An improved reduced-order model for pressure drop across arterial stenoses.
Quantification of pressure drop across stenotic arteries is a major element in the functional assessment of occlusive arterial disease. Accurate estimation of the pressure drop with a numerical model allows the calculation of Fractional Flow Reserve (FFR), which is a haemodynamic index employed for...
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2021
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oai:doaj.org-article:b4e8e890ef7a4f349cd4af13adbb7fe62021-12-02T20:17:25ZAn improved reduced-order model for pressure drop across arterial stenoses.1932-620310.1371/journal.pone.0258047https://doaj.org/article/b4e8e890ef7a4f349cd4af13adbb7fe62021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0258047https://doaj.org/toc/1932-6203Quantification of pressure drop across stenotic arteries is a major element in the functional assessment of occlusive arterial disease. Accurate estimation of the pressure drop with a numerical model allows the calculation of Fractional Flow Reserve (FFR), which is a haemodynamic index employed for guiding coronary revascularisation. Its non-invasive evaluation would contribute to safer and cost-effective diseases management. In this work, we propose a new formulation of a reduced-order model of trans-stenotic pressure drop, based on a consistent theoretical analysis of the Navier-Stokes equation. The new formulation features a novel term that characterises the contribution of turbulence effect to pressure loss. Results from three-dimensional computational fluid dynamics (CFD) showed that the proposed model produces predictions that are significantly more accurate than the existing reduced-order models, for large and small symmetric and eccentric stenoses, covering mild to severe area reductions. FFR calculations based on the proposed model produced zero classification error for three classes comprising positive (≤ 0.75), negative (≥ 0.8) and intermediate (0.75 - 0.8) classes.Konstantinos G LyrasJack LeePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10, p e0258047 (2021) |
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Medicine R Science Q Konstantinos G Lyras Jack Lee An improved reduced-order model for pressure drop across arterial stenoses. |
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Quantification of pressure drop across stenotic arteries is a major element in the functional assessment of occlusive arterial disease. Accurate estimation of the pressure drop with a numerical model allows the calculation of Fractional Flow Reserve (FFR), which is a haemodynamic index employed for guiding coronary revascularisation. Its non-invasive evaluation would contribute to safer and cost-effective diseases management. In this work, we propose a new formulation of a reduced-order model of trans-stenotic pressure drop, based on a consistent theoretical analysis of the Navier-Stokes equation. The new formulation features a novel term that characterises the contribution of turbulence effect to pressure loss. Results from three-dimensional computational fluid dynamics (CFD) showed that the proposed model produces predictions that are significantly more accurate than the existing reduced-order models, for large and small symmetric and eccentric stenoses, covering mild to severe area reductions. FFR calculations based on the proposed model produced zero classification error for three classes comprising positive (≤ 0.75), negative (≥ 0.8) and intermediate (0.75 - 0.8) classes. |
format |
article |
author |
Konstantinos G Lyras Jack Lee |
author_facet |
Konstantinos G Lyras Jack Lee |
author_sort |
Konstantinos G Lyras |
title |
An improved reduced-order model for pressure drop across arterial stenoses. |
title_short |
An improved reduced-order model for pressure drop across arterial stenoses. |
title_full |
An improved reduced-order model for pressure drop across arterial stenoses. |
title_fullStr |
An improved reduced-order model for pressure drop across arterial stenoses. |
title_full_unstemmed |
An improved reduced-order model for pressure drop across arterial stenoses. |
title_sort |
improved reduced-order model for pressure drop across arterial stenoses. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doaj.org/article/b4e8e890ef7a4f349cd4af13adbb7fe6 |
work_keys_str_mv |
AT konstantinosglyras animprovedreducedordermodelforpressuredropacrossarterialstenoses AT jacklee animprovedreducedordermodelforpressuredropacrossarterialstenoses AT konstantinosglyras improvedreducedordermodelforpressuredropacrossarterialstenoses AT jacklee improvedreducedordermodelforpressuredropacrossarterialstenoses |
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1718374367925108736 |