Correlation between chest CT changes and T lymphocyte subsets in COVID-19_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

TANG Guangxiao , LIU Xueyan , LI Chunhua , WANG Huiqiu , SHU Weiqiang , ZHAO Jing , LIU Yu ,  LV Shengxiu

Department of Radiology, Chongqing Public Health Medical Center, Chongqing, 400036 , China;

Corresponding author：

LV Shengxiu, Email: 598341390@qq.com

Keywords：

COVID-19; Immune level; T lymphocytes; CT; CD4⁺

DOI：

10.7507/1671-6205.202311034

Video：

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Objective To evaluate the relationship between CT lesion changes in COVID-19 patients and different subgroups of T lymphocytes, providing reference information for assessing patient conditions, predicting outcomes, and evaluating treatment efficacy. Methods Clinical and imaging data of confirmed COVID-19 patients admitted to the Chongqing Public Health Medical Center from January 24 to March 15, 2020, were collected. Based on the absorption characteristics of lesions in CT images, patients were categorized into three groups: Group A (obviously continuously absorbed), Group B (stable-slow absorption), and Group C (progressive absorption). The relationship between CT changes and T lymphocyte subgroups was analyzed according to lesion absorption. Results A total of 47 patients were included, with 18 in Group A, 14 in Group B, and 15 in Group C. At different stages—admission, during treatment, and at the end of treatment—the levels of T lymphocytes were observed as follows: Group A>Group B>Group C. When lesions were absorbed, the average count of CD4⁺ T lymphocytes was (544.43 ± 163.34) cells/μl; when lesions showed little change or increased, CD4⁺ T lymphocyte levels decreased to varying degrees. During treatment, both Group A and Group B showed CD4⁺ T lymphocyte levels returning to above normal levels, with an average increase of 134 cells/μl in Group A, which was lower than that in Group B (192 cells/μl) and Group C (149 cells/μl). Finally, T lymphocyte levels reached normal in all groups, but Group A levels were higher than those in Groups B and C (P<0.05). Upon follow-up, the average CD4⁺ T lymphocyte count was (544.43 ± 163.34) cells/μl in 52 cases of lesion absorption, (339.06 ± 145.98) cells/μl in 31 cases of minimal change, and (230.50 ± 95.24) cells/μl in 16 cases of lesion progression, with statistically significant differences among the three groups (P<0.05). Conclusions The increase in lung lesions in patients indicates poor immune function, necessitating enhanced immune regulation. Conversely, if a decrease in T lymphocyte levels is detected during the course of the disease, attention should be given to the risk of lesion progression, and timely CT re-examinations should be conducted to monitor changes in lesions.

Citation： TANG Guangxiao, LIU Xueyan, LI Chunhua, WANG Huiqiu, SHU Weiqiang, ZHAO Jing, LIU Yu, LV Shengxiu. Correlation between chest CT changes and T lymphocyte subsets in COVID-19. Chinese Journal of Respiratory and Critical Care Medicine, 2024, 23(10): 691-695. doi: 10.7507/1671-6205.202311034 Copy

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1. Coronavirus disease (COVID-19). https://www.who.int/news-room/fact-sheets/detail/coronavirus-disease-.
2. Wu Z, McGoogan JM. 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 [published online ahead of print, 2020 Feb 24]. JAMA, 2020;10.1001/jama. 2020.2648.
3. Li YX, Wu W, Yang T, et al. Characteristics of Peripheral Blood Leukocyte Differential Counts in Patients With COVID-19. Zhonghua Nei Ke Za Zhi, 2020, 59(5): 372-374.
4. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223): 507–513.
5. Chen Y, Liu Q, Guo D. Emerging coronaviruses: Genome structure, replication, and pathogenesis. J Med Virol, 2020, 92(4): 418-423.
6. Wang W, Tang J, Wei F. Updated understanding of the outbreak of 2019 novel coronavirus (2019-nCoV) in Wuhan, China. J Med Virol, 2020, 92(4): 441-447.
7. Salehi S, Abedi A, Balakrishnan S, et al. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients [published online ahead of print, 2020 Mar 14]. AJR Am J Roentgenol, 2020, 215(1): 87-93.
8. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet, 2020, 395(10223): 507-513.
9. Pan F, Ye T, Sun P, et al. Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Pneumonia. Radiology, 2020, 295(3): 715-721.
10. Wang X, Xu W, Hu G, et al. Retraction Note to: SARS-CoV-2 infects T lymphocytes through its spike protein-mediated membrane fusion. Cell Mol Immunol, 2020, 17(8): 894.
11. Qin C, Zhou L, Hu Z, et al. Dysregulation of Immune Response in Patients With Coronavirus 2019 (COVID-19) in Wuhan, China. Clin Infect Dis. 2020 Jul 28;71(15): 762-768.
12. Wang F, Nie J, Wang H, et al. Characteristics of peripheral lymphocyte subset alteration in COVID-19 pneumonia J Infect Dis, 2020, 221(11): 1762-1769.
13. Li G, Fan Y, Lai Y, et al. Coronavirus infections and immune responses. J Med Virol. 2020;92(4): 424–432.
14. Cao X. COVID-19: immunopathology and its implications for therapy. Nat Rev Immunol, 2020, 20(5): 269-270.

Chinese Journal of Respiratory and Critical Care Medicine

Correlation between chest CT changes and T lymphocyte subsets in COVID-19

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