An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images.

Journal: EBioMedicine
Published Date:

Abstract

BACKGROUND: Determining the origin of bone metastatic cancer (OBMC) is of great significance to clinical therapeutics. It is challenging for pathologists to determine the OBMC with limited clinical information and bone biopsy.

Authors

  • Lianghui Zhu
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen, Guangdong, China.
  • Huijuan Shi
    Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University Guangzhou, China.
  • Huiting Wei
    Department of Pathology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
  • Chengjiang Wang
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen, Guangdong, China.
  • Shanshan Shi
    CICU, Children's Hospital, Zhejiang University School of Medicine, 310052 Hangzhou, Zhejiang, China.
  • Fenfen Zhang
    Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University Guangzhou, China.
  • Renao Yan
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen, Guangdong, China.
  • Yiqing Liu
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China.
  • Tingting He
  • Liyuan Wang
    College of Biosystems Engineering and Food Science,Zhejiang University, Hangzhou 310058,China.
  • Junru Cheng
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen, Guangdong, China.
  • Hufei Duan
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China.
  • Hong Du
    Department of Pathology, GuangZhou First People's Hospital, Guangzhou, China.
  • Fengjiao Meng
    Department of Pathology, Zhongshan People's Hospital, Zhongshan, China.
  • Wenli Zhao
    Department of Pathology, The First People's Hospital of Huizhou, Huizhou, China.
  • Xia Gu
    Department of Pathology, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Linlang Guo
    Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Yingpeng Ni
    Department of Pathology, Jieyang People's Hospital (Jieyang Affiliated Hospital, Sun Yat-Sen University), Jieyang, China.
  • Yonghong He
    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China.
  • Tian Guan
    Key Laboratory of Food Quality and Safety of Guangdong Province, College of Food Science, South China Agricultural University, Guangzhou, 510642, China.
  • Anjia Han
    Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University Guangzhou, China.