The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning–based FFRCT, or high-risk plaque features?

Objectives The present study aimed to compare the diagnostic performance of a machine learning (ML)–based FFRCT algorithm, quantified subtended myocardial volume, and high-risk plaque features for predicting if a coronary stenosis is hemodynamically significant, with reference to FFRICA.