[Home ] [Archive]    
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
IJRR Information::
For Authors::
For Reviewers::
Subscription::
News & Events::
Web Mail::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
ISSN
Hard Copy 2322-3243
Online 2345-4229
..
Online Submission
Now you can send your articles to IJRR office using the article submission system.
..

AWT IMAGE

AWT IMAGE

:: Volume 20, Issue 3 (7-2022) ::
Int J Radiat Res 2022, 20(3): 579-585 Back to browse issues page
Identifying features and severity of 2019 coronavirus disease (COVID-19) on admission based on thoracic computer tomography
Z. Mo , Q. Zhang , X.W. Luo , Y. Zhang , T. Qin , Y.Z. Zhu
Department of Radiology, The 901st Hospital of the Joint Logistics Support Force of PLA, Heifei 230031, People Republic of China , zhangyu105fsk@163.com
Abstract:   (845 Views)
Background: To investigate the computer tomography (CT) features of 2019 coronavirus disease (COVID-19)-related pneumonia and its value for identifying severity. Materials and Methods: Seventy-three patients with COVID-19 were divided into severe and nonsevere groups. CT signs were divided into two states: presence and absence; involvement range was divided into four grades; and affected lobes were divided into two states: ≥3 lobes and < 3 lobes; laboratory indices were divided into two states: normal and abnormal; co-occurrence of signs was divided into three states: ground-glass opacity (GGO) plus consolidation, only GGO, or only consolidation. The numbers of patients were respectively recorded. Statistical analysis was performed through the χ2 test, followed by multivariate logistic regression analysis. Results: Some indicators differed, including pure GGO (p<0.001), GGO with focal consolidation (p=0.009), patchy consolidation (p=0.004), sheeted consolidation (p<0.001), fibrotic appearance (p=0.020), involvement grade (p<0.001), affected lobes (p=0.027), pleural effusion (p=0.001), subpleural line (p=0.015), crazy paving signs (p<0.001), halo signs (p=0.020), thickened bronchial walls (p<0.001), air bronchi signs (p=0.003), lesions in mid/inner zone (p<0.001), liver function (p=0.044), interleukin-6 (p<0.001), c-reactive protein (p<0.001), lymphocyte count (p<0.001), and age (p=0.036). Pure GGO (OR:30.711, HR:1.292~729.882, p=0.034) and involvement grade (OR:0.017, HR:0.001~0.342, p=0.008) were independent risk factors. Conclusion: On admission, CT signs of COVID-19-related pneumonia were diverse but characteristic, and some CT findings may be potential warning factors for severity, while a lack of GGO and extensive pneumonia may be independent risk factors.
Keywords: 2019 coronavirus disease, pneumonia, Tomography, X-ray compute.
Full-Text [PDF 1908 kb]   (389 Downloads)    
Type of Study: Original Research | Subject: Radiation Biology
References
1. Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al. (2020) Time Course of Lung Changes on Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Pneumonia. Radiology, 295(3): 715-721. [DOI:10.1148/radiol.2020200370] [PMID] []
2. Coronaviridae Study Group of the International Committee on Taxonomy of Viruses (2020) The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol, 5(4): 536-544. [DOI:10.1038/s41564-020-0695-z] [PMID] []
3. Jiang S, Shi Z, Shu Y, Song J, Gao GF, Tan W, et al. (2020) A distinct name is needed for the new coronavirus. Lancet, 395(10228): 949. [DOI:10.1016/S0140-6736(20)30419-0]
4. Wu Z and McGoogan JM (2020) Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA, 323(13): 1239-1242. [DOI:10.1001/jama.2020.2648] [PMID]
5. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. (2020) Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med, 382(18): 1708-1720. [DOI:10.1056/NEJMoa2002032] [PMID] []
6. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. (2020) Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet, 395(10224): 565-574. [DOI:10.1016/S0140-6736(20)30251-8]
7. Yu WB, Tang GD, Zhang L, Corlett RT (2020) Decoding the evolution and transmissions of the novel pneumonia coronavirus (SARS-CoV-2 / HCoV-19) using whole genomic data. Zool Res, 41(3): 247-257.
8. He X, Zheng J, Ren J, Zheng G, Liu L (2020) Chest high-resolution computed tomography imaging findings of coronavirus disease 2019 (Covid-19) pneumonia. Int J Radiat Res, 18(2): 343-349.
9. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, 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, 296(2): E32-E40. [DOI:10.1148/radiol.2020200642] [PMID] []
10. Wang YXJ, Liu WH, Yang M, Chen W (2020) The role of CT for Covid-19 patient's management remains poorly defined. Ann Transl Med, 8(4): 145. [DOI:10.21037/atm.2020.02.71] [PMID] []
11. Song F, Shi N, Shan F, Zhang Z, Shen J, Lu H, et al. (2020) Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia. Radiology, 295(1): 210-217. [DOI:10.1148/radiol.2020200274] [PMID] []
12. Lieveld AWE, Azijli K, Teunissen BP, van Haaften RM, Kootte RS, van den Berk IAH, et al. (2021) Chest CT in COVID-19 at the ED: Validation of the COVID-19 Reporting and Data System (CO-RADS) and CT severity score: a prospective, multicenter, observational study. Chest, 159(3):1126-1135. [DOI:10.1016/j.chest.2020.11.026] [PMID] []
13. Zhang K, Liu X, Shen J, Li Z, Sang Y, Wu X, et al. (2020) Clinically applicable Ai system for accurate diagnosis, quantitative measurements, and prognosis of COVID-19 pneumonia using computed tomography. Cell, 182(5): 1360. https://doi.org/10.1016/j.cell.2020.04.045 [DOI:10.1016/j.cell.2020.08.029] [PMID] []
14. Metlay JP, Waterer GW, Long AC, Anzueto A, Brozek J, Crothers K, et al. (2019) Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America. Am J Respir Crit Care Med, 200(7): e45-e67. [DOI:10.1164/rccm.201908-1581ST] [PMID] []
15. Hansell DM, Bankier AA, MacMahon H, McLoud TC, Müller NL, Remy J (2008) Fleischner Society: glossary of terms for thoracic imaging. Radiology, 246(3): 697-722. [DOI:10.1148/radiol.2462070712] [PMID]
16. Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X, et al. (2020) CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology, 295(1): 202-207. [DOI:10.1148/radiol.2020200230] [PMID] []
17. Jin YH, Cai L, Cheng ZS, Cheng H, Deng T, Fan YP, et al. (2020)A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Mil Med Res, 7(1): 4.
18. Pan Y, Guan H, Zhou S, Wang Y, Li Q, Zhu T, 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, 30(6): 3306-3309. [DOI:10.1007/s00330-020-06731-x] [PMID] []
19. Cheng ZJ and Shan J (2020) 2019 Novel coronavirus: where we are and what we know. Infection, 48(2): 155-163. https://doi.org/10.20944/preprints202001.0381.v1 [DOI:10.1007/s15010-020-01401-y]
20. Tian S, Hu W, Niu L, Liu H, Xu H, Xiao SY (2020) Pulmonary pathology of Early-phase (2020) 2019 novel coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer. J Thorac Oncol, 15(5): 700-704. [DOI:10.1016/j.jtho.2020.02.010] [PMID] []
21. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, et al. (2020) Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med, 8(4): 420-422. [DOI:10.1016/S2213-2600(20)30076-X]
22. Alves GR, Marchiori E, Irion K, Nin CS, Watte G, Pasqualotto AC, et al. (2016) The halo sign: HRCT findings in 85 patients. J Bras Pneumol, 42(6): 435-439. [DOI:10.1590/s1806-37562015000000029] [PMID] []
23. Godoy MC, Viswanathan C, Marchiori E, Truong MT, Benveniste MF, Rossi S, et al. (2012) The reversed halo sign: update and differential diagnosis. Br J Radiol, 85(1017): 1226-1235. [DOI:10.1259/bjr/54532316] [PMID] []
24. Ooi GC and Daqing M (2003) SARS: radiological features. Respirology, 8(1): S15-9. [DOI:10.1046/j.1440-1843.2003.00519.x] [PMID] []
25. Ajlan AM, Ahyad RA, Jamjoom LG, Alharthy A, Madani TA (2014) Middle East respiratory syndrome coronavirus (MERS-CoV) infection: chest CT findings. AJR Am J Roentgenol, 203(4): 782-787. [DOI:10.2214/AJR.14.13021] [PMID]
26. Bradley BT and Bryan A (2019) Emerging respiratory infections: The infectious disease pathology of SARS, MERS, pandemic influenza, and Legionella. Semin Diagn Pathol, 36(3): 152-159. [DOI:10.1053/j.semdp.2019.04.006] [PMID] []
27. Liu J, Zheng X, Tong Q, Li W, Wang B, Sutter K, et al. (2020) Overlapping and discrete aspects of the pathology and pathogenesis of the emerging human pathogenic coronaviruses SARS-CoV, MERS-CoV, and 2019-nCoV. J Med Virol, 92(5): 491-494. [DOI:10.1002/jmv.25709] [PMID] []
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML     Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mo Z, Zhang Q, Luo X, Zhang Y, Qin T, Zhu Y. Identifying features and severity of 2019 coronavirus disease (COVID-19) on admission based on thoracic computer tomography. Int J Radiat Res 2022; 20 (3) :579-585
URL: http://ijrr.com/article-1-4343-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 20, Issue 3 (7-2022) Back to browse issues page
International Journal of Radiation Research
Persian site map - English site map - Created in 0.06 seconds with 50 queries by YEKTAWEB 4645