«A team of researchers have developed an artificial intelligence-enabled tool they believe could make it easier to predict which patients are more likely to have a heart attack in the next 5 years. The Cedars Sinai-led group of investigators described the tool in The Lancet Digital Health, where they detailed their goal of developing and validating a deep learning system for coronary CT angiography (CCTA)-derived measures of plaque volume and stenosis severity.»
«Describing CCTA as a “robust first-line test for the evaluation of coronary artery stenosis severity,” the researchers pointed out that atherosclerotic plaque quantification from CCTA enables accurate assessment of coronary artery disease burden and prognosis. Beyond the assessment of stenosis severity, CCTA also enables non-invasive whole-heart quantification of atherosclerosis, according to the authors, adding that advances in CT technology also allow for semi-automated measurements of coronary atherosclerotic plaque with high accuracy when compared with intravascular ultrasound.»
«The algorithm the team has developed outlines coronary arteries in 3D images, and then identifies blood and plaque deposits in the coronary arteries, according to the investigators, who have found that the AI tool’s measurements parallel the plaque amounts seen in coronary CT angiography.»
Article written by Mark Mc. Graw.