Putri Annisa Kamila, Nick S Nurmohamed, Ibrahim Danad, Ruurt A Jukema, Pieter G Raijmakers, Roel S Driessen, Michiel J Bom, Pepijn van Diemen, Gianluca Pontone, Daniele Andreini, Hyuk-Jae Chang, Richard J Katz, Andrew D Choi, Paul Knaapen, Jeroen J Bax, Alexander van Rosendael, Ran Heo, Hyung-Bok Park, Hugo Marques, Wijnand J Stuijfzand, Jung Hyun Choi, Joon-Hyung Doh, Ae-Young Her, Bon-Kwon Koo, Chang-Wook Nam, Sang-Hoon Shin, Jason Cole, Alessia Gimelli, Muhammad Akram Khan, Bin Lu, Yang Gao, Faisal Nabi, Mouaz H Al-Mallah, Ryo Nakazato, Randall C Thompson, James J Jang, Michael Ridner, Chris Rowan, Erick Avelar, Philippe Généreux, Guus A de Waard
Aims: To evaluate the ability of artificial intelligence-based quantitative CT (AI-QCT) parameters, diameter stenosis, percent atheroma volume (PAV) and average lumen area (ALA) to rule-in or rule-out ischaemia. Methods and results: This post-hoc, vessel-level analysis included patients with suspected coronary artery disease from the computed tomographic evaluation of atherosclerotic determinants of myocardial ischaemia (CREDENCE) (612 patients; 1727 vessels) and PACIFIC-1 (208 patients; 612 vessels) studies who underwent CCTA and invasive fractional flow reserve (FFR). In addition to diameter stenosis, PAV and ALA were evaluated as key predictors of ischaemia. We report abnormal FFR prevalence based on these variables and define rule-out (<15% ischaemia prevalence, defer further testing), rule-in (>75% prevalence, ischaemia highly likely; further testing typically unnecessary), and intermediate risk (15–75%, consider additional functional assessment). PAV and ALA were dichotomized using median values derived from the CREDENCE cohort (14.7% and 3.9 mm2) and validated in PACIFIC-1. In CREDENCE, all vessels with 1–24% stenosis were ruled-out. Among vessels with 25–49% stenosis, 74% met rule-out criteria, while 26%, characterized by large PAV and small ALA, were intermediate risk. Within the proposed framework vessels with 50–69% stenosis were classified as intermediate risk. For 70–99% stenosis, 93% met rule-in criteria, except a small subset with small PAV and large ALA. In PACIFIC-1, 86% of vessels with <50% stenosis were ruled-out, and 61% of those with 50–99% stenosis were ruled-in. Conclusion: A simplified framework incorporating AI-QCT parameters including diameter stenosis, PAV (>14.7%), and ALA (<3.9 mm2), stratifies myocardial ischaemia risk. Most non-obstructive lesions can be ruled-out, while most stenoses >70% are reliably ruled-in. This practical approach enhances the diagnostic utility of CCTA and streamlines clinical decision-making. © The Author(s) 2026. Published by Oxford University Press on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Department of Cardiology, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, Netherlands; Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia; Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Department of Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Department of Cardiology, Radboud University Medical Center, Nijmegen, Netherlands; Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy; Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy; Department of University Cardiology and Cardiac Imaging, IRCCS Ospedale Galeazzi Sant’Ambrogio, Milan, Italy; Division of Cardiology, Severance Cardiovascular Hospital and Severance Biomedical Science Institute, Yonsei University College of Medicine, Yonsei University Health System, Seoul, South Korea; Division of Cardiology, The George Washington University School of Medicine, Washington, DC, United States; Division of Cardiology, The George Washington University School of Medicine, Washington, DC, United States; Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Department of Cardiology, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, Netherlands; Heart Center, Turku University Hospital and University of Turku, Turku, Finland; Department of Cardiology, Division of Heart and Lungs, Utrecht University, Utrecht University Medical Center, Utrecht, Netherlands
