Literature DB >> 27718417

Initial experience of automated breast volume scanning (ABVS) and ultrasound elastography in predicting breast cancer subtypes and staging.

Xiao-Lei Wang1, Lin Tao1, Xian-Li Zhou2, Hong Wei1, Jia-Wei Sun1.   

Abstract

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.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Automated breast volume scanning; Breast carcinoma; Shear wave velocity; Ultrasound

Mesh:

Year:  2016        PMID: 27718417     DOI: 10.1016/j.breast.2016.09.012

Source DB:  PubMed          Journal:  Breast        ISSN: 0960-9776            Impact factor:   4.380


  5 in total

1.  PARP9 is overexpressed in human breast cancer and promotes cancer cell migration.

Authors:  Xinghong Tang; Hongying Zhang; Yan Long; Hui Hua; Yangfu Jiang; Jing Jing
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Review 2.  Automatic breast ultrasound: state of the art and future perspectives.

Authors:  Luca Nicosia; Federica Ferrari; Anna Carla Bozzini; Antuono Latronico; Chiara Trentin; Lorenza Meneghetti; Filippo Pesapane; Maria Pizzamiglio; Nicola Balesetreri; Enrico Cassano
Journal:  Ecancermedicalscience       Date:  2020-06-23

Review 3.  Evaluation of Diagnostic Performance of Automatic Breast Volume Scanner Compared to Handheld Ultrasound on Different Breast Lesions: A Systematic Review.

Authors:  Shahad A Ibraheem; Rozi Mahmud; Suraini Mohamad Saini; Hasyma Abu Hassan; Aysar Sabah Keiteb; Ahmed M Dirie
Journal:  Diagnostics (Basel)       Date:  2022-02-19

4.  Using Ultrasound-Based Multilayer Perceptron to Differentiate Early Breast Mucinous Cancer and its Subtypes From Fibroadenoma.

Authors:  Ting Liang; Junhui Shen; Shumei Zhang; Shuzhen Cong; Juanjuan Liu; Shufang Pei; Shiyao Shang; Chunwang Huang
Journal:  Front Oncol       Date:  2021-12-01       Impact factor: 6.244

5.  The potential of endoscopic ultrasound sonography (EUS)-elastography in determining the stage of pancreatic tumor.

Authors:  Afsaneh Saffarian; Pegah Eslami; Arash Dooghaie Moghadam; Faezeh Almasi; Mohamad Amin Pourhoseingholi; Hamid Asadzadeh Aghdaei; Amir Sadeghi; Mohammad Reza Zali
Journal:  Gastroenterol Hepatol Bed Bench       Date:  2021
  5 in total

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