1 Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy; firstname.lastname@example.org
2 Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy; email@example.com (S.I.); Fabrizio.firstname.lastname@example.org (F.A.); email@example.com (P.C.); firstname.lastname@example.org (M.C.); email@example.com (F.D.S.); firstname.lastname@example.org (N.F.); email@example.com (A.P.); firstname.lastname@example.org (V.S.); email@example.com (A.V.)
3 Medical Oncology Division, Igea SpA, 80013 Naples, Italy
4 Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80125 Naples, Italy; firstname.lastname@example.org (F.U.); email@example.com (D.P.); firstname.lastname@example.org (S.M.); email@example.com (F.G.); firstname.lastname@example.org (R.G.); email@example.com (R.G.)
5 Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy * Correspondence: firstname.lastname@example.org Abstract: Objective: To investigate two commercial software and their efficacy in the assessment of chest CT sequelae in patients affected by COVID-19 pneumonia, comparing the consistency of tools.
Materials and Methods: Included in the study group were 120 COVID-19 patients (56 women and 104 men; 61 years of median age; range: 21–93 years) who underwent chest CT examinations at discharge between 5 March 2020 and 15 March 2021 and again at a follow-up time (3 months; range 30–237 days). A qualitative assessment by expert radiologists in the infectious disease field (experience of at least 5 years) was performed, and a quantitative evaluation using thoracic VCAR software (GE Healthcare, Chicago, Illinois, United States) and a pneumonia module of ANKE ASG340 CT workstation (HTS Med & Anke, Naples, Italy) was performed.
The qualitative evaluation included the presence of ground glass opacities (GGOs) consolidation, interlobular septal thickening, fibrotic-like changes (reticular pattern and/or honeycombing), bronchiectasis, air bronchogram, bronchial wall thickening, pulmonary nodules surrounded by GGOs, pleural and pericardial effusion, lymphadenopathy, and emphysema.
A quantitative evaluation included the measurements of GGOs, consolidations, emphysema, residual healthy parenchyma, and total lung volumes for the right and left lung. A chi-square test and non-parametric test were utilized to verify the differences between groups.
Correlation coefficients were used to analyze the correlation and variability among quantitative measurements by different computer tools. A receiver operating characteristic (ROC) analysis was performed.
Results: The correlation coefficients showed great variability among the quantitative measurements by different tools when calculated on baseline CT scans and considering all patients. Instead, a good correlation (≥0.6) was obtained for the quantitative GGO, as well as the consolidation volumes obtained by two tools when calculated on baseline CT scans, considering the control group.
An excellent correlation (≥0.75) was obtained for the quantitative residual healthy lung parenchyma volume, GGO, consolidation volumes obtained by two tools when calculated on follow-up CT scans, and for residual healthy lung parenchyma and GGO quantification when the percentage change of these volumes were calculated between a baseline and follow-up scan.
The highest value of accuracy to identify patients with RT-PCR positive compared to the control group was obtained by a GGO total volume quantification by thoracic VCAR (accuracy = 0.75). Conclusions: Computer aided quantification could be an easy and feasible way to assess chest CT sequelae due to COVID-19 pneumonia; however, a great variability among measurements provided by different tools should be considered.
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