Abstract

Introduction: Myocardial perfusion, scar size, sympathetic denervation and innervation-perfusion mismatch, obtained from positron emission tomography (PET) and late gadolinium enhanced cardiovascular magnetic resonance imaging (LGE-CMR), may all provide better risk prediction of ventricular arrhythmias (VA). There may, however, be overlap between these risk markers, as some are based on similar pathophysiology. The aim of this study was to assess the role of PET and LGE-CMR derived risk markers in predicting VA inducibility in the same patient population. Methods: Patients (n=52, 66 ± 9 years, 90% male, LVEF 29 ± 6%) with ischemic cardiomyopathy and left ventricular ejection fraction (LVEF) ≤35% who were referred for primary prevention implantable cardioverter-defibrillator (ICD) implantation were included. LGE-CMR was performed to assess LV volumes, function, and scar size. [ 15 O]H 2 O PET and [ 11 C]HED PET were performed to assess both resting and hyperemic myocardial blood flow (MBF), and sympathetic innervation. Perfusion and innervation defects, and mismatch were calculated. After ICD implantation, an electrophysiological study (EPS) was performed and was considered positive in case of sustained VA. Results: Patients with positive EPS (n=25) showed lower hyperemic MBF (1.36 ± 0.39 vs. 1.71 ± 0.39 mL·min -1 ·g -1 , P =0.003), larger innervation defect size (28 ± 12 vs. 21 ± 13%, P =0.048), and tended to have larger scar size (24 ± 13 vs. 18 ± 9 g, P =0.07) and perfusion defect size (22 ± 13 vs. 15 ± 11%, P =0.06) compared with EPS negative patients (n=27). No differences were observed in LV volumes, LVEF, and innervation-perfusion mismatch size. Multivariable analysis revealed that impaired hyperemic MBF was the only independent predictor for VA inducibility (OR 0.78, 95% CI 0.65-0.94, P =0.007). A combination of risk markers did not yield incremental predictive value over hyperemic MBF alone. Conclusion: Of all previously validated risk markers for VA, impaired hyperemic MBF was the only independent predictor of VA inducibility. Moreover, a combined approach of different imaging variables did not have incremental value. These results may suggest that quantitative PET perfusion imaging may be promising for risk prediction of VA.

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