摘要
目的:应用COPD分析软件自动测量受试者CT定量指标全肺低衰减区百分比(LAA%)(阈值≤-950 HU),探讨其与临床肺功能指标的相关性。方法:选取COPD患者463例(COPD组)及肺功能正常患者93例(正常组),均行肺功能检查及吸气相薄层CT检查。按照2005版美国胸科学会和欧洲呼吸协会(ATS/ERS)分级标准,将COPD组分为5个亚组:轻度组96例,中度组92例,中重度组95例,重度组86例及极重度组94例。将吸气相薄层CT图像上传至肺气肿后处理工作站,自动测量各肺叶LAA%(阈值≤-950 HU),将各组全肺LAA%行两两比较。使用Spearman相关分析比较COPD组LAA%与肺功能指标[FEV_(1)%(第1秒用力呼气容积占预计值的百分比)、FVC(用力肺活量)、FEV_(1)/FVC]的相关性。结果:正常组与COPD各组LAA%、FEV_(1)%、FVC、FEV_(1)/FVC两两比较差异均有统计学意义(均P<0.05)。LAA%与肺功能指标(FEV_(1)%、FVC、FEV_(1)/FVC)均呈负相关(r_(s)=-0.447,-0.264,-0.570;均P<0.05)。结论:CT定量指标全肺LAA%可反映肺功能严重程度,可作为一种无创、敏感的肺气肿检查手段应用于临床工作。
Objective:To assess the correlation between LAA%(threshold≤-950 HU),a quantitative CT index,and clinical lung function index,by using COPD analysis software.Methods:A total of 463 COPD patients(COPD group)and 93 patients with normal lung function(the normal group)were selected.Lung function examination and inspiratory phase thin-slice CT examination were required at the same time.According to the ATS/ERS classification criteria,463 COPD patients were divided into 5 subgroups,96 cases were in the mild group,92 cases in the moderate group,95 cases in the moderate-severe group,86 cases in the severe group and 94 cases in the extremely severe group.The inspiratory phase thin-slice CT of all patients was uploaded to the digital workstation,and LAA%was automatically measured,and LAA%of each group was compared.The correlation between LAA%and pulmonary function indices(FEV_(1)%,FVC,FEV_(1)/FVC)in the COPD subgroups was compared by Spearman correlation analysis.Results:LAA%,FEV_(1)%,FVC,FEV_(1)/FVC were different in pairwise comparisons between the normal group and 5 COPD subgroups(all P<0.05).LAA%was negative correlation with FEV_(1)%,FVC,FEV_(1)/FVC(r_(s)=-0.447,-0.264,-0.570,all P<0.05).Conclusions:LAA%,the quantitative CT index,reflects the severity of lung function,and can be used as a non-invasive and sensitive means to detect emphysema in clinical work.
作者
张涛
易燊雯
吴婧
毛山
徐军
徐宸宇
谷伟
叶亮
ZHANG Tao;YI Shenwen;WU Jing;MAO Shan;XU Jun;XU Chenyu;GU Wei;YE Liang(Department of Radiology,Nanjing First Hospital,Nanjing Hospital of Nanjing Medical University,Nanjing 210006,China;Department of Respiratory,Nanjing First Hospital,Nanjing Hospital of Nanjing Medical University,Nanjing 210006,China)
出处
《中国中西医结合影像学杂志》
2024年第6期653-656,共4页
Chinese Imaging Journal of Integrated Traditional and Western Medicine
基金
南京市卫生科技发展重点项目(ZKX21041)
江苏省卫健委医学科研重点项目(ZDB2020012)。
关键词
肺疾病
慢性阻塞性
人工智能
体层摄影术
X线计算机
肺功能
Pulmonary disease,chronic obstructive
Artificial intelligence
Tomography,X-ray computed
Pulmonary function