Coronary CT angiography–derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia - von Knebel Doeberitz, Philipp L.; De Cecco, Carlo N.; Schoepf, U. Joseph; Duguay, Taylor M.; Albrecht, Moritz H.; van Assen, Marly; Bauer, Maximilian J.; Savage, Rock H.; Pannell, J. Trent; De Santis, Domenico; Johnson, Addison A.; Varga-Szemes, Akos; et al. (European radiology, 2019)
Keywords: Angiography; Arteriosclerosis; Artificial intelligence; Atherosclerosis; Blood vessels; Cardiac; Computed tomography; Computed Tomography Angiography - methods; Coronary Angiography - methods; Coronary Stenosis - diagnosis; Coronary Stenosis - etiology; Coronary Stenosis - physiopathology; Diagnosis, Computer-Assisted - methods; Diagnostic Radiology; Diagnostic systems; Evaluation; Female; Fractional Flow Reserve, Myocardial - physiology; Grading; Humans; Identification methods; Imaging; Internal Medicine; Interventional Radiology; Ischemia; Learning algorithms; Lesions; Machine Learning; Male; Markers; Medical imaging; Medicine; Medicine & Public Health; Middle Aged; Multivariate analysis; Neuroradiology; Plaque, Atherosclerotic - complications; Plaque, Atherosclerotic - diagnosis; Plaque, Atherosclerotic - physiopathology; Radiology; Retrospective Studies; Risk analysis; ROC Curve; Stenosis; Ultrasound; Angiography; Coronary artery disease; Spiral computed tomography