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Value of multi-parameter MRI combined with immune inflammatory markers in predicting axillary lymph node metastasis of breast cancer
DAI Xingwei  SHEN Yunxia  HUANG Yiqiao  YANG Chunyan  WANG Xiurong 

Cite this article as: Dai XW, Shen YX, Huang YQ, et al. Value of multi-parameter MRI combined with immune inflammatory markers in predicting axillary lymph node metastasis of breast cancer[J]. Chin J Magn Reson Imaging, 2022, 13(7): 116-120, 128. DOI:10.12015/issn.1674-8034.2022.07.021.

[Abstract] Objective To investigate the value of multi-parameter MRI combined with immune inflammatory markers in axillary lymph node metastasis (ALNM) of breast cancer.Materials and Methods In this retrospective analysis, 52 breast cancer patients were divided into lymph node metastasis group and non-metastasis group according to the pathological results. The relationship between clinical, pathological, immune inflammatory markers, multi-parameter MRI features and axillary lymph node metastasis was evaluated by univariate analysis. Multivariate logistic regression was used to screen clinical and MRI risk factors to establish clinical prediction model, MRI prediction model and combined model. The correlation between immune inflammatory markers, immunohistochemical factor expression and multi-parameter MRI features were analyzed by spearman rank correlation analysis. Evaluate model effectiveness by drawing receiver operating characteristic (ROC) curve and calibration curve. The predictive performance of different models was compared and verified by the Delong test and decision curve analysis (DCA).Results Logistic regression analysis showed that Ki-67 expression, platelet-lymphocyte ratio (PLR), tumor size, the peritumoral maximum apparent diffusion coefficient (ADCpmax), the ratio of peritumoral tumor ADC (ADCratio) and MRI lymph node characteristics were statistically significant (P<0.05). PLR was positively correlated with ADCpmax and ADCratio (P<0.05). The area under the curve (AUC) of the clinical prediction model (Ki-67+PLR) was 0.722, the AUC of the multi-parameter MRI prediction model (tumor length+ADCpmax+ADCratio+MRI lymph node characteristics) was 0.898, and the AUC of the combined prediction model was 0.914. DCA showed that the clinical value of the combined model was higher than that of the clinical prediction model.Conclusions Multi-parameter MRI combined with immune inflammatory index PLR can be used to predict the status of axillary lymph nodes in breast cancer patients non-invasively before surgery, and provide a reference for clinical diagnosis and prognosis evaluation.
[Keywords] breast cancer;magnetic resonance imaging;apparent diffusion coefficient;inflammatory markers;lymph node metastasis

DAI Xingwei1, 2   SHEN Yunxia2*   HUANG Yiqiao2   YANG Chunyan3   WANG Xiurong2  

1 Shenzhen Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen 518116, China

2 Department of Radiology, Longgang Central Hospital of Shenzhen, Shenzhen 518116, China

3 Department of Obstetrics and Gynecology, Longgang Central Hospital of Shenzhen, Shenzhen 518116, China

Shen YX, E-mail:

Conflicts of interest   None.

Received  2022-03-15
Accepted  2022-07-01
DOI: 10.12015/issn.1674-8034.2022.07.021
Cite this article as: Dai XW, Shen YX, Huang YQ, et al. Value of multi-parameter MRI combined with immune inflammatory markers in predicting axillary lymph node metastasis of breast cancer[J]. Chin J Magn Reson Imaging, 2022, 13(7): 116-120, 128.DOI:10.12015/issn.1674-8034.2022.07.021

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