Quantitative myocardial perfusion evaluation with positron emission tomography and the risk of cardiovascular events in patients with coronary artery disease: a systematic review of prognostic studies

Aims: To evaluate the prognostic value of quantitative myocardial perfusion imaging with positron emission tomography (PET) for adverse cardiovascular outcomes in patients with known or suspected coronary artery disease (CAD). Methods and results: A search in MEDLINE and Embase was conducted for studies that evaluated (i) myocardial perfusion in absolute terms with PET, (ii) prognostic value for the development of major adverse cardiovascular events (MACE), cardiac death, and/or all-cause mortality, and (iii) patients with known or suspected CAD. Studies were divided according to the radiotracer utilized and their included population (patients with and without previous infarction). Comprehensive description and a selected instance of pooling were performed. Eight studies (n = 6804) were analysed and documented clear variability in population, quantitative PET variables operationalization [stress myocardial blood flow (sMBF) and flow reserve (MFR)], statistical covariate structure, follow-up, and radiotracer utilized. MFR was independently associated with MACE in eight studies [range of adjusted hazard ratios (HRs): 1.19-2.93]. The pooling instance demonstrated that MFR significantly associates with the development of MACEs (HR: 1.92 [1.29, 2.84]; P = 0.001). sMBF was only associated with MACE in two studies that evaluated it, and only one study documented sMBF as a better predictor than MFR. Conclusion: This systematic review demonstrates the prognostic value of quantitative myocardial perfusion evaluated with PET, in the form of MFR and sMBF, for the development of major adverse cardiovascular outcomes in populations with known or suspected CAD. In the qualitative comparison, MFR seems to outperform sMBF as an independent prognostic factor. Evidence is still lacking for assessing quantitative PET for the occurrence of cardiac death and all-cause mortality. There is clear heterogeneity in predictor operationalization and study performances.