Non-Invasive Detection of Coronary Artery Disease in Patients With Left Bundle Branch Block Using 64-Slice Computed Tomography Original Research Article

Objectives The goal of this study was to evaluate the diagnostic accuracy of 64-slice computed tomography (CT) to identify coronary artery disease (CAD) in patients with complete left bundle branch block (LBBB). Background Left bundle branch block increases risk of cardiac mortality, and prognosis is primarily determined by the underlying coronary disease. Non-invasive stress tests have limited performance, and conventional coronary angiography (CCA) is usually required. Methods Sixty-six consecutive patients with complete LBBB and sinus rhythm admitted for CCA were enrolled. Computed tomography was performed 3 ± 3.9 days before CCA. The accuracy of 64-slice CT to detect significant stenosis (>50% lumen narrowing) was compared with quantitative coronary angiography. All segments were analyzed regardless of image quality from coronary calcification or motion artifacts. Results were analyzed by patient and by coronary segment (990) using the American Heart Association 15-segment model. Results Lower heart rates were associated with improved image quality. Computed tomography correctly identified 35 of 37 (95%) patients without significant stenosis and 28 of 29 (97%) patients with significant stenosis on CCA. Computed tomography correctly assessed 68 of 94 (72%) significant stenosis. Overall, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 64-slice CT for identifying CAD by patient was 95%, 97%, 95%, 93%, and 97%, respectively, and by segment was 97%, 72%, 99%, 91%, and 97%, respectively. Conclusions In a routine clinical practice, 64-slice CT detects with excellent accuracy a significant CAD in patients with complete LBBB. A normal CT in this clinical setting is a robust tool to act as a filter and avoid invasive diagnostic procedures.