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Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation

Radiomics, via the extraction of quantitative information from conventional radiologic images, can identify imperceptible imaging biomarkers that can advance the characterization of coronary plaques and the surrounding adipose tissue. Such an approach can unravel the underlying pathophysiology of at...

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Autores principales: Cheng, Kevin, Lin, Andrew, Yuvaraj, Jeremy, Nicholls, Stephen J., Wong, Dennis T.L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8069372/
https://www.ncbi.nlm.nih.gov/pubmed/33921502
http://dx.doi.org/10.3390/cells10040879
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author Cheng, Kevin
Lin, Andrew
Yuvaraj, Jeremy
Nicholls, Stephen J.
Wong, Dennis T.L.
author_facet Cheng, Kevin
Lin, Andrew
Yuvaraj, Jeremy
Nicholls, Stephen J.
Wong, Dennis T.L.
author_sort Cheng, Kevin
collection PubMed
description Radiomics, via the extraction of quantitative information from conventional radiologic images, can identify imperceptible imaging biomarkers that can advance the characterization of coronary plaques and the surrounding adipose tissue. Such an approach can unravel the underlying pathophysiology of atherosclerosis which has the potential to aid diagnostic, prognostic and, therapeutic decision making. Several studies have demonstrated that radiomic analysis can characterize coronary atherosclerotic plaques with a level of accuracy comparable, if not superior, to current conventional qualitative and quantitative image analysis. While there are many milestones still to be reached before radiomics can be integrated into current clinical practice, such techniques hold great promise for improving the imaging phenotyping of coronary artery disease.
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spelling pubmed-80693722021-04-26 Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation Cheng, Kevin Lin, Andrew Yuvaraj, Jeremy Nicholls, Stephen J. Wong, Dennis T.L. Cells Review Radiomics, via the extraction of quantitative information from conventional radiologic images, can identify imperceptible imaging biomarkers that can advance the characterization of coronary plaques and the surrounding adipose tissue. Such an approach can unravel the underlying pathophysiology of atherosclerosis which has the potential to aid diagnostic, prognostic and, therapeutic decision making. Several studies have demonstrated that radiomic analysis can characterize coronary atherosclerotic plaques with a level of accuracy comparable, if not superior, to current conventional qualitative and quantitative image analysis. While there are many milestones still to be reached before radiomics can be integrated into current clinical practice, such techniques hold great promise for improving the imaging phenotyping of coronary artery disease. MDPI 2021-04-12 /pmc/articles/PMC8069372/ /pubmed/33921502 http://dx.doi.org/10.3390/cells10040879 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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/).
spellingShingle Review
Cheng, Kevin
Lin, Andrew
Yuvaraj, Jeremy
Nicholls, Stephen J.
Wong, Dennis T.L.
Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation
title Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation
title_full Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation
title_fullStr Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation
title_full_unstemmed Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation
title_short Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation
title_sort cardiac computed tomography radiomics for the non-invasive assessment of coronary inflammation
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8069372/
https://www.ncbi.nlm.nih.gov/pubmed/33921502
http://dx.doi.org/10.3390/cells10040879
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