Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study.

Journal: Breast (Edinburgh, Scotland)
PMID: 36308926

Abstract

INTRODUCTION: Predicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.

Authors

  • Bao Li
    Key Laboratory of Cardiovascular Diseases, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
  • Fengling Li
    Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, China.
  • Zhenyu Liu
    School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.
  • FangPing Xu
    Department of Pathology, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
  • Guolin Ye
    The First People's Hospital of Foshan, Foshan, 528000, China.
  • Wei Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Yimin Zhang
    Jiangsu CM Clinical Innovation Center of Degenerative Bone & Joint Disease, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, China.
  • Teng Zhu
    Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
  • Lizhi Shao
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Computer Science and Engineering, Southeast University, Nanjing, China.
  • Chi Chen
    Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China.
  • Caixia Sun
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China; Key Laboratory of Big Data-Based Precision Medicine, Ministry of Industry and Information Technology, Beihang University, Beijing, China.
  • Bensheng Qiu
    Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China.
  • Hong Bu
    Laboratory of Pathology Key Laboratory of Transplant Engineering and Immunology NHC, West China Hospital Sichuan University Chengdu China.
  • Kun Wang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Keywords

External Resources

Popular Topics
Recent Journals