Generic placeholder image

Current Respiratory Medicine Reviews

Editor-in-Chief

ISSN (Print): 1573-398X
ISSN (Online): 1875-6387

Research Article

Comparison of Initial Thoracic CT Images of COVID-19 Patients with Non-Variant, Alpha, Delta, and Omicron Variants: A Retrospective Study

Author(s): Emrah Altuntas*, Meltem Ceyhan Bilgici, Muzaffer Elmalı, Arda Onar and Orhan Bas

Volume 20, Issue 1, 2024

Published on: 06 November, 2023

Page: [47 - 57] Pages: 11

DOI: 10.2174/011573398X268050231031112211

Price: $65

Abstract

Background: CT findings and Ground glass opacity (GGO) volumes may differ between SARS CoV-2 non-variant, alpha, delta, and omicron variants.

Objective: To compare the thoracic CT findings, GGO volumes, and GGOs’ lung uptake rates among patients with COVID-19 variants.

Methods: Thoracic CT images of 83 patients with non-variant, 78 patients with alpha variant, 93 patients with delta variant, and 73 patients with omicron variant having positive Real-Time Polymerase Chain Reaction test results were analyzed retrospectively. GGO volumes and lung volumes were calculated by using the Cavalieri Principle. Differences in CT findings, ground-glass opacity volumes, and lung involvement rates between non-variant and variant groups were evaluated.

Results: There were significant differences found in the incidence of GGOs (p < 0.001), air bronchogram (p = 0.007), reticulation (p = 0.002) and subpleural lines, and linear opacities (p = 0.034) between non-variant and variant groups. GGO uptake rates (ground glass opacity volumes × 100 ÷ lung volume) were 8.88% in the non-variant, 4.83% in the alpha variant, 3.50% in the delta variant, and 2.02% in the omicron variant. In estimating variant groups, it was determined that the increase in the rate of GGOs in the right lung increased the probability of having an omicron variant, whereas the presence of nodules decreased it. The possibility of the delta variant increased with an increase in the rate of ground glass opacities in the left lung.

Conclusion: Thoracic CT findings solely can be helpful in distinguishing COVID-19 variants. Decreased frequency of uptake rates of GGOs suggested that the severity of COVID-19 disease was gradually decreasing.

Keywords: COVID-19, thoracic CT, variant, ground glass opacities, Cavalieri principle.

Graphical Abstract
[1]
Cellina M, Orsi M, Valenti Pittino C, Toluian T, Oliva G. Chest computed tomography findings of COVID-19 pneumonia: pictorial essay with literature review. Jpn J Radiol 2020; 38(11): 1012-9.
[http://dx.doi.org/10.1007/s11604-020-01010-7] [PMID: 32588277]
[2]
World Health Organization (WHO). Tracking SARS-CoV-2 variants 2023. Available from: https://www.who.int/activities/tracking-SARS-CoV-2-variants
[3]
Centers for Disease Control and Prevention (CDC). COVID data tracker 2023. Available from: https://covid.cdc.gov/covid-data-tracker/#variant-proportions
[4]
Nyberg T, Ferguson NM, Nash SG, et al. Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: A cohort study. Lancet 2022; 399(10332): 1303-12.
[http://dx.doi.org/10.1016/S0140-6736(22)00462-7] [PMID: 35305296]
[5]
Liu Y, Liu J, Johnson BA, et al. Delta spike P681R mutation enhances SARS-CoV-2 fitness over Alpha variant. Cell Rep 2022; 39(7): 110829.
[http://dx.doi.org/10.1016/j.celrep.2022.110829] [PMID: 35550680]
[6]
Aydin S, Unver E, Karavas E, Yalcin S, Kantarci M. Computed tomography at every step: Long coronavirus disease. Respir Investig 2021; 59(5): 622-7.
[http://dx.doi.org/10.1016/j.resinv.2021.05.014] [PMID: 34210624]
[7]
Pan Y, Guan H, Zhou S, et al. 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): 3306-9.
[http://dx.doi.org/10.1007/s00330-020-06731-x] [PMID: 32055945]
[8]
Xie X, Zhong Z, Zhao W, Zheng C, Wang F, Liu J. Chest CT for typical 2019-nCoV pneumonia: Relationship to negative RT-PCR testing. Radiology 2020; 296: E41-5.
[http://dx.doi.org/10.1148/radiol.2020200343] [PMID: 32049601]
[9]
Penha D, Pinto eg, Matos F, et al. CO-RADS: Coronavirus classification review. J Clin Imaging Sci 2021; 11: 9.
[http://dx.doi.org/10.25259/JCIS_192_2020] [PMID: 33767901]
[10]
Majidi H, Niksolat F. Chest CT in patients suspected of COVID-19 infection: A reliable alternative for RT-PCR. Am J Emerg Med 2020; 38(12): 2730-2.
[http://dx.doi.org/10.1016/j.ajem.2020.04.016] [PMID: 32312575]
[11]
Ren LL, Wang YM, Wu ZQ, et al. Identification of a novel coronavirus causing severe pneumonia in human: A descriptive study. Chin Med J 2020; 133(9): 1015-24.
[http://dx.doi.org/10.1097/CM9.0000000000000722] [PMID: 32004165]
[12]
Rubin GD, Ryerson CJ, Haramati LB, et al. 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): 172-80.
[http://dx.doi.org/10.1148/radiol.2020201365] [PMID: 32255413]
[13]
Özel M, Aslan A, Araç S. Use of the COVID-19 reporting and data system (CO-RADS) classification and chest computed tomography involvement score (CT-IS) in COVID-19 pneumonia. Radiol Med 2021; 126(5): 679-87.
[http://dx.doi.org/10.1007/s11547-021-01335-x] [PMID: 33580449]
[14]
Yoon SH, Lee KH, Kim JY, et al. Chest radiographic and CT findings of the 2019 novel coronavirus disease (COVID-19): Analysis of nine patients treated in Korea. Korean J Radiol 2020; 21(4): 494-500.
[http://dx.doi.org/10.3348/kjr.2020.0132] [PMID: 32100485]
[15]
Li B, Li X, Wang Y, et al. Diagnostic value and key features of computed tomography in Coronavirus Disease 2019. Emerg Microbes Infect 2020; 9(1): 787-93.
[http://dx.doi.org/10.1080/22221751.2020.1750307] [PMID: 32241244]
[16]
Ye Z, Zhang Y, Wang Y, Huang Z, Song B. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): A pictorial review. Eur Radiol 2020; 30(8): 4381-9.
[http://dx.doi.org/10.1007/s00330-020-06801-0] [PMID: 32193638]
[17]
Ng MY, Lee EYP, Yang J, et al. Imaging profile of the COVID-19 infection: Radiologic findings and literature review. Radiol Cardiothorac Imaging 2020; 2(1): e200034.
[http://dx.doi.org/10.1148/ryct.2020200034] [PMID: 33778547]
[18]
Sahin B, Acer N, Sonmez OF, et al. Comparison of four methods for the estimation of intracranial volume: A gold standard study. Clin Anat 2007; 20(7): 766-73.
[http://dx.doi.org/10.1002/ca.20520] [PMID: 17708568]
[19]
Carotti M, Salaffi F, Sarzi-Puttini P, et al. Chest CT features of coronavirus disease 2019 (COVID-19) pneumonia: Key points for radiologists. Radiol Med (Torino) 2020; 125(7): 636-46.
[http://dx.doi.org/10.1007/s11547-020-01237-4] [PMID: 32500509]
[20]
Bai HX, Hsieh B, Xiong Z, et al. Performance of radiolo- gists in differentiating COVID-19 from viral pneumonia on chest CT. Radiology 2020; 296(2): E46-54.
[http://dx.doi.org/10.1148/radiol.2020200823] [PMID: 32155105]
[21]
Liu KC, Xu P, Lv WF, et al. CT manifestations of coronavirus disease-2019: A retrospective analysis of 73 cases by disease severity. Eur J Radiol 2020; 126: 108941.
[http://dx.doi.org/10.1016/j.ejrad.2020.108941] [PMID: 32193037]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy