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Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model
Background: The conventional FFRct numerical calculation method uses a model with a multi-scale geometry based upon CFD, and rigid walls. Therefore, important interactions between the elastic vessel wall and blood flow are not routinely considered. Changes in the resistance of coronary microcirculat...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039540/ https://www.ncbi.nlm.nih.gov/pubmed/35492614 http://dx.doi.org/10.3389/fphys.2022.861446 |
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author | Xi, Xiaolu Liu, Jincheng Sun, Hao Xu, Ke Wang, Xue Zhang, Liyuan Du, Tianming Liu, Jian Li, Bao |
author_facet | Xi, Xiaolu Liu, Jincheng Sun, Hao Xu, Ke Wang, Xue Zhang, Liyuan Du, Tianming Liu, Jian Li, Bao |
author_sort | Xi, Xiaolu |
collection | PubMed |
description | Background: The conventional FFRct numerical calculation method uses a model with a multi-scale geometry based upon CFD, and rigid walls. Therefore, important interactions between the elastic vessel wall and blood flow are not routinely considered. Changes in the resistance of coronary microcirculation during hyperaemia are likewise not typically incorporated using a fluid–structure interaction (FSI) algorithm. It is likely that both have resulted in FFRct calculation errors. Objective: In this study we incorporated both the influence of vascular elasticity and coronary microcirculatory structure on FFR, to improve the accuracy of FFRct calculation. Thus, in this study, a physics-driven 3D–0D coupled model including fluid–structure interaction was established to calculate accurate FFRct values. Methods: Based upon a novel geometric multi-scale modeling technology, a FSI simulation approach was used. A lumped parameter model (0D) was used as the outlet boundary condition for the 3D FSI coronary artery model to incorporate physiological microcirculation, with bidirectional coupling between the two models. Results: The accuracy, sensitivity, specificity, and both positive and negative predictive values of FFR(DC) calculated based upon the coupled 3D–0D model were 86.7, 66.7, 84.6, 66.7, and 91.7%, respectively. Compared to the calculated value using the basic CFD model (MSE = 5.9%, accuracy rate = 80%), the FFR(CFD) calculated based on the coupled 3D–0D model has a smaller MSE of 1.9%. Conclusion: The physics-driven coupled 3D–0D model that incorporates fluid–structure interactions not only consider the influence of the elastic vessel wall on blood flow, but also provides reliable microvascular resistance boundary conditions for the 3D FSI model. This allows for a calculation that is based upon conditions that are closer to the physiological environment, and thus improves the accuracy of FFRct calculation. It is likely that more accurate information will provide an enhanced recommendation regarding percutaneous coronary intervention (PCI) in the clinic. |
format | Online Article Text |
id | pubmed-9039540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90395402022-04-27 Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model Xi, Xiaolu Liu, Jincheng Sun, Hao Xu, Ke Wang, Xue Zhang, Liyuan Du, Tianming Liu, Jian Li, Bao Front Physiol Physiology Background: The conventional FFRct numerical calculation method uses a model with a multi-scale geometry based upon CFD, and rigid walls. Therefore, important interactions between the elastic vessel wall and blood flow are not routinely considered. Changes in the resistance of coronary microcirculation during hyperaemia are likewise not typically incorporated using a fluid–structure interaction (FSI) algorithm. It is likely that both have resulted in FFRct calculation errors. Objective: In this study we incorporated both the influence of vascular elasticity and coronary microcirculatory structure on FFR, to improve the accuracy of FFRct calculation. Thus, in this study, a physics-driven 3D–0D coupled model including fluid–structure interaction was established to calculate accurate FFRct values. Methods: Based upon a novel geometric multi-scale modeling technology, a FSI simulation approach was used. A lumped parameter model (0D) was used as the outlet boundary condition for the 3D FSI coronary artery model to incorporate physiological microcirculation, with bidirectional coupling between the two models. Results: The accuracy, sensitivity, specificity, and both positive and negative predictive values of FFR(DC) calculated based upon the coupled 3D–0D model were 86.7, 66.7, 84.6, 66.7, and 91.7%, respectively. Compared to the calculated value using the basic CFD model (MSE = 5.9%, accuracy rate = 80%), the FFR(CFD) calculated based on the coupled 3D–0D model has a smaller MSE of 1.9%. Conclusion: The physics-driven coupled 3D–0D model that incorporates fluid–structure interactions not only consider the influence of the elastic vessel wall on blood flow, but also provides reliable microvascular resistance boundary conditions for the 3D FSI model. This allows for a calculation that is based upon conditions that are closer to the physiological environment, and thus improves the accuracy of FFRct calculation. It is likely that more accurate information will provide an enhanced recommendation regarding percutaneous coronary intervention (PCI) in the clinic. Frontiers Media S.A. 2022-04-12 /pmc/articles/PMC9039540/ /pubmed/35492614 http://dx.doi.org/10.3389/fphys.2022.861446 Text en Copyright © 2022 Xi, Liu, Sun, Xu, Wang, Zhang, Du, Liu and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Xi, Xiaolu Liu, Jincheng Sun, Hao Xu, Ke Wang, Xue Zhang, Liyuan Du, Tianming Liu, Jian Li, Bao Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model |
title | Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model |
title_full | Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model |
title_fullStr | Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model |
title_full_unstemmed | Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model |
title_short | Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model |
title_sort | accurate calculation of ffr based on a physics-driven fluid‐structure interaction model |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039540/ https://www.ncbi.nlm.nih.gov/pubmed/35492614 http://dx.doi.org/10.3389/fphys.2022.861446 |
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