[Value and limitations of multislice spiral CT in diagnosing coronary artery stenoses].

OBJECTIVE: To evaluate the value and limitations of multislice spiral CT in diagnosing coronary artery stenoses. METHODS: A total of 65 patients with known or suspected coronary artery disease were examined by multislice spiral CT (retrospectively ECG-gating; 0.5 s rotation; one-sector reconstruction algorithm; intravenous contrast agent) and the results were compared with quantitative coronary angiography. RESULTS: In the 889 coronary artery segments of 65 patients, 795 could be evaluated by CT (89.4%), 148 out of 167 coronary artery segments with significant stenoses (> or = 50% reduction of vessel diameter) were correctly detected by CT, 597 out of 628 coronary artery segments with normal or mild stenosis (< 50% reduction of vessel diameter) were correctly detected by CT. These values correspond to a sensitivity of 88.6%, specificity of 95.1%, positive predictive value of 82.7%, and negative predictive value of 96.9% for the detection of significant coronary artery stenosis by CT. Adding the 23 coronary artery segments with significant stenosis which could not be judged by CT, the sensitivity of CT for diagnosing coronary stenosis was 77.9%. In the 795 evaluable coronary artery segments, 78 out of 86 coronary artery segments with high-grade stenosis (> or = 75% reduction of vessel diameter) were correctly detected by CT, 692 of 709 coronary artery segments with normal or mild stenosed (< 75% reduction of vessel diameter) were correctly detected by CT. These values correspond to a sensitivity of 90.7%, specificity of 97.6%, positive predictive value of 82.1%, and negative predictive value of 98.9% for the detection of high-grade coronary artery segments stenosis by CT. Adding 13 coronary artery segments with high-grade stenosis which could not be judged by CT, the sensitivity was 78.8%. CONCLUSION: Multislice spiral CT permits the visualization of significant coronary artery stenosis with high accuracy in case of sufficient image quality.