Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis
- PMID: 33778660
- PMCID: PMC7808356
- DOI: 10.1148/ryct.2021200510
Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis
Abstract
Purpose: To determine the diagnostic performance of the COVID-19 Reporting and Data System (CO-RADS) and the Radiological Society of North America (RSNA) categorizations in patients with clinically suspected coronavirus disease 2019 (COVID-19) infection.
Materials and methods: In this meta-analysis, studies from 2020, up to August 24, 2020 were assessed for inclusion criteria of studies that used CO-RADS or the RSNA categories for scoring chest CT in patients with suspected COVID-19. A total of 186 studies were identified. After review of abstracts and text, a total of nine studies were included in this study. Patient information (n¸ age, sex), CO-RADS and RSNA scoring categories, and other study characteristics were extracted. Study quality was assessed with the QUADAS-2 tool. Meta-analysis was performed with a random effects model.
Results: Nine studies (3283 patients) were included. Overall study quality was good, except for risk of non-performance of repeated reverse transcriptase polymerase chain reaction (RT-PCR) after negative initial RT-PCR and persistent clinical suspicion in four studies. Pooled COVID-19 frequencies in CO-RADS categories were: 1, 8.8%; 2, 11.1%; 3, 24.6%; 4, 61.9%; and 5, 89.6%. Pooled COVID-19 frequencies in RSNA classification categories were: negative 14.4%; atypical, 5.7%; indeterminate, 44.9%; and typical, 92.5%. Pooled pairs of sensitivity and specificity using CO-RADS thresholds were the following: at least 3, 92.5% (95% CI: 87.1, 95.7) and 69.2% (95%: CI: 60.8, 76.4); at least 4, 85.8% (95% CI: 78.7, 90.9) and 84.6% (95% CI: 79.5, 88.5); and 5, 70.4% (95% CI: 60.2, 78.9) and 93.1% (95% CI: 87.7, 96.2). Pooled pairs of sensitivity and specificity using RSNA classification thresholds for indeterminate were 90.2% (95% CI: 87.5, 92.3) and 75.1% (95% CI: 68.9, 80.4) and for typical were 65.2% (95% CI: 37.0, 85.7) and 94.9% (95% CI: 86.4, 98.2).
Conclusion: COVID-19 infection frequency was higher in patients categorized with higher CORADS and RSNA classification categories.
2021 by the Radiological Society of North America, Inc.
Figures
Similar articles
-
Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia.Insights Imaging. 2021 Apr 28;12(1):55. doi: 10.1186/s13244-021-00998-4. Insights Imaging. 2021. PMID: 33913066 Free PMC article.
-
Radiological Society of North America (RSNA) Expert Consensus Statement Related to Chest CT Findings in COVID-19 Versus CO-RADS: Comparison of Reporting System Performance Among Chest Radiologists and End-User Preference.Can Assoc Radiol J. 2021 Nov;72(4):806-813. doi: 10.1177/0846537120968919. Epub 2020 Nov 3. Can Assoc Radiol J. 2021. PMID: 33138634
-
Applicability of CO-RADS in an Anonymized Cohort Including Early and Advanced Stages of COVID-19 in Comparison to the Recommendations of the German Radiological Society and Radiological Society of North America.Rofo. 2022 Aug;194(8):862-872. doi: 10.1055/a-1740-4310. Epub 2022 Feb 24. Rofo. 2022. PMID: 35211925 English.
-
Thoracic imaging tests for the diagnosis of COVID-19.Cochrane Database Syst Rev. 2020 Sep 30;9:CD013639. doi: 10.1002/14651858.CD013639.pub2. Cochrane Database Syst Rev. 2020. Update in: Cochrane Database Syst Rev. 2020 Nov 26;11:CD013639. doi: 10.1002/14651858.CD013639.pub3. PMID: 32997361 Updated.
-
Thoracic imaging tests for the diagnosis of COVID-19.Cochrane Database Syst Rev. 2020 Nov 26;11:CD013639. doi: 10.1002/14651858.CD013639.pub3. Cochrane Database Syst Rev. 2020. Update in: Cochrane Database Syst Rev. 2021 Mar 16;3:CD013639. doi: 10.1002/14651858.CD013639.pub4. PMID: 33242342 Updated.
Cited by
-
Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia.Insights Imaging. 2021 Apr 28;12(1):55. doi: 10.1186/s13244-021-00998-4. Insights Imaging. 2021. PMID: 33913066 Free PMC article.
-
Diagnostic value of chest computed tomography imaging for COVID-19 based on reverse transcription-polymerase chain reaction: a meta-analysis.Infect Dis Poverty. 2021 Oct 21;10(1):126. doi: 10.1186/s40249-021-00910-8. Infect Dis Poverty. 2021. PMID: 34674774 Free PMC article.
-
Doubts and concerns about COVID-19 uncertainties on imaging data, clinical score, and outcomes.BMC Pulm Med. 2023 Nov 25;23(1):472. doi: 10.1186/s12890-023-02763-3. BMC Pulm Med. 2023. PMID: 38007479 Free PMC article.
-
A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes.Methods Mol Biol. 2022;2511:395-404. doi: 10.1007/978-1-0716-2395-4_30. Methods Mol Biol. 2022. PMID: 35838977
-
The role of chest imaging in the diagnosis, management, and monitoring of coronavirus disease 2019 (COVID-19).Insights Imaging. 2021 Nov 2;12(1):155. doi: 10.1186/s13244-021-01096-1. Insights Imaging. 2021. PMID: 34727257 Free PMC article. Review.
References
-
- Johns Hopkins University School of Medicine . CORONAVIRUS RESOURCE CENTER. https://coronavirus.jhu.edu/. Updated June 13, 2020August 24, 2020.
-
- Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, Schluger NW, Volpi A, Yim JJ, Martin IBK, Anderson DJ, Kong C, Altes T, Bush A, Desai SR, Goldin J, Goo JM, Humbert M, Inoue Y, Kauczor HU, Luo F, Mazzone PJ, Prokop M, Remy-Jardin M, Richeldi L, Schaefer-Prokop CM, Tomiyama N, Wells AU, Leung AN. The Role of Chest Imaging in Patient Management During the COVID-19 Pandemic: A Multinational Consensus Statement From the Fleischner Society. Chest 2020;158(1):106-116. doi: 10.1016/j.chest.2020.04.003 - PMC - PubMed
-
- Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5 - PMC - PubMed
-
- Adams HJA, Kwee TC, Yakar D, Hope MD, Kwee RM. Systematic Review and Meta-Analysis on the Value of Chest CT in the Diagnosis of Coronavirus Disease (COVID-19): Sol Scientiae, Illustra Nos. AJR Am J Roentgenol 2020:1-9. doi: 10.2214/AJR.20.23391 - PubMed
-
- Prokop M, van Everdingen W, van Rees Vellinga T, Quarles van Ufford H, Stoger L, Beenen L, Geurts B, Gietema H, Krdzalic J, Schaefer-Prokop C, van Ginneken B, Brink M, Society C-SRWGotDR . CO-RADS: A Categorical CT Assessment Scheme for Patients Suspected of Having COVID-19-Definition and Evaluation. Radiology 2020;296(2):E97-E104. doi: 10.1148/radiol.2020201473 - PMC - PubMed
LinkOut - more resources
Full Text Sources
Other Literature Sources