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

• Machine learning-based FFR CT and subtended myocardium volume both performed well for predicting hemodynamically significant coronary stenosis. • Subtended myocardium volume was more accurate than machine learning-based FFR CT for "gray zone" lesions with simulated FFR value from 0.7 to 0.8. • CT-derived high-risk plaque features failed to correctly identify hemodynamically significant stenosis.