Myocardial Energy Estimated by PET Strain and Myocardial Flow Reserve: New Strategy for Coronary Artery Disease

Introduction: Myocardial flow reserve (MFR), which is quantitatively measured by ¹³N-ammonia positron emission tomography (NH₃-PET), can predict the prognosis of patients with various heart diseases. We have applied feature-tracking technique to NH₃-PET and developed the world's first PET-dedicated cardiac function analysis algorithm that can measure regional myocardial strain ratio (MSR) of stress to rest MS. PET-derived MSR and MFR are considered as independent vectors and we propose their sum as myocardial energy (ME). Present study aimed to investigate the potential of ME as prognostic factors in ischemic heart disease (IHD).

Methods: Between January 2017 to January 2019, 263 consecutive patients who underwent resting/ stressed myocardial NH₃-PET because of known or suspected coronary artery disease at a single center were enrolled. In this study, we included patients with coronary artery stenosis of more than 50%, diagnosed by coronary computed tomography angiography, from this cohort. Among them, congenital heart disease, a transplanted heart or adenosine ineffectiveness were excluded.

MSR was defined as the ratio of strains at stress and rest, and ME was calculated from the following equation.

The endpoint was major adverse cardiac events (MACEs) comprising all-cause death, acute coronary syndrome, hospitalization due to heart failure, revascularization, and cerebrovascular disease. The ability to predict MACE was assessed using the receiver-operating characteristic (ROC) analysis. The predictability of ME was analyzed using Kaplan–Meier analysis. The Cox proportional hazards regression model was used to calculate hazard ratios (HR) with 95% confidence intervals (CI).

Results: Consecutive 95 patients were prospectively analyzed. The ROC curve analysis demonstrated a cutoff of 2.29 for MACE with ME (sensitivity and specificity of 83% and 60%). Patients with ME <2.29 had a significantly higher MACE rate than those with ME ≥2.29 (p=0.0016). The Cox proportional hazards regression analysis indicated that ME was an independent marker that could predict MACE in imaging parameters (HR: 24.2, 95% CI: 1.66–353, p=0.020).

Conclusions: ME helped identify patients at higher risk of MACE, and it may be a new index for risk stratification in IHD.

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