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A prediction tool for plaque progression based on patient-specific multi-physical modeling

Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. Based on the follow-up coronary intravascular ultrasound imaging data, we performed patient-specific multi-physical modeling s...

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Autores principales: Pan, Jichao, Cai, Yan, Wang, Liang, Maehara, Akiko, Mintz, Gary S., Tang, Dalin, Li, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057612/
https://www.ncbi.nlm.nih.gov/pubmed/33780445
http://dx.doi.org/10.1371/journal.pcbi.1008344
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author Pan, Jichao
Cai, Yan
Wang, Liang
Maehara, Akiko
Mintz, Gary S.
Tang, Dalin
Li, Zhiyong
author_facet Pan, Jichao
Cai, Yan
Wang, Liang
Maehara, Akiko
Mintz, Gary S.
Tang, Dalin
Li, Zhiyong
author_sort Pan, Jichao
collection PubMed
description Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. Based on the follow-up coronary intravascular ultrasound imaging data, we performed patient-specific multi-physical modeling study on four patients to obtain the evolutional processes of the microenvironment during plaque progression. Four main pathophysiological processes, i.e., lipid deposition, inflammatory response, migration and proliferation of smooth muscle cells (SMCs), and neovascularization were coupled based on the interactions demonstrated by experimental and clinical observations. A scoring table integrating the dynamic microenvironmental indicators with the classical risk index was proposed to differentiate their progression to stable and unstable plaques. The heterogeneity of plaque microenvironment for each patient was demonstrated by the growth curves of the main microenvironmental factors. The possible plaque developments were predicted by incorporating the systematic index with microenvironmental indicators. Five microenvironmental factors (LDL, ox-LDL, MCP-1, SMC, and foam cell) showed significant differences between stable and unstable group (p < 0.01). The inflammatory microenvironments (monocyte and macrophage) had negative correlations with the necrotic core (NC) expansion in the stable group, while very strong positive correlations in unstable group. The inflammatory microenvironment is strongly correlated to the NC expansion in unstable plaques, suggesting that the inflammatory factors may play an important role in the formation of a vulnerable plaque. This prediction tool will improve our understanding of the mechanism of plaque progression and provide a new strategy for early detection and prediction of high-risk plaques.
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spelling pubmed-80576122021-05-04 A prediction tool for plaque progression based on patient-specific multi-physical modeling Pan, Jichao Cai, Yan Wang, Liang Maehara, Akiko Mintz, Gary S. Tang, Dalin Li, Zhiyong PLoS Comput Biol Research Article Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. Based on the follow-up coronary intravascular ultrasound imaging data, we performed patient-specific multi-physical modeling study on four patients to obtain the evolutional processes of the microenvironment during plaque progression. Four main pathophysiological processes, i.e., lipid deposition, inflammatory response, migration and proliferation of smooth muscle cells (SMCs), and neovascularization were coupled based on the interactions demonstrated by experimental and clinical observations. A scoring table integrating the dynamic microenvironmental indicators with the classical risk index was proposed to differentiate their progression to stable and unstable plaques. The heterogeneity of plaque microenvironment for each patient was demonstrated by the growth curves of the main microenvironmental factors. The possible plaque developments were predicted by incorporating the systematic index with microenvironmental indicators. Five microenvironmental factors (LDL, ox-LDL, MCP-1, SMC, and foam cell) showed significant differences between stable and unstable group (p < 0.01). The inflammatory microenvironments (monocyte and macrophage) had negative correlations with the necrotic core (NC) expansion in the stable group, while very strong positive correlations in unstable group. The inflammatory microenvironment is strongly correlated to the NC expansion in unstable plaques, suggesting that the inflammatory factors may play an important role in the formation of a vulnerable plaque. This prediction tool will improve our understanding of the mechanism of plaque progression and provide a new strategy for early detection and prediction of high-risk plaques. Public Library of Science 2021-03-29 /pmc/articles/PMC8057612/ /pubmed/33780445 http://dx.doi.org/10.1371/journal.pcbi.1008344 Text en © 2021 Pan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Pan, Jichao
Cai, Yan
Wang, Liang
Maehara, Akiko
Mintz, Gary S.
Tang, Dalin
Li, Zhiyong
A prediction tool for plaque progression based on patient-specific multi-physical modeling
title A prediction tool for plaque progression based on patient-specific multi-physical modeling
title_full A prediction tool for plaque progression based on patient-specific multi-physical modeling
title_fullStr A prediction tool for plaque progression based on patient-specific multi-physical modeling
title_full_unstemmed A prediction tool for plaque progression based on patient-specific multi-physical modeling
title_short A prediction tool for plaque progression based on patient-specific multi-physical modeling
title_sort prediction tool for plaque progression based on patient-specific multi-physical modeling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057612/
https://www.ncbi.nlm.nih.gov/pubmed/33780445
http://dx.doi.org/10.1371/journal.pcbi.1008344
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