Why the study?
Infection of cardiac implantable electronic devices is a significant public health problem, requiring evaluation of diagnostic tools.
Does 18F-FDG PET/CT accurately diagnose infection in patients suspected of Cardiac Implantable Electronic Devices' Infection?
Does 18F-FDG PET/CT accurately diagnose infection in patients suspected of Cardiac Implantable Electronic Devices' Infection?
18F-FDG PET/CT demonstrates high sensitivity and diagnostic accuracy for evaluating suspected cardiac implantable electronic device infections.
Background: Infection of Cardiac Implantable Electronic Devices (CIEDI) is a real public health problem. The main aim of this study was to determine the diagnostic performance of 18F-FDG PET/CT in the diagnosis of CIEDI. Methods: A total of 48 patients, who performed 18F-FDG PET/CT for the clinical suspicion of CIEDI were retrospectively analyzed; all patients were provided with a model with procedural recommendations before the exam. Sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy (DA) of 18F-FDG PET/CT were calculated; the reproducibility of qualitative analysis was assessed with Cohen’s κ test. The semi-quantitative parameters (SUVmax, SQR and TBR) were evaluated in CIEDI+ and CIEDI− patients using the Student’ t-test; ROC curves were elaborated to detect cut-off values. The trend of image quality with regards to procedural recommendation adherence was evaluated. Results: Se, Sp, PPV, NPV and DA were respectively 96.2%, 81.8%, 86.2%, 94.7% and 89.6%. The reproducibility of qualitative analysis was excellent (K = 0.89). Semiquantitative parameters resulted statistically different in CIEDI+ and CIEDI− patients. Cut-off values were SUVmax = 2.625, SQR = 3.766 and TBR = 1.29. Trend curves showed increasing image quality due to adherence to procedural recommendations. Conclusions: 18F-FDG-PET/CT is a valid tool in the management of patients suspected of CIEDI and adherence to procedural recommendations improves its image quality.
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Pisani et al. (2024) studied this question.
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