Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.

Journal: Radiology
Published Date: Oct 26, 2021

Abstract

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non-small cell lung cancer (NSCLC). Purpose To develop a deep learning signature for N2 metastasis prediction and prognosis stratification in clinical stage I NSCLC. Materials and Methods In this retrospective study conducted from May 2020 to October 2020 in a population with clinical stage I NSCLC, an internal cohort was adopted to establish a deep learning signature. Subsequently, the predictive efficacy and biologic basis of the proposed signature were investigated in an external cohort. A multicenter diagnostic trial (registration number: ChiCTR2000041310) was also performed to evaluate its clinical utility. Finally, on the basis of the N2 risk scores, the instructive significance of the signature in prognostic stratification was explored. The diagnostic efficiency was quantified with the area under the receiver operating characteristic curve (AUC), and the survival outcomes were assessed using the Cox proportional hazards model. Results A total of 3096 patients (mean age ± standard deviation, 60 years ± 9; 1703 men) were included in the study. The proposed signature achieved AUCs of 0.82, 0.81, and 0.81 in an internal test set ( = 266), external test cohort ( = 133), and prospective test cohort ( = 300), respectively. In addition, higher deep learning scores were associated with a lower frequency of mutation ( = .04), higher rate of fusion ( = .02), and more activation of pathways of tumor proliferation ( < .001). Furthermore, in the internal test set and external cohort, higher deep learning scores were predictive of poorer overall survival (adjusted hazard ratio, 2.9; 95% CI: 1.2, 6.9; = .02) and recurrence-free survival (adjusted hazard ratio, 3.2; 95% CI: 1.4, 7.4; = .007). Conclusion The deep learning signature could accurately predict N2 disease and stratify prognosis in clinical stage I non-small cell lung cancer. © RSNA, 2021 . See also the editorial by Park and Lee in this issue.

Authors

  • Yifan Zhong
    Division of Thyroid Surgery, Jilin Provincial Key Laboratory of Surgical Translational Medicine, Jilin Provincial Precision Medicine Laboratory of Molecular Biology and Translational Medicine On Differentiated Thyroid Carcinoma, China-Japan Union Hospital Of Jilin University, Changchun, 130000, People's Republic of China.
  • Yunlang She
    Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
  • Jiajun Deng
    Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
  • Shouyu Chen
    From the Departments of Thoracic Surgery (Y.Z., Y. She, J.D., D.X., C.C.), Radiology (T.W., J.S.), and Pathology (C.W.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Rd, Shanghai 200433, China; Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C., H.Q., Y.W.); Department of Thoracic Surgery, Ningbo No. 2 Hospital, Chinese Academy of Sciences, Zhejiang, China (M.Y.); Department of Thoracic Surgery, The First Hospital of Lanzhou University, Gansu, China (M.M., C.C.); The International Science and Technology Cooperation Base for Development and Application of Key Technologies in Thoracic Surgery, Gansu Province, China (M.M., C.C.); and Department of Thoracic Surgery, Affiliated Hospital of Zunyi Medical College, Zunyi Medical College, Guizhou, China (Y. Song).
  • Tingting Wang
    Department of Anesthesiology, Taizhou Hospital, Linhai, China.
  • Minglei Yang
    Biomedical Engineering, CT Collaboration of Siemens Healthineers, No. 278, Zhouzhu Road, Pudong New District, Shanghai, 201318, People's Republic of China.
  • Minjie Ma
    From the Departments of Thoracic Surgery (Y.Z., Y. She, J.D., D.X., C.C.), Radiology (T.W., J.S.), and Pathology (C.W.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Rd, Shanghai 200433, China; Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C., H.Q., Y.W.); Department of Thoracic Surgery, Ningbo No. 2 Hospital, Chinese Academy of Sciences, Zhejiang, China (M.Y.); Department of Thoracic Surgery, The First Hospital of Lanzhou University, Gansu, China (M.M., C.C.); The International Science and Technology Cooperation Base for Development and Application of Key Technologies in Thoracic Surgery, Gansu Province, China (M.M., C.C.); and Department of Thoracic Surgery, Affiliated Hospital of Zunyi Medical College, Zunyi Medical College, Guizhou, China (Y. Song).
  • Yongxiang Song
    From the Departments of Thoracic Surgery (Y.Z., Y. She, J.D., D.X., C.C.), Radiology (T.W., J.S.), and Pathology (C.W.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Rd, Shanghai 200433, China; Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C., H.Q., Y.W.); Department of Thoracic Surgery, Ningbo No. 2 Hospital, Chinese Academy of Sciences, Zhejiang, China (M.Y.); Department of Thoracic Surgery, The First Hospital of Lanzhou University, Gansu, China (M.M., C.C.); The International Science and Technology Cooperation Base for Development and Application of Key Technologies in Thoracic Surgery, Gansu Province, China (M.M., C.C.); and Department of Thoracic Surgery, Affiliated Hospital of Zunyi Medical College, Zunyi Medical College, Guizhou, China (Y. Song).
  • Haoyu Qi
    From the Departments of Thoracic Surgery (Y.Z., Y. She, J.D., D.X., C.C.), Radiology (T.W., J.S.), and Pathology (C.W.), Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Rd, Shanghai 200433, China; Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai, China (S.C., H.Q., Y.W.); Department of Thoracic Surgery, Ningbo No. 2 Hospital, Chinese Academy of Sciences, Zhejiang, China (M.Y.); Department of Thoracic Surgery, The First Hospital of Lanzhou University, Gansu, China (M.M., C.C.); The International Science and Technology Cooperation Base for Development and Application of Key Technologies in Thoracic Surgery, Gansu Province, China (M.M., C.C.); and Department of Thoracic Surgery, Affiliated Hospital of Zunyi Medical College, Zunyi Medical College, Guizhou, China (Y. Song).
  • Yin Wang
    State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China.
  • Jingyun Shi
    Dept of Respiratory Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
  • Chunyan Wu
    Department of Obstetrics and Gynecology, Xi'an Daxing Hospital, Xi'an 710000, Shaanxi, China.
  • Dong Xie
    Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
  • Chang Chen
    Biomass Energy and Environmental Engineering Research Center, College of Chemical Engineering, Beijing University of Chemical Technology, 505 Zonghe Building A, 15 North 3rd Ring East Road, Beijing, 100029, China. chenchang@mail.buct.edu.cn.

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