Diagnostic value of coronary flow reserve assessment by dynamic 99mTc-MIBI SPECT-CZT gamma camera for the detection of coronary artery disease

Abstract

Abstract Background Coronary flow reserve (CFR) obtained by dynamic acquisition of myocardial blood flow using 99mTc-MIBI SPECT-CZT gamma camera may be useful to diagnose myocardial perfusion defects in patients with coronary artery disease (CAD). Purpose To assess the feasibility and diagnostic value of SPECT-derived CFR in patients with suspected of confirmed CAD. Methods The study group comprised 55 patients (pts) (43.6% females, mean age 64.6±8.4 years) with suspected CAD who were referred for scheduled coronary angiography. All pts underwent myocardial perfusion study with solid-state CZT nuclear camera (dipyridamole stress protocol) to calculate myocardial blood flow reserve. We measured total CFR, as well as CFR in three coronary territories: left anterior descending artery (LAD CFR), right coronary artery (RCA CFR) and left circumflex artery (LCx CFR). Results On coronary angiography 27 pts were found to have significant CAD (at least one major coronary artery ≥70% narrowed). Mean total CFR in pts with CAD was lower than in pts without CAD (1.73±0.59 vs 2.09±0.56, respectively, p=0.02). Similar differences were noted in LAD territory (1.47±0.57 vs 2.00±0.57; respectively, p=0.004) and RCA territory (1.55±0.54 vs 2.01±0.62; respectively, p=0.03). However, the differences in LCx CFR between CAD and no-CAD group did not reach statistical significance. Modest, but significant correlations were detected between LAD CFR and the percentage of LAD stenosis (r=−0.3; p=0.02). Total CFR has acceptable diagnostic value for detecting significant CAD (AUC=0.672; p=0.03). The criterion with the highest diagnostic accuracy was CFR <1.8 – its sensitivity was 63%, specificity 71.4%, and overall accuracy 67%. In analysis of coronary territories the highest diagnostic value was achieved for CFR LAD (AUC=0.744; p=0.007). Conclusions SPECT-derived CFR provides acceptable diagnostic accuracy for the detection of significant CAD. Funding Acknowledgement Type of funding sources: None.