CT whole lung radiomic nomogram:a potential biomarker for lung function evaluation and identification of COPD  

作　　者：Tao-Hu Zhou Xiu-Xiu Zhou Jiong Ni Yan-Qing Ma Fang-Yi Xu Bing Fan Yu Guan Xin-Ang Jiang Xiao-Qing Lin Jie Li Yi Xia Xiang Wang Yun Wang Wen-Jun Huang Wen-Ting Tu Peng Dong Zhao-Bin Li Shi-Yuan Liu Li Fan 

机构地区：[1]Department of Radiology,the Second Affiliated Hospital of Naval Medical University,Shanghai 200003,China [2]School of Medical Imaging,Shandong Second Medical University,Weifang 261053,Shandong,China [3]Department of Radiology,School of Medicine,Tongji Hospital,Tongji University,Shanghai 200065,China [4]Department of Radiology,Zhejiang Province People’s Hospital,Affiliated People’s Hospital of Hangzhou Medical College,Hangzhou 310014,China [5]Department of Radiology,Sir Run Run Shaw Hospital,Zhejiang 310018,China [6]Jiangxi Provincial People’s Hospital,the First Affiliated Hospital of Nanchang Medical College,Nanchang 330006,China [7]College of Health Sciences and Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China [8]Department of Radiology,the Second People’s Hospital of Deyang,Deyang 618000,Sichuan,China [9]Department of Radiation Oncology,Shanghai Jiao Tong University Affiliated Sixth People’s Hospital,Shanghai 200233,China

出　　处：《Military Medical Research》2025年第1期36-47,共12页军事医学研究(英文版)

基　　金：supported by the National Key Research and Development Program of China(2022YFC2010002,2022YFC2010000 and 2022YFC2010005);the National Natural Science Foundation of China(82171926,81930049 and 82202140);the Medical Imaging Database Construction Program of National Health Commission(YXFSC2022JJSJ002);the Clinical Innovative Project of Shanghai Changzheng Hospital(2020YLCYJ-Y24);the Program of Science and Technology Commission of Shanghai Municipality(21DZ2202600);the Shanghai Sailing Program(20YF1449000).

摘　　要：Background:Computed tomography(CT)plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease(COPD).This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients.Methods:This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group.The radiomic features of the whole lung volume were extracted.Least absolute shrinkage and selection operator(LASSO)logistic regression was applied for feature selection and radiomic signature construction.A radiomic nomogram was established by combining the radiomic score and clinical factors.Receiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA)were used to evaluate the predictive performance of the radiomic nomogram in the training,internal validation,and independent external validation cohorts.Results:Eighteen radiomic features were collected from the whole lung volume to construct a radiomic model.The area under the curve(AUC)of the radiomic model in the training,internal,and independent external validation cohorts were 0.888[95%confidence interval(CI)0.869–0.906],0.874(95%CI 0.844–0.904),and 0.846(95%CI 0.822–0.870),respectively.All were higher than the clinical model(AUC were 0.732,0.714,and 0.777,respectively,P<0.001).DCA demonstrated that the nomogram constructed by combining radiomic score,age,sex,height,and smoking status was superior to the clinical factor model.Conclusions:The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.

关 键 词：Chronic obstructive pulmonary disease(COPD) Computed tomography(CT) Radiomic 

分 类 号：R563.9[医药卫生—呼吸系统] R816.4[医药卫生—内科学]