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. 2021 Jan 14;3(1):e200510.
doi: 10.1148/ryct.2021200510. eCollection 2021 Feb.

Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis

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Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis

Robert M Kwee et al. Radiol Cardiothorac Imaging. .

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 ( 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.

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Figures

Flow diagram of study selection. The asterisk indicates that there were duplicate studies.
Figure 1:
Flow diagram of study selection. The asterisk indicates that there were duplicate studies.
Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) quality assessments of included studies.
Figure 2:
Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) quality assessments of included studies.

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References

    1. Johns Hopkins University School of Medicine . CORONAVIRUS RESOURCE CENTER. https://coronavirus.jhu.edu/. Updated June 13, 2020August 24, 2020.
    1. 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
    1. 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
    1. 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
    1. 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

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