ISSN 1004-4140
CN 11-3017/P

胸部薄层CT平扫对于重型新型冠状病毒感染的诊断价值

The Clinical Value of Thin-section Chest Computed Tomography Scan for the Classification of Coronavirus Disease 2019 (COVID-19)

  • 摘要: 目的:探讨胸部薄层CT平扫在新型冠状病毒感染(COVID-19)分型中的临床价值。方法:回顾性分析2022年12月20日至2022年12月31日于我院感染科诊断为COVID-19的134例患者,所有患者均行胸部薄层CT平扫检查,并具有完整的临床资料。根据临床分型将患者分为非重症组和重症组,对比分析两组患者的临床资料和肺部影像学特征并进行统计学分析。结果:两组间合并糖尿病的差异具有统计学意义,且重症组(45.8%)合并糖尿病的发生率高于非重症组(25.5%);两组间性别、年龄、平均病程及临床症状的差异均无统计学意义;两组之间病变数量、对称性分布、周围为主分布、弥漫分布、边缘模糊、大片状、束带状、血管束增厚、铺路石征、拱廊征以及煎蛋征的差异有统计学意义;重症组的病灶数量>10个、弥漫分布、大片状、束带状、血管束增厚、铺路石征、拱廊征的发生率高于非重症组,而非重症组的周围为主分布、边缘模糊以及煎蛋征的发生率高于重症组。结论:胸部薄层CT平扫能够明确新冠患者肺部异常影像学表现,评估病变的数量、分布范围及形态特点,合并基础病、病变数量、分布特点、边缘模糊、大片状、束带状、血管束增厚及铺路石征、拱廊征、煎蛋征等特殊征象能有效提示COVID-19分型,为COVID-19的诊治提供更多影像依据。

     

    Abstract: Objective: To investigate the clinical value of thin-section chest computed tomography (CT) in the typing of coronavirus disease 2019 (COVID-19). Methods: A retrospective analysis was performed on 134 patients diagnosed with COVID-19 in our hospital’s Department of Infectious Diseases from December 20, 2022, to December 31, 2022. All patients underwent thin-section chest CT scan with complete clinical data. According to clinical classification, patients were divided into the non-severe and severe groups. Clinical data and imaging features of the two groups were compared and analyzed, and statistical analysis was conducted. Results: There was a statistically significant difference with respect to diabetes mellitus between the two groups, and the incidence of diabetes mellitus in the severe group (45.8%) was higher than that in the non-severe group (25.5%); There were no significant differences in sex, age, average course of disease, and clinical symptoms between the two groups; There were significant differences in the number of lesions, symmetrical distribution, predominant peripheral distribution, diffuse distribution, blurred edge, morphology of large flake and band, vascular bundle thickening, paving stone sign, arcade sign, and fried egg sign between the two groups, the number of lesions >10, diffuse distribution, morphology of large flake and band, vascular bundle thickening, paving stone sign, and arcade sign were more common in the severe group than in the non-severe group, while predominant peripheral distribution, blurred edge, and fried egg sign were more common in the non-severe group than in the severe group. Conclusions: Thin-section chest CT scan can identify the abnormal imaging manifestations of the lung in patients with COVID-19 and evaluate the number, distribution range, and morphological characteristics of the lesions. Combined background diseases, number, distribution characteristics, blurred edge, large flake and band morphology, vascular bundle thickening, paving stone sign, arcade sign, and fried egg sign can effectively indicate the classification of patients with COVID-19. This can provide imaging evidence for the diagnosis and treatment of COVID-19.

     

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