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A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation
Peripheral arterial occlusive disease is a chronic pathology affecting at least 8–12 million people in the USA, typically treated with a vein graft bypass or through the deployment of a stent in order to restore the physiological circulation. Failure of peripheral endovascular interventions occurs a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373284/ https://www.ncbi.nlm.nih.gov/pubmed/30094656 http://dx.doi.org/10.1007/s10237-018-1065-0 |
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author | Garbey, Marc Casarin, Stefano Berceli, Scott A. |
author_facet | Garbey, Marc Casarin, Stefano Berceli, Scott A. |
author_sort | Garbey, Marc |
collection | PubMed |
description | Peripheral arterial occlusive disease is a chronic pathology affecting at least 8–12 million people in the USA, typically treated with a vein graft bypass or through the deployment of a stent in order to restore the physiological circulation. Failure of peripheral endovascular interventions occurs at the intersection of vascular biology, biomechanics, and clinical decision making. It is our hypothesis that the majority of endovascular treatment approaches share the same driving mechanisms and that a deep understanding of the adaptation process is pivotal in order to improve the current outcome of the procedure. The postsurgical adaptation of vein graft bypasses offers the perfect example of how the balance between intimal hyperplasia and wall remodeling determines the failure or the success of the intervention. Accordingly, this work presents a versatile computational model able to capture the feedback loop that describes the interaction between events at cellular/tissue level and mechano-environmental conditions. The work here presented is a generalization and an improvement of a previous work by our group of investigators, where an agent-based model uses a cellular automata principle on a fixed hexagonal grid to reproduce the leading events of the graft’s restenosis. The new hybrid model here presented allows a more realistic simulation both of the biological laws that drive the cellular behavior and of the active role of the membranes that separate the various layers of the vein. The novel feature is to use an immersed boundary implementation of a highly viscous flow to represent SMC motility and matrix reorganization in response to graft adaptation. Our implementation is modular, and this makes us able to choose the right compromise between closeness to the physiological reality and complexity of the model. The focus of this paper is to offer a new modular implementation that combines the best features of an agent-based model, continuum mechanics, and particle-tracking methods to cope with the multiscale nature of the adaptation phenomena. This hybrid method allows us to quickly test various hypotheses with a particular attention to cellular motility, a process that we demonstrated should be driven by mechanical homeostasis in order to maintain the right balance between cells and extracellular matrix in order to reproduce a distribution similar to histological experimental data from vein grafts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10237-018-1065-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6373284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-63732842019-03-01 A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation Garbey, Marc Casarin, Stefano Berceli, Scott A. Biomech Model Mechanobiol Original Paper Peripheral arterial occlusive disease is a chronic pathology affecting at least 8–12 million people in the USA, typically treated with a vein graft bypass or through the deployment of a stent in order to restore the physiological circulation. Failure of peripheral endovascular interventions occurs at the intersection of vascular biology, biomechanics, and clinical decision making. It is our hypothesis that the majority of endovascular treatment approaches share the same driving mechanisms and that a deep understanding of the adaptation process is pivotal in order to improve the current outcome of the procedure. The postsurgical adaptation of vein graft bypasses offers the perfect example of how the balance between intimal hyperplasia and wall remodeling determines the failure or the success of the intervention. Accordingly, this work presents a versatile computational model able to capture the feedback loop that describes the interaction between events at cellular/tissue level and mechano-environmental conditions. The work here presented is a generalization and an improvement of a previous work by our group of investigators, where an agent-based model uses a cellular automata principle on a fixed hexagonal grid to reproduce the leading events of the graft’s restenosis. The new hybrid model here presented allows a more realistic simulation both of the biological laws that drive the cellular behavior and of the active role of the membranes that separate the various layers of the vein. The novel feature is to use an immersed boundary implementation of a highly viscous flow to represent SMC motility and matrix reorganization in response to graft adaptation. Our implementation is modular, and this makes us able to choose the right compromise between closeness to the physiological reality and complexity of the model. The focus of this paper is to offer a new modular implementation that combines the best features of an agent-based model, continuum mechanics, and particle-tracking methods to cope with the multiscale nature of the adaptation phenomena. This hybrid method allows us to quickly test various hypotheses with a particular attention to cellular motility, a process that we demonstrated should be driven by mechanical homeostasis in order to maintain the right balance between cells and extracellular matrix in order to reproduce a distribution similar to histological experimental data from vein grafts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10237-018-1065-0) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2018-08-09 2019 /pmc/articles/PMC6373284/ /pubmed/30094656 http://dx.doi.org/10.1007/s10237-018-1065-0 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Garbey, Marc Casarin, Stefano Berceli, Scott A. A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation |
title | A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation |
title_full | A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation |
title_fullStr | A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation |
title_full_unstemmed | A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation |
title_short | A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation |
title_sort | versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373284/ https://www.ncbi.nlm.nih.gov/pubmed/30094656 http://dx.doi.org/10.1007/s10237-018-1065-0 |
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