characterization of brain tissue: experimental techniques, human testing considerations, and perspectives.Acta biomaterialia · 2025Review
- Average Biomechanical Responses of the Human Brain Grouped by Age and Sex.Annals of biomedical engineering · 2025Article
- Article
- Full-field, frequency-domain comparison of simulated and measured human brain deformation.Biomechanics and modeling in mechanobiology · 2025Article
- Automated data-driven discovery of material models based on symbolic regression: A case study on the human brain cortex.Acta biomaterialia · 2024Article
- Region-Dependent Mechanical Properties of Human Brain Tissue Under Large Deformations Using Inverse Finite Element Modeling.Annals of biomedical engineering · 2024Article
- Effect of Direction and Frequency of Skull Motion on Mechanical Vulnerability of the Human Brain.Journal of biomechanical engineering · 2023Article
- Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports.Annals of biomedical engineering · 2022Review
- Evaluation of cerebral cortex viscoelastic property estimation with nonlinear inversion magnetic resonance elastography.Physics in medicine and biology · 2022Article
- Cerebral vascular strains in dynamic head impact using an upgraded model with brain material property heterogeneity.Journal of the mechanical behavior of biomedical materials · 2022Article
- MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury.Annals of biomedical engineering · 2021Review
- Integrating material properties from magnetic resonance elastography into subject-specific computational models for the human brain.Brain multiphysics · 2021Article
- Subject-Specific Head Model Generation by Mesh Morphing: A Personalization Framework and Its Applications.Frontiers in bioengineering and biotechnology · 2021Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
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
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.