A novel arterial redox-specific machine learning-derived radiomic signature of perivascular adipose tissue predicts cardiac mortality from routine CCTA
Kotanidis C, Akawi N, Thomas S, Siddique M, Oikonomou E, Alashi A, Akoumianakis I, Antonopoulos A, Krasopoulos G, Sayeed R, Neubauer S, Channon K, Desai M, Antoniades C. A novel arterial redox-specific machine learning-derived radiomic signature of perivascular adipose tissue predicts cardiac mortality from routine CCTA. European Heart Journal 2020, 41: ehaa946.1372. DOI: 10.1093/ehjci/ehaa946.1372.Peer-Reviewed Original ResearchArterial oxidative stressMajor adverse cardiovascular eventsVascular redox stateInternal mammary arteryVascular oxidative stressCardiac riskArm 2Radiomics signatureOxidative stressArm 3Arm 1High-risk plaque featuresEpicardial adipose tissue volumeFat attenuation indexFuture cardiac riskRadiomic featuresAdverse cardiovascular eventsPerivascular adipose tissueCardiac risk predictionAdipose tissue volumeBritish Heart FoundationLucigenin-enhanced chemiluminescenceEx vivo quantificationLong-term riskAdipose tissue composition