18F-FDG PET/CT for invasive fungal infection in immunocompromised patients.

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18F-FDG PET/CT for invasive fungal infection in immunocompromised patients.

QJM. 2018 Jun 18;:

Authors: Leroy-Freschini B, Treglia G, Argemi X, Bund C, Kessler R, Herbrecht R, Imperiale A

Background: Opportunistic invasive fungal infections (IFIs) comprise a heterogeneous spectrum of pathogens, whose early diagnosis remains challenging. Candida spp. and Aspergillus spp, the most frequent pathogens in immunocompromised patients, frequently affect lungs, liver, bone and skin.
Aim: To evaluate the impact of 18F-FDG PET/CT in the management of immunocompromised patients with IFI.
Design: A single-center retrospective study included 51 immunocompromised patients with IFI diagnosis undergoing 83 18F-FDG PET/CTs.
Methods: Twenty-nine 18F-FDG PET/CTs were performed for primary work-up in 29 treatment-naïve patients. Fifty-four PET/CTs were performed during follow-up to confirm IFI suspicion in 22 patients who had antifungal drug therapy before PET/CT. When available, histological and/or microbiological criteria were used to assess IFI diagnosis.
Results: Aspergillus spp. and Candida spp. were the most frequent microorganisms responsible for IFI in our population. 18F-FDG PET/CT sensitivity, specificity, positive and negative predictive values, and global accuracy were 93%, 81%, 95%, 72%, and 90%, respectively. 18F-FDG PET/CT influenced the diagnostic work-up at primary staging in 16/29 patients (55%) by assessing the extent of infection and targeting the diagnostic procedure. 18F-FDG PET/CT results during treatment induced antifungal drugs dosage increase and/or new drugs addition in 8/54 cases (15%) and contributed to the reduction of antifungal drugs dosage or treatment withdraws in 17 cases (31%).
Conclusions: We recommend the utilization of 18F-FDG PET/CT to improve the primary staging work-up of immunocompromised patients with IFI and to assess treatment effectiveness or disease relapse. Both 18F-FDG PET/CT and conventional imaging should be integrated into a well-defined imaging diagnostic algorithm considering the clinical context and both strengths and limitations of each diagnostic modality.

PMID: 29917146 [PubMed – as supplied by publisher]

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