Plaque burden improves the detection of ischemic CAD over stenosis from coronary computed tomography angiography.
Journal:
The international journal of cardiovascular imaging
Published Date:
Apr 22, 2025
Abstract
In symptomatic patients undergoing coronary CTA for suspected coronary artery disease (CAD), we assessed if quantification of plaque burden, in addition to luminal narrowing and clinical risk factors, offers incremental value for the identification of ischemic CAD on a per patient level. We evaluated 2145 patients who underwent coronary CTA for suspected CAD with sequential selective downstream O-water positron emission tomography (PET) myocardial perfusion imaging. Coronary CTA scans were analyzed using Artificial Intelligence-guided Quantitative Computed Tomography (AI-QCT), with measurement of maximum diameter stenosis, percent atheroma volume (PAV), percent calcified plaque volume (CPV) and percent noncalcified plaque volume (NCPV). Ischemic CAD was defined as the presence of abnormal stress perfusion on O-water PET. PAV on top of the clinical variables and ≥ 50% stenosis improved the prediction of ischemic CAD on a per patient level as compared to clinical variables and ≥ 50% stenosis (AUC = 0.91 vs. AUC = 0.87, p < 0.001). The best diagnostic performance was achieved when PAV with a cut-off value of 12.2% was applied in patients with intermediate (30-70%) stenosis; using this approach, the sensitivity, specificity, positive and negative predictive values and diagnostic accuracy for ischemic CAD were 76%, 91%, 64%, 95% and 88%. The addition of quantitative plaque volume on top of clinical variables and ≥ 50% diameter stenosis improves the detection of ischemic CAD as defined by PET perfusion imaging. Applying a PAV threshold of 12.2% in patients with intermediate stenosis provided the best diagnostic performance.
Authors
Keywords
Aged
Artificial Intelligence
Computed Tomography Angiography
Coronary Angiography
Coronary Artery Disease
Coronary Stenosis
Coronary Vessels
Female
Humans
Male
Middle Aged
Multidetector Computed Tomography
Myocardial Perfusion Imaging
Plaque, Atherosclerotic
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Retrospective Studies
Risk Factors
Severity of Illness Index
Vascular Calcification