ArticleCoronary artery disease2025
First comparison between artificial intelligence-guided coronary computed tomography angiography versus single-photon emission computed tomography testing for ischemia in clinical practice.
Article in Coronary artery disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Deep Learning and Cardiovascular Diseases: An Updated Narrative Review.Journal of clinical medicine · 2026Review
- Diagnostic Performance of a Novel AI-Guided Coronary Computed Tomography Algorithm for Predicting Myocardial Ischemia (AI-QCTJournal of the Society for Cardiovascular Angiography & Interventions · 2026Article
- Artificial intelligence and multimodal diagnostic approaches in cardiovascular disease.Archivos peruanos de cardiologia y cirugia cardiovascularReview
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5 authors.
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Abstract
backgroundNoninvasive cardiac testing with coronary computed tomography angiography (CCTA) and single-photon emission computed tomography (SPECT) are becoming alternatives to invasive angiography for the evaluation of obstructive coronary artery disease. We aimed to evaluate whether a novel artificial intelligence (AI)-assisted CCTA program is comparable to SPECT imaging for ischemic testing.
methodsCCTA images were analyzed using an artificial intelligence convolutional neural network machine-learning-based model, atherosclerosis imaging-quantitative computed tomography (AI-QCT) ISCHEMIA . A total of 183 patients (75 females and 108 males, with an average age of 60.8 years ± 12.3 years) were selected. All patients underwent AI-QCT ISCHEMIA -augmented CCTA, with 60 undergoing concurrent SPECT and 16 having invasive coronary angiograms. Eight studies were excluded from analysis due to incomplete data or coronary anomalies.
resultsA total of 175 patients (95%) had CCTA performed, deemed acceptable for AI-QCT ISCHEMIA interpretation. Compared to invasive angiography, AI-QCT ISCHEMIA -driven CCTA showed a sensitivity of 75% and specificity of 70% for predicting coronary ischemia, versus 70% and 53%, respectively for SPECT. The negative predictive value was high for female patients when using AI-QCT ISCHEMIA compared to SPECT (91% vs. 68%, P = 0.042). Area under the receiver operating characteristic curves were similar between both modalities (0.81 for AI-CCTA, 0.75 for SPECT, P = 0.526). When comparing both modalities, the correlation coefficient was r = 0.71 ( P < 0.04).
conclusionAI-powered CCTA is a viable alternative to SPECT for detecting myocardial ischemia in patients with low- to intermediate-risk coronary artery disease, with significant positive and negative correlation in results. For patients who underwent confirmatory invasive angiography, the results of AI-CCTA and SPECT imaging were comparable. Future research focusing on prospective studies involving larger and more diverse patient populations is warranted to further investigate the benefits offered by AI-driven CCTA.
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