Deep learning radiomics fusion model to predict visceral pleural invasion of clinical stage IA lung adenocarcinoma: a multicenter study.

Journal: Journal of cardiothoracic surgery
Published Date: May 28, 2025

Abstract

AIM: To assess the predictive performance, risk stratification capabilities, and auxiliary diagnostic utility of radiomics, deep learning, and fusion models in identifying visceral pleural invasion (VPI) in lung adenocarcinoma.

Authors

  • Jiabi Zhao
    Department of Radiology, Zhongshan Hospital, Fudan University, No.180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
  • Tingting Wang
    Department of Anesthesiology, Taizhou Hospital, Linhai, China.
  • Bin Wang
    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China; New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga 2650, Australia. Electronic address: bin.a.wang@dpi.nsw.gov.au.
  • Bhuva Maheshkumar Satishkumar
    Department of Radiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, No.507 Zhengmin Road, Yangpu District, Shanghai, 200433, China.
  • Lumin Ding
    Department of Radiology, Shanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, 200124, China.
  • Xiwen Sun
    Department of Radiology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Caizhong Chen
    Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, PR China.

Keywords

External Resources

Popular Topics
Recent Journals