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.
Radiol Cardiothorac Imaging
; 2(5): e200441, 2020 Oct.
Article
in English
| MEDLINE | ID: covidwho-1156013
ABSTRACT
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 ANDMETHODS:
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Observational study
/
Prognostic study
/
Randomized controlled trials
Language:
English
Journal:
Radiol Cardiothorac Imaging
Year:
2020
Document Type:
Article
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