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Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges

Patient-specific computer models have been developed representing a variety of aspects of the cardiovascular system spanning the disciplines of electrophysiology, electromechanics, solid mechanics, and fluid dynamics. These physiological mechanistic models predict macroscopic phenomena such as elect...

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Detalles Bibliográficos
Autores principales: Gray, Richard A., Pathmanathan, Pras
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5908828/
https://www.ncbi.nlm.nih.gov/pubmed/29512059
http://dx.doi.org/10.1007/s12265-018-9792-2
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author Gray, Richard A.
Pathmanathan, Pras
author_facet Gray, Richard A.
Pathmanathan, Pras
author_sort Gray, Richard A.
collection PubMed
description Patient-specific computer models have been developed representing a variety of aspects of the cardiovascular system spanning the disciplines of electrophysiology, electromechanics, solid mechanics, and fluid dynamics. These physiological mechanistic models predict macroscopic phenomena such as electrical impulse propagation and contraction throughout the entire heart as well as flow and pressure dynamics occurring in the ventricular chambers, aorta, and coronary arteries during each heartbeat. Such models have been used to study a variety of clinical scenarios including aortic aneurysms, coronary stenosis, cardiac valvular disease, left ventricular assist devices, cardiac resynchronization therapy, ablation therapy, and risk stratification. After decades of research, these models are beginning to be incorporated into clinical practice directly via marketed devices and indirectly by improving our understanding of the underlying mechanisms of health and disease within a clinical context.
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spelling pubmed-59088282018-04-20 Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges Gray, Richard A. Pathmanathan, Pras J Cardiovasc Transl Res Review Patient-specific computer models have been developed representing a variety of aspects of the cardiovascular system spanning the disciplines of electrophysiology, electromechanics, solid mechanics, and fluid dynamics. These physiological mechanistic models predict macroscopic phenomena such as electrical impulse propagation and contraction throughout the entire heart as well as flow and pressure dynamics occurring in the ventricular chambers, aorta, and coronary arteries during each heartbeat. Such models have been used to study a variety of clinical scenarios including aortic aneurysms, coronary stenosis, cardiac valvular disease, left ventricular assist devices, cardiac resynchronization therapy, ablation therapy, and risk stratification. After decades of research, these models are beginning to be incorporated into clinical practice directly via marketed devices and indirectly by improving our understanding of the underlying mechanisms of health and disease within a clinical context. Springer US 2018-03-06 2018 /pmc/articles/PMC5908828/ /pubmed/29512059 http://dx.doi.org/10.1007/s12265-018-9792-2 Text en © The Author(s) 2018 Open Access This 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 Review
Gray, Richard A.
Pathmanathan, Pras
Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges
title Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges
title_full Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges
title_fullStr Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges
title_full_unstemmed Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges
title_short Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges
title_sort patient-specific cardiovascular computational modeling: diversity of personalization and challenges
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5908828/
https://www.ncbi.nlm.nih.gov/pubmed/29512059
http://dx.doi.org/10.1007/s12265-018-9792-2
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