Yumin Kim, Andrew D Choi, Anha Telluri, Isabella Lipkin, Andrew J Bradley, Alfateh Sidahmed, Rebecca Jonas, Daniele Andreini, Ravi Bathina, Andrea Baggiano, Rodrigo Cerci, Eui-Young Choi, Jung-Hyun Choi, So-Yeon Choi, Namsik Chung, Jason Cole, Joon-Hyung Doh, Sang-Jin Ha, Ae-Young Her, Cezary Kepka, Jang-Young Kim, Jin Won Kim, Sang-Wook Kim, Woong Kim, Gianluca Pontone, Todd C Villines, Iksung Cho, Ibrahim Danad, Ran Heo, Sang-Eun Lee, Ji Hyun Lee, Hyung-Bok Park, Ji-Min Sung, Tami Crabtree, James P Earls, James K Min, Hyuk-Jae Chang
AIMS: We compared diagnostic performance, costs, and association with major adverse cardiovascular events (MACE) of clinical coronary computed tomography angiography (CCTA) interpretation versus semiautomated approach that use artificial intelligence and machine learning for atherosclerosis imaging-quantitative computed tomography (AI-QCT) for patients being referred for nonemergent invasive coronary angiography (ICA). METHODS: CCTA data from individuals enrolled into the randomized controlled Computed Tomographic Angiography for Selective Cardiac Catheterization trial for an American College of Cardiology (ACC)/American Heart Association (AHA) guideline indication for ICA were analyzed...
February 27, 2023: Clinical Cardiology