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FDG PET/CT Imaging Features and Clinical Utility in COVID-19

Overview
Journal Clin Imaging
Publisher Elsevier
Specialty Radiology
Date 2021 Aug 21
PMID 34418873
Citations 6
Authors
Affiliations
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Abstract

Purpose: To determine the imaging findings and potential clinical utility of FDG PET/CT in patients with laboratory-confirmed COVID-19.

Methods: We performed a single institution retrospective review of patients diagnosed with COVID-19 using real time reverse transcription-polymerase chain reaction (RT-PCR) who underwent FDG PET/CT for routine cancer care between March 1, 2020 to April 30, 2020, during the height of the pandemic in New York City, New York, United States. PET/CT scans were retrospectively reviewed for imaging findings suspicious for COVID-19. For positive scans, PET and CT findings were recorded, including location, FDG avidity (SUV) and CT morphology. Patient demographics and COVID-19 specific clinical data were collected and analyzed with respect to PET/CT scan positivity, lung SUV, and time interval between PET/CT and RT-PCR.

Results: Thirty-one patients (21 males and 10 females, mean age 57 years ± 16) were evaluated. Thirteen of 31 patients had positive PET/CT scans, yielding a detection rate of 41.9%. Patients with positive scans had significantly higher rates of symptomatic COVID-19 infection (77% vs 28%, p = 0.01) and hospitalizations (46% vs. 0%, p = 0.002) compared to patients with negative scans. Eleven of 13 patients (84.6%) with positive scans had FDG-avid lung findings, with mean lung SUV of 5.36. Six of 13 patients (46.2%) had extrapulmonary findings of FDG-avid thoracic lymph nodes. The detection rate was significantly lower when the scan was performed before RT-PCR versus after RT-PCR (18.8% (n = 3/16) vs. 66.7% (n = 10/15), p = 0.009). Lung SUV was not associated with COVID-19 symptoms, severity, or disease course.

Conclusion: FDG PET/CT has limited sensitivity for detecting COVID-19 infection. However, a positive PET scan is associated with higher risk of symptomatic infection and hospitalizations, which may be helpful in predicting disease severity.

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