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Histology-informed multiscale modeling of human brain white matter
In this study, we propose a novel micromechanical model for the brain white matter, which is described as a heterogeneous material with a complex network of axon fibers embedded in a soft ground matrix. We developed this model in the framework of RVE-based multiscale theories in combination with the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638412/ https://www.ncbi.nlm.nih.gov/pubmed/37949949 http://dx.doi.org/10.1038/s41598-023-46600-3 |
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author | Saeidi, Saeideh Kainz, Manuel P. Dalbosco, Misael Terzano, Michele Holzapfel, Gerhard A. |
author_facet | Saeidi, Saeideh Kainz, Manuel P. Dalbosco, Misael Terzano, Michele Holzapfel, Gerhard A. |
author_sort | Saeidi, Saeideh |
collection | PubMed |
description | In this study, we propose a novel micromechanical model for the brain white matter, which is described as a heterogeneous material with a complex network of axon fibers embedded in a soft ground matrix. We developed this model in the framework of RVE-based multiscale theories in combination with the finite element method and the embedded element technique for embedding the fibers. Microstructural features such as axon diameter, orientation and tortuosity are incorporated into the model through distributions derived from histological data. The constitutive law of both the fibers and the matrix is described by isotropic one-term Ogden functions. The hyperelastic response of the tissue is derived by homogenizing the microscopic stress fields with multiscale boundary conditions to ensure kinematic compatibility. The macroscale homogenized stress is employed in an inverse parameter identification procedure to determine the hyperelastic constants of axons and ground matrix, based on experiments on human corpus callosum. Our results demonstrate the fundamental effect of axon tortuosity on the mechanical behavior of the brain’s white matter. By combining histological information with the multiscale theory, the proposed framework can substantially contribute to the understanding of mechanotransduction phenomena, shed light on the biomechanics of a healthy brain, and potentially provide insights into neurodegenerative processes. |
format | Online Article Text |
id | pubmed-10638412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106384122023-11-11 Histology-informed multiscale modeling of human brain white matter Saeidi, Saeideh Kainz, Manuel P. Dalbosco, Misael Terzano, Michele Holzapfel, Gerhard A. Sci Rep Article In this study, we propose a novel micromechanical model for the brain white matter, which is described as a heterogeneous material with a complex network of axon fibers embedded in a soft ground matrix. We developed this model in the framework of RVE-based multiscale theories in combination with the finite element method and the embedded element technique for embedding the fibers. Microstructural features such as axon diameter, orientation and tortuosity are incorporated into the model through distributions derived from histological data. The constitutive law of both the fibers and the matrix is described by isotropic one-term Ogden functions. The hyperelastic response of the tissue is derived by homogenizing the microscopic stress fields with multiscale boundary conditions to ensure kinematic compatibility. The macroscale homogenized stress is employed in an inverse parameter identification procedure to determine the hyperelastic constants of axons and ground matrix, based on experiments on human corpus callosum. Our results demonstrate the fundamental effect of axon tortuosity on the mechanical behavior of the brain’s white matter. By combining histological information with the multiscale theory, the proposed framework can substantially contribute to the understanding of mechanotransduction phenomena, shed light on the biomechanics of a healthy brain, and potentially provide insights into neurodegenerative processes. Nature Publishing Group UK 2023-11-10 /pmc/articles/PMC10638412/ /pubmed/37949949 http://dx.doi.org/10.1038/s41598-023-46600-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Saeidi, Saeideh Kainz, Manuel P. Dalbosco, Misael Terzano, Michele Holzapfel, Gerhard A. Histology-informed multiscale modeling of human brain white matter |
title | Histology-informed multiscale modeling of human brain white matter |
title_full | Histology-informed multiscale modeling of human brain white matter |
title_fullStr | Histology-informed multiscale modeling of human brain white matter |
title_full_unstemmed | Histology-informed multiscale modeling of human brain white matter |
title_short | Histology-informed multiscale modeling of human brain white matter |
title_sort | histology-informed multiscale modeling of human brain white matter |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638412/ https://www.ncbi.nlm.nih.gov/pubmed/37949949 http://dx.doi.org/10.1038/s41598-023-46600-3 |
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