From Lumen to Myocardium With Artificial Intelligence: A Clinician's Guide to Comprehensive Cardiac CT.
Authors
Affiliations (5)
Affiliations (5)
- From the Department of Medicine, Valley Health System, Las Vegas, NV.
- Department of Medicine, Iran University of Medical Sciences, Tehran, Iran.
- Department of Internal Medicine, Sunrise Health GME Consortium, Las Vegas, NV.
- Department of Medicine, University of Naples Federico II, Naples, Italy.
- Departments of Medicine, Westchester Medical Center, New York Medical College, Valhalla, NY.
Abstract
Coronary artery disease assessment has long focused on stenosis severity, yet luminal narrowing alone fails to capture ischemic burden, plaque vulnerability, or myocardial health. This mismatch drives unnecessary invasive coronary angiography and delays preventive therapy. Cardiac computed tomography (CT) has evolved from a simple anatomical gatekeeper into a comprehensive, noninvasive platform that addresses this gap. This review synthesizes current evidence and provides practical guidance for clinicians, with an emphasis on artificial intelligence integration. High-quality coronary CT angiography now serves as a foundational anatomical roadmap, with trials demonstrating its feasibility for planning complex revascularization (SYNTAX III REVOLUTION) and safely reducing invasive procedures (DISCHARGE). CT-derived fractional flow reserve improves diagnostic specificity, reduces nonobstructive catheterization, and guides revascularization decisions, though prognostic evidence remains mixed and image-quality constraints apply. Quantitative plaque characterization, particularly low-attenuation and total plaque volumes, strongly predicts myocardial infarction and mortality, outperforming stenosis severity and supporting proactive preventive therapy even in nonobstructive disease. Emerging applications include CT-derived extracellular volume for detecting diffuse fibrosis and cardiac amyloidosis, with prognostic value across aortic stenosis and heart failure.