1. Comprehensive Risk System Based on Shear Wave Elastography and BI-RADS Categories in Assessing Axillary Lymph Node Metastasis of Invasive Breast Cancer—A Multicenter Study
- Author
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Huiting Zhang, Yijie Dong, Xiaohong Jia, Jingwen Zhang, Zhiyao Li, Zhirui Chuan, Yanjun Xu, Bin Hu, Yunxia Huang, Cai Chang, Jinfeng Xu, Fajin Dong, Xiaona Xia, Chengrong Wu, Wenjia Hu, Gang Wu, Qiaoying Li, Qin Chen, Wanyue Deng, Qiongchao Jiang, Yonglin Mou, Huannan Yan, Xiaojing Xu, Hongju Yan, Ping Zhou, Yang Shao, Ligang Cui, Ping He, Linxue Qian, Jinping Liu, Liying Shi, Yanan Zhao, Yongyuan Xu, Yanyan Song, Weiwei Zhan, and Jianqiao Zhou
- Subjects
breast neoplasms ,lymphatic metastasis ,ultrasonography ,elasticity imaging techniques ,risk assessment ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
PurposeTo develop a risk stratification system that can predict axillary lymph node (LN) metastasis in invasive breast cancer based on the combination of shear wave elastography (SWE) and conventional ultrasound.Materials and MethodsA total of 619 participants pathologically diagnosed with invasive breast cancer underwent breast ultrasound examinations were recruited from a multicenter of 17 hospitals in China from August 2016 to August 2017. Conventional ultrasound and SWE features were compared between positive and negative LN metastasis groups. The regression equation, the weighting, and the counting methods were used to predict axillary LN metastasis. The sensitivity, specificity, and the areas under the receiver operating characteristic curve (AUC) were calculated.ResultsA significant difference was found in the Breast Imaging Reporting and Data System (BI-RADS) category, the “stiff rim” sign, minimum elastic modulusof the internal tumor and peritumor region of 3 mm between positive and negative LN groups (p < 0.05 for all). There was no significant difference in the diagnostic performance of the regression equation, the weighting, and the counting methods (p > 0.05 for all). Using the counting method, a 0–4 grade risk stratification system based on the four characteristics was established, which yielded an AUC of 0.656 (95% CI, 0.617–0.693, p < 0.001), a sensitivity of 54.60% (95% CI, 46.9%–62.1%), and a specificity of 68.99% (95% CI, 64.5%–73.3%) in predicting axillary LN metastasis.ConclusionA 0–4 grade risk stratification system was developed based on SWE characteristics and BI-RADS categories, and this system has the potential to predict axillary LN metastases in invasive breast cancer.
- Published
- 2022
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