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The research progress in predicting the efficacy of neoadjuvant chemotherapy for breast cancer according to longitudinal images-based deep learning
HUANG Yao  WANG Xiaoxia  JIANG Fujie  ZHANG Jiuquan 

Cite this article as: HUANG Y, WANG X X, JIANG F J, et al. The research progress in predicting the efficacy of neoadjuvant chemotherapy for breast cancer according to longitudinal images-based deep learning[J]. Chin J Magn Reson Imaging, 2023, 14(3): 175-178, 183. DOI:10.12015/issn.1674-8034.2023.03.032.


[Abstract] Neoadjuvant chemotherapy (NACT) has been established as the standard of care for locally progressive breast cancer. Imaging plays a crucial role in keeping track of the treatment progress and effectiveness for breast cancer patients. Studies have demonstrated the efficacy and importance of utilizing longitudinal images for dynamic evaluation and forecasting the effectiveness of NACT in breast cancer treatment. When compared to single-timing images, longitudinal images offer significant benefits. In this paper, we analyzed the limitations of single-time imaging in predicting the efficacy of breast cancer NACT, and described the current status, problems and application prospects of ultrasound and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based longitudinal images in predicting the efficacy of breast cancer NACT. This paper proposes that future research can enhance the accuracy of NACT efficacy prediction through the use of multimodal, multiseries longitudinal images, as well as incorporating data from multiple centers and large sample sizes to improve the generalizability of the model. The goal is to offer guidance for future research in using longitudinal images to predict NACT efficacy in breast cancer.
[Keywords] breast cancer；magnetic resonance imaging；longitudinal images；neoadjuvant chemotherapy；efficacy prediction

HUANG Yao1, 2   WANG Xiaoxia2   JIANG Fujie2   ZHANG Jiuquan1, 2*  

1 School of Medicine, Chongqing University, Chongqing 400030, China

2 Department of Radiology, Chongqing University Cancer Hospital, Chongqing 400030, China

Corresponding author: Zhang JQ, E-mail: zhangjq_radiol@foxmail.com

Conflicts of interest   None.

ACKNOWLEDGMENTS 2021 SKY Imaging Research Fund of the Chinese International Medical Foundation (No. Z-2014-07-2101); Chongqing Natural Science Foundation (No. cstc2021jcyj-msxmX0387, CSTB2022NSCQ-MSX1158); Medical Research Project of Chongqing Municipal Health Commission (No. 2022WSJK027).
Received  2022-11-07
Accepted  2023-03-01
DOI: 10.12015/issn.1674-8034.2023.03.032
Cite this article as: HUANG Y, WANG X X, JIANG F J, et al. The research progress in predicting the efficacy of neoadjuvant chemotherapy for breast cancer according to longitudinal images-based deep learning[J]. Chin J Magn Reson Imaging, 2023, 14(3): 175-178, 183. DOI:10.12015/issn.1674-8034.2023.03.032.

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