Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: To develop a MRI-based deep learning signature for predicting axillary response after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients.

Authors

  • Biyuan Zhang
    Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, People's Republic of China (B.Z., Y.Y., H.W., Q.W.).
  • Yimiao Yu
    Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, People's Republic of China (B.Z., Y.Y., H.W., Q.W.).
  • Yan Mao
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Haiji Wang
    Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, People's Republic of China (B.Z., Y.Y., H.W., Q.W.).
  • Meng Lv
    State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
  • Xiaohui Su
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, People's Republic of China (X.S., Z.Z., T.B.).
  • Yongmei Wang
    The Second Hospital of Jilin University, Changchun, 130000, Jilin, People's Republic of China.
  • Zhenghao Li
    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Zaixian Zhang
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, People's Republic of China (X.S., Z.Z., T.B.).
  • Tiantian Bian
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong, People's Republic of China (X.S., Z.Z., T.B.).
  • Qi Wang
    Biotherapeutics Discovery Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.