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OBJECTIVE: The purpose of the study was to investigate patient characteristics associated with image quality and their impact on the diagnostic accuracy of MDCT for the detection of coronary artery stenosis. MATERIALS AND METHODS: Two hundred ninety-one patients with a coronary artery calcification (CAC) score of or=50%) stenoses was assessed using quantitative coronary angiography (QCA) per patient and per vessel using a modified 19-segment model. The effect of CAC, obesity, heart rate, and heart rate variability on image quality and accuracy were evaluated by multiple logistic regression. Image quality and accuracy were further analyzed in subgroups of significant predictor variables. Diagnostic analysis was determined for image quality strata using receiver operating characteristic (ROC) curves. RESULTS: Increasing body mass index (BMI) (odds ratio OR=0.89, p<0.001), increasing heart rate (OR=0.90, p<0.001), and the presence of breathing artifact (OR=4.97, p<or=0.001) were associated with poorer image quality whereas sex, CAC score, and heart rate variability were not. Compared with examinations of white patients, studies of black patients had significantly poorer image quality (OR=0.58, p=0.04). At a vessel level, CAC score (10 Agatston units) (OR=1.03, p=0.012) and patient age (OR=1.02, p=0.04) were significantly associated with the diagnostic accuracy of quantitative MDCT compared with QCA. A trend was observed in differences in the areas under the ROC curves across image quality strata at the vessel level (p=0.08). CONCLUSION: Image quality is significantly associated with patient ethnicity, BMI, mean scan heart rate, and the presence of breathing artifact but not with CAC score at a patient level. At a vessel level, CAC score and age were associated with reduced diagnostic accuracy.
Dewey et al. (Tue,) studied this question.