中国中西医结合影像学杂志2026，Vol.24Issue(5)：576-580,5.DOI:10.3969/j.issn.1672-0512.2026.05.010
慢性阻塞性肺疾病高危人群的胸部CT定量分析
Quantitative analysis of chest CT in high-risk populations with chronic obstructive pulmonary disease
摘要
Abstract
Objective:To develop a predictive model for individuals at high risk of chronic obstructive pulmonary disease(COPD)based on chest CT quantitative features combined with clinical factors,and to provide an imaging tool for early identification and intervention of COPD.Methods:This prospective study enrolled 418 healthy check-up participants.Based on pulmonary function test cutoff values,they were divided into a low-risk group[forced expiratory volume in first second to forced vital capacity ratio(FEV1/FVC)>70%,and FEV1 as a percentage of predicted value(FEV1%pred)≥95%;n=143]and a high-risk group(FEV1/FVC>70%,and 80%<FEV1%pred<95%;n=275).Chest CT quantitative parameters were compared between the two groups.Variable selection was performed using the least absolute shrinkage and selection operator(LASSO)algorithm,followed by logistic regression analysis to construct the prediction model.The model's predictive performance was evaluated using ROC curves,calibration was assessed with calibration curves,and net clinical benefit was evaluated using decision curve analysis(DCA).Results:Significant differences were observed between the two groups in sex ratio,smoking history,and 16 chest CT quantitative parameters,including the percentage of low-attenuation areas(LAA%)in the whole lung and individual lobes(right upper,middle,and lower lobes;left upper and lower lobes);the ratio of lumen area to total airway area(L/A)in the whole lung and at bronchial generations 5-8;and the ratio of wall area to total airway area(W/A)in the whole lung and at generations 5-8(all P<0.05).Following variable selection using the LASSO algorithm,smoking history,right middle lobe LAA%,left upper lobe LAA%,and W/A at the 7th generation bronchus were included in a multivariate logistic regression analysis.A predictive model for identifying individuals at high risk of COPD was constructed based on former smoking history,right middle lobe LAA%,left upper lobe LAA%,and W/A at the 7th generation bronchus,and the model achieved an AUC of 0.714,with an optimal cutoff value of 0.520,sensitivity of 47.6%,and specificity of 88.4%.The calibration curve demonstrated good agreement between predicted and actual probabilities.DCA indicated a net clinical benefit within a specific range of threshold probabilities.Conclusions:The prediction model,which incorporates smoking history and CT quantitative parameters(right middle lobe LAA%,left upper lobe LAA%,and W/A at the 7th generation bronchus),is useful for identifying individuals at high risk of COPD.It demonstrates potential clinical applicability and may serve as a complementary tool to pulmonary function testing.关键词
肺疾病,慢性阻塞性/高危人群/体层摄影术,X线计算机/定量分析Key words
Pulmonary disease,Chronic obstructive/Risk groups/Tomography,X-ray computed/Quantitative analysis分类
医药卫生引用本文复制引用
李宇峰,丁玖乐,陆秋怡,周宜静,邢伟..慢性阻塞性肺疾病高危人群的胸部CT定量分析[J].中国中西医结合影像学杂志,2026,24(5):576-580,5.基金项目
国家重点研发计划项目(2022YFC2010000). （2022YFC2010000）
