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Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties

Axonal injury represents a critical target area for the prevention and treatment of traumatic brain and spinal cord injuries. Finite element (FE) models of the head and/or brain are often used to predict brain injury caused by external mechanical loadings, such as explosive waves and direct impact....

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Autores principales: Pan, Yi, Sullivan, Daniel, Shreiber, David I., Pelegri, Assimina A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4126384/
https://www.ncbi.nlm.nih.gov/pubmed/25152875
http://dx.doi.org/10.3389/fbioe.2013.00019
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author Pan, Yi
Sullivan, Daniel
Shreiber, David I.
Pelegri, Assimina A.
author_facet Pan, Yi
Sullivan, Daniel
Shreiber, David I.
Pelegri, Assimina A.
author_sort Pan, Yi
collection PubMed
description Axonal injury represents a critical target area for the prevention and treatment of traumatic brain and spinal cord injuries. Finite element (FE) models of the head and/or brain are often used to predict brain injury caused by external mechanical loadings, such as explosive waves and direct impact. The accuracy of these numerical models depends on correctly determining the material properties and on the precise depiction of the tissues’ microstructure (microscopic level). Moreover, since the axonal microstructure for specific regions of the brain white matter is locally oriented, the stress, and strain fields are highly anisotropic and axon orientation dependent. Additionally, mechanical strain has been identified as the proximal cause of axonal injury, which further demonstrates the importance of this multi-scale relationship. In this study, our previously developed FE and kinematic axonal models are coupled and applied to a pseudo 3-dimensional representative volume element of central nervous system white matter to investigate the multi-scale mechanical behavior. An inverse FE procedure was developed to identify material parameters of spinal cord white matter by combining the results of uniaxial testing with FE modeling. A satisfactory balance between simulation and experiment was achieved via optimization by minimizing the squared error between the simulated and experimental force-stretch curve. The combination of experimental testing and FE analysis provides a useful analysis tool for soft biological tissues in general, and specifically enables evaluations of the axonal response to tissue-level loading and subsequent predictions of axonal damage.
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spelling pubmed-41263842014-08-22 Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties Pan, Yi Sullivan, Daniel Shreiber, David I. Pelegri, Assimina A. Front Bioeng Biotechnol Bioengineering and Biotechnology Axonal injury represents a critical target area for the prevention and treatment of traumatic brain and spinal cord injuries. Finite element (FE) models of the head and/or brain are often used to predict brain injury caused by external mechanical loadings, such as explosive waves and direct impact. The accuracy of these numerical models depends on correctly determining the material properties and on the precise depiction of the tissues’ microstructure (microscopic level). Moreover, since the axonal microstructure for specific regions of the brain white matter is locally oriented, the stress, and strain fields are highly anisotropic and axon orientation dependent. Additionally, mechanical strain has been identified as the proximal cause of axonal injury, which further demonstrates the importance of this multi-scale relationship. In this study, our previously developed FE and kinematic axonal models are coupled and applied to a pseudo 3-dimensional representative volume element of central nervous system white matter to investigate the multi-scale mechanical behavior. An inverse FE procedure was developed to identify material parameters of spinal cord white matter by combining the results of uniaxial testing with FE modeling. A satisfactory balance between simulation and experiment was achieved via optimization by minimizing the squared error between the simulated and experimental force-stretch curve. The combination of experimental testing and FE analysis provides a useful analysis tool for soft biological tissues in general, and specifically enables evaluations of the axonal response to tissue-level loading and subsequent predictions of axonal damage. Frontiers Media S.A. 2013-12-09 /pmc/articles/PMC4126384/ /pubmed/25152875 http://dx.doi.org/10.3389/fbioe.2013.00019 Text en Copyright © 2013 Pan, Sullivan, Shreiber and Pelegri. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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
Pan, Yi
Sullivan, Daniel
Shreiber, David I.
Pelegri, Assimina A.
Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties
title Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties
title_full Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties
title_fullStr Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties
title_full_unstemmed Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties
title_short Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties
title_sort finite element modeling of cns white matter kinematics: use of a 3d rve to determine material properties
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4126384/
https://www.ncbi.nlm.nih.gov/pubmed/25152875
http://dx.doi.org/10.3389/fbioe.2013.00019
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