Abstract 4222: 64-Detector Row Coronary Computed Tomographic Angiographic Plaque Predictors of Exercise-Induced ST-Segment Depression and Impaired Exercise Capacity by Exercise Treadmill Testing
64-detector row coronary computed tomographic angiography (CCTA) has been proposed as a useful method for evaluation of coronary artery disease (CAD) in low-to-intermediate risk patients. ST-segment depression and Duke treadmill score (DTS) by exercise treadmill testing (ETT) has been traditionally used to evaluate ischemia and functional capacity in these patients. At present, CCTA predictors of ST-segment depression and DTS are unknown. We studied 156 low-to-intermediate patients without known CAD who underwent both ETT and CCTA. ETTs were scored for ST-segment depression and DTS. CCTAs were scored for the absence or presence of mild (>50%), moderate (50 –70%), or severe (>70%) coronary artery stenosis; as well as a modified Duke coronary artery disease index as a graded measure of plaque burden. Coronary arteries were also graded for non-calcified, calcified, and mixed plaque by # of segments. Among the study group, 22.4% (n=35) had ST-segment depression and 26.9% (n=42) had intermediate-to-high risk DTS. By CCTA, 21.2% (n=33) had severe CAD, and 49.4% (n=77) had mild or moderate CAD. 45.7% (n=16) patients with and 15.2% (n=15) of patients without ST-segment depression had severe CAD. Age, coronary calcium, and CCTA-identified severe CAD predicted both ST-depression and abnormal DTS in univariate analysis, while only age and CCTA-identified severe CAD predicted ST-depression and abnormal DTS in multivariate analysis. (Table 1⇓). Mixed, but not calcified or non-calcified plaque burden, predicted ST-segment depression and abnormal DTS. In low-to-intermediate risk symptomatic patients without known CAD, CCTA-identified plaque measures predict ST-segment depression and DTS (Table 1⇓). There is incremental diagnostic yield of CCTACCTA for identification of severe CAD above ST-segment depression and DTS in low-to-intermediate risk patients.