Cargando…

Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials

PURPOSE: To compare the prognostic value and reproducibility of visual versus AI-assisted analysis of lung involvement on submillisievert low-dose chest CT in COVID-19 patients. MATERIALS AND METHODS: This was a HIPAA-compliant, institutional review board-approved retrospective study. From March 15...

Descripción completa

Detalles Bibliográficos
Autores principales: Gieraerts, Christopher, Dangis, Anthony, Janssen, Lode, Demeyere, Annick, De Bruecker, Yves, De Brucker, Nele, van Den Bergh, Annelies, Lauwerier, Tine, Heremans, André, Frans, Eric, Laurent, Michaël, Ector, Bavo, Roosen, John, Smismans, Annick, Frans, Johan, Gillis, Marc, Symons, Rolf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Radiological Society of North America 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586438/
https://www.ncbi.nlm.nih.gov/pubmed/33778634
http://dx.doi.org/10.1148/ryct.2020200441
_version_ 1783599997554524160
author Gieraerts, Christopher
Dangis, Anthony
Janssen, Lode
Demeyere, Annick
De Bruecker, Yves
De Brucker, Nele
van Den Bergh, Annelies
Lauwerier, Tine
Heremans, André
Frans, Eric
Laurent, Michaël
Ector, Bavo
Roosen, John
Smismans, Annick
Frans, Johan
Gillis, Marc
Symons, Rolf
author_facet Gieraerts, Christopher
Dangis, Anthony
Janssen, Lode
Demeyere, Annick
De Bruecker, Yves
De Brucker, Nele
van Den Bergh, Annelies
Lauwerier, Tine
Heremans, André
Frans, Eric
Laurent, Michaël
Ector, Bavo
Roosen, John
Smismans, Annick
Frans, Johan
Gillis, Marc
Symons, Rolf
author_sort Gieraerts, Christopher
collection PubMed
description PURPOSE: To compare the prognostic value and reproducibility of visual versus AI-assisted analysis of lung involvement on submillisievert low-dose chest CT in COVID-19 patients. MATERIALS AND METHODS: This was a HIPAA-compliant, institutional review board-approved retrospective study. From March 15 to June 1, 2020, 250 RT-PCR confirmed COVID-19 patients were studied with low-dose chest CT at admission. Visual and AI-assisted analysis of lung involvement was performed by using a semi-quantitative CT score and a quantitative percentage of lung involvement. Adverse outcome was defined as intensive care unit (ICU) admission or death. Cox regression analysis, Kaplan-Meier curves, and cross-validated receiver operating characteristic curve with area under the curve (AUROC) analysis was performed to compare model performance. Intraclass correlation coefficients (ICCs) and Bland- Altman analysis was used to assess intra- and interreader reproducibility. RESULTS: Adverse outcome occurred in 39 patients (11 deaths, 28 ICU admissions). AUC values from AI-assisted analysis were significantly higher than those from visual analysis for both semi-quantitative CT scores and percentages of lung involvement (all P<0.001). Intrareader and interreader agreement rates were significantly higher for AI-assisted analysis than visual analysis (all ICC ≥0.960 versus ≥0.885). AI-assisted variability for quantitative percentage of lung involvement was 17.2% (coefficient of variation) versus 34.7% for visual analysis. The sample size to detect a 5% change in lung involvement with 90% power and an α error of 0.05 was 250 patients with AI-assisted analysis and 1014 patients with visual analysis. CONCLUSION: AI-assisted analysis of lung involvement on submillisievert low-dose chest CT outperformed conventional visual analysis in predicting outcome in COVID-19 patients while reducing CT variability. Lung involvement on chest CT could be used as a reliable metric in future clinical trials.
format Online
Article
Text
id pubmed-7586438
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Radiological Society of North America
record_format MEDLINE/PubMed
spelling pubmed-75864382020-11-06 Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials Gieraerts, Christopher Dangis, Anthony Janssen, Lode Demeyere, Annick De Bruecker, Yves De Brucker, Nele van Den Bergh, Annelies Lauwerier, Tine Heremans, André Frans, Eric Laurent, Michaël Ector, Bavo Roosen, John Smismans, Annick Frans, Johan Gillis, Marc Symons, Rolf Radiol Cardiothorac Imaging Original Research PURPOSE: To compare the prognostic value and reproducibility of visual versus AI-assisted analysis of lung involvement on submillisievert low-dose chest CT in COVID-19 patients. MATERIALS AND METHODS: This was a HIPAA-compliant, institutional review board-approved retrospective study. From March 15 to June 1, 2020, 250 RT-PCR confirmed COVID-19 patients were studied with low-dose chest CT at admission. Visual and AI-assisted analysis of lung involvement was performed by using a semi-quantitative CT score and a quantitative percentage of lung involvement. Adverse outcome was defined as intensive care unit (ICU) admission or death. Cox regression analysis, Kaplan-Meier curves, and cross-validated receiver operating characteristic curve with area under the curve (AUROC) analysis was performed to compare model performance. Intraclass correlation coefficients (ICCs) and Bland- Altman analysis was used to assess intra- and interreader reproducibility. RESULTS: Adverse outcome occurred in 39 patients (11 deaths, 28 ICU admissions). AUC values from AI-assisted analysis were significantly higher than those from visual analysis for both semi-quantitative CT scores and percentages of lung involvement (all P<0.001). Intrareader and interreader agreement rates were significantly higher for AI-assisted analysis than visual analysis (all ICC ≥0.960 versus ≥0.885). AI-assisted variability for quantitative percentage of lung involvement was 17.2% (coefficient of variation) versus 34.7% for visual analysis. The sample size to detect a 5% change in lung involvement with 90% power and an α error of 0.05 was 250 patients with AI-assisted analysis and 1014 patients with visual analysis. CONCLUSION: AI-assisted analysis of lung involvement on submillisievert low-dose chest CT outperformed conventional visual analysis in predicting outcome in COVID-19 patients while reducing CT variability. Lung involvement on chest CT could be used as a reliable metric in future clinical trials. Radiological Society of North America 2020-10-22 /pmc/articles/PMC7586438/ /pubmed/33778634 http://dx.doi.org/10.1148/ryct.2020200441 Text en 2020 by the Radiological Society of North America, Inc. This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.
spellingShingle Original Research
Gieraerts, Christopher
Dangis, Anthony
Janssen, Lode
Demeyere, Annick
De Bruecker, Yves
De Brucker, Nele
van Den Bergh, Annelies
Lauwerier, Tine
Heremans, André
Frans, Eric
Laurent, Michaël
Ector, Bavo
Roosen, John
Smismans, Annick
Frans, Johan
Gillis, Marc
Symons, Rolf
Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials
title Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials
title_full Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials
title_fullStr Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials
title_full_unstemmed Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials
title_short Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials
title_sort prognostic value and reproducibility of ai-assisted analysis of lung involvement in covid-19 on low-dose submillisievert chest ct: sample size implications for clinical trials
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586438/
https://www.ncbi.nlm.nih.gov/pubmed/33778634
http://dx.doi.org/10.1148/ryct.2020200441
work_keys_str_mv AT gieraertschristopher prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT dangisanthony prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT janssenlode prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT demeyereannick prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT debrueckeryves prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT debruckernele prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT vandenberghannelies prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT lauweriertine prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT heremansandre prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT franseric prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT laurentmichael prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT ectorbavo prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT roosenjohn prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT smismansannick prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT fransjohan prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT gillismarc prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials
AT symonsrolf prognosticvalueandreproducibilityofaiassistedanalysisoflunginvolvementincovid19onlowdosesubmillisievertchestctsamplesizeimplicationsforclinicaltrials