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A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation

Atherogenesis, the formation of plaques in the wall of blood vessels, starts as a result of lipid accumulation (low-density lipoprotein cholesterol) in the vessel wall. Such accumulation is related to the site of endothelial mechanotransduction, the endothelial response to mechanical stimuli and hae...

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Autores principales: Alimohammadi, Mona, Pichardo-Almarza, Cesar, Agu, Obiekezie, Díaz-Zuccarini, Vanessa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405845/
https://www.ncbi.nlm.nih.gov/pubmed/28427316
http://dx.doi.org/10.1177/0954411917697356
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author Alimohammadi, Mona
Pichardo-Almarza, Cesar
Agu, Obiekezie
Díaz-Zuccarini, Vanessa
author_facet Alimohammadi, Mona
Pichardo-Almarza, Cesar
Agu, Obiekezie
Díaz-Zuccarini, Vanessa
author_sort Alimohammadi, Mona
collection PubMed
description Atherogenesis, the formation of plaques in the wall of blood vessels, starts as a result of lipid accumulation (low-density lipoprotein cholesterol) in the vessel wall. Such accumulation is related to the site of endothelial mechanotransduction, the endothelial response to mechanical stimuli and haemodynamics, which determines biochemical processes regulating the vessel wall permeability. This interaction between biomechanical and biochemical phenomena is complex, spanning different biological scales and is patient-specific, requiring tools able to capture such mathematical and biological complexity in a unified framework. Mathematical models offer an elegant and efficient way of doing this, by taking into account multifactorial and multiscale processes and mechanisms, in order to capture the fundamentals of plaque formation in individual patients. In this study, a mathematical model to understand plaque and calcification locations is presented: this model provides a strong interpretability and physical meaning through a multiscale, complex index or metric (the penetration site of low-density lipoprotein cholesterol, expressed as volumetric flux). Computed tomography scans of the aortic bifurcation and iliac arteries are analysed and compared with the results of the multifactorial model. The results indicate that the model shows potential to predict the majority of the plaque locations, also not predicting regions where plaques are absent. The promising results from this case study provide a proof of concept that can be applied to a larger patient population.
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spelling pubmed-54058452017-05-08 A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation Alimohammadi, Mona Pichardo-Almarza, Cesar Agu, Obiekezie Díaz-Zuccarini, Vanessa Proc Inst Mech Eng H Special Issue Articles Atherogenesis, the formation of plaques in the wall of blood vessels, starts as a result of lipid accumulation (low-density lipoprotein cholesterol) in the vessel wall. Such accumulation is related to the site of endothelial mechanotransduction, the endothelial response to mechanical stimuli and haemodynamics, which determines biochemical processes regulating the vessel wall permeability. This interaction between biomechanical and biochemical phenomena is complex, spanning different biological scales and is patient-specific, requiring tools able to capture such mathematical and biological complexity in a unified framework. Mathematical models offer an elegant and efficient way of doing this, by taking into account multifactorial and multiscale processes and mechanisms, in order to capture the fundamentals of plaque formation in individual patients. In this study, a mathematical model to understand plaque and calcification locations is presented: this model provides a strong interpretability and physical meaning through a multiscale, complex index or metric (the penetration site of low-density lipoprotein cholesterol, expressed as volumetric flux). Computed tomography scans of the aortic bifurcation and iliac arteries are analysed and compared with the results of the multifactorial model. The results indicate that the model shows potential to predict the majority of the plaque locations, also not predicting regions where plaques are absent. The promising results from this case study provide a proof of concept that can be applied to a larger patient population. SAGE Publications 2017-04-21 2017-05 /pmc/articles/PMC5405845/ /pubmed/28427316 http://dx.doi.org/10.1177/0954411917697356 Text en © IMechE 2017 http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Special Issue Articles
Alimohammadi, Mona
Pichardo-Almarza, Cesar
Agu, Obiekezie
Díaz-Zuccarini, Vanessa
A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation
title A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation
title_full A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation
title_fullStr A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation
title_full_unstemmed A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation
title_short A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation
title_sort multiscale modelling approach to understand atherosclerosis formation: a patient-specific case study in the aortic bifurcation
topic Special Issue Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405845/
https://www.ncbi.nlm.nih.gov/pubmed/28427316
http://dx.doi.org/10.1177/0954411917697356
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