Evaluation of Chest CT Findings using the Reporting and Data System of Patients with Suspected COVID-19 Infection






How to Cite

Sever, I. halil, Ozkul, B., Koyuncu Sokmen, B., & Inan Gurcan, N. (2021). Evaluation of Chest CT Findings using the Reporting and Data System of Patients with Suspected COVID-19 Infection. Iranian Red Crescent Medical Journal, 23(7). https://doi.org/10.32592/ircmj.2021.23.7.861 (Original work published August 3, 2021)


Background: The simultaneous interpretation of computed tomography (CT) scans performed on patients with suspected clinical signs of coronavirus disease 2019 (COVID-19) or a history of contact may accelerate patient isolation, particularly during the peak of the pandemic. The use of an appropriate scoring system can lead to the conveyance of the findings in a more understandable way and the elimination of differences in interpretations.

Objectives: This study aimed to evaluate the diagnostic performance of the coronavirus disease 2019 (COVID-19) imaging reporting and data system (CO-RADS) in admitted patients with suspected COVID-19 infection.

Methods: This retrospective study included all patients admitted to our hospital with COVID-19 pneumonia suspicion within March 20-May 15, 2020, who were examined by both CT and real-time reverse transcription polymerase chain reaction (rRT-PCR) at initial presentation. Four radiologists, who were blinded to the rRT-PCR results and medical history, assessed all images independently and classified the CT findings according to the CO-RADS previously defined. Diagnostic value of the scoring system and interobserver agreement in rRT-PCR positive-negative groups and for CO-RADS 1-5 were evaluated.

Results: In this study, 274 (153 men and 121 women; 48.8±17.3 years) rRT-PCR positive and 437 (208 men and 229 women; 49.0±19.5 years) rRT-PCR negative individuals were included. It was found that CO-RADS had a good diagnostic performance with area under the receiver operating characteristic roc curve of 0.857. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were obtained at 81.9%, 89.4%, 75.7%, 92.5%, and 84.8%, respectively. The interobserver agreement of four radiologists in CO-RADS 1 and 5 was substantial to almost perfect according to the kappa values. Other CO-RADS  scores showed a fair to moderate agreement. The interrater agreement was slightly higher in the PCR (-) patient group than in the positive one.

Conclusion: In conclusion, CO-RADS was a successful scoring system for distinguishing highly suspicious cases in terms of COVID-19 infection lung involvement, showing high interobserver agreement.



  1. World Health Organization. Coronavirus disease (Covid-19) outbreak situation. Geneva: World Health Organization; 2019.
  2. Prokop M, van Everdingen W, van Rees Vellinga T, Quarles van Ufford H, Stöger L, Beenen L, et al. CO-RADS: a categorical ct assessment scheme for patients suspected of having COVID-19-definition and evaluation. Radiology. 2020;296(2):E97-104. doi: 10.1148/radiol.2020201473. [PubMed: 32339082].
  3. Li Y, Yao L, Li J, Song Y, Cai Z, Yang C. Stability issues of RT-PCR testing of SARS-CoV-2 for hospitalized patients clinically diagnosed with COVID-19. J Med Virol. 2020;92(7):903-8. doi: 10.1002/jmv.25786. [PubMed: 32219885].
  4. Wang W, Xu Y, Gao R, Lu R, Han K, Wu G, et al. Detection of SARS-CoV-2 in different types of clinical specimens. JAMA. 2020;323(18):1843-4. doi: 10.1001/jama.2020.3786. [PubMed: 32159775].
  5. Corman VM, Landt O, Kaiser M, Molenkamp R, Meijer A, Chu DK, et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill. 2020;25(3):2000045. doi: 10.2807/1560-7917.ES.2020.25.3.2000045. [PubMed: 31992387].
  6. Hare S, Rodrigues J, Nair A, Robinson G. Lessons from the frontline of the COVID-19 outbreak. London: BMJ Opinion; 2020.
  7. Xie X, Zhong Z, Zhao W, Zheng C, Wang F, Liu J. Chest CT for typical coronavirus disease 2019 (COVID-19) Pneumonia: relationship to negative RT-PCR testing. Radiology. 2020;296(2):E41-5. doi: 10.1148/radiol.2020200343. [PubMed: 32049601].
  8. Chan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514-23. doi: 10.1016/S0140-6736(20)30154-9. [PubMed: 31986261].
  9. Islam N, Salameh JP, Leeflang MM, Hooft L, McGrath TA, van der Pol CB, et al. Thoracic imaging tests for the diagnosis of COVID-19. Cochrane Database Syst Rev. 2020;11:CD013639. doi: 10.1002/14651858.CD013639. [PubMed: 33242342].
  10. Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, et al. Radiological society of north america expert consensus statement on reporting chest CT findings related to COVID-19. endorsed by the society of thoracic radiology, the American College of Radiology, and RSNA - Secondary Publication. J Thorac Imaging. 2020;35(4):219-27. doi: 10.1097/RTI.0000000000000524. [PubMed: 32324653].
  11. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. 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. Eur Radiol. 2020;30(9):4930-42. doi: 10.1007/s00330-020-06863-0. [PubMed: 32346790].
  12. Rubin EJ, Baden LR, Morrissey S, Campion EW. Medical Journals and the 2019-nCoV Outbreak. N Engl J Med. 2020;382(9):866. doi: 10.1056/NEJMe2001329. [PubMed: 31986242].
  13. Gralinski LE, Menachery VD. Return of the coronavirus: 2019-nCoV. Viruses. 2020;12(2):135. doi: 10.3390/v12020135. [PubMed: 31991541].
  14. Duarte R, Furtado I, Sousa L, Carvalho CFA. The 2019 novel coronavirus (2019-nCoV): novel virus, old challenges. Acta Med Port. 2020;33(3):157-7. doi: 10.20344/amp.13547. [PubMed: 32023427].
  15. Wang M, Cao R, Zhang L, Yang X, Liu J, Xu M, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res. 2020;30(3):269-71. doi: 10.1038/s41422-020-0282-0. [PubMed: 32020029].
  16. Sharma G, Volgman AS, Michos ED. Sex differences in mortality from COVID-19 pandemic: are men vulnerable and women protected? JACC Case Rep. 2020;2(9):1407-10. doi: 10.1016/j.jaccas.2020.04.027. [PubMed: 32373791].
  17. Klein SL, Dhakal S, Ursin RL, Deshpande S, Sandberg K, Mauvais-Jarvis F. Biological sex impacts COVID-19 outcomes. PLoS Pathog. 2020;16(6):e1008570. doi: 10.1371/journal.ppat.1008570. [PubMed: 32569293].
  18. Huang P, Liu T, Huang L, Liu H, Lei M, Xu W, et al. Use of chest CT in combination with negative RT-PCR assay for the 2019 novel coronavirus but high clinical suspicion. Radiology. 2020;295(1):22-3. doi: 10.1148/radiol.2020200330. [PubMed: 32049600].
  19. Lei J, Li J, Li X, Qi X. CT imaging of the 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology. 2020;295(1):18. doi: 10.1148/radiol.2020200236. [PubMed: 32003646].
  20. Shi H, Han X, Zheng C. Evolution of CT manifestations in a patient recovered from 2019 novel coronavirus (2019-nCoV) pneumonia in Wuhan, China. Radiology. 2020;295(1):20. doi: 10.1148/radiol.2020200269. [PubMed: 32032497].
  21. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of chest CT and RT-PCR testing for coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020;296(2):E32-40. doi: 10.1148/radiol.2020200642. [PubMed: 32101510].
  22. Fang Y, Zhang H, Xie J, Lin M, Ying L, Pang P, et al. Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology. 2020;296(2):E115-7. doi: 10.1148/radiol.2020200432. [PubMed: 32073353].
  23. Long C, Xu H, Shen Q, Zhang X, Fan B, Wang C, et al. Diagnosis of the coronavirus disease (COVID-19): rRT-PCR or CT? Eur J Radiol. 2020;126:108961. doi: 10.1016/j.ejrad.2020.108961. [PubMed: 32229322].
  24. De Smet K, De Smet D, Ryckaert T, Laridon E, Heremans B, Vandenbulcke R, et al. Diagnostic performance of chest CT for SARS-CoV-2 infection in individuals with or without COVID-19 symptoms. Radiology. 2021;298(1):E30-7. doi: 10.1148/radiol.2020202708. [PubMed: 32776832].