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Serial stenosis assessment—can we rely on invasive coronary physiology
Atherosclerosis is a widespread disease affecting coronary arteries. Diffuse atherosclerotic disease affects the whole vessel, posing difficulties in determining lesion significance by angiography. Research has confirmed that revascularization guided by invasive coronary physiology indices improves...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10185833/ https://www.ncbi.nlm.nih.gov/pubmed/37200979 http://dx.doi.org/10.3389/fcvm.2023.1172906 |
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author | Ilic, Ivan Timcic, Stefan Odanovic, Natalija Otasevic, Petar Collet, Carlos |
author_facet | Ilic, Ivan Timcic, Stefan Odanovic, Natalija Otasevic, Petar Collet, Carlos |
author_sort | Ilic, Ivan |
collection | PubMed |
description | Atherosclerosis is a widespread disease affecting coronary arteries. Diffuse atherosclerotic disease affects the whole vessel, posing difficulties in determining lesion significance by angiography. Research has confirmed that revascularization guided by invasive coronary physiology indices improves patients' prognosis and quality of life. Serial lesions can be a diagnostic challenge because the measurement of functional stenosis significance using invasive physiology is influenced by a complex interplay of factors. The use of fractional flow reserve (FFR) pullback provides a trans-stenotic pressure gradient (ΔP) for each of the lesions. The strategy of treating the lesion with greater ΔP first and then reevaluating another lesion has been advocated. Similarly, non-hyperemic indices can be used to assess the contribution of each stenosis and predict the effect of lesion treatment on physiology indices. Pullback pressure gradient (PPG) integrates physiological variables of coronary pressure along the epicardial vessel and characteristics of discrete and diffuse coronary stenoses into a quantitative index that can be used to guide revascularization. We proposed an algorithm that integrates FFR pullbacks and calculates PPG to determine individual lesion importance and to guide intervention. Computer modeling of the coronaries and the use of non-invasive FFR measurement together with mathematical algorithms for fluid dynamics can make predictions of lesion significance in serial stenoses easier and provide practical solutions for treatment. All these strategies need to be validated before widespread clinical use. |
format | Online Article Text |
id | pubmed-10185833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101858332023-05-17 Serial stenosis assessment—can we rely on invasive coronary physiology Ilic, Ivan Timcic, Stefan Odanovic, Natalija Otasevic, Petar Collet, Carlos Front Cardiovasc Med Cardiovascular Medicine Atherosclerosis is a widespread disease affecting coronary arteries. Diffuse atherosclerotic disease affects the whole vessel, posing difficulties in determining lesion significance by angiography. Research has confirmed that revascularization guided by invasive coronary physiology indices improves patients' prognosis and quality of life. Serial lesions can be a diagnostic challenge because the measurement of functional stenosis significance using invasive physiology is influenced by a complex interplay of factors. The use of fractional flow reserve (FFR) pullback provides a trans-stenotic pressure gradient (ΔP) for each of the lesions. The strategy of treating the lesion with greater ΔP first and then reevaluating another lesion has been advocated. Similarly, non-hyperemic indices can be used to assess the contribution of each stenosis and predict the effect of lesion treatment on physiology indices. Pullback pressure gradient (PPG) integrates physiological variables of coronary pressure along the epicardial vessel and characteristics of discrete and diffuse coronary stenoses into a quantitative index that can be used to guide revascularization. We proposed an algorithm that integrates FFR pullbacks and calculates PPG to determine individual lesion importance and to guide intervention. Computer modeling of the coronaries and the use of non-invasive FFR measurement together with mathematical algorithms for fluid dynamics can make predictions of lesion significance in serial stenoses easier and provide practical solutions for treatment. All these strategies need to be validated before widespread clinical use. Frontiers Media S.A. 2023-05-02 /pmc/articles/PMC10185833/ /pubmed/37200979 http://dx.doi.org/10.3389/fcvm.2023.1172906 Text en © 2023 Ilic, Timcic, Odanovic, Otasevic and Collet. 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) (https://creativecommons.org/licenses/by/4.0/) . 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 | Cardiovascular Medicine Ilic, Ivan Timcic, Stefan Odanovic, Natalija Otasevic, Petar Collet, Carlos Serial stenosis assessment—can we rely on invasive coronary physiology |
title | Serial stenosis assessment—can we rely on invasive coronary physiology |
title_full | Serial stenosis assessment—can we rely on invasive coronary physiology |
title_fullStr | Serial stenosis assessment—can we rely on invasive coronary physiology |
title_full_unstemmed | Serial stenosis assessment—can we rely on invasive coronary physiology |
title_short | Serial stenosis assessment—can we rely on invasive coronary physiology |
title_sort | serial stenosis assessment—can we rely on invasive coronary physiology |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10185833/ https://www.ncbi.nlm.nih.gov/pubmed/37200979 http://dx.doi.org/10.3389/fcvm.2023.1172906 |
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