Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Sep;30(9):4930-4942.
doi: 10.1007/s00330-020-06863-0. Epub 2020 Apr 28.

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

Sana Salehi  1 , Aidin Abedi  1 , Sudheer Balakrishnan  1 , Ali Gholamrezanezhad  2   3
Affiliations

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

Sana Salehi et al. Eur Radiol. 2020 Sep.

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.

Keywords: COVID-19; Coronavirus; Diagnosis; Pandemics; Pneumonia, viral; Tomography, X-ray computed.

PubMed Disclaimer

Conflict of interest statement

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Figures

Fig. 1
Fig. 1
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion (COVID-RADS 3/high suspicion) for COVID-19 are underlined. GGO, ground glass opacity
Fig. 2
Fig. 2
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion for COVID-19 are underlined (COVID-RADS 2B/moderate suspicion). GGO, ground glass opacity
Fig. 3
Fig. 3
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion for COVID-19 are underlined (COVID-RADS 3/high suspicion). GGO, ground glass opacity
Fig. 4
Fig. 4
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion for COVID-19 are underlined (COVID-RADS 3/high suspicion). GGO, ground glass opacity
Fig. 5
Fig. 5
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion (COVID-RADS 2A/moderate suspicion) for COVID-19 are underlined. GGO, ground glass opacity
Fig. 6
Fig. 6
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion (COVID-RADS 2A/moderate suspicion) for COVID-19 are underlined. GGO, ground glass opacity
Fig. 7
Fig. 7
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion (COVID-RADS 0/low suspicion) for COVID-19 are underlined
Fig. 8
Fig. 8
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion (COVID-RADS 1/low suspicion) for COVID-19 are underlined
Fig. 9
Fig. 9
An example report card for grading of the imaging based on the proposed classification. Corresponding COVID-RADS grade and the level of suspicion (COVID-RADS 1/low suspicion) for COVID-19 are underlined
See this image and copyright information in PMC

References

    1. 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#/bda7594.... Accessed 31 Mar 2020
    1. 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-c.... Accessed 28 Mar 2020
    1. Xie X, Zhong Z, Zhao W et al (2020) Chest CT for typical 2019-nCoV pneumonia: relationship to negative RT-PCR testing. Radiology 200343. 10.1148/radiol.2020200343 - PMC - PubMed
    1. Fang Y, Zhang H, Xie J et al (2020) Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology 200432. 10.1148/radiol.2020200432 - PMC - PubMed
    1. 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. 10.1148/radiol.2020200642 - PMC - PubMed

Publication types

LinkOut - more resources