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Research progress on artificial intelligence in MRI for breast cancer diagnosis and treatment response prediction
SUN Shaomei  WANG Ruolan  BI Chengliu  LI Qinqing  YANG Jun 

Cite this article as: SUN S M, WANG R L, BI C L, et al. Research progress on artificial intelligence in MRI for breast cancer diagnosis and treatment response prediction[J]. Chin J Magn Reson Imaging, 2025, 16(2): 193-197, 228. DOI:10.12015/issn.1674-8034.2025.02.031.


[Abstract] Breast cancer seriously endangers the life and health of women. The key to improve the survival rate and quality of life of the breast cancer patients are accurate and efficient diagnoses and treatment strategies. In recent years, the research of artificial intelligence (AI) based on breast MRI has made remarkable progress in early diagnosis, accurate treatment and prognosis evaluation. This review summarizes the research progress of AI MRI in differentiation of benign and malignant breast lesions, breast cancer molecular classification, quantitative evaluation of breast background parenchyma enhancement, prediction of axillary lymph node status, prognosis and recurrence prediction in recent years. Simultaneously, the current limitations and challenges are presented to provide a reference for optimizing diagnostic and treatment strategies and promoting the development of AI technology based on breast MRI.
[Keywords] breast cancer；magnetic resonance imaging；artificial intelligence；deep learning；radiomics；diagnose；prognosis

SUN Shaomei   WANG Ruolan   BI Chengliu   LI Qinqing   YANG Jun*  

Department of Radiology, Yunnan Cancer Hospital (the Third Affiliated Hospital of Kunming Medical University), Kunming 650118, China

Corresponding author: YANG J, E-mail: imdyang@163.com

Conflicts of interest   None.

Received  2024-10-29
Accepted  2025-02-10
DOI: 10.12015/issn.1674-8034.2025.02.031
Cite this article as: SUN S M, WANG R L, BI C L, et al. Research progress on artificial intelligence in MRI for breast cancer diagnosis and treatment response prediction[J]. Chin J Magn Reson Imaging, 2025, 16(2): 193-197, 228. DOI:10.12015/issn.1674-8034.2025.02.031.

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