16-detector row computed tomographic coronary angiography in patients undergoing evaluation for aortic valve replacement: comparison with catheter angiography

AIM: To evaluate the diagnostic accuracy of 16-detector row computed tomography (CT) in assessing haemodynamically significant coronary artery stenoses in patients under evaluation for aortic stenosis pre-aortic valve replacement. SUBJECTS AND METHODS: Forty consecutive patients under evaluation for severe aortic stenosis and listed for cardiac catheterization before potential aortic valve replacement underwent coronary artery calcium (CAC) scoring and retrospective electrocardiogram (ECG)-gated multi-detector row computed tomographic coronary angiography (MDCTA) using a GE Lightspeed 16-detector row CT within 1 month of invasive coronary angiography (ICA) for comparative purposes. All 13 major coronary artery segments of the American Heart Association model Were evaluated for the presence of >= 50% stenosis and compared to the reference standard. Data were analysed on, a segment-by-segment basis and also in "whole patient" terms. RESULTS: A total of 412/450 segments from 35 patients were suitable for analysis.. The overall accuracy of MDCTA for detection of segments with >= 50% stenosis was high, with a sensitivity of 81.3%, specificity 95.0%, positive predictive value (PPV) 57.8%, and negative predictive value (NPV) 98.4%. On a "whole - patient" basis, 100% (19/19) of patients with significant coronary disease were correctly identified and there were no false- negatives. Excluding patients with CAC >1000 from the analysis improved the accuracy of MDCTA to: sensitivity 90%, specificity 98. 1 %, PPV 60%, NPV 99.7%. CONCLUSION: Non-invasive 16-detector row MDCTA accurately excludes significant coronary disease in patients with severe aortic stenosis undergoing evaluation before aortic valve replacement and in whom ICA can therefore be avoided. Its segment- by-segment accuracy is improved further if CAC > 1000 is used as a gatekeeper to MDCTA. (C) 2006 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.