Comparison of morphological and metabolic imaging of COVID-19 pneumonia in a prospective clinical study

Abstract Purpose To evaluate morphological and metabolic findings in novel coronavirus 19 disease (COVID-19) with 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT). Materials and methods This was a single-centre, prospective clinical trial enrolling consecutive patients who required hospitalisation due to COVID-19 infection. All patients underwent routine chest CT on admission and a follow-up FDG-PET/CT scan on the 7th day of hospitalisation. COVID-19 related lung alterations, such as ground-glass opacity (GGO) and consolidation were quantified with semi-automated software using deep learning (DL) and metabolic parameters were expressed with PET-based metabolic inflammatory volume (MIV) and total inflammatory activity (TIA). The primary outcome was defined as increased inflammatory state on PET scan, with the median MIV and TIA being the cut-off value. Results Forty-four patients were enrolled (25 men; median [IQR] age: 52 [49-61] years). The median [IQR] MIV and TIA were 209 [73-517] ml and 499 [155-1429], respectively. The percentage of GGO and total lung CT severity scores at baseline CT showed weak correlation with MIV and TIA (r=0.33-0.39; p=0.13-0.34). At follow-up, we detected a strong correlation between all chest CT abnormalities and MIV and TIA (r=0.77; p<0.01 and r=0.75; p<0.01, respectively), as well as between CT severity scores and MIV and TIA (r=0.77; p<0.01 and r=0.75; p<0.01, respectively). Logistic regression analysis adjusted for demographics revealed that the extent of chest CT abnormalities on follow-up was an independent predictor of high inflammatory state (OR [by 1% change] =1.11 for both MIV and TIA; p=0.018 for MIV and p=0.021 for TIA). Also, a model encompassing CT abnormalities, interleukin-6 and lactate-dehydrogenase levels at follow-up showed high predictive values for inflammatory state, with an area-under-the-curve (AUC) on receiver operating characteristics analysis of 0.88. Conclusion The metabolic inflammatory volume and activity of COVID-19-pneumonia showed good correlation with morphological changes on CT imaging performed 7 days after patient hospitalization. Combining CT and laboratory data (lactate dehydrogenase and interleukin-6 levels), FDG-PET-based lung inflammatory status could effectively be predicted. Trial registration: www.clinicaltrials.gov (ID: NCT05009563). Registered 17 August 2021 (retrospectively registered), first patient enrolled: 13 January 2021..

Medienart:	Preprint

Erscheinungsjahr:	2022
Erschienen:	2022

Enthalten in:	ResearchSquare.com - (2022) vom: 28. Nov. Zur Gesamtaufnahme - year:2022

Sprache:	Englisch

Beteiligte Personen:

Czibor, Sándor [VerfasserIn] Száraz, Lili [VerfasserIn] Simon, Judit [VerfasserIn] Dombai, Brigitta [VerfasserIn] Gyebnár, János [VerfasserIn] Szántó, Péter [VerfasserIn] Magyar, Máté [VerfasserIn] Dey, Damini [VerfasserIn] Szakács, László [VerfasserIn] Zsarnóczay, Emese [VerfasserIn] Müller, Veronika [VerfasserIn] Merkely, Béla [VerfasserIn] Györke, Tamás [VerfasserIn] Maurovich-Horvat, Pál [VerfasserIn]

Links:	Volltext [kostenfrei]

Themen:	570 Biology

doi:	10.21203/rs.3.rs-2209230/v1

funding:
Förderinstitution / Projekttitel:

PPN (Katalog-ID):	XRA037776096