Abstrakt
Features of high-risk coronary artery plaques prone to major adverse cardiac events (MACE) were identified by intravascular ultrasound (IVUS) virtual histology (VH). These plaque features are: thin-cap fibroatheroma (TCFA), plaque burden PB >= 70%, or minimal luminal area MLA = 70%, correctness was 80.8% for baseline PB >= 70% and 85.6% for 50% <= PB< 70%.
Accuracy of predicted MLA <= 4 mm(2) was 81.6% for baseline MLA <= 4 mm(2) and 80.2% for 4 mm(2) < MLA <= 6 mm(2). Location-specific prediction of future high-risk coronary artery plaques is feasible through machine learning using focal vascular features and demographic variables.
Our approach outperforms previously reported results and shows the importance of local factors on high-risk coronary artery plaque development.