Predicting axillary lymph node metastasis in breast cancer using a multimodal radiomics and deep learning model.

Journal: Frontiers in immunology
PMID:

Abstract

OBJECTIVE: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting axillary lymph node metastasis (ALNM) in breast cancer (BC). The objective is to provide guidance for developing scientifically individualized treatment plans, assessing prognosis, and planning preoperative interventions.

Authors

  • Fuyu Guo
    Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
  • Shiwei Sun
    Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Xiaoqian Deng
    Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
  • Yue Wang
    Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
  • Wei Yao
    Department of Respiratory Medicine, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Peng Yue
    Department of Urology, Handan First Hospital, Handan, China.
  • Shaoduo Wu
    Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
  • Junrong Yan
    Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
  • Xiaojun Zhang
    Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
  • Yangang Zhang
    Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.