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Computational fluid dynamics modelling in cardiovascular medicine
This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-c...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4717410/ https://www.ncbi.nlm.nih.gov/pubmed/26512019 http://dx.doi.org/10.1136/heartjnl-2015-308044 |
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author | Morris, Paul D Narracott, Andrew von Tengg-Kobligk, Hendrik Silva Soto, Daniel Alejandro Hsiao, Sarah Lungu, Angela Evans, Paul Bressloff, Neil W Lawford, Patricia V Hose, D Rodney Gunn, Julian P |
author_facet | Morris, Paul D Narracott, Andrew von Tengg-Kobligk, Hendrik Silva Soto, Daniel Alejandro Hsiao, Sarah Lungu, Angela Evans, Paul Bressloff, Neil W Lawford, Patricia V Hose, D Rodney Gunn, Julian P |
author_sort | Morris, Paul D |
collection | PubMed |
description | This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. |
format | Online Article Text |
id | pubmed-4717410 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47174102016-01-28 Computational fluid dynamics modelling in cardiovascular medicine Morris, Paul D Narracott, Andrew von Tengg-Kobligk, Hendrik Silva Soto, Daniel Alejandro Hsiao, Sarah Lungu, Angela Evans, Paul Bressloff, Neil W Lawford, Patricia V Hose, D Rodney Gunn, Julian P Heart Review This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. BMJ Publishing Group 2016-01-01 2015-10-28 /pmc/articles/PMC4717410/ /pubmed/26512019 http://dx.doi.org/10.1136/heartjnl-2015-308044 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Review Morris, Paul D Narracott, Andrew von Tengg-Kobligk, Hendrik Silva Soto, Daniel Alejandro Hsiao, Sarah Lungu, Angela Evans, Paul Bressloff, Neil W Lawford, Patricia V Hose, D Rodney Gunn, Julian P Computational fluid dynamics modelling in cardiovascular medicine |
title | Computational fluid dynamics modelling in cardiovascular medicine |
title_full | Computational fluid dynamics modelling in cardiovascular medicine |
title_fullStr | Computational fluid dynamics modelling in cardiovascular medicine |
title_full_unstemmed | Computational fluid dynamics modelling in cardiovascular medicine |
title_short | Computational fluid dynamics modelling in cardiovascular medicine |
title_sort | computational fluid dynamics modelling in cardiovascular medicine |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4717410/ https://www.ncbi.nlm.nih.gov/pubmed/26512019 http://dx.doi.org/10.1136/heartjnl-2015-308044 |
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