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The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society
Open accessAbstract
With more than 900 000 confirmed cases worldwide and nearly 50 000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19.
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“CXR was selected as the imaging input because it is widely available and commonly indicated by guidelines”
From Federated learning for predicting clinical outcomes in patients with COVID-19 (2021) · cites this paper as [23]
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Cites
Wu, Z., & McGoogan, J. M. (2020) · JAMA · doi:10.1001/jama.2020.2648 · Cited by 17,016
Pathological findings of COVID-19 associated with acute respiratory distress syndrome
Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C., Liu, S., Zhao, P., Liu, H., Zhu, L., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30076-x · Cited by 8,545
Ai, T., Yang, Z., Hou, H., Zhan, C., Chen, C., Lv, W., Tao, Q., Sun, Z., & Xia, L. (2020) · Radiology · doi:10.1148/radiol.2020200642 · Cited by 5,793
Detection of SARS-CoV-2 in Different Types of Clinical Specimens
Wang, W., Xu, Y., Gao, R., Lu, R., Han, K., Wu, G., & Tan, W. (2020) · JAMA · doi:10.1001/jama.2020.3786 · Cited by 5,116
SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients
Zou, L., Ruan, F., Huang, M.-X., Liang, L.-J., Huang, H., Hong, Z.-S., Yu, J.-X., Kang, M., Song, Y.-C., Xia, J., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2001737 · Cited by 4,590
Epidemiology of COVID-19 Among Children in China
Dong, Y., Mo, X., Hu, Y., Qi, X., Jiang, F., Jiang, Z., & Tong, S. (2020) · PEDIATRICS · doi:10.1542/peds.2020-0702 · Cited by 4,240
Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany
Rothe, C., Schunk, M., Sothmann, P., Bretzel, G., Froeschl, G., Wallrauch, C., Zimmer, T., Thiel, V., Jänke, C., Guggemos, W., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2001468 · Cited by 4,211
Li, R., Pei, S., Chen, B., Song, Y., Zhang, T., Yang, W., & Shaman, J. (2020) · Science · doi:10.1126/science.abb3221 · Cited by 3,633
Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR
Fang, Y., Zhang, H., Xie, J., Lin, M., Ying, L., Pang, P., & Ji, W. (2020) · Radiology · doi:10.1148/radiol.2020200432 · Cited by 3,340
Mizumoto, K., Kagaya, K., Zarebski, A. E., & Chowell, G. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.10.2000180 · Cited by 2,317
Driggin, E., Madhavan, M. V., Bikdeli, B., Chuich, T., Laracy, J. C., Biondi‐Zoccai, G., Brown, T. S., Der-Nigoghossian, C. A., Zidar, D. A., Haythe, J. H., et al. (2020) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2020.03.031 · Cited by 2,086
Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients
Salehi, S., Abedi, A., Balakrishnan, S., & Gholamrezanezhad, A. (2020) · American Journal of Roentgenology · doi:10.2214/ajr.20.23034 · Cited by 1,600
Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19
Wong, H. Y. F., Lam, H. Y. S., Fong, A. H.-T., Leung, S. T., Chin, T. W.-Y., Lo, C. S.-Y., Lui, M. M., Lee, J. C. Y., Chiu, K. W.-H., Chung, T. W., et al. (2020) · Radiology · doi:10.1148/radiol.2020201160 · Cited by 1,524
Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19)
Nishiura, H., Kobayashi, T., Miyama, T., Suzuki, A., Jung, S.-M., Hayashi, K., Kinoshita, R., Yang, Y., Yuan, B., Akhmetzhanov, A. R., et al. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.03.020 · Cited by 1,279
Simpson, S. A., Kay, F. U., Abbara, S., Bhalla, S., Chung, J. H., Chung, M., Henry, T. S., Kanne, J. P., Kligerman, S. J., Ko, J. P., et al. (2020) · Radiology Cardiothoracic Imaging · doi:10.1148/ryct.2020200152 · Cited by 764
Self-citationLi, Y., Yao, L., Li, J., Chen, L., Song, Y., Cai, Z., & Yang, C. (2020) · Journal of Medical Virology · doi:10.1002/jmv.25786 · Cited by 687
Coronavirus (COVID-19) Outbreak: What the Department of Radiology Should Know
Kooraki, S., Hosseiny, M., Myers, L., & Gholamrezanezhad, A. (2020) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2020.02.008 · Cited by 512
Is There a Role for Lung Ultrasound During the COVID ‐19 Pandemic?
Soldati, G., Smargiassi, A., Inchingolo, R., Buonsenso, D., Perrone, T., Briganti, D. F., Perlini, S., Torri, E., Mariani, A., Mossolani, E. E., et al. (2020) · Journal of Ultrasound in Medicine · doi:10.1002/jum.15284 · Cited by 454
Chest CT Findings in Cases from the Cruise Ship Diamond Princess with Coronavirus Disease (COVID-19)
Inui, S., Fujikawa, A., Jitsu, M., Kunishima, N., Watanabe, S., Suzuki, Y., Umeda, S., & Uwabe, Y. (2020) · Radiology Cardiothoracic Imaging · doi:10.1148/ryct.2020200110 · Cited by 447
Radiology Department Preparedness for COVID-19: Radiology Scientific Expert Review Panel
Mossa-Basha, M., Meltzer, C. C., Kim, D. C., Tuite, M. J., Kolli, K. P., & Tan, B. S. (2020) · Radiology · doi:10.1148/radiol.2020200988 · Cited by 324
Abandoning Daily Routine Chest Radiography in the Intensive Care Unit: Meta-Analysis
Oba, Y., & Zaza, T. (2010) · Radiology · doi:10.1148/radiol.10090946 · Cited by 137
Hejblum, G., Chalumeau-Lemoine, L., Ioos, V., Boëlle, P., Salomon, L., Simon, T., Vibert, J. F., & Guidet, B. (2009) · The Lancet · doi:10.1016/s0140-6736(09)61459-8 · Cited by 133
Radiology Department Preparedness for COVID-19: Facing an Unexpected Outbreak of the Disease
Orsi, M., Oliva, A. G., & Cellina, M. I. (2020) · Radiology · doi:10.1148/radiol.2020201214 · Cited by 38
AzuRéa network for the RadioDay study group, Lakhal, K., Serveaux-Delous, M., Lefrant, J. Y., Capdevila, X., & Jaber, S. (2012) · Intensive Care Medicine · doi:10.1007/s00134-012-2650-9 · Cited by 33
ACR Appropriateness Criteria® Intensive Care Unit Patients
Suh, R. D., Genshaft, S. J., Kirsch, J., Kanne, J. P., Chung, J. H., Donnelly, E. F., Ginsburg, M. E., Heitkamp, D. E., Henry, T. S., Kazerooni, E. A., et al. (2015) · Journal of Thoracic Imaging · doi:10.1097/rti.0000000000000174 · Cited by 30
Self-citation
Flagged first, then by citations
Research works printed but not linked: 6
- Centers for Disease Control and Prevention, Coronavirus Disease 2019 (COVID-19) Interim Infection Prevention and Control Recommendations
- Orsi MA, 2020, Radiology, 201214
- World Health Organization, Critical preparedness, readiness and response actions for COVID-19
- Centers for Disease Control and Prevention, Coronavirus Disease 2019 (COVID-19) Public Health Recommendations for Community-Related Exposure
- Centers for Disease Control and Prevention. Interim U.S, Guidance for Risk Assessment and Public Health Management of Healthcare Personnel with Potential Exposure in a Healthcare Setting to Patients with Coronavirus Disease (COVID-19)
- Nishiura H, 2020, Int J Infect Dis
Cited by
Sorted by citations
Wang, L., Lin, Z. Q., & Wong, A. M. (2020) · Scientific Reports · doi:10.1038/s41598-020-76550-z · Cited by 3,228
Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images
Fan, D.-P., Zhou, T., Ji, G.-P., Zhou, Y., Chen, G., Fu, H., Shen, J., & Shao, L. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.2996645 · Cited by 1,273
COVID-19 Image Data Collection: Prospective Predictions are the Future
Cohen, J., Morrison, P., Dao, L., Roth, K., Duong, T. Q., & Ghassemi, M. (2020) · The Journal of Machine Learning for Biomedical Imaging · doi:10.59275/j.melba.2020-48g7 · Cited by 1,110
Prokop, M., van Everdingen, W. M., Vellinga, T. V. R., van Ufford, H. M. E. Q., Stöger, J. L., Beenen, L. F. M., Geurts, B. H. J., Gietema, H. A., Krdzalic, J., Schaefer‐Prokop, C. M., et al. (2020) · Radiology · doi:10.1148/radiol.2020201473 · Cited by 922
Self-citationDiagnostics for SARS-CoV-2 infections
Kevadiya, B. D., Machhi, J., Herskovitz, J., Oleynikov, M. D., Blomberg, W. R., Bajwa, N., Soni, D., Das, S., Hasan, M., Patel, M., et al. (2021) · Nature Materials · doi:10.1038/s41563-020-00906-z · Cited by 860
Metadata
- Authors
- Rubin, G. D., Ryerson, C. J., Haramati, L. B., Sverzellati, N., Kanne, J. P., Raoof, S., Schluger, N. W., Volpi, A., Yim, J.-J., Martin, I. B. K., Anderson, D. J., Kong, C., Altes, T., Bush, A., Desai, S. R., Goldin, O., Goo, J. M., Humbert, M., Inoue, Y., Kauczor, H.-U., Luo, F., Mazzone, P. J., Prokop, M., Remy-Jardin, M., Richeldi, L., Schaefer-Prokop, C. M., Tomiyama, N., Wells, A. U., & Leung, A. N.
- Affiliations
- University of Parma (IT)
- Università Cattolica del Sacro Cuore (IT)
- Corresponding author
- Rubin, Geoffrey D.
- ORCID
- Rubin, Geoffrey D.
- Ryerson, Christopher J.
- Haramati, Linda B.
- Sverzellati, Nicola
- Kanne, Jeffrey P.
- Schluger, Neil W.
- Volpi, Annalisa
- Yim, Jae-Joon
- Anderson, Deverick J.
- Kong, Christina
- Altes, Talissa
- Bush, Andrew
- Desai, Sujal R.
- Goo, Jin Mo
- Humbert, Marc
- Inoue, Yoshikazu
- Kauczor, Hans-Ulrich
- Luo, Fengming
- Mazzone, Peter J.
- Prokop, Mathias
- Richeldi, Luca
- Tomiyama, Noriyuki
- Wells, Athol U.
- Leung, Ann N.
- Venue
- Radiology
- Published
- 2020-07
- Volume
- 296
- Issue
- 1
- Pages
- 172-180
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- PMC
- PMC7233395
- OpenAlex
- W4230649743
- Cited by
- 1,101
- References
- 25
- Citations by year
- 2026: 17 · 2025: 35 · 2024: 76 · 2023: 123 · 2022: 189 · 2021: 330 · 2020: 328
- FWCI
- 31.82
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Radiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Ultrasound in Clinical Applications
- Keywords
- COVID-19 pandemic, chest imaging, chest radiography, computed tomography, clinical management, diagnostic decision-making, clinical guidelines, community transmission, disease severity, risk factors for progression
- MeSH terms
- Personal Protective Equipment, Betacoronavirus, COVID-19, SARS-CoV-2, Humans, Pneumonia, Viral, Severity of Illness Index, Societies, Medical, Radiography, Thoracic, Triage, Video Recording, Global Health, Coronavirus Infections, Disease Progression, Guideline Adherence, Consensus, Pandemics
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