ISSN 1004-4140
CN 11-3017/P

COVID-19相关性血管异常的薄层CT特征分析

李兴鹏, 袁辉, 杜常月, 刘晓燕, 李玲, 刘梦珂, 张怡梦, 张妍, 郝琪, 段淑红, 王仁贵

李兴鹏, 袁辉, 杜常月, 等. COVID-19相关性血管异常的薄层CT特征分析[J]. CT理论与应用研究, 2023, 32(5): 667-674. DOI: 10.15953/j.ctta.2023.026.
引用本文: 李兴鹏, 袁辉, 杜常月, 等. COVID-19相关性血管异常的薄层CT特征分析[J]. CT理论与应用研究, 2023, 32(5): 667-674. DOI: 10.15953/j.ctta.2023.026.
LI X P, YUAN H, DU C Y, et al. Analysis of Thin Slice Computed Tomography Features of Coronavirus Disease 2019 Related Vascular Abnormalities[J]. CT Theory and Applications, 2023, 32(5): 667-674. DOI: 10.15953/j.ctta.2023.026. (in Chinese).
Citation: LI X P, YUAN H, DU C Y, et al. Analysis of Thin Slice Computed Tomography Features of Coronavirus Disease 2019 Related Vascular Abnormalities[J]. CT Theory and Applications, 2023, 32(5): 667-674. DOI: 10.15953/j.ctta.2023.026. (in Chinese).

COVID-19相关性血管异常的薄层CT特征分析

详细信息
    作者简介:

    李兴鹏: 男,首都医科大学在读硕士,主要从事胸部影像学和淋巴影像学等方面研究,E-mail:lxp17634986228@163.com

    通讯作者:

    段淑红: 女,首都医科大学附属北京世纪坛医院感染科主任医师,主要从事感染性疾病临床工作,E-mail:duanshuhong@bjsjth.cn

    王仁贵: 男,医学博士,首都医科大学附属北京世纪坛医院放射科主任、主任医师、教授、博士生导师,主要从事淋巴影像学、呼吸肿瘤和肺部弥漫性疾病的影像学研究,E-mail:wangrg@bjsjth.cn

  • 中图分类号: R  814;R  563.1

Analysis of Thin Slice Computed Tomography Features of Coronavirus Disease 2019 Related Vascular Abnormalities

  • 摘要: 目的:探讨胸部薄层CT平扫对新型冠状病毒感染(COVID-19)相关性血管异常的CT特征分析的临床价值。材料与方法:回顾性收集2022年12月5日至2022年12月17日北京世纪坛医院感染科确诊COVID-19且胸部薄层CT平扫图像显示有病变累及血管的患者73例,所有患者有完整的胸部薄层CT平扫资料和有较完整的临床资料。依据年龄>60岁和≤60岁将患者分为老年组和青壮年组,观察所有患者胸部影像学表现,并进行不同年龄组间统计学分析。结果:73例COVID-19患者中,青壮年组和老年组组间对比有统计学意义的影像学指标如下:病变分布中央血管周、病变大小10~30 mm、病变大小>30 mm、病变占肺叶体积百分比≤30%、病变占肺叶体积百分比>50%(白肺)、病变形态大片状、病变优势类型腺泡样、血管扭曲、血管周缘模糊、树芽征、粗大纤维索条。结论:①胸部薄层 CT平扫可明确COVID-19相关性血管异常的病变数量、位置、累及部位、范围、血管异常和病变类型,对COVID-19血管异常的定性诊断和鉴别诊断有一定的意义;②胸部薄层CT平扫检查对于发现临床症状不典型但有COVID-19累及血管的老年患者有重要意义;③COVID-19相关性“血管增粗”既可以是血管本身管径的增粗,也可以由血管周围间质炎性水肿造成。
    Abstract: Objective: This study aimed to explore the clinical value of thin slice computed tomography (CT) plain scan in the analysis of CT features of vascular abnormalities associated with coronavirus disease 2019 (COVID-19). Materials and methods: A total of 73 patients with COVID-19 confirmed by the Department of Infection of Beijing Shijitan Hospital from December 5, 2022 to December 17, 2022, were included in the study. Chest thin CT plain scan images showed that the lesions involved blood vessels were retrospectively collected. All patients had complete chest thin CT plain scan and relatively complete clinical data. According to age (>60 and ≤60 years), the patients were divided into the young and elderly groups. The chest imaging manifestations of all patients were observed and statistically analyzed between different age groups. Results: Among the 73 patients with COVID-19, the imaging indexes with statistical significance between the young and elderly groups were as follows: the distribution of the lesion around the central blood vessel, size of the lesion (10~30 mm), size of the lesion (>30 mm), percentage of the lesion to the volume of the lung lobe (≤30), percentage of the lesion to the volume of the lung lobe (>50) (white lung), shape of the lesion was large, the dominant type of the lesion was acinar, vascular distortion, vascular margin fuzzy, and tree-bud sign thick fiber rope. Conclusion: (1) Chest thin-slice CT plain scan can identify the number, location, involved location, scope, vascular abnormality, and pathological type of COVID-19-related vascular abnormality, which has certain significance for the qualitative and differential diagnosis of COVID-19 vascular abnormality. (2) The chest thin CT plain scan is of great significance for finding elderly patients with COVID-19 involving blood vessels. (3) COVID-19-related "blood vessel thickening" can be caused by either the diameter of the blood vessel itself or the inflammatory edema of the perivascular interstitium.
  • 图  1   病变优势类型

    Figure  1.   Dominant types of lesions

    图  2   COVID-19相关性血管异常表现

    Figure  2.   Abnormal manifestations of COVID-19-related vessels

    图  3   特殊征象类型

    Figure  3.   Special sign types

    表  1   COVID-19不同年龄组的临床指标比较

    Table  1   Comparison of clinical indicators of COVID-19 in different age groups

    临床指标组别统计检验
    青壮年组(年龄≤60岁;
    n=29)
    老年组(年龄>60;
    n=44)
    $\chi^2 /t$P
      平均年龄/岁40.6±12.676.9±9.8-13.806 0.00
      性别/例(%)     男18(62.1)34(77.3)1.9720.16
         女11(37.9)10(22.7)1.9720.16
      病程/d4.6±2.44.0±2.90.8030.42
      发热/例(%)29(100.0) 44(100.0)
      咳嗽/例(%)19(65.5)30(68.2)0.0560.81
      咽痛/例(%)13(44.8)14(31.8)1.2690.26
      胸闷/例(%)1(3.4)4(9.1)0.64
      气憋/例(%)1(3.4)4(9.1)0.64
    下载: 导出CSV

    表  2   COVID-19不同年龄组的影像学指标比较

    Table  2   Comparison of imaging indicators of COVID-19 in different age groups

    影像学指标组别统计检验
    青壮年组(年龄
    ≤60岁;n=29)
    老年组(年龄
    >60;n=44)
    $\chi^2 /t$P
      病变数量/例(%)  单发2(6.9)0(0.0) 0.15
      多发27(93.1)44(100.0)0.15
      ≤106(20.7)12(27.3)0.4080.52
      >1021(72.4)32(72.7)0.0010.98
      病变分布/例(%)  单叶2(6.9)1(2.3)0.56
      单肺4(13.8)3(6.8)0.43
      双肺23(79.3)40(90.9)0.18
      胸膜内26(89.7)38(86.4)1.00
      中央血管束周18(62.1)39(88.6)7.2090.01
      累及部位/例(%)  气道27(93.1)42(95.5)1.00
      血道29(100.0) 44(100.0)
      间质27(93.1)39(88.6)0.70
      混合 29(100.0) 44(100.0)1.00
      病变大小/例(%)  ≤10 mm1(3.4)1(2.3)1.00
      10~30 mm11(38.0)6(13.6)5.7750.02
      >30 mm17(58.6)37(84.1)5.8900.02
      病变占肺叶体积百分比
      (半定量分析)/例(%)
      ≤106(20.7)8(18.1)0.0710.79
      ≤3018(62.1)16(36.4)4.6420.03
      ≤504(13.8)9(20.5)0.5300.47
      >50(白肺)1(3.4)11(25.0)0.02
      病变形态/例(%)  小结节8(27.6)7(15.9)1.4600.23
      斑片状25(86.2)33(75.0)1.3450.25
      大片状14(48.3)36(81.8)5.6700.02
      束带状4(13.8)6(13.6)1.00
      混合型16(55.2)30(68.2)1.2690.26
      病变密度/例(%)  GGO26(89.7)34(77.3)1.8310.18
      实变12(41.4)20(45.5)0.1180.73
      网格影11(37.9)21(47.7)0.6810.41
      蜂窝影  0(0.0) 3(6.8)0.27
      病变优势类型/例(%)  OP样13(44.8)13(29.5)1.7800.18
      细支气管炎样10(34.5)15(34.1)0.0010.97
      NSIP样  0(0.0) 5(11.4)0.15
      UIP样  0(0.0) 3(6.8)0.27
      叶段实变样2(6.9)8(18.2)0.30
      腺泡样4(13.8)  0(0.0) 0.02
      病变边缘/例(%)  模糊25(86.2)41(93.2)0.43
      清楚4(13.8)3(6.8)0.43
      不规则17(58.6)34(77.3)2.8880.09
      血管异常/例(%)  血管增粗28(96.6)44(100.0)0.40
      血管扭曲2(6.9)16(36.4)8.1700.00
      血管周GGO/实变29(100.0)44(100.0)
      血管与伴行气管
      比例增大
    17(58.6)20(45.5)1.2120.27
      血管周缘模糊23(79.3)31(70.5)7.2900.01
      其他特殊征象/例(%)  胸腔积液  0(0.0) 4(9.1)0.15
      晕征14(48.3)22(50.0)0.0210.89
      反晕征5(17.2)8(18.2)0.0110.92
      拱廊征5(17.2)10(22.7)0.3220.57
      铺路石征11(37.9)18(40.9)0.0650.80
      胸膜下线8(27.6)21(47.7)2.9610.09
      支气管充气征9(31.0)16(36.4)0.2200.64
      树芽征9(31.0)1(2.3)0.00
      粗大纤维索条9(31.0)27(61.4)6.4330.01
    下载: 导出CSV
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  • 期刊类型引用(2)

    1. 高子晴,卢吴柱,叶大林,林宇红,陈晓波. 床旁超声无创性评估新型冠状病毒感染中型患者肺部病变的临床研究. 中国中西医结合影像学杂志. 2023(04): 428-431 . 百度学术
    2. 林军,李焕兴,罗槑,陈竹,吴桂辉,曾义岚. 新型冠状病毒肺炎患者肺部超声特征. 中华实验和临床感染病杂志(电子版). 2021(01): 37-45 . 百度学术

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出版历程
  • 收稿日期:  2023-02-23
  • 修回日期:  2023-03-22
  • 录用日期:  2023-03-26
  • 网络出版日期:  2023-04-23
  • 发布日期:  2023-09-21

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