Dynamic Computed Tomography Myocardial Perfusion Imaging

Abstract

Background— The clinical analysis of myocardial dynamic computed tomography myocardial perfusion imaging lacks standardization. The objective of this prospective study was to compare different analysis approaches to diagnose ischemia in patients with stable angina referred for invasive coronary angiography. Methods and Results— Patients referred for evaluation of stable angina symptoms underwent adenosine-stress dynamic computed tomography myocardial perfusion imaging with a second-generation dual-source scanner. Quantitative perfusion parameters, such as blood flow, were calculated by parametric deconvolution for each myocardial voxel. Initially, perfusion parameters were extracted according to standard 17-segment model of the left ventricle (fully automatic analysis). These were then manually sampled by an operator (semiautomatic analysis). Areas under the receiver-operating characteristic curves of the 2 different approaches were compared. Invasive fractional flow reserve ≤0.80 or diameter stenosis ≥80% on quantitative coronary angiography was used as reference standard to define ischemia. We enrolled 115 patients (88 men; age 57±9 years). There were 72 of 286 (25%) vessels causing ischemia in 52 of 115 (45%) patients. The semiautomatic analysis method was better than the fully automatic method at predicting ischemia (areas under the receiver-operating characteristic curves, 0.87 versus 0.69; P <0.001) with readings obtained in the endocardial myocardium performing better than those in the epicardial myocardium (areas under the receiver-operating characteristic curves, 0.87 versus 0.72; P <0.001). The difference in performance between blood flow, expressed as relative to remote myocardium, and absolute blood flow was not statistically significant (areas under the receiver-operating characteristic curves, 0.90 versus 0.87; P =ns). Conclusions— Endocardial perfusion parameters obtained by semiautomatic analysis of dynamic computed tomography myocardial perfusion imaging may permit robust discrimination between coronary vessels causing ischemia versus not causing ischemia.