The study compared the performance for detection and grading of coronary stenoses using artificial intelligence-enabled quantitative coronary computed tomography angiography (AI-QCT) analyses to core lab-interpreted coronary computed tomography angiography (CTA), core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR).
AI Evaluation of Stenosis on Coronary CT Angiography, Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve: A CREDENCE Trial Substudy. Griffin WF, Choi AD, Riess JS, Marques H, Chang HJ, Choi JH, Doh JH, Her AY, Koo BK, Nam CW, Park HB, Shin SH, Cole J, Gimelli A, Khan MA, Lu B, Gao Y, Nabi F, Nakazato R, Schoepf UJ, Driessen RS, Bom MJ, Thompson R, Jang JJ, Ridner M, Rowan C, Avelar E, Généreux P, Knaapen P, de Waard GA, Pontone G, Andreini D, Earls JP. JACC Cardiovasc Imaging. 2022 Feb 15:S1936-878X(22)00001-8.