Quantitative analysis of imaging characteristics in lung adenocarcinoma in situ using artificial intelligence.

Journal: Thoracic cancer
PMID:

Abstract

BACKGROUND: With the rising incidence of pulmonary nodules (PNs), lung adenocarcinoma in situ (AIS) is a critical early stage of lung cancer, necessitating accurate diagnosis for early intervention. This study applies artificial intelligence (AI) for quantitative imaging analysis to differentiate AIS from atypical adenomatous hyperplasia (AAH) and minimally invasive adenocarcinoma (MIA), aiming to enhance clinical diagnosis and prevent misdiagnosis.

Authors

  • Wensong Shi
    Department of Thoracic Surgery, The fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou, China.
  • Yuzhui Hu
    Department of Geratology, Ninth People's Hospital of Zhengzhou, Zhengzhou, China.
  • Yulun Yang
    Department of Thoracic Surgery, The fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou, China.
  • Yinsen Song
    Translational Medicine Research Center (Key Laboratory of Organ Transplantation of Henan Province), The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou, China.
  • Guotao Chang
    Department of Thoracic Surgery, The fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou, China.
  • He Qian
    Institute of Microelectronics, Tsinghua University, Beijing, 10084, China; Center for Brain-Inspired Computing Research, Tsinghua University, Beijing, 10084, China. Electronic address: qianh@tsinghua.edu.cn.
  • Zhengpan Wei
    Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Liang Gao
    State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
  • Yingli Sun
    Central Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
  • Ming Li
    Radiology Department, Huadong Hospital, Affiliated with Fudan University, Shanghai, China.
  • Hang Yi
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, PR China.
  • Sikai Wu
    Department of Hepatobiliary and Vascular Surgery, The First Affiliated Hospital, School of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan Province, P. R. China.
  • Kun Wang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Yousheng Mao
    Department of Thoracic Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS), China.
  • Siyuan Ai
    Department of Thoracic Surgery, Liangxiang Hospital, Beijing, China.
  • Liang Zhao
    Graduate School of Advanced Integrated Studies in Human Survivability (Shishu-Kan), Kyoto University, Kyoto, Japan.
  • Huiyu Zheng
    Department of Thoracic Surgery, The fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou, China.
  • Xiangnan Li
    1 The Nursing College of Zhengzhou University, Zhengzhou 450052, China ; 2 Department of Thoracic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.