Multiple Tumor-related autoantibodies test enhances CT-based deep learning performance in diagnosing lung cancer with diameters < 70 mm: a prospective study in China.

Journal: BMC pulmonary medicine
Published Date: Jul 29, 2025

Abstract

BACKGROUND: Deep learning (DL) demonstrates high sensitivity but low specificity in lung cancer (LC) detection during CT screening, and the seven Tumor-associated antigens autoantibodies (7-TAAbs), known for its high specificity in LC, was employed to improve the DL's specificity for the efficiency of LC screening in China.

Authors

  • Qingcheng Meng
    Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
  • Pengfei Ren
  • Lanwei Guo
    Department of Clinical Research Management, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
  • Pengrui Gao
    Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
  • Tong Liu
    Intensive Care Medical Center, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, People's Republic of China.
  • Wenda Chen
    Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
  • Wentao Liu
    Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
  • Hui Peng
    College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
  • Mengjia Fang
    Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
  • Shuo Meng
    Department of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China.
  • Hong Ge
    Department of Radiotherapy, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
  • Meng Li
    Co-Innovation Center for the Sustainable Forestry in Southern China; Cerasus Research Center; College of Biology and the Environment, Nanjing Forestry University, Nanjing, China.
  • XueJun Chen
    Gansu Meteorological Service Center, Lanzhou, 730020, Gansu, China.

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