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Research progress of machine learning for predicting breast cancer response to neoadjuvant chemotherapy based on MRI
CHEN Zhigeng  LI Xiang  SHA Lin 

Cite this article as: Chen ZG, Li X, Sha L. Research progress of machine learning for predicting breast cancer response to neoadjuvant chemotherapy based on MRI[J]. Chin J Magn Reson Imaging, 2021, 12(12): 102-104. DOI:10.12015/issn.1674-8034.2021.12.024.


[Abstract] Neoadjuvant chemotherapy (NAC) is the essential component of breast cancer treatment plan. Breast cancer will show varying degrees of remission after NAC. An accurate method of efficacy prognosis can help in the adjustment of treatment plan and the selection of surgical modality that can benefit patients to the maximum extent. Machine learning (ML) can extract high-throughput information from MR images to reflect tumor heterogeneity and predict tumor response early in NAC or even before therapy. This article reviews the progress of research on ML combined with breast MRI to predict the efficacy of NAC.
[Keywords] machine learning；magnetic resonance imaging；breast cancer；neoadjuvant chemotherapy

CHEN Zhigeng   LI Xiang*   SHA Lin*  

Department of Radiology, the Second Affiliated Hospital of Dalian Medical University, Dalian 116027, China

Li X, E-mail: lixiang_5007@163.com Sha L, E-mail:drshalin@163.com

Conflicts of interest   None.

Received  2021-07-02
Accepted  2021-09-08
DOI: 10.12015/issn.1674-8034.2021.12.024
Cite this article as: Chen ZG, Li X, Sha L. Research progress of machine learning for predicting breast cancer response to neoadjuvant chemotherapy based on MRI[J]. Chin J Magn Reson Imaging, 2021, 12(12): 102-104. DOI:10.12015/issn.1674-8034.2021.12.024.

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