Prediction of STAS in lung adenocarcinoma with nodules ≤ 2 cm using machine learning: a multicenter retrospective study.

Journal: BMC cancer
Published Date: Mar 7, 2025

Abstract

BACKGROUND AND OBJECTIVE: Spread through air spaces (STAS) is an important factor in determining the aggressiveness and recurrence risk of lung cancer, especially in early-stage adenocarcinoma. Preoperative identification of STAS is crucial for optimizing surgical strategies. This study aimed to develop and validate machine learning models to predict the presence of STAS using preoperative clinical, radiological, and pathological data in lung cancer patients.

Authors

  • Zhan Zhang
    School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
  • Yue Zhao
    The Affiliated Eye Hospital, Nanjing Medical University, Nanjing, China.
  • Yi-Jun Ma
    Department of Thoracic Surgery, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong Province, 250063, China.
  • Chuan-Qi Chen
    Department of Gastrointestinal Surgery, Qilu Hospital of Shandong University, Jinan, Shandong Province, 250063, China.
  • Zhen-Yi Li
    Department of Thoracic Surgery, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong Province, 250063, China.
  • Yv-Kai Wang
    Department of Thoracic Surgery, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong Province, 250063, China.
  • Si-Jie Zhang
    Department of Thoracic Surgery, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong Province, 250063, China.
  • Hai-Ming Li
    Department of Thoracic Surgery, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong Province, 250063, China.
  • Yongmeng Li
    Department of Thoracic Surgery, Qianfoshan Hospital in the Shandong Province, Jinan, Shandong, China.
  • Yu Tian
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Hui Tian
    School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.

Keywords

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