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European Radiology

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01-09-2020 | Coronavirus | Chest

Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies

Authors: Sana Salehi, Aidin Abedi, Sudheer Balakrishnan, Ali Gholamrezanezhad

Published in: European Radiology | Issue 9/2020

Abstract

Background

In the vast majority of the laboratory-confirmed coronavirus disease 2019 (COVID-19) patients, computed tomography (CT) examinations yield a typical pattern and the sensitivity of this modality has been reported to be 97% in a large-scale study. Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care.

Purpose

To compose a comprehensive lexicon for description of the imaging findings and propose a grading system and structured reporting format for CT findings in COVID-19.

Material and methods

We updated our published systematic review on imaging findings in COVID-19 to include 37 published studies pertaining to diagnostic features of COVID-19 in chest CT. Using the reported imaging findings of 3647 patients, we summarized the typical chest CT findings, atypical features, and temporal changes of COVID-19 in chest CT. Subsequently, we extracted a list of descriptive terms and mapped it to the terminology that is commonly used in imaging literature.

Results

We composed a comprehensive lexicon that can be used for documentation and reporting of typical and atypical CT imaging findings in COVID-19 patients. Using the same data, we propose a grading system with five COVID-RADS categories. Each COVID-RADS grade corresponds to a low, moderate, or high level of suspicion for pulmonary involvement of COVID-19.

Conclusion

The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients.

Key Points

• Chest CT has high sensitivity in diagnosing the coronavirus disease 2019 (COVID-19).

• Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care.

• The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients.

Johns Hopkins Center for Systems Science and Engineering (2020) Coronavirus COVID-19 global cases. In: ArcGIS. https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6. Accessed 31 Mar 2020

Hare S, Rodrigues J, Nair A, Robinson G (2020) Lessons from the frontline of the covid-19 outbreak. In: BMJ Opin. https://blogs.bmj.com/bmj/2020/03/20/lessons-from-the-frontline-of-the-covid-19-outbreak/. Accessed 28 Mar 2020

Xie X, Zhong Z, Zhao W et al (2020) Chest CT for typical 2019-nCoV pneumonia: relationship to negative RT-PCR testing. Radiology 200343. https://doi.org/10.1148/radiol.2020200343

Fang Y, Zhang H, Xie J et al (2020) Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology 200432. https://doi.org/10.1148/radiol.2020200432

Ai T, Yang Z, Hou H et al (2020) Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology 200642. https://doi.org/10.1148/radiol.2020200642

Huang P, Liu T, Huang L et al (2020) Use of chest CT in combination with negative RT-PCR assay for the 2019 novel coronavirus but high clinical suspicion. Radiology 295:22–23. https://doi.org/10.1148/radiol.2020200330CrossRefPubMed

Kanne JP, Little BP, Chung JH et al (2020) Essentials for radiologists on COVID-19: an update—radiology scientific expert panel. Radiology 200527. https://doi.org/10.1148/radiol.2020200527

American College of Radiology (ACR) (2020) ACR recommendations for the use of chest radiography and computed tomography (CT) for suspected COVID-19 infection. https://www.acr.org/Advocacy-and-Economics/ACR-Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection. Accessed 31 Mar 2020

The American Society of Emergency Radiology (ASER) (2020) STR / ASER COVID-19 position statement. https://thoracicrad.org/wp-content/uploads/2020/03/STR-ASER-Position-Statement-1.pdf. Accessed 30 Mar 2020

10.

Chan JF, Yuan S, Kok KH et al (2020) A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet 395:514–523. https://doi.org/10.1016/s0140-6736(20)30183-5CrossRefPubMedPubMedCentral

11.

Centers for Disease Control and Prevention (2020) Coronavirus disease 2019 (COVID-19). https://www.cdc.gov/coronavirus/2019-ncov/about/testing.html. Accessed 2 Mar 2020

12.

Assadi M, Velez E, Najafi MH, Gholamrezanezhad A (2019) The need for standardization of nuclear cardiology reporting and data system (NCAD-RADS): learning from coronary artery disease (CAD), breast imaging (BI), liver imaging (LI), and prostate imaging (PI) RADS. J Nucl Cardiol 26:660–665. https://doi.org/10.1007/s12350-018-01473-2CrossRefPubMed

13.

Gholamrezanezhad A, Kessler M, Hayeri SM (2017) The need for standardization of musculoskeletal practice reporting: learning from ACR BI-RADS, liver imaging-reporting and data system, and prostate imaging-reporting and data system. J Am Coll Radiol 14:1585–1587. https://doi.org/10.1016/j.jacr.2017.06.019CrossRefPubMed

14.

Schwartz LH, Panicek DM, Berk AR et al (2011) Improving communication of diagnostic radiology findings through structured reporting. Radiology 260:174–181. https://doi.org/10.1148/radiol.11101913CrossRefPubMedPubMedCentral

15.

Abedi A, Tofighi S, Salehi S et al (2019) Reason for exam imaging reporting and data system (RI-RADS): a grading system to standardize radiology requisitions. Eur J Radiol 120:108661. https://doi.org/10.1016/j.ejrad.2019.108661CrossRefPubMed

16.

Tofighi S, Abedi A, Salehi S et al (2020) Reason for exam imaging reporting and data system: consensus reached on quality assessment of radiology requisitions. J Patient Saf. https://doi.org/10.1097/PTS.0000000000000653

17.

Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A (2020) Coronavirus disease 2019 (COVID-19, 2019-nCoV): a systematic review of imaging findings in 919 patients. AJR Am J Roentgenol:1–7. https://doi.org/10.2214/AJR.20.23034

18.

Pan Y, Guan H, Zhou S et al (2020) Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): a study of 63 patients in Wuhan, China. Eur Radiol. https://doi.org/10.1007/s00330-020-06731-x

19.

Zhou S, Wang Y, Zhu T, Xia L (2020) CT features of coronavirus disease 2019 (COVID-19) pneumonia in 62 patients in Wuhan, China. AJR Am J Roentgenol:1–8. https://doi.org/10.2214/AJR.20.22975

20.

Wang D, Hu B, Hu C et al (2020) Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. https://doi.org/10.1001/jama.2020.1585

21.

Pan Y, Guan H (2020) Imaging changes in patients with 2019-nCov. Eur Radiol. https://doi.org/10.1007/s00330-020-06713-z

22.

Bernheim A, Mei X, Huang M et al (2020) Chest CT findings in coronavirus disease-19 (COVID-19): relationship to duration of infection. Radiology 200463. https://doi.org/10.1148/radiol.2020200463

23.

Guan W-J, Ni Z-Y, Hu Y et al (2020) Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. https://doi.org/10.1056/NEJMoa2002032

24.

Inui S, Fujikawa A, Jitsu M et al (2020) Chest CT findings in cases from the cruise ship “diamond princess” with coronavirus disease 2019 (COVID-19). Radiology Cardiothoracic Imaging 2:e200110. https://doi.org/10.1148/ryct.2020200110CrossRefPubMedCentral

25.

Bai HX, Hsieh B, Xiong Z et al (2020) Performance of radiologists in differentiating COVID-19 from viral pneumonia on chest CT. Radiology 200823. https://doi.org/10.1148/radiol.2020200823

26.

Zhao W, Zhong Z, Xie X et al (2020) Relation between chest CT findings and clinical conditions of coronavirus disease (COVID-19) pneumonia: a multicenter study. AJR Am J Roentgenol :1–6. https://doi.org/10.2214/AJR.20.22976

27.

Hansell DM, Bankier AA, MacMahon H et al (2008) Fleischner society: glossary of terms for thoracic imaging. Radiology 246:697–722. https://doi.org/10.1148/radiol.2462070712CrossRefPubMed

28.

Kooraki S, Hosseiny M, Myers L, Gholamrezanezhad A (2020) Coronavirus (COVID-19) outbreak: what the Department of Radiology should know. J Am Coll Radiol. https://doi.org/10.1016/j.jacr.2020.02.008

29.

Rossi SE, Franquet T, Volpacchio M, Giménez A, Aguilar G (2005) Tree-in-Bud Pattern at Thin-Section CT of the Lungs: Radiologic-Pathologic Overview. Radiographics 25 (3):789–801. https://doi.org/10.1148/rg.253045115

30.

Salehi S, Abedi A, Gholamrezanezhad A (2020) Reply to vascular changes detected with thoracic CT in Coronavirus Disease (COVID-19) might be significant determinants for accurate diagnosis and optimal patient management. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.20.23339

Title: Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies
Authors: Sana Salehi
Aidin Abedi
Sudheer Balakrishnan
Ali Gholamrezanezhad
Publication date: 01-09-2020
Publisher: Springer Berlin Heidelberg
Keywords: Coronavirus
Computed Tomography
Computed Tomography
COVID-19
Published in: European Radiology / Issue 9/2020
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-020-06863-0

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Springer Medicine

Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies

Abstract

Background

Purpose

Material and methods

Results

Conclusion

Key Points

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Purpose

Material and methods

Results

Conclusion

Key Points

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