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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. Site interpretation of CCTAs were compared to those analyzed by a cloud-based software (Cleerly, Inc.) that performs AI-QCT for stenosis determination, coronary vascular measurements and quantification and characterization of atherosclerotic plaque. CCTA interpretation and AI-QCT guided findings were related to MACE at 1-year follow-up., Results: Seven hundred forty-seven stable patients (60 ± 12.2 years, 49% women) were included. Using AI-QCT, 9% of patients had no CAD compared with 34% for clinical CCTA interpretation. Application of AI-QCT to identify obstructive coronary stenosis at the ≥50% and ≥70% threshold would have reduced ICA by 87% and 95%, respectively. Clinical outcomes for patients without AI-QCT-identified obstructive stenosis was excellent; for 78% of patients with maximum stenosis < 50%, no cardiovascular death or acute myocardial infarction occurred. When applying an AI-QCT referral management approach to avoid ICA in patients with <50% or <70% stenosis, overall costs were reduced by 26% and 34%, respectively., Conclusions: In stable patients referred for ACC/AHA guideline-indicated nonemergent ICA, application of artificial intelligence and machine learning for AI-QCT can significantly reduce ICA rates and costs with no change in 1-year MACE., (© 2023 The Authors. Clinical Cardiology published by Wiley Periodicals, LLC.)

Breast arterial calcification (BAC) is a type of medial artery calcification that can be seen incidentally on mammography. Studies have suggested association of BAC with cardiovascular risk factors, coronary artery disease (CAD), and cardiovascular morbidity and mortality. Recently published studies have also suggested a modest correlation of BAC with coronary artery calcium (CAC) scoring. Roughly 40 million mammograms are already performed annually in the United States with overlap in patients that undergo CAD screening via CAC scoring. Thus, identification of cardiovascular risk by demonstrating an association between BAC and CAC may enable an instrumental sex-specific methodology to identify asymptomatic women at risk for CAD. The purpose of this article is to review the current state of the literature for BAC and its association with CAC, to review contemporary breast cancer screening guidelines, and to discuss the clinical implications of these findings., (© 2017 Wiley Periodicals, Inc.)