Identification of lymph node metastasis in pre-operation cervical cancer patients by weakly supervised deep learning from histopathological whole-slide biopsy images.

Journal: Cancer medicine
Published Date: Aug 10, 2023

Abstract

BACKGROUND: Lymph node metastasis (LNM) significantly impacts the prognosis of individuals diagnosed with cervical cancer, as it is closely linked to disease recurrence and mortality, thereby impacting therapeutic schedule choices for patients. However, accurately predicting LNM prior to treatment remains challenging. Consequently, this study seeks to utilize digital pathological features extracted from histopathological slides of primary cervical cancer patients to preoperatively predict the presence of LNM.

Authors

  • Qingqing Liu
    Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
  • Nan Jiang
  • Yiping Hao
    Cheeloo College of Medicine, Shandong University, No. 44 Wenhua West Road, Lixia District, Jinan, 250012, Shandong Province, China.
  • Chunyan Hao
    Department of Pathology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan City, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Tingting Bian
    Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining City, China.
  • Xiaohong Wang
    School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China. wxhong@buaa.edu.cn.
  • Hua Li
    Department of Stomatology, The First Medical Center Chinese PLA General Hospital Beijing China.
  • Yan Zhang
    Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, China.
  • Yanjun Kang
    Department of Obstetrics and Gynecology, Women and Children's Hospital, Qingdao University, Qingdao City, China.
  • Fengxiang Xie
    Department of Pathology, KingMed Diagnostics, Jinan City, China.
  • Yawen Li
    School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China.
  • XuJi Jiang
    Cheeloo College of Medicine, Shandong University, Jinan City, China.
  • Yuan Feng
    School of Mechanical and Electronic Engineering, Soochow University, Suzhou, Jiangsu, China.
  • Zhonghao Mao
    Cheeloo College of Medicine, Shandong University, No. 44 Wenhua West Road, Lixia District, Jinan, 250012, Shandong Province, China.
  • Qi Wang
    Biotherapeutics Discovery Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
  • Qun Gao
    School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai 264005, China.
  • Wenjing Zhang
    Department of Pharmacy, Shanghai Changhai Hospital, Naval Medical University, Shanghai, People's Republic of China.
  • Baoxia Cui
    Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
  • Taotao Dong
    Department of Obstetrics and Gynecology Qilu Hospital Cheeloo College of Medicine Shandong University Jinan Shandong China.

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