Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative study
Purpose: To compare the diagnostic performance and interobserver agreement of three reporting systems for computed tomography findings in coronavirus disease 2019 (COVID-19), namely the COVID-19 Reporting and Data System (CO-RADS), COVID-19 Imaging Reporting and Data System (COVID-RADS), and Radiolo...
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Elsevier
2021-08-01
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844021018466 |
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Article |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ryo Kurokawa Shohei Inui Wataru Gonoi Yudai Nakai Masanori Ishida Yusuke Watanabe Takatoshi Kubo Yosuke Amano Koh Okamoto Hidenori Kage Sohei Harada Goh Tanaka Takuya Kawahara Takahide Nagase Kyoji Moriya Osamu Abe |
spellingShingle |
Ryo Kurokawa Shohei Inui Wataru Gonoi Yudai Nakai Masanori Ishida Yusuke Watanabe Takatoshi Kubo Yosuke Amano Koh Okamoto Hidenori Kage Sohei Harada Goh Tanaka Takuya Kawahara Takahide Nagase Kyoji Moriya Osamu Abe Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative study Heliyon Diagnostic performance Interobserver agreement Chest computed tomography COVID-19 |
author_facet |
Ryo Kurokawa Shohei Inui Wataru Gonoi Yudai Nakai Masanori Ishida Yusuke Watanabe Takatoshi Kubo Yosuke Amano Koh Okamoto Hidenori Kage Sohei Harada Goh Tanaka Takuya Kawahara Takahide Nagase Kyoji Moriya Osamu Abe |
author_sort |
Ryo Kurokawa |
title |
Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative study |
title_short |
Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative study |
title_full |
Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative study |
title_fullStr |
Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative study |
title_full_unstemmed |
Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative study |
title_sort |
standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: a retrospective comparative study |
publisher |
Elsevier |
series |
Heliyon |
issn |
2405-8440 |
publishDate |
2021-08-01 |
description |
Purpose: To compare the diagnostic performance and interobserver agreement of three reporting systems for computed tomography findings in coronavirus disease 2019 (COVID-19), namely the COVID-19 Reporting and Data System (CO-RADS), COVID-19 Imaging Reporting and Data System (COVID-RADS), and Radiological Society of North America (RSNA) expert consensus statement, in a low COVID-19 prevalence area. Method: This institutional review board approval single-institutional retrospective study included 154 hospitalized patients between April 1 and May 21, 2020; 26 (16.9 %; 63.2 ± 14.1 years, 21 men) and 128 (65.7 ± 16.4 years, 87 men) patients were diagnosed with and without COVID-19 according to reverse transcription-polymerase chain reaction results, respectively. Written informed consent was waived due to the retrospective nature of the study. Six radiologists independently classified chest computed tomography images according to each reporting system. The area under receiver operating characteristic curves, sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and interobserver agreements were calculated and compared across the systems using paired t-test and kappa analysis. Results: Mean area under receiver operating characteristic curves were as follows: CO-RADS, 0.89 (95 % confidence interval [CI], 0.87–0.90); COVID-RADS, 0.78 (0.75–0.80); and RSNA expert consensus statement, 0.88 (0.86–0.90). Average kappa values across observers were 0.52 (95 % CI: 0.45–0.60), 0.51 (0.41–0.61), and 0.57 (0.49–0.64) for CO-RADS, COVID-RADS, and RSNA expert consensus statement, respectively. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were the highest at 0.71, 0.53, 0.72, 0.96, and 0.56 in the CO-RADS; 0.56, 0.31, 0.54, 0.95, and 0.35 in the COVID-RADS; 0.83, 0.49, 0.61, 0.96, and 0.55 in the RSNA expert consensus statement, respectively. Conclusions: The CO-RADS exhibited the highest specificity, positive predictive value, which are especially important in a low-prevalence population, while maintaining high accuracy and negative predictive value, demonstrating the best performance in a low-prevalence population. |
topic |
Diagnostic performance Interobserver agreement Chest computed tomography COVID-19 |
url |
http://www.sciencedirect.com/science/article/pii/S2405844021018466 |
work_keys_str_mv |
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doaj-32142502aa2f4504b13a320b723674782021-09-01T12:17:15ZengElsevierHeliyon2405-84402021-08-0178e07743Standardized reporting systems of chest computed tomography in a population with low coronavirus disease 2019 prevalence: A retrospective comparative studyRyo Kurokawa0Shohei Inui1Wataru Gonoi2Yudai Nakai3Masanori Ishida4Yusuke Watanabe5Takatoshi Kubo6Yosuke Amano7Koh Okamoto8Hidenori Kage9Sohei Harada10Goh Tanaka11Takuya Kawahara12Takahide Nagase13Kyoji Moriya14Osamu Abe15Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan; Corresponding author.Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Respiratory Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Infectious Diseases, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Respiratory Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Infection Control and Prevention, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Respiratory Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanClinical Research Promotion Center, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Respiratory Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Infectious Diseases, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, JapanPurpose: To compare the diagnostic performance and interobserver agreement of three reporting systems for computed tomography findings in coronavirus disease 2019 (COVID-19), namely the COVID-19 Reporting and Data System (CO-RADS), COVID-19 Imaging Reporting and Data System (COVID-RADS), and Radiological Society of North America (RSNA) expert consensus statement, in a low COVID-19 prevalence area. Method: This institutional review board approval single-institutional retrospective study included 154 hospitalized patients between April 1 and May 21, 2020; 26 (16.9 %; 63.2 ± 14.1 years, 21 men) and 128 (65.7 ± 16.4 years, 87 men) patients were diagnosed with and without COVID-19 according to reverse transcription-polymerase chain reaction results, respectively. Written informed consent was waived due to the retrospective nature of the study. Six radiologists independently classified chest computed tomography images according to each reporting system. The area under receiver operating characteristic curves, sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and interobserver agreements were calculated and compared across the systems using paired t-test and kappa analysis. Results: Mean area under receiver operating characteristic curves were as follows: CO-RADS, 0.89 (95 % confidence interval [CI], 0.87–0.90); COVID-RADS, 0.78 (0.75–0.80); and RSNA expert consensus statement, 0.88 (0.86–0.90). Average kappa values across observers were 0.52 (95 % CI: 0.45–0.60), 0.51 (0.41–0.61), and 0.57 (0.49–0.64) for CO-RADS, COVID-RADS, and RSNA expert consensus statement, respectively. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were the highest at 0.71, 0.53, 0.72, 0.96, and 0.56 in the CO-RADS; 0.56, 0.31, 0.54, 0.95, and 0.35 in the COVID-RADS; 0.83, 0.49, 0.61, 0.96, and 0.55 in the RSNA expert consensus statement, respectively. Conclusions: The CO-RADS exhibited the highest specificity, positive predictive value, which are especially important in a low-prevalence population, while maintaining high accuracy and negative predictive value, demonstrating the best performance in a low-prevalence population.http://www.sciencedirect.com/science/article/pii/S2405844021018466Diagnostic performanceInterobserver agreementChest computed tomographyCOVID-19 |