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Zhou T, Tu W, Dong P, Duan S, Zhou X, Ma Y, Wang Y, Liu T, Zhang H, Feng Y, Huang W, Ge Y, Liu S, Li Z, Fan L. CT-Based Radiomic Nomogram for the Prediction of Chronic Obstructive Pulmonary Disease in Patients with Lung cancer. Acad Radiol 2023; 30:2894-2903. [PMID: 37062629 DOI: 10.1016/j.acra.2023.03.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 04/18/2023]
Abstract
RATIONALE AND OBJECTIVES To develop and validate a model for predicting chronic obstructive pulmonary disease (COPD) in patients with lung cancer based on computed tomography (CT) radiomic signatures and clinical and imaging features. MATERIALS AND METHODS We retrospectively enrolled 443 patients with lung cancer who underwent pulmonary function test as the primary cohort. They were randomly assigned to the training (n = 311) or validation (n = 132) set in a 7:3 ratio. Additionally, an independent external cohort of 54 patients was evaluated. The radiomic lung nodule signature was constructed using the least absolute shrinkage and selection operator algorithm, while key variables were selected using logistic regression to develop the clinical and combined models presented as a nomogram. RESULTS COPD was significantly related to the radiomics signature in both cohorts. Moreover, the signature served as an independent predictor of COPD in the multivariate regression analysis. For the training, internal, and external cohorts, the area under the receiver operating characteristic curve (ROC, AUC) values of our radiomics signature for COPD prediction were 0.85, 0.85, and 0.76, respectively. Additionally, the AUC values of the radiomic nomogram for COPD prediction were 0.927, 0.879, and 0.762 for the three cohorts, respectively, which outperformed the other two models. CONCLUSION The present study presents a nomogram that incorporates radiomics signatures and clinical and radiological features, which could be used to predict the risk of COPD in patients with lung cancer with one-stop chest CT scanning.
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Affiliation(s)
- TaoHu Zhou
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China; School of Medical Imaging, Weifang Medical University, Weifang, SD, China
| | - WenTing Tu
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China
| | - Peng Dong
- School of Medical Imaging, Weifang Medical University, Weifang, SD, China
| | - ShaoFeng Duan
- GE Healthcare, Precision Health Institution, Shanghai, China
| | - XiuXiu Zhou
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China
| | - YanQing Ma
- Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, ZJ, China
| | - Yun Wang
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China
| | - Tian Liu
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China
| | - HanXiao Zhang
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, JS, China
| | - Yan Feng
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China
| | - WenJun Huang
- School of Medical Imaging, Weifang Medical University, Weifang, SD, China
| | - YanMing Ge
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, SD, China
| | - Shiyuan Liu
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China
| | - Zhaobin Li
- Department of Radiation Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Li Fan
- Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China.
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Zhang LJ, Yang J, Jin Z, Lu GM. Cardiothoracic Imaging in China: Opening Up New Horizons. J Thorac Imaging 2022; 37:353-354. [PMID: 36306266 PMCID: PMC9592163 DOI: 10.1097/rti.0000000000000681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Long Jiang Zhang
- Department of Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu Province
| | - Junjie Yang
- Senior Department of Cardiology, Sixth Medical Center of PLA General Hospital
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Guang Ming Lu
- Department of Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu Province
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