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Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data

OBJECTIVES: The aim of this study was to investigate whether algorithmic interpretation (AI) of instantaneous wave-free ratio (iFR) pressure-wire pull back data would be noninferior to expert human interpretation. BACKGROUND: Interpretation of iFR pressure-wire pull back data can be complex and is s...

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Autores principales: Cook, Christopher M., Warisawa, Takayuki, Howard, James P., Keeble, Thomas R., Iglesias, Juan F., Schampaert, Erick, Bhindi, Ravinay, Ambrosia, Alphonse, Matsuo, Hitoshi, Nishina, Hidetaka, Kikuta, Yuetsu, Shiono, Yasutsugu, Nakayama, Masafumi, Doi, Shunichi, Takai, Manabu, Goto, Sonoka, Yakuta, Yohei, Karube, Kenichi, Akashi, Yoshihiro J., Clesham, Gerald J., Kelly, Paul A., Davies, John R., Karamasis, Grigoris V., Kawase, Yoshiaki, Robinson, Nicholas M., Sharp, Andrew S.P., Escaned, Javier, Davies, Justin E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645043/
https://www.ncbi.nlm.nih.gov/pubmed/31320025
http://dx.doi.org/10.1016/j.jcin.2019.05.025
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author Cook, Christopher M.
Warisawa, Takayuki
Howard, James P.
Keeble, Thomas R.
Iglesias, Juan F.
Schampaert, Erick
Bhindi, Ravinay
Ambrosia, Alphonse
Matsuo, Hitoshi
Nishina, Hidetaka
Kikuta, Yuetsu
Shiono, Yasutsugu
Nakayama, Masafumi
Doi, Shunichi
Takai, Manabu
Goto, Sonoka
Yakuta, Yohei
Karube, Kenichi
Akashi, Yoshihiro J.
Clesham, Gerald J.
Kelly, Paul A.
Davies, John R.
Karamasis, Grigoris V.
Kawase, Yoshiaki
Robinson, Nicholas M.
Sharp, Andrew S.P.
Escaned, Javier
Davies, Justin E.
author_facet Cook, Christopher M.
Warisawa, Takayuki
Howard, James P.
Keeble, Thomas R.
Iglesias, Juan F.
Schampaert, Erick
Bhindi, Ravinay
Ambrosia, Alphonse
Matsuo, Hitoshi
Nishina, Hidetaka
Kikuta, Yuetsu
Shiono, Yasutsugu
Nakayama, Masafumi
Doi, Shunichi
Takai, Manabu
Goto, Sonoka
Yakuta, Yohei
Karube, Kenichi
Akashi, Yoshihiro J.
Clesham, Gerald J.
Kelly, Paul A.
Davies, John R.
Karamasis, Grigoris V.
Kawase, Yoshiaki
Robinson, Nicholas M.
Sharp, Andrew S.P.
Escaned, Javier
Davies, Justin E.
author_sort Cook, Christopher M.
collection PubMed
description OBJECTIVES: The aim of this study was to investigate whether algorithmic interpretation (AI) of instantaneous wave-free ratio (iFR) pressure-wire pull back data would be noninferior to expert human interpretation. BACKGROUND: Interpretation of iFR pressure-wire pull back data can be complex and is subjective. METHODS: Fifteen human experts interpreted 1,008 iFR pull back traces (691 unique, 317 duplicate). For each trace, experts determined the hemodynamic appropriateness for percutaneous coronary intervention (PCI) and, in such cases, the optimal physiological strategy for PCI. The heart team (HT) interpretation was determined by consensus of the individual expert opinions. The same 1,008 pull back traces were also interpreted algorithmically. The coprimary hypotheses of this study were that AI would be noninferior to the interpretation of the median expert human in determining: 1) the hemodynamic appropriateness for PCI; and 2) the physiological strategy for PCI. RESULTS: Regarding the hemodynamic appropriateness for PCI, the median expert human demonstrated 89.3% agreement with the HT in comparison with 89.4% for AI (p < 0.01 for noninferiority). Across the 372 cases judged as hemodynamically appropriate for PCI according to the HT, the median expert human demonstrated 88.8% agreement with the HT in comparison with 89.7% for AI (p < 0.0001 for noninferiority). On reproducibility testing, the HT opinion itself changed 1 in 10 times for both the appropriateness for PCI and the physiological PCI strategy. In contrast, AI showed no change. CONCLUSIONS: AI of iFR pressure-wire pull back data was noninferior to expert human interpretation in determining both the hemodynamic appropriateness for PCI and the optimal physiological strategy for PCI.
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spelling pubmed-66450432019-07-31 Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data Cook, Christopher M. Warisawa, Takayuki Howard, James P. Keeble, Thomas R. Iglesias, Juan F. Schampaert, Erick Bhindi, Ravinay Ambrosia, Alphonse Matsuo, Hitoshi Nishina, Hidetaka Kikuta, Yuetsu Shiono, Yasutsugu Nakayama, Masafumi Doi, Shunichi Takai, Manabu Goto, Sonoka Yakuta, Yohei Karube, Kenichi Akashi, Yoshihiro J. Clesham, Gerald J. Kelly, Paul A. Davies, John R. Karamasis, Grigoris V. Kawase, Yoshiaki Robinson, Nicholas M. Sharp, Andrew S.P. Escaned, Javier Davies, Justin E. JACC Cardiovasc Interv Article OBJECTIVES: The aim of this study was to investigate whether algorithmic interpretation (AI) of instantaneous wave-free ratio (iFR) pressure-wire pull back data would be noninferior to expert human interpretation. BACKGROUND: Interpretation of iFR pressure-wire pull back data can be complex and is subjective. METHODS: Fifteen human experts interpreted 1,008 iFR pull back traces (691 unique, 317 duplicate). For each trace, experts determined the hemodynamic appropriateness for percutaneous coronary intervention (PCI) and, in such cases, the optimal physiological strategy for PCI. The heart team (HT) interpretation was determined by consensus of the individual expert opinions. The same 1,008 pull back traces were also interpreted algorithmically. The coprimary hypotheses of this study were that AI would be noninferior to the interpretation of the median expert human in determining: 1) the hemodynamic appropriateness for PCI; and 2) the physiological strategy for PCI. RESULTS: Regarding the hemodynamic appropriateness for PCI, the median expert human demonstrated 89.3% agreement with the HT in comparison with 89.4% for AI (p < 0.01 for noninferiority). Across the 372 cases judged as hemodynamically appropriate for PCI according to the HT, the median expert human demonstrated 88.8% agreement with the HT in comparison with 89.7% for AI (p < 0.0001 for noninferiority). On reproducibility testing, the HT opinion itself changed 1 in 10 times for both the appropriateness for PCI and the physiological PCI strategy. In contrast, AI showed no change. CONCLUSIONS: AI of iFR pressure-wire pull back data was noninferior to expert human interpretation in determining both the hemodynamic appropriateness for PCI and the optimal physiological strategy for PCI. Elsevier 2019-07-22 /pmc/articles/PMC6645043/ /pubmed/31320025 http://dx.doi.org/10.1016/j.jcin.2019.05.025 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cook, Christopher M.
Warisawa, Takayuki
Howard, James P.
Keeble, Thomas R.
Iglesias, Juan F.
Schampaert, Erick
Bhindi, Ravinay
Ambrosia, Alphonse
Matsuo, Hitoshi
Nishina, Hidetaka
Kikuta, Yuetsu
Shiono, Yasutsugu
Nakayama, Masafumi
Doi, Shunichi
Takai, Manabu
Goto, Sonoka
Yakuta, Yohei
Karube, Kenichi
Akashi, Yoshihiro J.
Clesham, Gerald J.
Kelly, Paul A.
Davies, John R.
Karamasis, Grigoris V.
Kawase, Yoshiaki
Robinson, Nicholas M.
Sharp, Andrew S.P.
Escaned, Javier
Davies, Justin E.
Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data
title Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data
title_full Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data
title_fullStr Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data
title_full_unstemmed Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data
title_short Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data
title_sort algorithmic versus expert human interpretation of instantaneous wave-free ratio coronary pressure-wire pull back data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645043/
https://www.ncbi.nlm.nih.gov/pubmed/31320025
http://dx.doi.org/10.1016/j.jcin.2019.05.025
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