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• Clinical Articles •
Multimodal MRI combined with clinicopathological indicators to predict pathological complete response of axillary lymph nodes after neoadjuvant therapy for breast cancer
PENG Xuehua  WANG Xinzheng  LI Ruifeng  CHEN Cuimei  LÜ Huixin  YI Qinqin 

Cite this article as PENG X H, WANG X Z, LI R F, et al. Multimodal MRI combined with clinicopathological indicators to predict pathological complete response of axillary lymph nodes after neoadjuvant therapy for breast cancer[J]. Chin J Magn Reson Imaging, 2026, 17(8): 88-97. DOI:10.12015/issn.1674-8034.2026.08.009.


[Abstract] Objective To establish a prediction model for axillary pathological complete response (pCR) after neoadjuvant therapy (NAT) in breast cancer patients with initially positive axillary lymph nodes, by integrating multimodal MRI features of the breast, axillary lymph nodes and peritumoral region before and after treatment, as well as clinicopathological indicators, and to evaluate its predictive performance.Materials and Methods A retrospective analysis was performed on patients with breast cancer and axillary lymph node metastasis admitted to our hospital from January 2022 to August 2025. MR imaging data and clinicopathological information before and after NAT were collected. Patients were randomly divided into a training set and a validation set at a ratio of 8:2. Logistic regression was used to screen independent predictors of axillary pCR and construct a nomogram. The model performance was assessed using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA), and bootstrap resampling (1000 times) was performed for internal validation to evaluate model stability.Results A total of 197 patients were included, with an axillary pCR rate of 58.38%. Positive HER-2 status, disappearance of peritumoral edema after NAT, and non-enhancement of residual lesions were identified as independent predictive factors (P < 0.05). The model achieved an area under the ROC curve (AUC) of 0.895 (95% CI: 0.839 to 0.943) in the training set and 0.895 (95% CI: 0.773 to 0.984) in the validation set. The bootstrap-corrected optimism-corrected AUC was 0.893 (95% CI: 0.846 to 0.944). The Hosmer-Lemeshow test indicated good model fitting, and DCA showed significant net clinical benefit within a threshold probability range of 12% to 90%.Conclusions The model established in this study can effectively predict axillary pCR after NAT in breast cancer patients with initially positive axillary lymph nodes, with favorable discrimination and calibration. It can provide evidence for individualized surgical decision-making for the axilla, reduce unnecessary axillary lymph node dissection (ALND), and improve patient prognosis.
[Keywords] breast cancer；magnetic resonance imaging；neoadjuvant therapy；axillary lymph nodes；pathological complete response

PENG Xuehua1   WANG Xinzheng1   LI Ruifeng1   CHEN Cuimei1   LÜ Huixin1   YI Qinqin2*  

1 Department of Medical Imaging, People's Hospital of Longhua, Shenzhen 518109, China

2 Department of Radiology, Shenzhen People's Hospital, Shenzhen 518020, China

Corresponding author: YI Q Q, E-mail: 359808772@qq.com

Conflicts of interest   None.

Received  2026-03-27
Accepted  2026-07-12
DOI: 10.12015/issn.1674-8034.2026.08.009
Cite this article as PENG X H, WANG X Z, LI R F, et al. Multimodal MRI combined with clinicopathological indicators to predict pathological complete response of axillary lymph nodes after neoadjuvant therapy for breast cancer[J]. Chin J Magn Reson Imaging, 2026, 17(8): 88-97. DOI:10.12015/issn.1674-8034.2026.08.009.

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