Альманах клинической медицины. 2021; 49: 171-178
Оценка взаимосвязи рентгенологических изменений и степени тяжести заболевания у пациентов с новой коронавирусной инфекцией COVID-19
https://doi.org/10.18786/2072-0505-2021-49-028Аннотация
Актуальность. Интерпретация изменений в легких, выявленных при компьютерной томографии (КТ) у пациентов с COVID-19, в некоторых случаях неоднозначна. Сегодня не существует высокодостоверного алгоритма оценки и предсказания течения заболевания на основании рентгенологических данных.
Цель – выявить взаимосвязь рентгенологических симптомов COVID-19 и клинической картины заболевания.
Материал и методы. В обсервационное ретроспективное когортное исследование включены 92 пациента, которые были распределены в 3 группы соответственно клинической тяжести течения COVID-19 (группа легкой COVID-19 – 29 пациентов, среднетяжелой COVID-19 – 33 и тяжелой COVID-19 – 30). Всем участникам исследования проведена КТ органов грудной клетки при поступлении в стационар и на 10-й день госпитализации.
Результаты. Практически у всех пациентов (n=28; 96,6%) в группе тяжелой COVID-19 наблюдалось увеличение объема поражения легких с течением заболевания. Риск ухудшения клинической картины у этих пациентов был в 15,037 раза выше в сравнении с пациентами со стабильным объемом поражения легких. На основании данных о распространенности поражения легких можно было с достаточно высокой точностью (площадь под ROC-кривой 0,831, чувствительность 87,5%, специфичность 70,0%; p<0,001) предсказать ухудшение клинического состояния пациентов. Наличие дилатации бронхов в общей группе больных было статистически значимо (p<0,01) связано с увеличением распространенности поражения легких. У 5 (62,5%) пациентов с выявленной дилатацией бронхов зарегистрировано клиническое ухудшение.
Заключение. Компьютерно-томографический паттерн у пациентов с COVID-19 не всегда коррелирует с клинической тяжестью заболевания. Таким образом, КТ легких не может быть использована для прогнозирования течения COVID-19 без учета данных клинического и лабораторного исследований.
Список литературы
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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.
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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.
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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.
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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.
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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.
Almanac of Clinical Medicine. 2021; 49: 171-178
Evaluation of an association of radiological findings and severity of the disease in patients with the new coronavirus infection (COVID-19)
https://doi.org/10.18786/2072-0505-2021-49-028Abstract
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.
References
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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.
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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.
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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.
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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.
