Multiparametric MRI-based Interpretable Machine Learning Radiomics Model for Distinguishing Between Luminal and Non-luminal Tumors in Breast Cancer: A Multicenter Study.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: To construct and validate an interpretable machine learning (ML) radiomics model derived from multiparametric magnetic resonance imaging (MRI) images to differentiate between luminal and non-luminal breast cancer (BC) subtypes.

Authors

  • Yi Zhou
    Eye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
  • Guihan Lin
    Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China; Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui 323000, China.
  • Weiyue Chen
    Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Zhejiang Engineering Research Center of Interventional Medicine Engineering and Biotechnology, Key Laboratory of Precision Medicine of Lishui City, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China; Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui 323000, China.
  • Yongjun Chen
    Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Changsheng Shi
    Department of Interventional Vascular Surgery, The Third Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China.
  • Zhiyi Peng
    Department of Radiology, First Affiliated Hospital of Zhejiang University, Hangzhou, 310003, China.
  • Ling Chen
    Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States.
  • Shibin Cai
    Department of Breast Surgery, The Fifth Affliated Hospital of Wenzhou Medical University, LiShui Municipal Central Hospital, Lishui, 323000, China. caisb614@foxmail.com.
  • Ying Pan
    Department of Endocrinology, Kunshan Hospital Affiliated to Jiangsu University, Kunshan, China.
  • Minjiang Chen
    Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital of Zhejiang University, Lishui 323000, China.
  • Chenying Lu
    Departments of Medicine and Radiology, State University of New York, Upstate Medical University Hospital, Syracuse, USA.
  • Jiansong Ji
    Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital of Zhejiang University, Lishui 323000, China.
  • Shuzheng Chen
    Department of Breast Surgery, The Fifth Affliated Hospital of Wenzhou Medical University, LiShui Municipal Central Hospital, Lishui, 323000, China. dr.susan@163.com.