Asymptomatic SARS-CoV-2 infection: Incidental findings on FDG PET/CT

Ricardo Bello Martinez, Munir Ghesani, Nasrin Ghesani, Somali Gavane

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Rationale and Objectives: Identify the incidental findings of Covid-19 pneumonitis on 18F-FDG PET/CT scan in asymptomatic oncologic patients. The goal was to detect clinically unsuspected Covid-19 infections to prevent community spread. Materials and Methods: Retrospective analysis was conducted to recognize the pattern of metabolic and radiographic alterations on 18F-FDG PET/CT scans in Covid-19 patients. 492 18F-FDG PET/CT scans were reviewed for pulmonary and systemic abnormalities. Results: 18F-FDG PET/CT demonstrated new lung infiltrates in 29 asymptomatic patients. 13/29 patients had Covid-19 infection confirmed by nasopharyngeal nucleic acid PCR test. The most common lung abnormality was pure ground-glass opacity (GGO) (90%) in peripheral distribution (100%), involving 1 lobe in four patients (30.8%), 2–3 lobes in four patients, and 4-5 lobes in five patients (38.4%). Mean SUVmax was 4.7 (range 1.3–13.1). Ten patients developed symptoms, mainly fever, fatigue, and dry cough, within 6.4 ± 7.8 days (range 1–24). Of the available laboratory data of 12 patients, eight developed lymphopenia, and five patients had neutrophilia. Five patients required hospitalization, and two died of complications. Conclusion: For a given geographic region in the later stage of a pandemic, such as Covid-19, community spread of the disease is common. Therefore, it is not surprising to find it in asymptomatic being imaged for other indications. Recognition of its manifestation and effectively mounting mitigation protocols is essential to further reduce SARS-CoV-2 spread, especially to susceptible groups, predominantly the elderly and people with comorbidities.

Original languageEnglish (US)
Pages (from-to)179-185
Number of pages7
JournalJournal of Medical Imaging and Radiation Sciences
Volume52
Issue number2
DOIs
StatePublished - Jun 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

Keywords

  • Covid-19
  • PET/CT
  • SARS-CoV-2
  • Severe acute respiratory syndrome coronavirus 2

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