The current approach to chest pain mainly focuses on symptom characteristics, conducting functional tests for ischemia assessment. However, several randomized clinical trials have shown these tests fail to improve patient prognosis. Intravascular imaging, such as intravascular ultrasound (IVUS), has shown that plaque burden, low-attenuation plaques, and minimal luminal area are important prognostic markers of coronary artery disease.
Coronary computed tomography angiography (CTA) accurately assesses atherosclerotic plaque characteristics, and several studies have highlighted its significant prognostic value. Notably, quantitative CTA with artificial intelligence (AI) enables comprehensive, automated quantitative analysis of the arterial tree.
The aim of this study was to identify the quantitative characteristics of atherosclerosis assessed by CTA and their association with major adverse cardiovascular events (MACE). Additionally, the prognostic value of these characteristics was compared against traditional clinical risk scores.
Primary endpoint included all-cause mortality, acute myocardial infarction (AMI), stroke, heart failure (HF), late revascularization (>90 days), and hospitalization for unstable angina. Secondary endpoint was all-cause mortality and AMI.
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A total of 3,551 patients were analyzed and follow-up for mean 4.8 years. Mean patient age was 58, they were mostly male. Most were at intermediate risk according to the Diamond-Forrester score. During follow-up, 5% of patients experienced adverse events, including death (n=34), AMI (n=24), stroke (n=12), hospitalization for HF (n=23), hospitalization for unstable angina (n=17), and late revascularization (n=84). The main predictors of MACE were stenosis luminal diameter and non-calcified plaque volume.
This is the first multicenter registry using artificial intelligence to quantify coronary artery disease. The use of AI-QCT can guide both anti-atherosclerotic therapies and interventional cardiology procedures, aimed at reducing adverse events during follow-up.
Original Title: CONFIRM-2: AI-guided Quantitative Coronary CT Angiography (AI-QCT) Technology in Patients With Suspected Coronary Artery Disease.
Reference: Alexander van Rosendael MD PhD et al TCT 2024.
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