ISSN 1004-4140
CN 11-3017/P

基于深度学习的CT定量指标对糖尿病合并新型冠状病毒肺部感染的影像学研究

李玲, 张明霞, 孙莹, 段淑红, 郭佳, 杜常月, 刘梦珂, 张怡梦, 孙磊, 霍萌, 王仁贵

李玲, 张明霞, 孙莹, 等. 基于深度学习的CT定量指标对糖尿病合并新型冠状病毒肺部感染的影像学研究[J]. CT理论与应用研究, 2023, 32(3): 373-379. DOI: 10.15953/j.ctta.2023.020.
引用本文: 李玲, 张明霞, 孙莹, 等. 基于深度学习的CT定量指标对糖尿病合并新型冠状病毒肺部感染的影像学研究[J]. CT理论与应用研究, 2023, 32(3): 373-379. DOI: 10.15953/j.ctta.2023.020.
LI L, ZHANG M X, SUN Y, et al. Imaging Study of COVID-19 Patients with Diabetes Mellitus by Computed Tomograpgh Quantitative Indicators Based on Deep Learning[J]. CT Theory and Applications, 2023, 32(3): 373-379. DOI: 10.15953/j.ctta.2023.020. (in Chinese).
Citation: LI L, ZHANG M X, SUN Y, et al. Imaging Study of COVID-19 Patients with Diabetes Mellitus by Computed Tomograpgh Quantitative Indicators Based on Deep Learning[J]. CT Theory and Applications, 2023, 32(3): 373-379. DOI: 10.15953/j.ctta.2023.020. (in Chinese).

基于深度学习的CT定量指标对糖尿病合并新型冠状病毒肺部感染的影像学研究

详细信息
    作者简介:

    李玲: 女,首都医科大学附属北京世纪坛医院住院医师,主要从事神经及呼吸系统影像诊断学,E-mail:liling.1995@qq.com

    通讯作者:

    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中心主任、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: O  242;R  814

Imaging Study of COVID-19 Patients with Diabetes Mellitus by Computed Tomograpgh Quantitative Indicators Based on Deep Learning

  • 摘要: 目的:探讨基于深度学习的CT定量指标对糖尿病合并新型冠状病毒感染(COVID-19)患者肺部感染的影像学特征分析。资料与方法:回顾性纳入2022年12月至2023年1月首都医科大学附属北京世纪坛医院感染科收治的COVID-19患者的临床及影像学数据,根据患者的糖尿病史分为糖尿病组及非糖尿病组,通过单因素分析两组的临床及CT定量影像学特征。结果:共纳入112例COVID-19患者,年龄26~95岁,平均(70.4±14.4)岁,女性占比44.6%(50/112例)。在临床方面,糖尿病组的C反应蛋白水平明显升高。在定量指标方面,糖尿病组患者的全肺及左肺病灶数目、病灶体积、病灶占比更大,糖尿病组的纵隔淋巴结数目更多;此外,糖尿病组患者的磨玻璃病灶及实性病灶体积更大,其磨玻璃实性病灶体积比更小。在影像学征象方面,糖尿病组患者的病灶形态呈大片状、束带状比例更高,其存在晕征、空气支气管征、空气潴留征、马赛克灌注及胸膜下黑带的比例更高。结论:糖尿病合并COVID-19患者的肺部病变具有相对的特征性,基于深度学习的CT定量指标显示糖尿病组的COVID-19患者肺部受累的病变范围更大、程度更重,其实性病灶成分占比相对增加。
    Abstract: Objective: To investigate the imaging characteristics of coronavirus disease 2019 (COVID-19) patients with diabetes mellitus using deep learning-based quantitative computed tomograpgh (CT) indicators. Materials and methods: The clinical and imaging data of 112 COVID-19 patients admitted to the Department of Infection, Beijing Shijitan Hospital, Capital Medical University, from December 2022 to January 2023 were retrospectively collected. The patients were divided into diabetic and non-diabetic groups according to their diabetes history, and the clinical and quantitative CT imaging characteristics of the two groups were analyzed using univariate analysis. Results: A total of 112 patients with COVID-19, aged 26-95 years (mean, (70.4±14.4) years), were included in the study, and 44.6% (50/112 cases) were female. In terms of clinical features, C-reactive protein levels were significantly higher in the diabetic group. In terms of CT quantitative indicators, patients in the diabetic group had higher number of whole lung and left lung lesions, lesion volume, and mediastinal lymph nodes than patients in the non-diabetic group. In addition, patients in the diabetic group had a larger volume of ground glass opacity and solid opacity, and patients in the diabetic group had a smaller volume ratio of ground glass opacity and solid opacity in terms of imaging signs, patients in the diabetic group had a higher proportion of lesions with large patchy and banded patterns, and they had a higher proportion of halo signs, air bronchial signs, air trapping signs, mosaic perfusion signs, and subpleural black bands. Conclusion: Pulmonary lesions in patients with diabetes combined with COVID-19 have characteristic features, and deep learning-based quantitative CT indicators, particularly the solid opacity observed in the lungs, can provide valuable information on the extent and severity of lesions in these patients.
  • 图  1   糖尿病合并COVID-19患者的胸部CT病灶征象

    患者,男,82岁,发热、咳嗽、咳痰3日就诊,既往合并糖尿病病史,就诊时C反应蛋白为82.61 mg/L、淋巴细胞百分比10.30%、中性粒细胞百分比为85.10%。(a)~(c)显示了基于深度学习的CT定量软件对病灶的划分;(d)~(f)显示了患者胸部CT病灶呈斑片状、大片状、束带状分布,可见马赛克灌注((d)星号)、铺路石征((d)箭头)、胸膜下黑带((e)箭头)及胸膜凹陷征((f)箭头)。

    Figure  1.   Chest CT lesion signs in COVID-19 patients with diabetes mellitus

    表  1   糖尿病合并COVID-19患者的临床资料

    Table  1   Clinical information of COVID-19 patients with diabetes mellitus

    临床指标组别统计检验
    糖尿病组(39例)非糖尿病组(73例)$Z/\chi ^2 $P
      年龄/岁($M(Q_1,Q_3)$) 73.0(66.0,84.0) 70.0(62.0,79.5)-1.6070.108
      性别(男,例(%))25(64.1) 37(50.7) 1.8520.174
      发病时间/天($M(Q_1,Q_3)$) 7(5.0,10.0) 7(5.5,10.0)-1.1220.262
      临床症状/例(%)
        发热39(100.0) 73(100.0)
        喘憋8(20.5) 14(19.2) 0.0290.865
        咳嗽36(92.3) 67(91.8) 1.000
        咳痰20(51.3) 37(50.7) 0.0040.952
        咽痛16(41.0) 30(41.1) <0.001 0.994
        流涕11(28.2) 26(35.6) 0.6310.427
        肌痛4(10.3) 4(5.5) 0.446
      实验室指标/(指标值$(M(Q_1,Q_3)$)
        C反应蛋白/(mg/L) 35.2(14.2,76.9)19.9(5.6,44.5)-2.5190.012
        白细胞/(×109/L)6.4(4.5,7.8)6.4(5.0,8.0)-0.6840.494
        淋巴细胞百分比/% 21.0(13.3,26.4) 22.8(16.3,32.1)-1.3740.169
        单核细胞百分比/%6.3(5.1,9.4)7.0(5.7,9.0)-0.7850.432
        中性粒细胞百分比/% 70.1(64.3,81.5) 66.4(58.2,75.5)-1.8170.069
        淋巴细胞/(×109/L)1.3(0.8,1.9)1.4(1.1,1.9)-1.6550.098
        单核细胞/(×109/L)0.4(0.3,0.6)0.5(0.4,0.6)-1.7050.088
        中性粒细胞/(×109/L)4.2(3.2,6.0)4.1(3.1,5.8)-0.0370.971
    下载: 导出CSV

    表  2   糖尿病合并COVID-19患者的CT影像定量指标情况

    Table  2   Quantitative CT imaging indicators in COVID-19 patients with diabetes mellitus

    病变分布组别统计检验
    糖尿病组(39例)非糖尿病组(73例)$Z/\chi^2 $P
    病灶数目/(个,$M(Q_1,Q_3)$)     全肺 8.0(5.0,12.0)6.0(3.0,9.0)-2.2690.023
         左肺4.0(2.0,6.0)2.0(2.0,4.0)-2.3730.018
         右肺3.0(3.0,7.0)3.0(2.0,5.0)-1.5690.117
    病灶体积/(cm3,$M(Q_1,Q_3)$)     全肺 317.3(69.9,666.4) 152.3(26.3,378.6)-2.6480.008
         左肺 133.0(24.2,320.6) 36.0(5.9,130.3)-3.3870.001
         右肺 134.2(31.8,397.6) 97.8(11.0,242.5)-1.7930.073
    病灶占比/(%,$M(Q_1,Q_3)$)     全肺 9.3(1.7,19.0)4.1(0.6,9.5)-2.6020.009
         左肺10.3(1.4,17.3)2.1(0.4,6.7)-3.2320.001
         右肺 7.2(1.2,25.2) 3.8(0.6,10.3)-1.8620.063
    磨玻璃病灶体积/(cm3,$M(Q_1,Q_3)$) 254.7(62.9,487.5) 125.3(23.3,311.7)-2.4830.013
    实性病灶体积/(cm3, $M(Q_1,Q_3)$) 52.9(6.7,172.2)18.1(2.2,53.9)-3.0200.003
    磨玻璃病灶占比/(%, $M(Q_1,Q_3)$) 82.6(73.1,91.5) 85.8(79.9,93.7)-2.1800.029
    实性病灶占比/(%, $M(Q_1,Q_3)$)17.4(8.5,26.9)14.2(6.3,20.1)-2.1770.029
    磨玻璃实性病灶体积比/(%,$M(Q_1,Q_3)$) 4.8(2.7,10.8) 6.0(4.0,15.0)-2.1710.030
    纵隔淋巴结/(个,$M(Q_1,Q_3)$)2.0(1.0,3.0)1.0(0,2.0) -3.848<0.001
    下载: 导出CSV

    表  3   糖尿病合并COVID-19患者的胸部CT病灶征象情况

    Table  3   Chest CT lesion signs in COVID-19 patients with diabetes mellitus

    影像指标组别统计检验
    糖尿病组(39例)非糖尿病组(73例)$\chi^2 $P
    分布模式/(例(%))支气管血管束分布0(0.0)2(2.7)2.6050.107
    胸膜下分布   3(7.7)14(19.2)0.542
    混合分布    36(92.3)57(78.1)4.0620.044
    病变形态/(例(%))结节状     26(66.7)49(68.1)0.0220.881
    斑片状     37(94.9)70(95.9)1.000
    大片状     29(74.4)38(52.1)5.2610.022
    束带状     22(56.4)23(31.5)6.5590.010
    特殊征象/(例(%))晕征      37(94.9)54(74.0)7.2880.007
    反晕征     18(46.2)30(41.1)0.2660.606
    蜂窝征     2(5.1)4(5.5)1.000
    铺路石征    24(61.5)35(47.9)1.8840.170
    空气支气管征  34(87.2)49(67.1)5.3290.021
    空气潴留征   18(46.2)19(26.0)4.6550.031
    马赛克灌注   28(71.8)28(38.4)11.369 0.001
    胸膜下线    15(38.5)23(31.5)0.5480.459
    胸膜凹陷征   26(66.7)44(60.3)0.4430.506
    胸膜下黑带   30(76.9)35(47.9)8.7650.003
    下载: 导出CSV
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  • 收稿日期:  2023-02-12
  • 修回日期:  2023-02-27
  • 录用日期:  2023-02-28
  • 网络出版日期:  2023-04-22
  • 发布日期:  2023-05-30

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