Advancing presurgical non-invasive spread through air spaces prediction in clinical stage IA lung adenocarcinoma using artificial intelligence and CT signatures.

Journal: Frontiers in surgery
Published Date: Jan 14, 2025

Abstract

BACKGROUND: To accurately identify spread through air spaces (STAS) in clinical stage IA lung adenocarcinoma, our study developed a non-invasive and interpretable biomarker combining clinical and radiomics features using preoperative CT.

Authors

  • Guanchao Ye
    Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Guangyao Wu
    Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yiying Li
    Department of Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Chi Zhang
    Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Lili Qin
    Department of Radiology, Dalian Public Health Clinical Center, Dalian, China.
  • Jianlin Wu
    Department of Respiratory Medicine, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
  • Jun Fan
    Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yu Qi
    Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Fan Yang
    School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou, China.
  • Yongde Liao
    Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Keywords

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