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Clinical Article
Prediction of axillary lymph node metastasis in breast cancer based on intra-tumoral and peri-tumoral MRI radiomics nomogram
ZHAO Nannan  ZHU Yun  TANG Xiaomin  YANG Zhao  LI Yang  ZHANG Shuni  WANG Lingling  LI Xiaoguang  XIE Zongyu 

Cite this article as: ZHAO N N, ZHU Y, TANG X M, et al. Prediction of axillary lymph node metastasis in breast cancer based on intra-tumoral and peri-tumoral MRI radiomics nomogram[J]. Chin J Magn Reson Imaging, 2023, 14(3): 81-87, 94. DOI:10.12015/issn.1674-8034.2023.03.014.

[Abstract] Objective To investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based intra-tumoural and peri-tumoural radiomics nomogram in predicting axillary lymph node (ALN) metastases in breast cancer patients.Materials and Methods A total of 180 breast cancer patients with confirmed by preoperative DCE-MRI and pathology in the First Affiliated Hospital of Bengbu Medical College were retrospectively analyzed, which was randomly divided into a training set (n=126) and a test set (n=54) in a ratio of 7∶3. Firstly, the region of interest (ROI) was outlined at the largest level of the DCE-MRI stage 2 lesion with a conformal outreach of 6 mm, and the optimal ROI was selected by regression with the least absolute shrinkage and selection operator (LASSO). The intra-tumoural, peri-tumoural and intra+peri-tumoural radiomics scores (Rad-score) were obtained by support vector machine (SVM) to construct the intra-tumour, peri-tumour and intra+peri-tumour models respectively. The clinical model was constructed by screening clinical risk factors through single-multifactor logistic regressionby, and the most effective intra+peri-tumoural Rad-score combined with the clinical risk factors was selected to construct the radiomics nomogram. The predictive performance of each model was analyzed using the receiver operating characteristic (ROC) curve and the correspongding area under the curve (AUC) was calculated. The clinical practicability of the prediction models was assessed using calibration curves.Results The nomogram model has the best diagnostic performance. And the AUC, sensitivity, specificity, and accuracy of the nomogram model was 0.945, 87.5%, 93.0%, 92.6% for the training set and 0.942, 90.9%, 90.6%, 90.2% for the test set respectively.Conclusions The nomogram model is essential in the preoperative prediction of ALN metastasis in breast cancer, which can precisely and non-invasively provide important guidance for clinical decision-making in a scientific and non-invasive manner.
[Keywords] breast cancer;lymph nodes;axillary node;peri-tumor;magnetic resonance imaging;radiomics;nomogram

ZHAO Nannan1, 2   ZHU Yun1   TANG Xiaomin1   YANG Zhao1, 2   LI Yang1, 2   ZHANG Shuni1, 2   WANG Lingling3   LI Xiaoguang4   XIE Zongyu1*  

1 Department of Radiology, the First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China

2 Graduate School of Bengbu Medical College, Bengbu 233004, China

3 School of Medical Imaging, Bengbu Medical College, Bengbu 233004, China

4 Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, China

Corresponding author: Xie ZY, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Key Project of Natural Science Fund of Anhui Provincial Department of Education (No. KJ2019A0402); University-Level Project of Bengbu Medical College (No. 2022byzd012).
Received  2022-11-09
Accepted  2023-02-28
DOI: 10.12015/issn.1674-8034.2023.03.014
Cite this article as: ZHAO N N, ZHU Y, TANG X M, et al. Prediction of axillary lymph node metastasis in breast cancer based on intra-tumoral and peri-tumoral MRI radiomics nomogram[J]. Chin J Magn Reson Imaging, 2023, 14(3): 81-87, 94. DOI:10.12015/issn.1674-8034.2023.03.014.

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