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Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients
PURPOSE: The capability of lung ultrasound (LUS) to distinguish the different pulmonary patterns of COVID-19 and quantify the disease burden compared to chest CT is still unclear. METHODS: PCR-confirmed COVID-19 patients who underwent both LUS and chest CT at the Emergency Department were retrospect...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7948674/ https://www.ncbi.nlm.nih.gov/pubmed/33743491 http://dx.doi.org/10.1016/j.ejrad.2021.109650 |
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author | Rizzetto, Francesco Perillo, Noemi Artioli, Diana Travaglini, Francesca Cuccia, Alessandra Zannoni, Stefania Tombini, Valeria Di Domenico, Sandro Luigi Albertini, Valentina Bergamaschi, Marta Cazzaniga, Michela De Mattia, Cristina Torresin, Alberto Vanzulli, Angelo |
author_facet | Rizzetto, Francesco Perillo, Noemi Artioli, Diana Travaglini, Francesca Cuccia, Alessandra Zannoni, Stefania Tombini, Valeria Di Domenico, Sandro Luigi Albertini, Valentina Bergamaschi, Marta Cazzaniga, Michela De Mattia, Cristina Torresin, Alberto Vanzulli, Angelo |
author_sort | Rizzetto, Francesco |
collection | PubMed |
description | PURPOSE: The capability of lung ultrasound (LUS) to distinguish the different pulmonary patterns of COVID-19 and quantify the disease burden compared to chest CT is still unclear. METHODS: PCR-confirmed COVID-19 patients who underwent both LUS and chest CT at the Emergency Department were retrospectively analysed. In both modalities, twelve peripheral lung zones were identified and given a Severity Score basing on main lesion pattern. On CT scans the well-aerated lung volume (%WALV) was visually estimated. Per-patient and per-zone assessments of LUS classification performance taking CT findings as reference were performed, further revisioning the images in case of discordant results. Correlations between number of disease-positive lung zones, Severity Score and %WALV on both LUS and CT were assessed. The area under receiver operating characteristic curve (AUC) was calculated to determine LUS performance in detecting %WALV ≤ 70 %. RESULTS: The study included 219 COVID-19 patients with abnormal chest CT. LUS correctly identified as positive 217 (99 %) patients, but per-zone analysis showed sensitivity = 75 % and specificity = 66 %. The revision of the 121 (55 %) cases with positive LUS and negative CT revealed COVID-compatible lesions in 42 (38 %) CT scans. Number of disease-positive zones, Severity Score and %WALV between LUS and CT showed moderate correlations. The AUCs for LUS Severity Score and number of LUS-positive zones did not differ in detecting %WALV ≤ 70 %. CONCLUSION: LUS in COVID-19 is valuable for case identification but shows only moderate correlation with CT findings as for lesion patterns and severity quantification. The number of disease-positive lung zones in LUS alone was sufficient to discriminate relevant disease burden. |
format | Online Article Text |
id | pubmed-7948674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79486742021-03-11 Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients Rizzetto, Francesco Perillo, Noemi Artioli, Diana Travaglini, Francesca Cuccia, Alessandra Zannoni, Stefania Tombini, Valeria Di Domenico, Sandro Luigi Albertini, Valentina Bergamaschi, Marta Cazzaniga, Michela De Mattia, Cristina Torresin, Alberto Vanzulli, Angelo Eur J Radiol Research Article PURPOSE: The capability of lung ultrasound (LUS) to distinguish the different pulmonary patterns of COVID-19 and quantify the disease burden compared to chest CT is still unclear. METHODS: PCR-confirmed COVID-19 patients who underwent both LUS and chest CT at the Emergency Department were retrospectively analysed. In both modalities, twelve peripheral lung zones were identified and given a Severity Score basing on main lesion pattern. On CT scans the well-aerated lung volume (%WALV) was visually estimated. Per-patient and per-zone assessments of LUS classification performance taking CT findings as reference were performed, further revisioning the images in case of discordant results. Correlations between number of disease-positive lung zones, Severity Score and %WALV on both LUS and CT were assessed. The area under receiver operating characteristic curve (AUC) was calculated to determine LUS performance in detecting %WALV ≤ 70 %. RESULTS: The study included 219 COVID-19 patients with abnormal chest CT. LUS correctly identified as positive 217 (99 %) patients, but per-zone analysis showed sensitivity = 75 % and specificity = 66 %. The revision of the 121 (55 %) cases with positive LUS and negative CT revealed COVID-compatible lesions in 42 (38 %) CT scans. Number of disease-positive zones, Severity Score and %WALV between LUS and CT showed moderate correlations. The AUCs for LUS Severity Score and number of LUS-positive zones did not differ in detecting %WALV ≤ 70 %. CONCLUSION: LUS in COVID-19 is valuable for case identification but shows only moderate correlation with CT findings as for lesion patterns and severity quantification. The number of disease-positive lung zones in LUS alone was sufficient to discriminate relevant disease burden. Elsevier B.V. 2021-05 2021-03-11 /pmc/articles/PMC7948674/ /pubmed/33743491 http://dx.doi.org/10.1016/j.ejrad.2021.109650 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Research Article Rizzetto, Francesco Perillo, Noemi Artioli, Diana Travaglini, Francesca Cuccia, Alessandra Zannoni, Stefania Tombini, Valeria Di Domenico, Sandro Luigi Albertini, Valentina Bergamaschi, Marta Cazzaniga, Michela De Mattia, Cristina Torresin, Alberto Vanzulli, Angelo Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients |
title | Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients |
title_full | Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients |
title_fullStr | Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients |
title_full_unstemmed | Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients |
title_short | Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients |
title_sort | correlation between lung ultrasound and chest ct patterns with estimation of pulmonary burden in covid-19 patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7948674/ https://www.ncbi.nlm.nih.gov/pubmed/33743491 http://dx.doi.org/10.1016/j.ejrad.2021.109650 |
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