Diagnostic accuracy of dual-source CT angiography and coronary risk stratification

Purpose: The aim of this study was to evaluate the diagnostic accuracy of dual-source computed tomography (DSCT) in coronary artery disease, and to test the possibility of using this technique for coronary risk stratification.

Background: With the advent of DSCT, it is possible to image coronary plaque noninvasively. However, the accuracy of this method in terms of sensitivity and specificity has not been determined. Furthermore, noninvasive determination of plaque composition and plaque burden may be important for improving coronary risk stratification.

Methods: Forty-six patients with known coronary artery disease underwent DSCT quantitative coronary angiography (QCA), and intravascular ultrasound (IVUS) were included in the study. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DSCT was calculated against QCA and IVUS. Plaque analysis software in a DSCT workstation was used to detect plaque characteristics associated with the Hounsfield unit (Hu) value compared with IVUS. Coronary artery plaques were classified into three types of lesions based on DSCT, and the relationship between different coronary lesions and clinical diagnosis was determined.

Results: DSCT angiography was performed in 46 patients, and a diagnostic-quality CT image was obtained in 44 patients. Coronary angiography was performed in 138 vessels and IVUS in 102 vessels of all 46 patients. Sensitivity, specificity, PPV, and NPV of DSCT compared with QCA was 100%, 98%, 92%, and 100%, respectively. The same corresponding index of DSCT compared with IVUS was 100%, 99%, 95%, and 100%, respectively. Quantitative coronary stenosis analysis revealed a good correlation between DSCT and QCA (r = 0.85, P < 0.05, 95% confidence interval [CI] 0.60-0.87). There was also a good correlation between DSCT and IVUS (r = 0.81, P < 0.05, 95% CI 0.56-0.82). In comparison with IVUS, DSCT predicted plaque characteristics more accurately. The coefficient correlation (r) of luminal cross-sectional area and external elastic membrane cross-sectional area between DSCT and IVUS was 0.82 (P < 0.01, CI 0.67-0.89) and 0.78 (P < 0.01, CI 0.67-0.86), respectively. Three different types of plaque were identified on IVUS. Fatty plaque had a 45 ± 14 Hu value, fibrous plaque 90 ± 20, and calcified plaque 530 ± 185, respectively, on DSCT. The relationship between clinical diagnosis and coronary plaque on DSCT indicated that lesions in patients with unstable angina pectoris or ST elevation myocardial infarction were mainly discrete soft plaques, but there was no significant difference in the distributive characteristics of the lesions in patients with non-ST elevation myocardial infarction and stable angina pectoris patients.

Conclusions: DSCT is a noninvasive tool that allows accurate evaluation of plaque characteristics, diagnosis of coronary artery disease, and stratification of coronary risk according to different coronary plaque type.