Combination of DCE-MRI and NME-DWI via Deep Neural Network for Predicting Breast Cancer Molecular Subtypes.

Journal: Clinical breast cancer
PMID: 38555225

Abstract

BACKGROUND: To explore whether the combination of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and nonmono-exponential (NME) model-based diffusion-weighted imaging (DWI) via deep neural network (DNN) can improve the prediction of breast cancer molecular subtypes compared to either imaging technique used alone.

Authors

  • Zhi-Chang Ba
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.
  • Hong-Xia Zhang
    Department of Ultrasound, Beijing Tian Tan Hospital, Capital Medical University, Beijing 100070, China.
  • Ao-Yu Liu
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.
  • Xin-Xiang Zhou
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.
  • Lu Liu
    College of Pharmacy, Harbin Medical University, Harbin, China.
  • Xin-Yi Wang
    Department of Ultrasound, Peking University Third Hospital, Beijing 10091, China; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/ Beijing), Breast Center, Peking University Cancer Hospital & Institute, Beijing 100142, China.
  • Abiyasi Nanding
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.
  • Xi-Qiao Sang
    Division of Respiratory Disease, Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
  • Zi-Xiang Kuai
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.

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