Diagnostic performance of F18 FDG PET in cardiac sarcoidosis: Are we getting closer to the truth?

Abstract

Sarcoidosis is a multi-systemic disease traditionally characterized by the presence of non-caseating granulomas. Cardiac sarcoidosis (CS) affects at least 25% of patients with systemic sarcoidosis and is associated with considerable morbidity and mortality. Advanced cardiovascular imaging techniques including Fluorine-18 fluorodeoxyglucose positron emission tomography (FDG PET) and cardiac magnetic resonance imaging have become pivotal in the diagnosis, management, and prognostication of patients with CS. However, studies utilizing advanced imaging to improve the identification and management of CS are limited by a multitude of factors, particularly the small sample sizes and observational nature. Given the fact that larger-scale studies are unlikely to be conducted for this less common disease, meta-analyses have been published to address the diagnostic performance of FDG PET for the detection of CS. Since the first meta-analysis by Youssef et al. published in 2012, which included seven studies, more single-center observational studies have been added to the literature, prompting an updated systematic review and meta-analysis. In this issue of the Journal of Nuclear Cardiology, Kim and colleagues are commended on performing an extensive and comprehensive literature search and metaanalysis with a clear and specific question, and rigorous inclusion and exclusion criteria for studies, and ultimately included 17 FDG PET studies involving 891 patients in their meta-analysis. Their main findings include a pooled sensitivity of FDG PET for the diagnosis of CS of 0.84 (95% CI 0.71 to 0.91) and a pooled specificity of 0.83 (95% CI 0.74 to 0.89) with significant heterogeneity stemming mainly from concomitant assessment of myocardial perfusion (MPI) at the time of FDG PET in 7 out of the 17 studies. Pooled sensitivity and specificity were slightly higher in studies that assessed MPI in addition to FDG but did not reach statistical significance. However, diagnostic odds ratio for CS using FDG PET was improved when assessment of myocardial perfusion was performed [25.7 (14.6 to 45.4) with MPI vs 14.2 (5 to 44.3) without MPI]. Meta-analyses in the area of imaging in CS diagnosis are challenging for many reasons. Despite the well-conducted meta-analysis by Kim et al. a major fundamental issue remains: there is no gold standard test for CS for a robust comparative assessment of diagnostic performance. Most studies included in this meta-analysis used the 1993 Japanese Ministry of Health and Welfare (JMHW) clinical diagnostic pathway as the reference standard. A severe limitation of this approach is that the JMHW clinical diagnostic pathway, and other diagnostic criteria with a clinical pathway, rely heavily on expert consensus opinion, and less so on supporting data, and have not been prospectively validated. Prior discussions have suggested that the lower specificity of FDG PET in some studies may reflect the fact that FDG PET is more sensitive than the JMHW criteria, and that the lower sensitivity of FDG PET in some studies may reflect the reduced specificity of the JMHW criteria. Thus, it is unclear, even with a rigorously conducted meta-analysis, that we are getting closer to the true diagnostic accuracy of FDG PET for CS. Moreover, the JMHW criteria did not take into account imaging findings from FDG PET or cardiac magnetic resonance imaging until their most recent update in 2017, Reprint requests: Panithaya Chareonthaitawee, MD, Department of Cardiovascular Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905; [email protected] J Nucl Cardiol 2020;27:2116–7. 1071-3581/$34.00 Copyright 2019 American Society of Nuclear Cardiology.