CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions
A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA was based on an extension of Murray's law and additional inlet conditions prescribed ite...
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sg-ntu-dr.10356-1718752023-11-18T16:48:27Z CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions Alzhanov, Nursultan Ng, Eddie Yin Kwee Su, Xiaohui Zhao, Yong School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Blood Flow Simulation Coronal Stenosis A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA was based on an extension of Murray's law and additional inlet conditions prescribed iteratively and was implemented in OpenFOAM v1912 for testing and validation. 3D models of CATs were created using CT scans and computational meshes, and the results were compared to invasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between the calculated and experimental FFR was within 2.33-5.26% in the steady-state and transient simulations, respectively, when convergence was reached. The PBA was a reliable and physiologically sound technique compared to a current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for convergence. The accuracy of the PBA method was further confirmed using an FDA nozzle, which demonstrated good alignment with the CFD-validated values. Published version 2023-11-14T05:50:24Z 2023-11-14T05:50:24Z 2023 Journal Article Alzhanov, N., Ng, E. Y. K., Su, X. & Zhao, Y. (2023). CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions. Bioengineering, 10(3), 309-. https://dx.doi.org/10.3390/bioengineering10030309 2306-5354 https://hdl.handle.net/10356/171875 10.3390/bioengineering10030309 36978700 2-s2.0-85151736233 3 10 309 en Bioengineering © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf |
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Engineering::Mechanical engineering Blood Flow Simulation Coronal Stenosis Alzhanov, Nursultan Ng, Eddie Yin Kwee Su, Xiaohui Zhao, Yong CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions |
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A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA was based on an extension of Murray's law and additional inlet conditions prescribed iteratively and was implemented in OpenFOAM v1912 for testing and validation. 3D models of CATs were created using CT scans and computational meshes, and the results were compared to invasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between the calculated and experimental FFR was within 2.33-5.26% in the steady-state and transient simulations, respectively, when convergence was reached. The PBA was a reliable and physiologically sound technique compared to a current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for convergence. The accuracy of the PBA method was further confirmed using an FDA nozzle, which demonstrated good alignment with the CFD-validated values. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Alzhanov, Nursultan Ng, Eddie Yin Kwee Su, Xiaohui Zhao, Yong |
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Article |
author |
Alzhanov, Nursultan Ng, Eddie Yin Kwee Su, Xiaohui Zhao, Yong |
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Alzhanov, Nursultan |
title |
CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions |
title_short |
CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions |
title_full |
CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions |
title_fullStr |
CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions |
title_full_unstemmed |
CFD computation of flow fractional reserve (FFR) in coronary artery trees using a novel physiologically based algorithm (PBA) under 3D steady and pulsatile flow conditions |
title_sort |
cfd computation of flow fractional reserve (ffr) in coronary artery trees using a novel physiologically based algorithm (pba) under 3d steady and pulsatile flow conditions |
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2023 |
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https://hdl.handle.net/10356/171875 |
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