Accuracy meets simplicity: A constitutive model for heterogenous brain tissue
Filla N, Hou J, Liu T, Budday S, Wang X (2024)
Publication Type: Journal article
Publication year: 2024
Journal
Book Volume: 150
Article Number: 106271
DOI: 10.1016/j.jmbbm.2023.106271
Abstract
We present a general, hyperelastic, stretch-based potential that shows promise for modeling the mechanics of brain tissue. A specific four-parameter model derived from this general potential outperforms alternative models, such as the modified Ogden model, the Gent model, Demiray model, and machine-learning models, in capturing brain tissue elasticity. Specifically, the stretch-based model achieved R2 values of 0.997, 0.992, and 0.993 (tension, compression, and shear) for the cortex, 0.995, 0.983, and 0.983 for the basal ganglia, 0.994, 0.929, and 0.970 for the corona radiata, and 0.990, 0.896, and 0.969 for the corpus callosum. This work has the potential to advance our understanding of brain tissue mechanics and provides a valuable tool to improve finite element models for the investigation of brain development, injuries, and disease.
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APA:
Filla, N., Hou, J., Liu, T., Budday, S., & Wang, X. (2024). Accuracy meets simplicity: A constitutive model for heterogenous brain tissue. Journal of the Mechanical Behavior of Biomedical Materials, 150. https://doi.org/10.1016/j.jmbbm.2023.106271
MLA:
Filla, Nicholas, et al. "Accuracy meets simplicity: A constitutive model for heterogenous brain tissue." Journal of the Mechanical Behavior of Biomedical Materials 150 (2024).
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