ISSN 1004-4140
CN 11-3017/P

人工智能定量分析新型冠状病毒感染不同病毒变异株CT特征

张凯, 柴军, 刘瑞, 赵建华, 王璟琛

张凯, 柴军, 刘瑞, 等. 人工智能定量分析新型冠状病毒感染不同病毒变异株CT特征[J]. CT理论与应用研究, 2023, 32(5): 595-602. DOI: 10.15953/j.ctta.2023.043.
引用本文: 张凯, 柴军, 刘瑞, 等. 人工智能定量分析新型冠状病毒感染不同病毒变异株CT特征[J]. CT理论与应用研究, 2023, 32(5): 595-602. DOI: 10.15953/j.ctta.2023.043.
ZHANG K, CHAI J, LIU R, et al. Quantitative Analysis of Computed Tomography Features of Different COVID-19 Infection Virus Variants Using Artificial Intelligence[J]. CT Theory and Applications, 2023, 32(5): 595-602. DOI: 10.15953/j.ctta.2023.043. (in Chinese).
Citation: ZHANG K, CHAI J, LIU R, et al. Quantitative Analysis of Computed Tomography Features of Different COVID-19 Infection Virus Variants Using Artificial Intelligence[J]. CT Theory and Applications, 2023, 32(5): 595-602. DOI: 10.15953/j.ctta.2023.043. (in Chinese).

人工智能定量分析新型冠状病毒感染不同病毒变异株CT特征

基金项目: 内蒙古自治区卫生健康科技计划项目(超高分辨率 CT 靶扫描技术联合低剂量对诊断亚实性肺结节的价值(202201015))。
详细信息
    作者简介:

    张凯: 男,硕士,内蒙古自治区人民医院影像医学科主治医师,主要研究方向胸部影像学,E-mail:28132311@qq.com

    通讯作者:

    柴军: 内蒙古自治区人民医院主任医师、硕士研究生导师,主要从事胸、腹部影像学研究及CT引导下穿刺术等,E-mail:amaschai@126.com

  • 中图分类号: O  242;R  814;R  563.1

Quantitative Analysis of Computed Tomography Features of Different COVID-19 Infection Virus Variants Using Artificial Intelligence

  • 摘要: 目的:人工智能(AI)定量分析比较新型冠状病毒感染德尔塔(Delta)和奥密克戎(Omicron)变异株感染患者的胸部CT影像学特征。方法:回顾性分析2022年2月20日至2022年4月19日在内蒙古自治区第四医院确诊的294例新型冠状病毒Delta变异株感染患者及2022年12月1日至12月30日在内蒙古自治区人民医院确诊的222例Omicron变异株感染患者的临床资料及首次CT影像学资料进行分析,分为Delta组和Omicron组,应用推想预测肺部感染辅助诊断软件进行定量计算,比较分析组间CT影像学征象及CT定量数据。结果:磨玻璃斑片影、磨玻璃结节影、索条、实变、铺路石征、小叶间隔增厚及病灶内增粗血管影等影像学征象在两组之间比较无统计学意义。Omicron组病灶分布较Delta组更容易出现沿支气管血管束分布;Delta组的全肺病灶体积、体积占比、右肺中叶病灶体积、体积占比、右肺下叶病灶体积、体积占比均高于Omicron组;Delta组患者病灶分布于 -570~-470 HU体积、-470~-370 HU体积、-370~-270 HU体积、-270~-170 HU体积均高于Omicron组。结论:Delta变异株感染患者肺炎早期CT病灶体积及体积占比Omicron组高,Omicron组病灶分布较Delta组更容易出现不典型的沿支气管血管束分布,人工智能肺炎辅助诊断系统对COVID-19患者定量评估肺炎感染区域体积及体积占比,为患者病情评估提供客观的参考数据。
    Abstract: Objective: To quantitatively analyze and compare the chest computed tomography (CT) imaging features of patients infected with delta and omicron variants of COVID-19 using artificial intelligence (AI). Method: The clinical data of 294 patients infected with the novel coronavirus delta variant diagnosed at the Fourth Hospital of Inner Mongolia Autonomous Region from February 20, 2022 to April 19, 2022 and 222 patients infected with the omicron variant diagnosed at the People's Hospital of Inner Mongolia Autonomous Region from December 1, 2022 to December 30, 2022 were retrospectively analyzed. CT imaging data were analyzed and divided into delta and omicron groups. Quantitative calculation was performed using deductive predictive pulmonary infection auxiliary diagnostic software, and CT imaging signs and quantitative CT data between groups were compared and analyzed. Results: No statistical significance was noted between the delta and omicron groups in imaging signs, such as ground-glass opacity, ground-glass nodule, cord-like lesion, consolidation, paving stone sign, thickened interlobular septum, and thickened vessels in the lesion. The distribution of lesions along the bronchial vascular bundle was more likely in the omicron than in the delta group. The total lung lesion volume, volume proportion, right middle lobe lesion volume, volume proportion, right inferior lobe lesion volume, and volume proportion in the delta group were higher than those in the omicron group. The proportions of lesions in the delta group in −570 ~ −470 HU, −470 ~ −370 HU, −370 ~ −270 HU, and −270 ~ −170 HU volumes were higher than those in the omicron group. Conclusion: In the early stage of COVID-19, the volume of CT lesions in the patients infected with the delta variant was higher than that in the omicron group, and the distribution of lesions in the omicron group was more likely to have atypical distribution along the bronchial vascular bundle than that in the delta group. The volume and volume proportion of the pneumonia-infected area in patients with COVID-19 were quantitatively evaluated using the AI-assisted diagnosis system for COVID-19 to provide objective reference data for patients' condition assessment.
  • 随着新型冠状病毒感染(coronavirus disease 2019,COVID-19)的持续流行,SARS-CoV-2经过多次的突变和变异,并已出现多种变异毒株谱系,包括谱系Alpha(B.1.1.7)、Delta(B.1617.2)谱系及Omicron(B.1.1.529)谱系等[1-2]。其中Delta和Omicron谱系均被列为需要密切关注的变异株[3],掌握不同变异株的肺炎演变规律对临床诊治COVID-19有着重要的意义,胸部CT检查在COVID-19的早期筛查、临床诊治以及病程观察中起着非常重要的作用[4-5]。既往研究发现,COVID-19早期患者主要CT表现为斑片状磨玻璃密度影、实变影、铺路石征及小叶间隔增厚等征象[6-7]。而早期病灶体积、病灶体积占全肺比例均是COVID-19严重程度、随访、预测过程中重要的监测指标[8-9]

    计算机AI辅助系统可以为临床诊断提供客观准确的定量测量结果。但对于CT在COVID-19不同病毒变异株定量分析研究较少,因此本研究应用AI定量分析,旨在评价新型冠状病毒感染Delta谱系与Omicron谱系不同病毒变异株的病变分布、体积、体积占比及影像学征象之间的差异,探讨疾病演变规律,为临床预防、诊治提供参考。

    回顾性分析2022年2月20日至2022年4月19日内蒙古自治区第四医院确诊的294例新型冠状病毒Delta变异株感染患者以及2022年12月1日至12月30日内蒙古自治区人民医院确诊的222例Omicron变异株感染患者的临床资料和首次CT检查影像学资料。纳入标准:符合WHO及国家卫生健康委员会的诊断标准,具有首次CT检查影像学资料即出现典型症状如发热、咳嗽、咽部不适等1~7 d;排除标准:轻型患者影像学未见肺炎表现者;既往胸部手术病史,胸部肿瘤、结核等其他影响AI计算的疾病患者;图像质量差、呼吸伪影等影响AI数据处理。

    扫描设备均为64排及以上螺旋CT,患者采用仰卧位,扫描范围从胸廓入口至包全肺底。扫描参数:管电压120 kV,自动管电流,层厚5 mm,重建1.25 mm。

    由推想预测提供的基于深度学习模型的人工智能计算机辅助系统,将CT扫描原始数据以DICOM格式导入推想预测工作站,应用推想预测肺部感染辅助诊断软件进行处理,再由两名(工作经验5年以上)影像医师校正,计算病变区域容积、占全肺体积的百分比,得出客观数据并记录。

    主观病变征象由两名丰富工作经验的放射诊断主治医师进行阅片,统计病灶的分布特点及CT影像征象特征。病灶分布特点分为胸膜下分布和支气管血管束周围分布,胸膜下分布主要定义为沿着胸膜下1/3区域分布,支气管血管束周围分布是指病变主要分布在支气管血管束走行的周围[10]。当两名放射诊断医师诊断结果出现争议时,再由第3名高年资医生进行裁定。

    影像学征象、病灶分布等计数资料描述采用例数(百分比);Delta组与Omicron组之间的比较采用卡方检验或Fisher确切概率法;定量数据经正态性检验不服从正态分布;描述采用中位数(四分位间距描述);Delta组与Omicron组比较采用非参数Mann-Whitney U检验。检验水准α=0.05,以P≤0.05为差异具有统计学意义。所有统计分析采用SPSS 22.0软件。

    Delta组患者入组293例,男165例,女128例,年龄21~91岁;Omicron组患者入组222例,男129例,女93例,年龄20~87岁。两组入组患者临床分型均为普通型,初次评估未见重型及危重型病例。

    Delta组患者与Omicron组患者出现磨玻璃斑片影、磨玻璃结节影、索条、实变、铺路石征、小叶间隔增厚及病灶内增粗血管影等(图1图3)影像学征象在两组之间比较无统计学意义(表1)。

    表  1  影像学征象比较
    Table  1.  Comparison of imaging findings
    特征组别统计检验
    Delta组(n=293)Omicron组(n=222)$\chi^2$P
    磨玻璃斑片影 164(56.0) 115(51.8) 0.375 0.879
    磨玻璃结节影 132(45.1) 99(45.0) 0.001 0.991
    索条     2(0.6) 3(1.4) 0.078#
    实变     130(44.4) 104(47.3) 0.427 0.513
    铺路石征   47(16.0) 38(17.1) 7.014 0.408
    小叶间隔增厚 40(13.6) 34(15.3) 0.533#
    增粗血管影  29(9.9) 25(11.4) 0.287 0.592
     注:#-采用Fisher确切概率法比较。
    下载: 导出CSV 
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    图  1  (a)女,24岁,Omicron组患者,新型冠状病毒感染核酸检测阳性1天,入院体温37.3°,右肺上叶后段磨玻璃密度结节。(b)男,55岁,Delta组患者,周身酸痛伴气短1周+新冠病毒核酸检测阳性 1天,入院体温38.3°,双肺下叶磨玻璃结节影
    Figure  1.  (a) A 24-year-old female patient in the Omicron group had a positive nucleic acid test result for novel coronavirus pneumonia for 1 day. She was admitted to the hospital with a temperature of 37.3° and a nodule of ground glass density in the posterior segment of the upper lobe of the right lung. (b) Male, 55-year-old patient in the delta group, with body pain and shortness of breath for 1 week + positive COVID-19 nucleic acid test for 1 day; admission temperature: 38.3°, ground glass nodules in the lower lobes of both lungs
    图  2  女,41岁,Omicron组患者,新型冠状病毒核酸检测阳性1天,咳嗽2天。双肺下叶斑片状磨玻璃影,胸膜下分布,病灶内可见增粗血管影
    Figure  2.  Female patient, 41-year-old, in the Omicron group, tested positive for novel coronavirus nucleic acid for 1 day and coughed for 2 days. Patchy ground-glass opacity was observed in the lower lobes of both lungs, subpleura distributed, and thickened vascular shadows were observed in the lesions
    图  3  (a)男,42岁,Omicron组患者,咽痛2天,新冠病毒核酸阳性1天。既往体建,右肺下叶胸膜下“铺路石征”。(b)女,65岁,新冠核酸阳性1天,发热、咳嗽半日。双肺多发斑片状磨玻璃影及实变影,胸膜下分布为著,病灶内增粗血管影
    Figure  3.  (a) A 42-year-old male patient in the Omicron group had sore throat for 2 days and tested positive for COVID-19 nucleic acid for 1 day. Previous body construction, subpleural "paving stone sign" in the inferior lobe of the right lung. (b) A 65-year-old female who tested positive for COVID-19 for 1 day experienced fever and cough for half a day. Multiple patchy ground glass shadows and consolidation shadows in both lungs, with subpleural distribution and thickened vascular shadows in the lesions

    94.2% 的Delta组患者病灶分布于胸膜下,而在病变沿支气管血管束分布(图4)的患者更容易为Omicron变异株患者(表2)。

    表  2  病灶分布比较
    Table  2.  Comparison of focal distribution
    分布组别P
    Delta组(n=293)Omicron组(n=222)
    支气管血管束分布17(5.8) 41(18.5)0.029
    胸膜下分布   276(94.2)181(81.5)
    下载: 导出CSV 
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    图  4  37岁女性,Omicron组患者,新型冠状病毒感染核酸检测阳性1天,咳嗽1天,CT MPR图像显示左肺下叶沿支气管血管束分布的斑片状磨玻璃密度及实变影
    Figure  4.  A 37-year-old woman in the omicron group tested positive for COVID-19 nucleic acid for 1 day and coughed for 1 day. CT images showed patchy ground glass, and consolidation is peribronchovascular bundle distribution in the lower lobe of the left lung

    Delta组的全肺病灶体积、体积占比、右肺中叶病灶体积、体积占比、右肺下叶病灶体积、体积占比均高于Omicron组,差异具有统计学意义(图5表3表4)。

    图  5  46岁女性,Delta组患者,应用肺部感染辅助诊断软件进行处理获取左肺上叶、下叶肺炎病灶体积及体积占比
    Figure  5.  A 46-year-old female patient in the delta group was treated with pulmonary infection auxiliary diagnostic software to obtain the volume and proportion of pneumonia lesions in the upper and lower lobes of the left lung
    表  3  Delta组与Omicron组肺炎体积及体积占比比较
    Table  3.  Comparison of pneumonia volume and volume proportion between the delta and omicron groups
    指标组别统计检验
    Delta组(n=293)Omicron组(n=222)ZP
     全肺病灶体积占比/%3.39(0.56~8.78)1.69(0.44~6.93)0.9170.025
     全肺病灶体积/cm3113.93(23.60~320.39)66.80(15.83~234.35)2.1740.030
     右肺上叶病灶体积占比/%0.63(0.00~3.63)0.40(0.00~2.82)1.3610.173
     右肺上叶病灶体积/cm35.63(0.00~28.83)3.23(0.00~27.00)1.3250.185
     右肺中叶病灶体积占比/%0.84(0.00~6.22)0.31(0.00~3.475)2.3800.017
     右肺中叶病灶体积/cm33.07(0.00~18.56)1.30(0.00~10.21)2.4470.014
     右肺下叶病灶体积占比/%4.61(0.62~17.34)2.18(0.24~12.69)2.9400.003
     右肺下叶病灶体积/cm337.68(5.58~117.28)17.02(1.90~82.04)2.9420.003
     左肺上叶病灶体积占比/%0.28(0.00~3.76)0.36(0.00~3.06)0.4680.639
     左肺上叶病灶体积/cm32.51(0.002~28.70)3.45(0.00~26.27)0.5480.584
     左肺下叶病灶体积占比/%3.27(0.35~14.18)1.63(0.15~12.67)1.9170.055
     左肺下叶病灶体积/cm323.21(2.45~86.92)11.49(0.95~69.64)2.0030.065
    下载: 导出CSV 
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    Delta组患者病灶分布于 -570~-470体积、-470~-370体积、-370~-270体积、-270~-170体积均高于Omicron组,差异具有统计学意义。

    表  4  不同CT值分段病变体积及体积占比
    Table  4.  Volume and volume proportion of different CT values
    指标组别统计检验
    Delta组(n=293)Omicron组(n=222)ZP
      -570~-470体积/cm314.66(2.85~44.29)9.01(2.12~31.59)1.9560.050
      -570~-470体积占比/%13.82(11.39~15.86)13.79(11.16~16.28)0.3370.736
      -470~-370体积/cm312.14(2.15~35.79)7.65(1.86~25.26)2.0830.037
      -470~-370体积占比/%11.31(8.80~13.77)11.05(8.56~13.28)0.5800.562
      -370~-270体积/cm39.43(1.81~27.9)6.11(1.34~18.07)2.3360.019
      -370~-270体积占比/%9.00(6.24~12.00)8.44(5.81~10.81)1.3950.163
      -270~-170体积/cm36.74(1.24~22.73)4.60(0.88~13.49)2.2120.027
      -270~-170体积占比/%6.63(4.39~10.00)6.29(4.17~8.67)1.2480.212
      -170~-70体积/cm34.65(0.97~16.92)3.17(0.61~10.73)1.9150.055
      -170~-70体积占比/%5.03(2.99~8.32)4.76(2.72~7.36)0.7410.458
      -70~-30体积/cm33.47(0.59~11.89)2.23(0.43~8.73)1.6340.102
      -70~-30体积占比/%3.49(1.60~5.78)3.25(1.49~6.34)0.0850.932
      30~70体积/cm30.58(0.06~2.85)0.38(0.03~2.33)1.6360.102
      30~70体积占比/%0.67(0.20~1.52)0.54(0.16~1.39)0.6730.501
    下载: 导出CSV 
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    德尔塔变异株B.1617.2谱系最早于2020年10月在印度记录[11],Omicron变异株的遗传谱系名称为B.1.1.529,于2021年11月于南非首次确认并命名[12],随着SARS-CoV-2的不断突变与变异,越来越多的不同变异株相继出现且被受关注[13]。胸部CT检查在新型冠状病毒感染的早期筛查、快速检出微小病灶、临床病情评估以及病程观察中起着非常重要的作用,本文希望通过研究对比Delta和Omicron不同变异株感染患者CT影像特征的差异,为临床诊治、评估COVID-19提供参考。

    本组研究发现Delta组患者与Omicron组患者均可出现磨玻璃斑片影、磨玻璃结节影、索条、实变、铺路石征、小叶间隔增厚及病灶内增粗血管影等影像学征象(图1图4);Omicron组病灶分布较Delta组更容易出现沿支气管血管束分布,与之前研究报道结果基本一致[14],可能由于Omicron变异株在支气管中的复制优于在肺实质内[15]

    基于深度学习模型的人工智能计算机辅助系统采用深度学习技术卷积神经网络模型,模仿人类认知过程。采用优质医学影像数据进行训练后,模型可自动挖掘医学图像中的规律,可对肺炎病灶进行准确分割计算,肺部病变体积、体积占比等定量分析(图5)有助于评价COVID-19患者病情严重程度。本次研究发现Delta组患者与Omicron组患者肺炎体积占比均较少,可能与入组患者均为出现典型症状1~7 d首次CT检查的影像学资料,为发病早期的患者且入组患者均为普通型患者,初次评估无重型及危重型病例有关。

    尽管Omicron变异体的遗传性比Delta变异体高3.7倍,但它被认为在住院率、重症监护病房收治率和死亡率方面毒性较低[16-18]。本研究发现Delta组患者与Omicron组患者肺炎右肺下叶病灶体积与体积占比均较高(表3),与之前报道一致[19-20]。Delta组的全肺病灶体积、体积占比、右肺中叶病灶体积、体积占比、右肺下叶病灶体积、体积占比均高于Omicron组,且病灶分布于-570~-470 HU体积、-470~-370 HU体积、-370~-270 HU体积、-270~-170 HU体积占比均高于Omicron组,提示Delta组感染肺炎较Omicron组重,与之前报道基本相符[21],考虑由于本研究未将患者合并的基础疾病进行分类,可能导致研究结果存在偏倚,期待进一步分类深入研究。

    本研究的不足:纳入患者分型较单一;缺少COVID-19重症患者数据;不能全面反映不同变异株感染患者的CT定量特征。未来期待开展进一步研究。

    综上所述,Delta变异株感染患者肺炎早期CT病灶体积、体积占比较Omicron组高;Omicron组病灶分布较Delta组更容易出现不典型的沿支气管血管束分布。计算机AI辅助系统相对于影像医师肉眼评估,可以快速、准确提供感染体积、体积占比等客观数据,为临床诊治、评估COVID-19病情程度、疗效评估提供了重要的参考依据。

  • 图  1   (a)女,24岁,Omicron组患者,新型冠状病毒感染核酸检测阳性1天,入院体温37.3°,右肺上叶后段磨玻璃密度结节。(b)男,55岁,Delta组患者,周身酸痛伴气短1周+新冠病毒核酸检测阳性 1天,入院体温38.3°,双肺下叶磨玻璃结节影

    Figure  1.   (a) A 24-year-old female patient in the Omicron group had a positive nucleic acid test result for novel coronavirus pneumonia for 1 day. She was admitted to the hospital with a temperature of 37.3° and a nodule of ground glass density in the posterior segment of the upper lobe of the right lung. (b) Male, 55-year-old patient in the delta group, with body pain and shortness of breath for 1 week + positive COVID-19 nucleic acid test for 1 day; admission temperature: 38.3°, ground glass nodules in the lower lobes of both lungs

    图  2   女,41岁,Omicron组患者,新型冠状病毒核酸检测阳性1天,咳嗽2天。双肺下叶斑片状磨玻璃影,胸膜下分布,病灶内可见增粗血管影

    Figure  2.   Female patient, 41-year-old, in the Omicron group, tested positive for novel coronavirus nucleic acid for 1 day and coughed for 2 days. Patchy ground-glass opacity was observed in the lower lobes of both lungs, subpleura distributed, and thickened vascular shadows were observed in the lesions

    图  3   (a)男,42岁,Omicron组患者,咽痛2天,新冠病毒核酸阳性1天。既往体建,右肺下叶胸膜下“铺路石征”。(b)女,65岁,新冠核酸阳性1天,发热、咳嗽半日。双肺多发斑片状磨玻璃影及实变影,胸膜下分布为著,病灶内增粗血管影

    Figure  3.   (a) A 42-year-old male patient in the Omicron group had sore throat for 2 days and tested positive for COVID-19 nucleic acid for 1 day. Previous body construction, subpleural "paving stone sign" in the inferior lobe of the right lung. (b) A 65-year-old female who tested positive for COVID-19 for 1 day experienced fever and cough for half a day. Multiple patchy ground glass shadows and consolidation shadows in both lungs, with subpleural distribution and thickened vascular shadows in the lesions

    图  4   37岁女性,Omicron组患者,新型冠状病毒感染核酸检测阳性1天,咳嗽1天,CT MPR图像显示左肺下叶沿支气管血管束分布的斑片状磨玻璃密度及实变影

    Figure  4.   A 37-year-old woman in the omicron group tested positive for COVID-19 nucleic acid for 1 day and coughed for 1 day. CT images showed patchy ground glass, and consolidation is peribronchovascular bundle distribution in the lower lobe of the left lung

    图  5   46岁女性,Delta组患者,应用肺部感染辅助诊断软件进行处理获取左肺上叶、下叶肺炎病灶体积及体积占比

    Figure  5.   A 46-year-old female patient in the delta group was treated with pulmonary infection auxiliary diagnostic software to obtain the volume and proportion of pneumonia lesions in the upper and lower lobes of the left lung

    表  1   影像学征象比较

    Table  1   Comparison of imaging findings

    特征组别统计检验
    Delta组(n=293)Omicron组(n=222)$\chi^2$P
    磨玻璃斑片影 164(56.0) 115(51.8) 0.375 0.879
    磨玻璃结节影 132(45.1) 99(45.0) 0.001 0.991
    索条     2(0.6) 3(1.4) 0.078#
    实变     130(44.4) 104(47.3) 0.427 0.513
    铺路石征   47(16.0) 38(17.1) 7.014 0.408
    小叶间隔增厚 40(13.6) 34(15.3) 0.533#
    增粗血管影  29(9.9) 25(11.4) 0.287 0.592
     注:#-采用Fisher确切概率法比较。
    下载: 导出CSV

    表  2   病灶分布比较

    Table  2   Comparison of focal distribution

    分布组别P
    Delta组(n=293)Omicron组(n=222)
    支气管血管束分布17(5.8) 41(18.5)0.029
    胸膜下分布   276(94.2)181(81.5)
    下载: 导出CSV

    表  3   Delta组与Omicron组肺炎体积及体积占比比较

    Table  3   Comparison of pneumonia volume and volume proportion between the delta and omicron groups

    指标组别统计检验
    Delta组(n=293)Omicron组(n=222)ZP
     全肺病灶体积占比/%3.39(0.56~8.78)1.69(0.44~6.93)0.9170.025
     全肺病灶体积/cm3113.93(23.60~320.39)66.80(15.83~234.35)2.1740.030
     右肺上叶病灶体积占比/%0.63(0.00~3.63)0.40(0.00~2.82)1.3610.173
     右肺上叶病灶体积/cm35.63(0.00~28.83)3.23(0.00~27.00)1.3250.185
     右肺中叶病灶体积占比/%0.84(0.00~6.22)0.31(0.00~3.475)2.3800.017
     右肺中叶病灶体积/cm33.07(0.00~18.56)1.30(0.00~10.21)2.4470.014
     右肺下叶病灶体积占比/%4.61(0.62~17.34)2.18(0.24~12.69)2.9400.003
     右肺下叶病灶体积/cm337.68(5.58~117.28)17.02(1.90~82.04)2.9420.003
     左肺上叶病灶体积占比/%0.28(0.00~3.76)0.36(0.00~3.06)0.4680.639
     左肺上叶病灶体积/cm32.51(0.002~28.70)3.45(0.00~26.27)0.5480.584
     左肺下叶病灶体积占比/%3.27(0.35~14.18)1.63(0.15~12.67)1.9170.055
     左肺下叶病灶体积/cm323.21(2.45~86.92)11.49(0.95~69.64)2.0030.065
    下载: 导出CSV

    表  4   不同CT值分段病变体积及体积占比

    Table  4   Volume and volume proportion of different CT values

    指标组别统计检验
    Delta组(n=293)Omicron组(n=222)ZP
      -570~-470体积/cm314.66(2.85~44.29)9.01(2.12~31.59)1.9560.050
      -570~-470体积占比/%13.82(11.39~15.86)13.79(11.16~16.28)0.3370.736
      -470~-370体积/cm312.14(2.15~35.79)7.65(1.86~25.26)2.0830.037
      -470~-370体积占比/%11.31(8.80~13.77)11.05(8.56~13.28)0.5800.562
      -370~-270体积/cm39.43(1.81~27.9)6.11(1.34~18.07)2.3360.019
      -370~-270体积占比/%9.00(6.24~12.00)8.44(5.81~10.81)1.3950.163
      -270~-170体积/cm36.74(1.24~22.73)4.60(0.88~13.49)2.2120.027
      -270~-170体积占比/%6.63(4.39~10.00)6.29(4.17~8.67)1.2480.212
      -170~-70体积/cm34.65(0.97~16.92)3.17(0.61~10.73)1.9150.055
      -170~-70体积占比/%5.03(2.99~8.32)4.76(2.72~7.36)0.7410.458
      -70~-30体积/cm33.47(0.59~11.89)2.23(0.43~8.73)1.6340.102
      -70~-30体积占比/%3.49(1.60~5.78)3.25(1.49~6.34)0.0850.932
      30~70体积/cm30.58(0.06~2.85)0.38(0.03~2.33)1.6360.102
      30~70体积占比/%0.67(0.20~1.52)0.54(0.16~1.39)0.6730.501
    下载: 导出CSV
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  • 期刊类型引用(1)

    1. 张丽平,周小亮. 中国人工智能发展的时空网络结构及驱动因子研究. 福建江夏学院学报. 2024(04): 40-54 . 百度学术

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  • 收稿日期:  2023-03-09
  • 修回日期:  2023-03-20
  • 录用日期:  2023-04-11
  • 网络出版日期:  2023-04-26
  • 发布日期:  2023-09-21

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