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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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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. |
format | Online Article Text |
id | pubmed-8057612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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