Related Experiment Video
Updated: Mar 14, 2026
Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
Initial experience of automated breast volume scanning (ABVS) and ultrasound elastography in predicting breast cancer
Xiao-Lei Wang1, Lin Tao1, Xian-Li Zhou1
1Department of In-Patient Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
Objectives:
Breast cancer is a heterogeneous disease consisting of distinct histopathological subtypes with different clinical outcomes. In this article, we identified the automated breast volume scanning (ABVS) and shear wave velocity (SWV) characteristics of different pathological types of breast carcinoma.
Methods:
A retrospective review of both ABVS and SWV imaging of 118 consecutive breast masses was performed. The imaging features of both techniques were assessed with reference to histopathological results.
Results:
Echo heterogeneity with a smooth and lobulated margin was a significant feature more frequently found in mucinous carcinoma groups (100%, P < 0.05). Between different stages of ductal carcinoma, echo homogeneity was more likely in high-grade ductal carcinomas (P < 0.05). SWV differences existed between inside tumor areas and either tumor boundary or tissues outside the tumors (P < 0.05), and values differed between different breast carcinoma stages. The central and tumor margin areas of ductal carcinomas were much harder than in tubular carcinoma and micro-carcinoma, respectively (P < 0.05). SWV ROC curve analyses yielded a cut-off value of 3.015 m/s between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma in the central part of lesions, with 83.5% sensitivity and 80% specificity for T0 vs T1-3 staging.
Conclusions:
Since some features were associated with different breast carcinoma types and stages, ABVS and SWV imaging has the potential to give clues about breast carcinoma differentiation in a non-invasive manner.
