Cheng, K.Lin, A.Yuvaraj, J.Nicholls, S.J.Wong, D.T.L.2021-06-092021-06-092021Cells, 2021; 10(4):879-1-879-172073-44092073-4409http://hdl.handle.net/2440/130682Radiomics, 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.en© 2021 by the authors. 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/).Machine learning; radiomics; coronary computed tomography angiography; acute coronary syndrome; atherosclerosis; plaque; peri-coronary adipose tissueJournal article100004070810.3390/cells100408790006428809000012-s2.0-85105127152574309Nicholls, S.J. [0000-0002-9668-4368]