Machine-learning-derived radiomics signature of pericoronary tissue in coronary CT angiography associates with functional ischemia.

ABSTRACT: Objectives: To determine the association between radiomics signature (Rad-signature) of pericoronary tissue (PCT) in coronary computed tomography angiography (CCTA) and CT-derived fractional flow reserve (CT-FFR), and explore the influential factors of functional ischemia. Methods: We retrospectively included 350 patients who underwent CCTA from 2 centers, consisting of the training (n = 134), validation (n = 66), and testing (with CCTA and invasive coronary angiography, n = 150) groups. After evaluating coronary stenosis level in CCTA (anatomical CT), pericoronary fat attenuation index (FAI), and CT-FFR, we extracted 1,691 radiomic features from PCT. By accumulating and weighting the most contributive features to functional ischemia (CT-FFR ≤ 0.8) the Ra

SUBMITTER: Feng Y 

PROVIDER: S-EPMC9550214 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature