Metabolic characterization of structural lung changes in patients with findings suggestive of incidental COVID-19 pneumonia on 18 F-FDG PET/CT. Pathophysiological insights from multimodal images obtained during the pandemic.

Purpose: To evaluate the metabolic uptake of different tomographic signs observed in patients with incidental structural findings suggestive of COVID-19 pneumonia through ¹⁸ F-FDG PET/CT.
Materials and Methods: We retrospectively analyzed 596 PET/CT studies performed from February 21, 2020 to April 17, 2020. After excluding 37 scans (non- ¹⁸ F-FDG PET tracers and brain studies), we analyzed the metabolic activity of several structural changes integrated in the CO-RADS score using the SUVmax of multimodal studies with ¹⁸ F-FDG.
Results: Forty-three patients with ¹⁸ F-FDG PET/CT findings suggestive of COVID-19 pneumonia were included (mean age: 68±12.3 years, 22 male). SUVmax values were higher in patients with CO-RADS categories 5-6 than in those with lower CO-RADS categories (6.1±3.0 vs. 3.6±2.1, p=0.004). In patients with CO-RADS 5-6, ground-glass opacities, bilaterality and consolidations exhibited higher SUVmax values (p-values of 0.01, 0.02 and 0.01, respectively). Patchy distribution and crazy paving pattern were also associated with higher SUVmax (p-values of 0.002 and 0.01). After multivariate analysis, SUVmax was significantly associated with a positive structural diagnosis of COVID-19 pneumonia (odds ratio=0.63, 95% confidence interval=0.41-0.90; p=0.02). The ROC curve of the regression model intended to confirm or rule out the structural diagnosis of COVID-19 pneumonia showed an AUC of 0.77 (standard error=0.072, p=0.003).
Conclusions: In those patients referred for standard oncologic and non-oncologic indications (43/559; 7.7%) during pandemic, imaging with ¹⁸ F-FDG PET/CT is a useful tool during incidental detection of COVID-19 pneumonia. Several CT findings characteristic of COVID-19 pneumonia, specifically those included in diagnostic CO-RADS scores (5-6), were associated with higher SUVmax values.
(Copyright © 2023 Sociedad Española de Medicina Nuclear e Imagen Molecular. Published by Elsevier España, S.L.U. All rights reserved.)