Evaluation of an association of radiological findings and severity of the disease in patients with the new coronavirus infection (COVID-19)

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Abstract

Rationale: Interpretation of lung abnormalities identified by computed tomography (CT) in patients with COVID-19 could be controversial in some cases. At present, there is no highly reliable algorithm for assessment and prediction of the disease coursed based on CT findings.

Aim: To identify an association of the radiological findings in COVID-19 and its clinical manifestations.

Materials and methods: This observational retrospective cohort study included 92 patients, categorized into three groups according to their clinical severity (mild COVID-19 29 patients, moderate COVID-19 33 patients, and severe COVID-19 30 patients). Chest CT was performed in all patients at admittance to the hospital and at day 10 of their hospital stay.

Results: Almost all patients with severe COVID-19 (28 patients, 96.6%) demonstrated an increase in the damaged lung parenchyma volume at the second CT. The risk of clinical deterioration in these patients was 15.037-fold higher, compared to that in the patients with a  stable volume of lung lesions. The area of pulmonary lesions at the first CT demonstrated its good prognostic ability (ROC area under the curve 0.831, sensitivity 87.5%, specificity 70.0%, p<0.001) to predict clinical deterioration. The presence of bronchial dilation in the total patient group significantly (p<0.01) correlated with an increase of the pulmonary lesion area. Clinical deterioration was found in 5 patients (62.5%) with bronchial dilatation.

Conclusion: CT patterns in COVID-19 patients do not always correlate with clinical severity of the disease. Therefore, lung CT cannot be used for prediction of the COVID-19 course as a  single method without clinical and laboratory assessments.

About the authors

A. D. Strutynskaya

Russian Medical Academy of Continuous Professional Education

Author for correspondence.
Email: strutynskaya@yandex.ru
ORCID iD: 0000-0001-9325-5587

Anastasia D. Strutynskaya – Postgraduate Student, Chair of Roentgenology and Radiology, Faculty of Surgery

2/1–1 Barrikadnaya ul., Moscow, 125993, Russian Federation

Russian Federation

D. S. Koshurnikov

Hospital for War Veterans No. 3

Email: fake@neicon.ru
ORCID iD: 0000-0002-7024-9560

Dmitry S. Koshurnikov – MD, PhD, Head of Department of Roentgenology

4 Startovaya ul., Moscow, 129336, Russian Federation

Russian Federation

I. E. Tyurin

Russian Medical Academy of Continuous Professional Education

Email: fake@neicon.ru
ORCID iD: 0000-0003-3931-1431

Igor E. Tyurin – MD, PhD, Head of Chair of Roentgenology and Radiology, Faculty of Surgery

2/1–1 Barrikadnaya ul., Moscow, 125993, Russian Federation

Russian Federation

M. A. Karnaushkina

Peoples' Friendship University of Russia

Email: fake@neicon.ru
ORCID iD: 0000-0002-8791-2920

Maria A. Karnaushkina – MD, PhD, Professor, Chair of Internal Medicine with a Course of Cardiology and Functional Diagnostics named after Academician V.S. Moiseev

6 Miklukho-Maklaya ul., Moscow, 117198, Russian Federation

Russian Federation

References

  1. Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, Schluger NW, Volpi A, Yim JJ, Martin IBK, Anderson DJ, Kong C, Altes T, Bush A, Desai SR, Goldin O, Goo JM, Humbert M, Inoue Y, Kauczor HU, Luo F, Mazzone PJ, Prokop M, Remy-Jardin M, Richeldi L, Schaefer-Prokop CM, Tomiyama N, Wells AU, Leung AN. The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society. Radiology. 2020;296(1): 172–180. doi: 10.1148/radiol.2020201365.
  2. Li L, Qin L, Xu Z, Yin Y, Wang X, Kong B, Bai J, Lu Y, Fang Z, Song Q, Cao K, Liu D, Wang G, Xu Q, Fang X, Zhang S, Xia J, Xia J. Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy. Radiology. 2020;296(2):E65–E71. doi: 10.1148/radiol.2020200905.
  3. Xie M, Chen Q. Insight into 2019 novel coronavirus – An updated interim review and lessons from SARS-CoV and MERS-CoV. Int J Infect Dis. 2020;94:119–124. doi: 10.1016/j.ijid.2020.03.071.
  4. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, Tao Q, Sun Z, Xia L. 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–E40. doi: 10.1148/radiol.2020200642.
  5. Nair A, Rodrigues JCL, Hare S, Edey A, Devaraj A, Jacob J, Johnstone A, McStay R, Denton E, Robinson G. A British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic. Clin Radiol. 2020;75(5): 329–334. doi: 10.1016/j.crad.2020.03.008.
  6. 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–E45. doi: 10.1148/radiol.2020200343.
  7. Revel MP, Parkar AP, Prosch H, Silva M, Sverzellati N, Gleeson F, Brady A; European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI). COVID-19 patients and the radiology department – advice from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI). Eur Radiol. 2020;30(9): 4903–4909. doi: 10.1007/s00330-020-06865-y.
  8. Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, Henry TS, Kanne JP, Kligerman S, Ko JP, Litt H. Radiological Society of North America Expert Consensus Document on Reporting Chest CT Findings Related to COVID-19: Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA. Radiol Cardiothorac Imaging. 2020;2(2):e200152. doi: 10.1148/ryct.2020200152.
  9. Sánchez-Oro R, Torres Nuez J, Martínez- Sanz G. Radiological findings for diagnosis of SARS-CoV-2 pneumonia (COVID-19). Med Clin (Barc). 2020;155(1): 36–40. English, Spanish. doi: 10.1016/j.medcli.2020.03.004.
  10. Li K, Fang Y, Li W, Pan C, Qin P, Zhong Y, Liu X, Huang M, Liao Y, Li S. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). Eur Radiol. 2020;30(8): 4407–4416. doi: 10.1007/s00330-020-06817-6.
  11. Hosseiny M, Kooraki S, Gholamrezanezhad A, Reddy S, Myers L. Radiology Perspective of Coronavirus Disease 2019 (COVID-19): Lessons From Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome. AJR Am J Roentgenol. 2020;214(5): 1078–1082. doi: 10.2214/AJR.20.22969.
  12. Bernheim A, Mei X, Huang M, Yang Y, Fayad ZA, Zhang N, Diao K, Lin B, Zhu X, Li K, Li S, Shan H, Jacobi A, Chung M. Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection. Radiology. 2020;295(3): 200463. doi: 10.1148/radiol.2020200463.
  13. Chen H, Ai L, Lu H, Li H. Clinical and imaging features of COVID-19. Radiol Infect Dis. 2020;7(2): 43–50. doi: 10.1016/j.jrid.2020.04.003.
  14. Zhang B, Zhang J, Chen H, Yang K, Zhang S. Unmatched clinical presentation and chest CT manifestation in a patient with severe coronavirus disease 2019 (COVID-19). Quant Imaging Med Surg. 2020;10(4): 871–873. doi: 10.21037/qims.2020.03.12.
  15. Hu X, Chen J, Jiang X, Tao S, Zhen Z, Zhou C, Wang J. CT imaging of two cases of one family cluster 2019 novel coronavirus (2019- nCoV) pneumonia: inconsistency between clinical symptoms amelioration and imaging sign progression. Quant Imaging Med Surg. 2020;10(2): 508–510. doi: 10.21037/qims.2020.02.10.
  16. Министерство здравоохранения Российской Федерации. Временные методические рекомендации: профилактика, диагностика и лечение новой коронавирусной инфекции (COVID-19) [Интернет]. Версия 10 (08.02.2021). Доступно на: https://static-0.minzdrav.gov.ru/system/attachments/attaches/000/054/588/original/%D0%92%D1%80%D0%B5%D0%BC%D0%B5%D0%BD%D0%B-D%D1%8B%D0%B5_%D0%9C%D0%A0_COVID-19_%28v.10%29-08.02.2021_%281%29.pdf.
  17. Hansell DM, Bankier AA, MacMahon H, Mc- Loud TC, Müller NL, Remy J. Fleischner Society: glossary of terms for thoracic imaging. Radiology. 2008;246(3): 697–722. doi: 10.1148/radiol.2462070712.
  18. Leslie KO. My approach to interstitial lung disease using clinical, radiological and histopathological patterns. J Clin Pathol. 2009;62(5): 387–401. doi: 10.1136/jcp.2008.059782.
  19. Kligerman SJ, Franks TJ, Galvin JR. From the radiologic pathology archives: organization and fibrosis as a response to lung injury in diffuse alveolar damage, organizing pneumonia, and acute fibrinous and organizing pneumonia. Radiographics. 2013;33(7): 1951–1975. doi: 10.1148/rg.337130057.
  20. Kanne JP, Little BP, Chung JH, Elicker BM, Ketai LH. Essentials for Radiologists on COVID-19: An Update-Radiology Scientific Expert Panel. Radiology. 2020;296(2):E113–E114. doi: 10.1148/radiol.2020200527.
  21. Pan Y, Guan H, Zhou S, Wang Y, Li Q, Zhu T, Hu Q, Xia L. 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. 2020;30(6): 3306–3309. doi: 10.1007/s00330-020-06731-x.
  22. Pan F, Ye T, Sun P, Gui S, Liang B, Li L, Zheng D, Wang J, Hesketh RL, Yang L, Zheng C. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology. 2020;295(3): 715–721. doi: 10.1148/radiol.2020200370.
  23. Liang T, Liu Z, Wu CC, Jin C, Zhao H, Wang Y, Wang Z, Li F, Zhou J, Cai S, Liang Y, Zhou H, Wang X, Ren Z, Yang J. Evolution of CT findings in patients with mild COVID-19 pneumonia. Eur Radiol. 2020;30(9): 4865–4873. doi: 10.1007/s00330-020-06823-8.
  24. Wang J, Xu Z, Wang J, Feng R, An Y, Ao W, Gao Y, Wang X, Xie Z. CT characteristics of patients infected with 2019 novel corona virus: association with clinical type. Clin Radiol. 2020;75(6): 408–414. doi: 10.1016/j.crad.2020.04.001.
  25. Xu X, Yu C, Qu J, Zhang L, Jiang S, Huang D, Chen B, Zhang Z, Guan W, Ling Z, Jiang R, Hu T, Ding Y, Lin L, Gan Q, Luo L, Tang X, Liu J. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2. Eur J Nucl Med Mol Imaging. 2020;47(5): 1275–1280. doi: 10.1007/s00259-020-04735-9.
  26. Lyu P, Liu X, Zhang R, Shi L, Gao J. The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics. Invest Radiol. 2020;55(7): 412–421. doi: 10.1097/RLI.0000000000000689.
  27. Liu F, Zhang Q, Huang C, Shi C, Wang L, Shi N, Fang C, Shan F, Mei X, Shi J, Song F, Yang Z, Ding Z, Su X, Lu H, Zhu T, Zhang Z, Shi L, Shi Y. CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients. Theranostics. 2020;10(12): 5613–5622. doi: 10.7150/thno.45985.

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Copyright (c) 2021 Strutynskaya A.D., Koshurnikov D.S., Tyurin I.E., Karnaushkina M.A.

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