Integrated prediction of lesion-specific ischaemia from quantitative coronary CT angiography using machine learning: a multicentre study

Objectives We aimed to investigate if lesion-specific ischaemia by invasive fractional flow reserve (FFR) can be predicted by an integrated machine learning (ML) ischaemia risk score from quantitative plaque measures from coronary computed tomography angiography (CTA).