AUTHOR=Zhang Huiting , Dong Yijie , Jia Xiaohong , Zhang Jingwen , Li Zhiyao , Chuan Zhirui , Xu Yanjun , Hu Bin , Huang Yunxia , Chang Cai , Xu Jinfeng , Dong Fajin , Xia Xiaona , Wu Chengrong , Hu Wenjia , Wu Gang , Li Qiaoying , Chen Qin , Deng Wanyue , Jiang Qiongchao , Mou Yonglin , Yan Huannan , Xu Xiaojing , Yan Hongju , Zhou Ping , Shao Yang , Cui Ligang , He Ping , Qian Linxue , Liu Jinping , Shi Liying , Zhao Yanan , Xu Yongyuan , Song Yanyan , Zhan Weiwei , Zhou Jianqiao TITLE=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 JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.830910 DOI=10.3389/fonc.2022.830910 ISSN=2234-943X ABSTRACT=Purpose

To 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 Methods

A 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.

Results

A 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.

Conclusion

A 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.