Resources / Publications
Thomas D Heseltine (1), Scott W Murray (1,2), Balazs Ruzsics (1), Michael Fisher (2,3)
European Cardiology Review, 15, February 2020. DOI: 10.15420/ecr.2019.14.2
Cardiac CT, coronary artery disease, atherosclerosis, fractional flow reserve CT, CT coronary angiography, machine learning, coronary artery calcium score, cardiovascular disease risk
Recent rapid technological advancements in cardiac CT have improved image quality and reduced radiation exposure to patients.Furthermore, key insights from large cohort trials have helped delineate cardiovascular disease risk as a function of overall coronaryplaque burden and the morphological appearance of individual plaques. The advent of CT-derived fractional flow reserve promises toestablish an anatomical and functional test within one modality. Recent data examining the short-term impact of CT-derived fractionalflow reserve on downstream care and clinical outcomes have been published. In addition, machine learning is a concept that is beingincreasingly applied to diagnostic medicine. Over the coming decade, machine learning will begin to be integrated into cardiac CT, andwill potentially make a tangible difference to how this modality evolves. The authors have performed an extensive literature review andcomprehensive analysis of the recent advances in cardiac CT. They review how recent advances currently impact on clinical care andpotential future directions for this imaging modality.
Dragonfly was used to quantify plaque characteristics.
(1) Royal Liverpool University Hospital, Liverpool, UK.
(2) Liverpool Centre for Cardiovascular Science, Liverpool, UK.
(3) Institute for Cardiovascular Medicine and Science, Liverpool Heart and Chest Hospital, Liverpool, UK.
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