Coronary CT angiography–derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia

Objectives We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)–derived plaque markers combined with deep machine learning–based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FFR as the reference standard.