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Diagnostic performance of a novel AI-guided coronary computed tomography algorithm for predicting myocardial ischemia (AI-QCT ISCHEMIA ) across sex and age subgroups

Title: Diagnostic performance of a novel AI-guided coronary computed tomography algorithm for predicting myocardial ischemia (AI-QCT ISCHEMIA ) across sex and age subgroups
Authors: Kamila, Putri Annisa; Hojjati, Tara; Nurmohamed, Nick S.; Danad, Ibrahim; Ding, Yipu; Jukema, Ruurt A.; Raijmakers, Pieter G.; Driessen, Roel S.; Bom, Michiel J.; van Diemen, Pepijn; Pontone, Gianluca; Andreini, Daniele; Chang, Hyuk Jae; Katz, Richard J.; Choi, Andrew D.; Knaapen, Paul; Bax, Jeroen J.; van Rosendael, Alexander; Heo, Ran; Park, Hyung Bok; Marques, Hugo; Stuijfzand, Wijnand J.; Choi, Jung Hyun; Doh, Joon Hyung; Her, Ae Young; Koo, Bon Kwon; Nam, Chang Wook; Shin, Sang Hoon; Cole, Jason; Gimelli, Alessia; Khan, Muhammad Akram; Lu, Bin; Gao, Yang; Nabi, Faisal; Al-Mallah, Mouaz H.; Nakazato, Ryo; Schoepf, U. Joseph; Thompson, Randall C.; Jang, James J.; Ridner, Michael; Rowan, Chris; Avelar, Erick; Généreux, Philippe; de Waard, Guus A.
Source: Kamila, P A, Hojjati, T, Nurmohamed, N S, Danad, I, Ding, Y, Jukema, R A, Raijmakers, P G, Driessen, R S, Bom, M J, van Diemen, P, Pontone, G, Andreini, D, Chang, H J, Katz, R J, Choi, A D, Knaapen, P, Bax, J J, van Rosendael, A, Heo, R, Park, H B, Marques, H, Stuijfzand, W J, Choi, J H, Doh, J H, Her, A Y, Koo, B K, Nam, C W, Shin, S H, Cole, J, Gimelli, A, Khan, M A, Lu, B, Gao, Y, Nabi, F, Al-Mallah, M H, Nakazato, R, Schoepf, U J, Thompson, R ....
Publication Year: 2026
Subject Terms: Artificial intelligence; Coronary artery disease; Coronary computed tomography angiography
Description: Background AI-QCT ISCHEMIA is a novel artificial intelligence algorithm that predicts myocardial ischemia using quantitative features from coronary computed tomography angiography, providing a noninvasive alternative to functional imaging. However, its diagnostic performance across key demographic subgroups, particularly by sex and age, remains underexplored. We aimed to evaluate the diagnostic performance of AI-QCT ISCHEMIA for predicting myocardial ischemia across these subgroups. Methods This post-hoc analysis included symptomatic patients with suspected coronary artery disease from the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) (n = 305; 868 vessels) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) (n = 208; 612 vessels) studies. All patients underwent coronary computed tomography angiography, myocardial perfusion imaging (SPECT and/or PET), and invasive coronary angiography with 3-vessel fractional flow reserve as the reference standard. Diagnostic performance was evaluated at the vessel level using receiver operating characteristic analysis and under the curve (AUC), stratified by sex and age groups. Results In computed tomographic evaluation of atherosclerotic determinants of myocardial ischemia, AI-QCT ISCHEMIA demonstrated higher diagnostic performance than myocardial perfusion imaging, with AUCs of 0.87 vs 0.63 in men and 0.85 vs 0.71 in women ( P < .001 for both). Similarly, in older (≥65 years) and younger (
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISSN: 2772-9303
Relation: info:eu-repo/semantics/altIdentifier/eissn/2772-9303
DOI: 10.1016/j.jscai.2025.104064
Availability: https://ciencia.ucp.pt/en/publications/dc774510-4dc3-44ed-aa43-6a012c8c6b60; https://doi.org/10.1016/j.jscai.2025.104064; https://ciencia.ucp.pt/ws/files/141753493/138620196.pdf; https://www.scopus.com/pages/publications/105026814087; https://hdl.handle.net/10400.14/56609
Rights: info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.32EBEB36
Database: BASE