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Published on: December 19, 2020
Comparison of Chest CT Grading Systems in Coronavirus Disease 2019 (COVID-19) Pneumonia
Shohei Inui1, Ryo Kurokawa1, Yudai Nakai1
1Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan (S.I., R.K., Y.N., Y.W., W.G., O.A,); Department of Radiology, Japan Self-Defense Forces Central Hospital, 1-2-24, Ikejiri, Setagaya-ku, Tokyo, 154-0001, Japan (S.I., A.F.); Department of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, 3-18-22, Honkomagome, Bunkyo-ku, Tokyo, 113-8677, Japan (M.K.); Department of Radiology, National Center for Geriatrics and Gerontology, 7-430, Morioka-cho, Obu, Aichi, 474-8511, Japan (K.S.); Department of Radiology, National Defense Medical College, 3-2, Namiki, Tokorozawa-shi, Saitama, 359-8513, Japan (H.S.); Clinical Research Promotion Center, The University of Tokyo Hospital, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan (T.K.); Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Chongno-gu, Seoul 03080, Republic of Korea (S.H.Y.); Department of Respiratory Medicine, Japan Self-Defense Forces Central Hospital, 1-2-24, Ikejiri, Setagaya-ku, Tokyo, 154-0001, Japan (Y.U.); Department of Neurology and Neuroscience, Nagoya City University Graduate School of Medical Sciences, 1, Kawasumi, Mizuho-ku, Nagoya, 467-8601, Japan (Y.U.).
Insights
The COVID-19 Reporting and Data System (CO-RADS) and British Society of Thoracic Imaging (BSTI) statement showed superior performance in diagnosing COVID-19 using CT scans compared to other systems.
Area of Science:
- Radiology
- Infectious Diseases
- Medical Imaging
Background:
- Chest CT is crucial for diagnosing COVID-19.
- Standardized reporting systems improve diagnostic accuracy and consistency.
- Several reporting systems exist for COVID-19 CT interpretation.
Purpose of the Study:
- To compare the diagnostic performance and interobserver agreement of four COVID-19 CT reporting systems.
- Evaluate the COVID-19 Reporting and Data System (CO-RADS), COVID-19 imaging reporting and data system (COVID-RADS), RSNA expert consensus statement, and BSTI guidance statement.
Main Methods:
- Case-control study including 100 patients (50 COVID-19 positive, 50 negative).
- Eight radiologists independently scored chest CTs using each of the four reporting systems.
- Calculated and compared Area Under the Receiver Operating Characteristic Curves (AUC) and Cohen's kappa for interobserver agreement.
Main Results:
- CO-RADS and BSTI statement demonstrated higher diagnostic performance (AUC) than COVID-RADS and RSNA statement (P < .05).
- Average AUCs: CO-RADS (0.84), COVID-RADS (0.80), RSNA (0.81), BSTI (0.84).
- Interobserver agreement (Cohen's kappa) was comparable across all systems, ranging from 0.61 to 0.63.
Conclusions:
- CO-RADS and BSTI statement offer superior diagnostic performance for COVID-19 on CT compared to COVID-RADS and RSNA statement.
- All evaluated systems provide reasonable performance and interobserver agreement for reporting COVID-19 CT findings.
Purpose:
To compare the performance and interobserver agreement of the COVID-19 Reporting and Data System (CO-RADS), the COVID-19 imaging reporting and data system (COVID-RADS), the RSNA expert consensus statement, and the British Society of Thoracic Imaging (BSTI) guidance statement.
Materials And Methods:
In this case-control study, total of 100 symptomatic patients suspected of having COVID-19 were included: 50 patients with COVID-19 (59±17 years, 38 men) and 50 patients without COVID-19 (65±24 years, 30 men). Eight radiologists independently scored chest CT images of the cohort according to each reporting system. The area under the receiver operating characteristic curves (AUC) and interobserver agreements were calculated and statistically compared across the systems.
Results:
A total of 800 observations were made for each system. The level of suspicion of COVID-19 correlated with the RT-PCR positive rate except for the "negative for pneumonia" classifications in all the systems (Spearman's coefficient: ρ=1.0, P=<.001 for all the systems). Average AUCs were as follows: CO-RADS, 0.84 (95% confidence interval, 0.83-0.85): COVID-RADS, 0.80 (0.78-0.81): the RSNA statement, 0.81 (0.79-0.82): and the BSTI statement, 0.84 (0.812-0.86). Average Cohen's kappa across observers was 0.62 (95% confidence interval, 0.58-0.66), 0.63 (0.58-0.68), 0.63 (0.57-0.69), and 0.61 (0.58-0.64) for CO-RADS, COVID-RADS, the RSNA statement and the BSTI statement, respectively. CO-RADS and the BSTI statement outperformed COVID-RADS and the RSNA statement in diagnostic performance (P=.<.05 for all the comparison).
Conclusions:
CO-RADS, COVID-RADS, the RSNA statement and the BSTI statement provided reasonable performances and interobserver agreements in reporting CT findings of COVID-19.
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