ISSN 1004-4140
CN 11-3017/P

CT定量分析在新冠状病毒肺炎诊断中的价值

舒意, 钟林泽, 曹力波, 白红利, 孙家瑜

舒意, 钟林泽, 曹力波, 白红利, 孙家瑜. CT定量分析在新冠状病毒肺炎诊断中的价值[J]. CT理论与应用研究, 2021, 30(2): 225-233. DOI: 10.15953/j.1004-4140.2021.30.02.10
引用本文: 舒意, 钟林泽, 曹力波, 白红利, 孙家瑜. CT定量分析在新冠状病毒肺炎诊断中的价值[J]. CT理论与应用研究, 2021, 30(2): 225-233. DOI: 10.15953/j.1004-4140.2021.30.02.10
SHU Yi, ZHONG Linze, CAO Libo, BAI Hongli, SUN Jiayu. The Value of CT Quantitative Analysis in the Diagnosis of COVID-19[J]. CT Theory and Applications, 2021, 30(2): 225-233. DOI: 10.15953/j.1004-4140.2021.30.02.10
Citation: SHU Yi, ZHONG Linze, CAO Libo, BAI Hongli, SUN Jiayu. The Value of CT Quantitative Analysis in the Diagnosis of COVID-19[J]. CT Theory and Applications, 2021, 30(2): 225-233. DOI: 10.15953/j.1004-4140.2021.30.02.10

CT定量分析在新冠状病毒肺炎诊断中的价值

详细信息
    作者简介:

    舒意(1989-),女,本科,四川大学华西医院放射技术初级技师,主要从事CT、MR扫描技术,Tel:18000524932,E-mail:570371557@qq.com;孙家瑜*(1982-),影像医学与核医学硕士,四川大学华西医院放射科副主任技师,主要从事心脏MR技术,Tel:18980606253,E-mail:sjy080512@163.com。

  • 中图分类号: R814

The Value of CT Quantitative Analysis in the Diagnosis of COVID-19

  • 摘要: 目的:探讨新冠状病毒肺炎(COVID-19)CT定量分析与临床严重程度的相关性。方法:收集我院2020年2月以来确诊的新冠状病毒肺炎患者38例肺部薄层高分辨CT(HRCT)数据,使用(COPD)肺功能定量分析软件获得相应参数:平均密度(MD)、全肺总容积(TV)、新冠肺炎病变组织容积(VCOVID-19),定量分析指标磨玻璃影PI-700~-534、网格状影PI-534~-188、实变影PI>-188。将其分为普通组和重度组分析两组定量数据之间的差异性,病灶分布特征及与氧饱和度的相关性。结果:38例COVID-19患者中有30例为普通型,8例为重度型。两组患者年龄、性别无差异(P>0.05)。(1)重度组病灶(包括PI-700~-534、PI-534~-188、PI>-188)占比及其平均肺密度均高于普通组(P<0.05)(2)重度组中,PI-700~-534与PI-534~-188占比差异不显著(P>0.05),但均高于PI>-188P<0.05);普通型组中,PI-700~-534>PI-534~-188>PI>-188P<0.05)。(3)两组患者病灶在肺叶的分布特征具有差异性(P<0.05)。(4)氧饱和度与COVID-19病灶占比、PI-534~-188占比呈负相关(P<0.05相关系数分别为-0.449和-0.443)。结论:CT定量分析可用于评价新冠状肺炎患者的病变范围和严重程度,为临床的诊治提供影像学依据。
    Abstract: Objective:Study of the correlation between the CT quantitative analysis and clinical manifestation of the COVID-19 based on High Resolution Computed Tomography (HRCT) images.Methods:We collected 38 cases of the COVID-19 patients in which 38 cases displayed positive test,and the rest of the cases were clinically proven and identified at the West China Hospital of Sichuan University.We classify patients displaying moderate clinical symptoms as non-severe patient group,and we identified the rest of the patients in the sample as severe group.By using the quantitative analysis tool Volume,we measured the following quantities,mean density (MD),Total pulmonary volume (TV),and COVID-19 infected total volume (including ground-glass opacity PI-700~-534,senile idiopathic pulmonary interstitial fibrosis PI-534~-188,and pulmonary consolidation with PI>-188).We thus investigated the correlation between the oxygen saturation level and pulmonary injury level for these two groups of our sample of 38 cases of COVID-19 patients.Results:In our sample of study,we classified 30 patients as moderate group,and the rest of 8 patients as severe group.Both groups displayed insignificant distribution in age and gender with P>0.05.(1) severe group has higher volumetric Lesion volume and mean density of the infected area this includes (including PI-700~-534,PI-534~-188,PI>-188).The distribution of lesions in the lungs of patients with two types is different comparing with the moderate group (P<0.05).(2) In the general group,the proportion of ground-glass lesions (PI-700~-534) was the largest,followed by the proportion of grid-like lesions (PI-534~-188) and the proportion of pulmonary consolidation with PI>-188 (P<0.05).In severe patients,there was no significant difference in the proportion of ground-glass lesions and grid-shaped lesions (P>0.05),but higher than the proportion of pulmonary consolidation with PI>-188 (P<0.05).(3) The distribution characteristics of lesions in the lungs of patients with different clinical types were different (P<0.05).(4) The oxygen saturation has a negative correlation with the VCOVID-19 and PI-534~-188.(The correlation coefficients were-0.449,-0.443,respectively).Conclusion:From our study,we concluded that the CT quantitative analysis is applicable as a clinical tool to diagnose patients with COVID-19.It could also be used to measure the pathological level and lesions ranges in these patients as well.
  • 期刊类型引用(2)

    1. 颜颖,魏巍,宋丽君,管文敏,张婷婷,孙婧,安冉,杨正汉,魏璇,王振常. 人工智能辅助诊断软件探究新型冠状病毒肺炎核酸转阴后的肺部CT表现及其与入院时临床分型的关系. 临床和实验医学杂志. 2024(04): 337-340 . 百度学术
    2. 李磊,姚采查,张培,张益华. 社区人群新型冠状病毒性肺炎辅助诊断技术应用价值分析. 上海医药. 2024(20): 40-43+49 . 百度学术

    其他类型引用(2)

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出版历程
  • 收稿日期:  2020-04-25
  • 网络出版日期:  2021-11-05

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