Quantitative coronary arterial stenosis assessment by multidetector CT and invasive coronary angiography for identifying patients with myocardial perfusion abnormalities
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Semi-quantitative stenosis assessment by coronary CT angiography only modestly predicts stress-induced myocardial perfusion abnormalities. The performance of quantitative CT angiography (QCTA) for identifying patients with myocardial perfusion defects remains unclear.
CorE-64 is a multicenter, international study to assess the accuracy of 64-slice QCTA for detecting ≥50% coronary arterial stenoses by quantitative coronary angiography (QCA). Patients referred for cardiac catheterization with suspected or known coronary artery disease were enrolled. Area under the receiver-operating-characteristic curve (AUC) was used to evaluate the diagnostic accuracy of the most severe coronary artery stenosis in a subset of 63 patients assessed by QCTA and QCA for detecting myocardial perfusion abnormalities on exercise or pharmacologic stress SPECT.
Diagnostic accuracy of QCTA for identifying patients with myocardial perfusion abnormalities by SPECT revealed an AUC of 0.71, compared to 0.72 by QCA (P = .75). AUC did not improve after excluding studies with fixed myocardial perfusion abnormalities and total coronary arterial occlusions. Optimal stenosis threshold for QCTA was 43% yielding a sensitivity of 0.81 and specificity of 0.50, respectively, compared to 0.75 and 0.69 by QCA at a threshold of 59%. Sensitivity and specificity of QCTA to identify patients with both obstructive lesions and myocardial perfusion defects were 0.94 and 0.77, respectively.
Coronary artery stenosis assessment by QCTA or QCA only modestly predicts the presence and the absence of myocardial perfusion abnormalities by SPECT. Confounding variables affecting the relationship between coronary anatomy and myocardial perfusion likely account for some of the observed discrepancies between coronary angiography and SPECT results.
KeywordsCT angiography SPECT myocardial ischemia cardiac computed tomography
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