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Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models
International Journal for Numerical Methods in Biomedical Engineering, Volume: 35, Issue: 11
Swansea University Authors:
Jason Carson , Perumal Nithiarasu
, Jason Carson
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DOI (Published version): 10.1002/cnm.3255
Abstract
In this work, we estimate the diagnostic threshold of the instantaneous wave‐free ratio (iFR) through the use of a one‐dimensional haemodynamic framework. To this end, we first compared the computed fractional flow reserve (cFFR) predicted from a 1D computational framework with invasive clinical mea...
Published in: | International Journal for Numerical Methods in Biomedical Engineering |
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ISSN: | 2040-7939 2040-7947 |
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Wiley
2019
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URI: | https://cronfa.swan.ac.uk/Record/cronfa51923 |
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2019-10-09T15:00:09.4099162 v2 51923 2019-09-16 Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models c1f2c28fbe6a41c5134b45abde5abb93 0000-0001-6634-9123 Jason Carson Jason Carson true false 3b28bf59358fc2b9bd9a46897dbfc92d 0000-0002-4901-2980 Perumal Nithiarasu Perumal Nithiarasu true false ced1a1a2f38e4b283f16f138ce1131c5 Jason Carson Jason Carson true false 2019-09-16 MEDE In this work, we estimate the diagnostic threshold of the instantaneous wave‐free ratio (iFR) through the use of a one‐dimensional haemodynamic framework. To this end, we first compared the computed fractional flow reserve (cFFR) predicted from a 1D computational framework with invasive clinical measurements. The framework shows excellent promise and utilises minimal patient data from a cohort of 52 patients with a total of 66 stenoses. The diagnostic accuracy of the cFFR model was 75.76%, with a sensitivity of 71.43%, a specificity of 77.78%, a positive predictive value of 60%, and a negative predictive value of 85.37%. The validated model was then used to estimate the diagnostic threshold of iFR. The model determined a quadratic relationship between cFFR and the ciFR. The iFR diagnostic threshold was determined to be 0.8910 from a receiver operating characteristic curve that is in the range of 0.89 to 0.9 that is normally reported in clinical studies. Journal Article International Journal for Numerical Methods in Biomedical Engineering 35 11 Wiley 2040-7939 2040-7947 coronary arteries, FFR, haemodynamic modelling, iFR 30 11 2019 2019-11-30 10.1002/cnm.3255 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University UKRI, MR/S004076/1 UKRI, MR/S004076/1 2019-10-09T15:00:09.4099162 2019-09-16T18:18:02.7463469 Jason Carson 0000-0001-6634-9123 1 Carl Roobottom 2 Robin Alcock 3 Perumal Nithiarasu 0000-0002-4901-2980 4 Jason Carson 5 51923__16218__dc8613cb12254428bca9d590a9e58f2b.pdf Carson2019.pdf 2020-01-07T13:47:47.7318614 Output 1614622 application/pdf Version of Record true Released under the terms of a Creative Commons Attribution License (CC-BY). true eng https://creativecommons.org/licenses/by/4.0/ |
title |
Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models |
spellingShingle |
Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models Jason Carson Perumal Nithiarasu Jason Carson |
title_short |
Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models |
title_full |
Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models |
title_fullStr |
Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models |
title_full_unstemmed |
Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models |
title_sort |
Computational instantaneous wave‐free ratio (IFR) for patient‐specific coronary artery stenoses using 1D network models |
author_id_str_mv |
c1f2c28fbe6a41c5134b45abde5abb93 3b28bf59358fc2b9bd9a46897dbfc92d ced1a1a2f38e4b283f16f138ce1131c5 |
author_id_fullname_str_mv |
c1f2c28fbe6a41c5134b45abde5abb93_***_Jason Carson 3b28bf59358fc2b9bd9a46897dbfc92d_***_Perumal Nithiarasu ced1a1a2f38e4b283f16f138ce1131c5_***_Jason Carson |
author |
Jason Carson Perumal Nithiarasu Jason Carson |
author2 |
Jason Carson Carl Roobottom Robin Alcock Perumal Nithiarasu Jason Carson |
format |
Journal article |
container_title |
International Journal for Numerical Methods in Biomedical Engineering |
container_volume |
35 |
container_issue |
11 |
publishDate |
2019 |
institution |
Swansea University |
issn |
2040-7939 2040-7947 |
doi_str_mv |
10.1002/cnm.3255 |
publisher |
Wiley |
document_store_str |
1 |
active_str |
0 |
description |
In this work, we estimate the diagnostic threshold of the instantaneous wave‐free ratio (iFR) through the use of a one‐dimensional haemodynamic framework. To this end, we first compared the computed fractional flow reserve (cFFR) predicted from a 1D computational framework with invasive clinical measurements. The framework shows excellent promise and utilises minimal patient data from a cohort of 52 patients with a total of 66 stenoses. The diagnostic accuracy of the cFFR model was 75.76%, with a sensitivity of 71.43%, a specificity of 77.78%, a positive predictive value of 60%, and a negative predictive value of 85.37%. The validated model was then used to estimate the diagnostic threshold of iFR. The model determined a quadratic relationship between cFFR and the ciFR. The iFR diagnostic threshold was determined to be 0.8910 from a receiver operating characteristic curve that is in the range of 0.89 to 0.9 that is normally reported in clinical studies. |
published_date |
2019-11-30T04:03:59Z |
_version_ |
1763753317749489664 |
score |
11.021648 |