Prognostic Value of Stress Myocardial Uptake Ratio and Area Under the Time-Activity Curve based Myocardial Flow Reserve for Predicting Cardiac Events Using an Anger-Type Gamma Camera

Background: Quantitative images reflecting myocardial blood flow can be generated with conventional myocardial perfusion imaging (MPI) using an Anger-type gamma camera (AG) through the myocardial uptake ratio (MUR) method.This approach is reportedly useful for detecting the presence of coronary artery disease (CAD), but its prognostic value for predicting major adverse cardiovascular events (MACE) remains unclear.The aim of this study was to evaluate whether quantitative MPI using AG improves the predictive accuracy for MACE compared to conventional MPI.Methods: Participants comprised 105 patients who underwent a 1-day adenosine stress/rest 99m Tc-sestamibi protocol and had follow-up data for over 5 years.Conventional MPI parameters assessed included perfusion scores, left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume, left ventricular endsystolic volume, phase standard deviation (phase SD), bandwidth (BW), and entropy.Quantitative MPI parameters included stress MUR, area under the time-activity curve (AUC) -based myocardial flow reserve (MFR), and coronary flow capacity as a combination of stress MUR and AUC-based MFR.The ability of these parameters to predict MACE was evaluated using receiver operating characteristic analysis.Results: Rest entropy (AUC=0.80)was the strongest predictor among conventional MPI parameters, followed by rest phase SD, BW (both AUCs=0.79), and LVEF (AUC=0.78).Quantitative MPI parameters showed stress MUR (AUC=0.85)and AUC-based MFR (AUC=0.83).Further, the combination of stress MUR and AUC-based MFR showed an AUC of 0.90, significantly superior to that of rest entropy (p<0.05).Conclusions: Quantitative MPI parameters using AG may improve the ability to predict MACE compared with conventional MPI parameters.