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Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach

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, w...

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Autores principales: Giudice, J. Sebastian, Alshareef, Ahmed, Wu, Taotao, Knutsen, Andrew K., Hiscox, Lucy V., Johnson, Curtis L., Panzer, Matthew B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129184/
https://www.ncbi.nlm.nih.gov/pubmed/34017826
http://dx.doi.org/10.3389/fbioe.2021.664268
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author Giudice, J. Sebastian
Alshareef, Ahmed
Wu, Taotao
Knutsen, Andrew K.
Hiscox, Lucy V.
Johnson, Curtis L.
Panzer, Matthew B.
author_facet Giudice, J. Sebastian
Alshareef, Ahmed
Wu, Taotao
Knutsen, Andrew K.
Hiscox, Lucy V.
Johnson, Curtis L.
Panzer, Matthew B.
author_sort Giudice, J. Sebastian
collection PubMed
description 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 in situ brain displacements obtained from cadaveric specimens. To minimize the geometric discrepancy between the FE models used in the iFE calibration and the cadaveric specimens from which the experimental data were obtained, subject-specific models of these cadaveric brain specimens were developed and used in the calibration process. Finally, the calibrated material parameters were extensively verified using independent brain displacement data from 33 rotational head impacts, spanning multiple loading directions (sagittal, coronal, axial), magnitudes (20–40 rad/s), durations (30–60 ms), and severity. Overall, the heterogeneous CAB-20MSym template model demonstrated good biofidelity with a mean overall CORA score of 0.63 ± 0.06 when compared to in situ brain displacement data. Strains predicted by the calibrated model under non-injurious rotational impacts in human volunteers (N = 6) also demonstrated similar biofidelity compared to in vivo measurements obtained from tagged magnetic resonance imaging studies. In addition to serving as an anatomically accurate model for further investigations of TBI biomechanics, the MRE-based framework for implementing material heterogeneity could serve as a foundation for incorporating subject-specific material properties in future models.
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spelling pubmed-81291842021-05-19 Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach Giudice, J. Sebastian Alshareef, Ahmed Wu, Taotao Knutsen, Andrew K. Hiscox, Lucy V. Johnson, Curtis L. Panzer, Matthew B. Front Bioeng Biotechnol Bioengineering and Biotechnology 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 in situ brain displacements obtained from cadaveric specimens. To minimize the geometric discrepancy between the FE models used in the iFE calibration and the cadaveric specimens from which the experimental data were obtained, subject-specific models of these cadaveric brain specimens were developed and used in the calibration process. Finally, the calibrated material parameters were extensively verified using independent brain displacement data from 33 rotational head impacts, spanning multiple loading directions (sagittal, coronal, axial), magnitudes (20–40 rad/s), durations (30–60 ms), and severity. Overall, the heterogeneous CAB-20MSym template model demonstrated good biofidelity with a mean overall CORA score of 0.63 ± 0.06 when compared to in situ brain displacement data. Strains predicted by the calibrated model under non-injurious rotational impacts in human volunteers (N = 6) also demonstrated similar biofidelity compared to in vivo measurements obtained from tagged magnetic resonance imaging studies. In addition to serving as an anatomically accurate model for further investigations of TBI biomechanics, the MRE-based framework for implementing material heterogeneity could serve as a foundation for incorporating subject-specific material properties in future models. Frontiers Media S.A. 2021-05-04 /pmc/articles/PMC8129184/ /pubmed/34017826 http://dx.doi.org/10.3389/fbioe.2021.664268 Text en Copyright © 2021 Giudice, Alshareef, Wu, Knutsen, Hiscox, Johnson and Panzer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Giudice, J. Sebastian
Alshareef, Ahmed
Wu, Taotao
Knutsen, Andrew K.
Hiscox, Lucy V.
Johnson, Curtis L.
Panzer, Matthew B.
Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach
title Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach
title_full Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach
title_fullStr Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach
title_full_unstemmed Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach
title_short Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach
title_sort calibration of a heterogeneous brain model using a subject-specific inverse finite element approach
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129184/
https://www.ncbi.nlm.nih.gov/pubmed/34017826
http://dx.doi.org/10.3389/fbioe.2021.664268
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