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Quantitative Analysis of Residual COVID-19 Lung CT Features: Consistency among Two Commercial Software.
Granata, Vincenza; Ianniello, Stefania; Fusco, Roberta; Urraro, Fabrizio; Pupo, Davide; Magliocchetti, Simona; Albarello, Fabrizio; Campioni, Paolo; Cristofaro, Massimo; Di Stefano, Federica; Fusco, Nicoletta; Petrone, Ada; Schininà, Vincenzo; Villanacci, Alberta; Grassi, Francesca; Grassi, Roberta; Grassi, Roberto.
  • Granata V; Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy.
  • Ianniello S; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Fusco R; Medical Oncology Division, Igea SpA, 80013 Naples, Italy.
  • Urraro F; Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80125 Naples, Italy.
  • Pupo D; Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80125 Naples, Italy.
  • Magliocchetti S; Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80125 Naples, Italy.
  • Albarello F; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Campioni P; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Cristofaro M; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Di Stefano F; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Fusco N; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Petrone A; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Schininà V; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Villanacci A; Radiology Unit, National Institute for Infectious Diseases Lazzaro Spallanzani IRCCS, 00149 Rome, Italy.
  • Grassi F; Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80125 Naples, Italy.
  • Grassi R; Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80125 Naples, Italy.
  • Grassi R; Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy.
J Pers Med ; 11(11)2021 Oct 28.
Article in English | MEDLINE | ID: covidwho-1488657
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 ASG-340 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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Prognostic study / Qualitative research / Randomized controlled trials Topics: Long Covid Language: English Year: 2021 Document Type: Article Affiliation country: Jpm11111103

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Prognostic study / Qualitative research / Randomized controlled trials Topics: Long Covid Language: English Year: 2021 Document Type: Article Affiliation country: Jpm11111103