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A novel physics-based model for fast computation of blood flow in coronary arteries
Blood flow and pressure calculated using the currently available methods have shown the potential to predict the progression of pathology, guide treatment strategies and help with postoperative recovery. However, the conspicuous disadvantage of these methods might be the time-consuming nature due to...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258997/ https://www.ncbi.nlm.nih.gov/pubmed/37303051 http://dx.doi.org/10.1186/s12938-023-01121-y |
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author | Hu, Xiuhua Liu, Xingli Wang, Hongping Xu, Lei Wu, Peng Zhang, Wenbing Niu, Zhaozhuo Zhang, Longjiang Gao, Qi |
author_facet | Hu, Xiuhua Liu, Xingli Wang, Hongping Xu, Lei Wu, Peng Zhang, Wenbing Niu, Zhaozhuo Zhang, Longjiang Gao, Qi |
author_sort | Hu, Xiuhua |
collection | PubMed |
description | Blood flow and pressure calculated using the currently available methods have shown the potential to predict the progression of pathology, guide treatment strategies and help with postoperative recovery. However, the conspicuous disadvantage of these methods might be the time-consuming nature due to the simulation of virtual interventional treatment. The purpose of this study is to propose a fast novel physics-based model, called FAST, for the prediction of blood flow and pressure. More specifically, blood flow in a vessel is discretized into a number of micro-flow elements along the centerline of the artery, so that when using the equation of viscous fluid motion, the complex blood flow in the artery is simplified into a one-dimensional (1D) steady-state flow. We demonstrate that this method can compute the fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA). 345 patients with 402 lesions are used to evaluate the feasibility of the FAST simulation through a comparison with three-dimensional (3D) computational fluid dynamics (CFD) simulation. Invasive FFR is also introduced to validate the diagnostic performance of the FAST method as a reference standard. The performance of the FAST method is comparable with the 3D CFD method. Compared with invasive FFR, the accuracy, sensitivity and specificity of FAST is 88.6%, 83.2% and 91.3%, respectively. The AUC of FFR(FAST) is 0.906. This demonstrates that the FAST algorithm and 3D CFD method show high consistency in predicting steady-state blood flow and pressure. Meanwhile, the FAST method also shows the potential in detecting lesion-specific ischemia. |
format | Online Article Text |
id | pubmed-10258997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102589972023-06-13 A novel physics-based model for fast computation of blood flow in coronary arteries Hu, Xiuhua Liu, Xingli Wang, Hongping Xu, Lei Wu, Peng Zhang, Wenbing Niu, Zhaozhuo Zhang, Longjiang Gao, Qi Biomed Eng Online Research Blood flow and pressure calculated using the currently available methods have shown the potential to predict the progression of pathology, guide treatment strategies and help with postoperative recovery. However, the conspicuous disadvantage of these methods might be the time-consuming nature due to the simulation of virtual interventional treatment. The purpose of this study is to propose a fast novel physics-based model, called FAST, for the prediction of blood flow and pressure. More specifically, blood flow in a vessel is discretized into a number of micro-flow elements along the centerline of the artery, so that when using the equation of viscous fluid motion, the complex blood flow in the artery is simplified into a one-dimensional (1D) steady-state flow. We demonstrate that this method can compute the fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA). 345 patients with 402 lesions are used to evaluate the feasibility of the FAST simulation through a comparison with three-dimensional (3D) computational fluid dynamics (CFD) simulation. Invasive FFR is also introduced to validate the diagnostic performance of the FAST method as a reference standard. The performance of the FAST method is comparable with the 3D CFD method. Compared with invasive FFR, the accuracy, sensitivity and specificity of FAST is 88.6%, 83.2% and 91.3%, respectively. The AUC of FFR(FAST) is 0.906. This demonstrates that the FAST algorithm and 3D CFD method show high consistency in predicting steady-state blood flow and pressure. Meanwhile, the FAST method also shows the potential in detecting lesion-specific ischemia. BioMed Central 2023-06-12 /pmc/articles/PMC10258997/ /pubmed/37303051 http://dx.doi.org/10.1186/s12938-023-01121-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Hu, Xiuhua Liu, Xingli Wang, Hongping Xu, Lei Wu, Peng Zhang, Wenbing Niu, Zhaozhuo Zhang, Longjiang Gao, Qi A novel physics-based model for fast computation of blood flow in coronary arteries |
title | A novel physics-based model for fast computation of blood flow in coronary arteries |
title_full | A novel physics-based model for fast computation of blood flow in coronary arteries |
title_fullStr | A novel physics-based model for fast computation of blood flow in coronary arteries |
title_full_unstemmed | A novel physics-based model for fast computation of blood flow in coronary arteries |
title_short | A novel physics-based model for fast computation of blood flow in coronary arteries |
title_sort | novel physics-based model for fast computation of blood flow in coronary arteries |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258997/ https://www.ncbi.nlm.nih.gov/pubmed/37303051 http://dx.doi.org/10.1186/s12938-023-01121-y |
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