سابِق|تال

مخطط أشعة الرئة الكامل باستخدام التصوير المقطعي المحوسب: علامة حيوية محتملة لتقييم وظائف الرئة والتعرف على مرض الانسداد الرئوي المزمن

  • role： Contribute equally, First author同等贡献者, 第一作者
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

    School of Medical Imaging, Shandong Second Medical University, Weifang 261053, Shandong, China

Tao-Hu Zhou12,  
  • role： Contribute equally同等贡献者
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Xiu-Xiu Zhou1,  
  • Affiliation：

    Department of Radiology, School of Medicine, Tongji Hospital, Tongji University, Shanghai 200065, China

Jiong Ni3,  
  • Affiliation：

    Department of Radiology, Zhejiang Province People’s Hospital, Affiliated People’s Hospital of Hangzhou Medical College, Hangzhou 310014, China

Yan-Qing Ma4,  
  • Affiliation：

    Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang 310018, China

Fang-Yi Xu5,  
  • Affiliation：

    Jiangxi Provincial People’s Hospital, the First Affiliated Hospital of Nanchang Medical College, Nanchang 330006, China

Bing Fan6,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Yu Guan1,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Xin-Ang Jiang1,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

    College of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

Xiao-Qing Lin17,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

    College of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

Jie Li17,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Yi Xia1,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Xiang Wang1,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Yun Wang1,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

    Department of Radiology, the Second People’s Hospital of Deyang, Deyang 618000, Sichuan, China

Wen-Jun Huang18,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Wen-Ting Tu1,  
  • Affiliation：

    School of Medical Imaging, Shandong Second Medical University, Weifang 261053, Shandong, China

Peng Dong2,  
  • Affiliation：

    Department of Radiation Oncology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China

Zhao-Bin Li9,  
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Shi-Yuan Liu1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

  • Email：fanli0930@163.com
  • Introduction：*fanli0930@163.com; zyxfl@smmu.edu.cn
Li Fan1*

ملخص

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.

مفهوم

Chronic obstructive pulmonary disease (COPD);Computed tomography (CT);Radiomic

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