Literature DB >> 28849324

Automated breast ultrasound: basic principles and emerging clinical applications.

Martina Zanotel1, Iliana Bednarova2, Viviana Londero2, Anna Linda2, Michele Lorenzon2, Rossano Girometti2, Chiara Zuiani2.   

Abstract

Automated breast ultrasound (ABUS) is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound (HHUS), such as operator dependence and the considerable amount of medical time necessary to perform and interpret HHUS. This new ultrasonography technique separates the moment of image acquisition (that may be performed also by a technician) from that of its interpretation, increasing reproducibility, reducing operator-dependence and physician time. Moreover, multiplanar reconstructions, especially the coronal view, introduce new diagnostic information. ABUS, with those advantages, has the potential to be used as an adjunctive tool to screening mammography, especially in the dense breast, where mammography has a relatively low sensitivity. Women's awareness of risks related to breast density is a hot topic, especially in the USA where legislative breast density notification laws increase the demand for supplemental ultrasound screening. Therefore, ABUS might have the potential to respond to this need. The purpose of this article is to present a summary of current state-of-the-art of ABUS technology and applications, with an emphasis on breast cancer screening. This article discusses also how to overcome some ABUS limitations, in order to be familiar with the new technique.

Entities:  

Keywords:  Automated breast ultrasound; Breast cancer; Screening; Ultrasonography

Mesh:

Year:  2017        PMID: 28849324     DOI: 10.1007/s11547-017-0805-z

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  55 in total

1.  Interobserver reliability of automated breast volume scanner (ABVS) interpretation and agreement of ABVS findings with hand held breast ultrasound (HHUS), mammography and pathology results.

Authors:  Michael Golatta; Dorothea Franz; Aba Harcos; Hans Junkermann; Geraldine Rauch; Alexander Scharf; Florian Schuetz; Christof Sohn; Joerg Heil
Journal:  Eur J Radiol       Date:  2013-03-27       Impact factor: 3.528

2.  Clinical utility of bilateral whole-breast US in the evaluation of women with dense breast tissue.

Authors:  S S Kaplan
Journal:  Radiology       Date:  2001-12       Impact factor: 11.105

3.  Prospective Study Comparing Two Second-Look Ultrasound Techniques: Handheld Ultrasound and an Automated Breast Volume Scanner.

Authors:  Yoonsoo Kim; Bong Joo Kang; Sung Hun Kim; Eun Jae Lee
Journal:  J Ultrasound Med       Date:  2016-08-08       Impact factor: 2.153

4.  Ultrasound as the Primary Screening Test for Breast Cancer: Analysis From ACRIN 6666.

Authors:  Wendie A Berg; Andriy I Bandos; Ellen B Mendelson; Daniel Lehrer; Roberta A Jong; Etta D Pisano
Journal:  J Natl Cancer Inst       Date:  2015-12-28       Impact factor: 13.506

5.  Occult cancer in women with dense breasts: detection with screening US--diagnostic yield and tumor characteristics.

Authors:  T M Kolb; J Lichy; J H Newhouse
Journal:  Radiology       Date:  1998-04       Impact factor: 11.105

6.  The efficacy of automated breast volume scanning over conventional ultrasonography among patients with breast lesions.

Authors:  Yuan-ming Xiao; Zhi-heng Chen; Qi-chang Zhou; Zhiyuan Wang
Journal:  Int J Gynaecol Obstet       Date:  2015-08-28       Impact factor: 3.561

7.  Automated breast ultrasound: lesion detection and BI-RADS classification--a pilot study.

Authors:  E Wenkel; M Heckmann; M Heinrich; S A Schwab; M Uder; R Schulz-Wendtland; W A Bautz; R Janka
Journal:  Rofo       Date:  2008-08-14

8.  Reduction in mortality from breast cancer after mass screening with mammography. Randomised trial from the Breast Cancer Screening Working Group of the Swedish National Board of Health and Welfare.

Authors:  L Tabár; C J Fagerberg; A Gad; L Baldetorp; L H Holmberg; O Gröntoft; U Ljungquist; B Lundström; J C Månson; G Eklund
Journal:  Lancet       Date:  1985-04-13       Impact factor: 79.321

9.  Automated Breast Ultrasound in Breast Cancer Screening of Women With Dense Breasts: Reader Study of Mammography-Negative and Mammography-Positive Cancers.

Authors:  Maryellen L Giger; Marc F Inciardi; Alexandra Edwards; John Papaioannou; Karen Drukker; Yulei Jiang; Rachel Brem; Jeremy Bancroft Brown
Journal:  AJR Am J Roentgenol       Date:  2016-04-04       Impact factor: 3.959

10.  Sensitivity and specificity of mammography and adjunctive ultrasonography to screen for breast cancer in the Japan Strategic Anti-cancer Randomized Trial (J-START): a randomised controlled trial.

Authors:  Noriaki Ohuchi; Akihiko Suzuki; Tomotaka Sobue; Masaaki Kawai; Seiichiro Yamamoto; Ying-Fang Zheng; Yoko Narikawa Shiono; Hiroshi Saito; Shinichi Kuriyama; Eriko Tohno; Tokiko Endo; Akira Fukao; Ichiro Tsuji; Takuhiro Yamaguchi; Yasuo Ohashi; Mamoru Fukuda; Takanori Ishida
Journal:  Lancet       Date:  2015-11-05       Impact factor: 79.321

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  9 in total

1.  Preoperative loco-regional staging of invasive lobular carcinoma with contrast-enhanced digital mammography (CEDM).

Authors:  Francesco Amato; Giulia Bicchierai; Donatello Cirone; Catherine Depretto; Federica Di Naro; Ermanno Vanzi; Gianfranco Scaperrotta; Tommaso Vincenzo Bartolotta; Vittorio Miele; Jacopo Nori
Journal:  Radiol Med       Date:  2019-11-26       Impact factor: 3.469

2.  Improved Inception V3 method and its effect on radiologists' performance of tumor classification with automated breast ultrasound system.

Authors:  Panpan Zhang; Zhaosheng Ma; Yingtao Zhang; Xiaodan Chen; Gang Wang
Journal:  Gland Surg       Date:  2021-07

3.  Study on automatic detection and classification of breast nodule using deep convolutional neural network system.

Authors:  Feiqian Wang; Xiaotong Liu; Na Yuan; Buyue Qian; Litao Ruan; Changchang Yin; Ciping Jin
Journal:  J Thorac Dis       Date:  2020-09       Impact factor: 2.895

4.  Influence of Breast Density on Patient's Compliance during Ultrasound Examination: Conventional Handheld Breast Ultrasound Compared to Automated Breast Ultrasound.

Authors:  Sara De Giorgis; Nicole Brunetti; Jeries Zawaideh; Federica Rossi; Massimo Calabrese; Alberto Stefano Tagliafico
Journal:  J Med Ultrasound       Date:  2020-06-04

5.  Re-evaluation of high-risk breast mammography lesions by target ultrasound and ABUS of breast non-mass-like lesions.

Authors:  Jianxing Zhang; Lishang Cai; Ling Chen; Xiyan Pang; Miao Chen; Dan Yan; Jia Liu; Liangping Luo
Journal:  BMC Med Imaging       Date:  2021-10-26       Impact factor: 1.930

6.  A Multi-Task Learning Framework for Automated Segmentation and Classification of Breast Tumors From Ultrasound Images.

Authors:  Jignesh Chowdary; Pratheepan Yogarajah; Priyanka Chaurasia; Velmathi Guruviah
Journal:  Ultrason Imaging       Date:  2022-02-07       Impact factor: 1.578

7.  Harmonic motion imaging of human breast masses: an in vivo clinical feasibility.

Authors:  Niloufar Saharkhiz; Richard Ha; Bret Taback; Xiaoyue Judy Li; Rachel Weber; Alireza Nabavizadeh; Stephen A Lee; Hanina Hibshoosh; Vittorio Gatti; Hermes A S Kamimura; Elisa E Konofagou
Journal:  Sci Rep       Date:  2020-09-17       Impact factor: 4.996

8.  Breast ultrasound: automated or hand-held? Exploring patients' experience and preference.

Authors:  Ilaria Mussetto; Licia Gristina; Simone Schiaffino; Simona Tosto; Edoardo Raviola; Massimo Calabrese
Journal:  Eur Radiol Exp       Date:  2020-02-10

9.  Automated Breast Volume Scanner (ABVS)-Based Radiomic Nomogram: A Potential Tool for Reducing Unnecessary Biopsies of BI-RADS 4 Lesions.

Authors:  Shi-Jie Wang; Hua-Qing Liu; Tao Yang; Ming-Quan Huang; Bo-Wen Zheng; Tao Wu; Chen Qiu; Lan-Qing Han; Jie Ren
Journal:  Diagnostics (Basel)       Date:  2022-01-12
  9 in total

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