Literature DB >> 21498319

Breast cancers initially detected by hand-held ultrasound: detection performance of radiologists using automated breast ultrasound data.

Jung Min Chang1, Woo Kyung Moon, Nariya Cho, Jeong Seon Park, Seung Ja Kim.   

Abstract

BACKGROUND: Ultrasonography (US) has been used as an important adjunct to mammography (MG), and automated breast US (ABUS) scanners were originally designed to effectively examine the breast in its entirety.
PURPOSE: To retrospectively assess the performance of radiologists in the detection of breast cancers, initially detected by hand-held ultrasound (HHUS), using 3D breast volume data obtained from a commercial ABUS system.
MATERIAL AND METHODS: Bilateral whole breast US was performed using ABUS in 61 consecutive women who were scheduled to undergo US-guided needle biopsy due to suspicious breast masses detected during screening HHUS. Fourteen cancers in 13 women and 48 normal breasts of 48 women with benign disease in the contralateral breast were selected. Three radiologists who had not performed the HHUS examinations independently reviewed the 3D ABUS data for any lesions that required recall for further evaluation. Sensitivities and false-positive rates were calculated.
RESULTS: The sensitivities of the three readers for cancer detection were 78.6% (11/14), 78.6%, and 57.1% (8/14), respectively, with false-positive rates of 20.8% (10/48), 12.5% (6/48) and 8.3% (4/48). Seven cancers were detected by all three readers, four cancers by two readers, and one cancer by one reader. Two invasive cancers were not detected by any reader.
CONCLUSION: Of HHUS-detected cancers, only 57.1-78.6% were identified with ABUS. A substantial level of experience and training is necessary to improve cancer detection by ABUS.

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Year:  2011        PMID: 21498319     DOI: 10.1258/ar.2010.100179

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  10 in total

1.  Comparison of automated breast volume scanning to hand-held ultrasound and mammography.

Authors:  Zhi Li Wang; Jian Hong Xu; Jian Hong Xw; Jun Lai Li; Yan Huang; Jie Tang
Journal:  Radiol Med       Date:  2012-06-28       Impact factor: 3.469

Review 2.  Automated breast ultrasound: basic principles and emerging clinical applications.

Authors:  Martina Zanotel; Iliana Bednarova; Viviana Londero; Anna Linda; Michele Lorenzon; Rossano Girometti; Chiara Zuiani
Journal:  Radiol Med       Date:  2017-08-28       Impact factor: 3.469

Review 3.  Risk-based Breast Cancer Screening: Implications of Breast Density.

Authors:  Christoph I Lee; Linda E Chen; Joann G Elmore
Journal:  Med Clin North Am       Date:  2017-07       Impact factor: 5.456

4.  Automated Breast Ultrasound: Dual-Sided Compared with Single-Sided Imaging.

Authors:  Eric D Larson; Won-Mean Lee; Marilyn A Roubidoux; Mitchel M Goodsitt; Chris Lashbrook; Fouzaan Zafar; Oliver D Kripfgans; Kai Thomenius; Paul L Carson
Journal:  Ultrasound Med Biol       Date:  2016-06-03       Impact factor: 2.998

5.  The clinical utility of automated breast volume scanner: a pilot study of 139 cases.

Authors:  Young Wook Kim; Seon Kwang Kim; Hyun Jo Youn; Eun Jung Choi; Sung Hoo Jung
Journal:  J Breast Cancer       Date:  2013-09-30       Impact factor: 3.588

6.  Automated Detection Algorithm of Breast Masses in Three-Dimensional Ultrasound Images.

Authors:  Ji-Wook Jeong; Donghoon Yu; Sooyeul Lee; Jung Min Chang
Journal:  Healthc Inform Res       Date:  2016-10-31

7.  False-negative results on computer-aided detection software in preoperative automated breast ultrasonography of breast cancer patients.

Authors:  Youngjune Kim; Jiwon Rim; Sun Mi Kim; Bo La Yun; So Yeon Park; Hye Shin Ahn; Bohyoung Kim; Mijung Jang
Journal:  Ultrasonography       Date:  2020-03-24

8.  Dependability of Automated Breast Ultrasound (ABUS) in Assessing Breast Imaging Reporting and Data System (BI-RADS) Category and Size of Malignant Breast Lesions Compared with Handheld Ultrasound (HHUS) and Mammography (MG).

Authors:  He Chen; Ming Han; Hui Jing; Zhao Liu; Haitao Shang; Qiucheng Wang; Wen Cheng
Journal:  Int J Gen Med       Date:  2021-12-01

9.  Computer-aided detection system for masses in automated whole breast ultrasonography: development and evaluation of the effectiveness.

Authors:  Jeoung Hyun Kim; Joo Hee Cha; Namkug Kim; Yongjun Chang; Myung-Su Ko; Young-Wook Choi; Hak Hee Kim
Journal:  Ultrasonography       Date:  2014-02-26

10.  Interobserver agreement on the interpretation of automated whole breast ultrasonography.

Authors:  Eun Jeong Kim; Sung Hun Kim; Bong Joo Kang; Yun Ju Kim
Journal:  Ultrasonography       Date:  2014-04-21
  10 in total

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