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

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; Jianqiao Zhou

doi:10.3389/fonc.2022.830910

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

Front Oncol. 2022 Mar 10:12:830910. doi: 10.3389/fonc.2022.830910. eCollection 2022.

Authors

Huiting Zhang¹, Yijie Dong¹, Xiaohong Jia¹, Jingwen Zhang¹, Zhiyao Li², Zhirui Chuan², Yanjun Xu³, Bin Hu⁴, Yunxia Huang⁵, Cai Chang⁵, Jinfeng Xu⁶, Fajin Dong⁶, Xiaona Xia⁷, Chengrong Wu⁷, Wenjia Hu⁸, Gang Wu⁸, Qiaoying Li⁹, Qin Chen¹⁰, Wanyue Deng¹⁰, Qiongchao Jiang¹¹, Yonglin Mou¹², Huannan Yan¹², Xiaojing Xu¹³, Hongju Yan¹³, Ping Zhou¹⁴, Yang Shao¹⁴, Ligang Cui¹⁵, Ping He¹⁵, Linxue Qian¹⁶, Jinping Liu¹⁶, Liying Shi¹⁷, Yanan Zhao¹⁸, Yongyuan Xu¹⁸, Yanyan Song¹⁹, Weiwei Zhan¹, Jianqiao Zhou¹

Affiliations

¹ Department of Ultrasound, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
² Department of Medical Ultrasound, Yunnan Cancer Hospital & The Third Affiliated Hospital of Kunming Medical University, Kunming, China.
³ Department of Ultrasound in Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Institute of Ultrasound in Medicine, Shanghai, China.
⁴ Department of Ultrasound, Minhang Hospital, Fudan University, Shanghai, China.
⁵ Department of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
⁶ Department of Ultrasound, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, and The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, China.
⁷ Department of Ultrasound Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
⁸ Department of Ultrasound, People's Hospital of Henan Province, Zhengzhou, China.
⁹ Department of Ultrasound Diseases, Tangdu Hospital, Four Military Medical University, Xi'an, China.
¹⁰ Department of Ultrasound, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
¹¹ Department of Ultrasound, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
¹² Department of Ultrasound, General Hospital of Northern Theater Command, Shenyang, China.
¹³ Department of Ultrasound, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
¹⁴ Department of Ultrasound, The Third Xiangya Hospital of Central South University, Changsha, China.
¹⁵ Department of Ultrasound, Peking University Third Hospital, Beijing, China.
¹⁶ Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
¹⁷ Department of Ultrasound, Affiliated Hospital of Guizhou Medical University, Guizhou, China.
¹⁸ Department of Ultrasound, Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China.
¹⁹ Department of Biostatistics, Institute of Medical Sciences, Shanghai Jiaotong University School of Medicine, Shanghai, China.

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 modulus of 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.

Keywords: breast neoplasms; elasticity imaging techniques; lymphatic metastasis; risk assessment; ultrasonography.

Copyright © 2022 Zhang, Dong, Jia, Zhang, Li, Chuan, Xu, Hu, Huang, Chang, Xu, Dong, Xia, Wu, Hu, Wu, Li, Chen, Deng, Jiang, Mou, Yan, Xu, Yan, Zhou, Shao, Cui, He, Qian, Liu, Shi, Zhao, Xu, Song, Zhan and Zhou.