Back to Search Start Over

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

Authors :
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
Source :
Frontiers in Oncology, Vol 12 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

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.

Details

Language :
English
ISSN :
2234943X
Volume :
12
Database :
Directory of Open Access Journals
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.929a39dbeb6c4310aee9167ab6f0826c
Document Type :
article
Full Text :
https://doi.org/10.3389/fonc.2022.830910