Coronary CT Angiography–based Morphologic Index for Predicting Hemodynamically Significant Coronary Stenosis

Abstract

Coronary artery disease (CAD) is a leading cause of morbidity and mortality globally. The early and accurate diagnosis of CAD is essential for effective treatment. While Coronary Computed Tomography Angiography (CCTA) offers detailed visualization of coronary anatomy, its predictive power for hemodynamically significant coronary stenosis remains under investigation. This study aimed to develop and validate a CCTA-based morphologic index to enhance the diagnostic accuracy for significant coronary stenosis, potentially reducing the need for invasive diagnostic procedures.