Additive value of epicardial adipose tissue quantification to coronary CT angiography–derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia

• Published in: European radiology 2022-06, Vol.32 (6), p.4243-4252
• Main Authors: Brandt, Verena, Decker, Josua, Schoepf, U. Joseph, Varga-Szemes, Akos, Emrich, Tilman, Aquino, Gilberto, Bayer, Richard R., Carson, Landin, Sullivan, Allison, Ellis, Lauren, von Knebel Doeberitz, Philipp L., Ebersberger, Ullrich, Bekeredjian, Raffi, Tesche, Christian
• Format: Article
• Language: English
• Subjects: Adipose tissue; Adipose Tissue - diagnostic imaging; Algorithms; Angiography; Body fat; Cardiac; Cardiovascular disease; Computed Tomography Angiography; Coronary Angiography; Coronary artery; Coronary Artery Disease; Coronary Stenosis - diagnosis; Diagnostic Radiology; Female; Fractional Flow Reserve, Myocardial; Heart diseases; Hemodynamics; Humans; Imaging; Internal Medicine; Interventional Radiology; Ischemia; Lesions; Machine learning; Male; Medical imaging; Medicine; Medicine & Public Health; Multivariate analysis; Neuroradiology; Plaque, Atherosclerotic - diagnosis; Predictive Value of Tests; Radiology; Retrospective Studies; Stenosis; Tomography, X-Ray Computed; Ultrasound
• ISSN: 1432-1084; 0938-7994; 1432-1084
• DOI: 10.1007/s00330-021-08481-w

Objectives Epicardial adipose tissue (EAT) from coronary CT angiography (CCTA) is strongly associated with coronary artery disease (CAD). We investigated the additive value of EAT volume to coronary plaque quantification and CT-derived fractional flow reserve (CT-FFR) to predict lesion-specific ischemia. Methods Patients ( n  = 128, 60.6 ± 10.5 years, 61% male) with suspected CAD who had undergone invasive coronary angiography (ICA) and CCTA were retrospectively analyzed. EAT volume and plaque measures were derived from CCTA using a semi-automatic software approach, while CT-FFR was calculated using a machine learning algorithm. The predictive value and discriminatory power of EAT volume, plaque measures, and CT-FFR to identify ischemic CAD were assessed using invasive FFR as the reference standard. Results Fifty-five of 152 lesions showed ischemic CAD by invasive FFR. EAT volume, CCTA ≥ 50% stenosis, and CT-FFR were significantly different in lesions with and without hemodynamic significance (all p