Literature DB >> 25280476

Automated breast ultrasound system (ABUS): reproducibility of mass localization, size measurement, and characterization on serial examinations.

Jung Min Chang1, Joo Hee Cha2, Jeong Seon Park3, Seung Ja Kim4, Woo Kyung Moon5.   

Abstract

BACKGROUND: Automated breast ultrasound (ABUS) is gaining popularity for breast cancer detection and diagnosis with its high reproducibility. Consistent recognition of breast lesions on serial exams is critical, and high reproducibility for lesion characterization is expected with ABUS, but not well reported.
PURPOSE: To retrospectively evaluate the reproducibility of ABUS for mass localization, size measurement, and characterization.
MATERIAL AND METHODS: Bilateral whole breast US images were obtained twice using a commercially available ABUS within a mean interval of 1.3 days. In total, 24 patients were imaged before biopsy or surgery. There were 24 breast cancers and nine benign diagnoses. Two breast radiologists reviewed every paired three-dimensional dataset with regard to lesion visibility, reproducibility of documented location (clockface location, distance from nipple, and lesion depth), size of the lesions, and similarity for lesion characteristics. Lesion similarity was classified as being identical, similar, or different by consensus reading using the SomoVu workstation. Intraclass correlation coefficients (ICCs) and the Bland-Altman method were used to determine the amount of agreement between assessments of lesion location and size.
RESULTS: Among 33 breast lesions, 31 lesions were depicted in both serial examinations. ICCs for the displayed lesion location (clock face location, distance from nipple), and the individual size of detected lesions were 0.994, 0.926, and 0.980, indicating excellent reliability. However, the ICC for lesion depth from the skin was 0.342 showing low reliability. For lesion similarity, 16 cancers and five benign lesions were classified as being identical, and six cancers and two benign lesions were classified as being similar. Two benign lesions were assessed to have different lesion characteristics and final assessment categories.
CONCLUSION: The ABUS provided reproducible images for mass localization, size measurement, and characterization, which may be useful for follow-up studies. © The Foundation Acta Radiologica 2014.

Entities:  

Keywords:  Automated breast ultrasound system; reproducibility; serial examination

Mesh:

Year:  2014        PMID: 25280476     DOI: 10.1177/0284185114551565

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


  10 in total

Review 1.  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

2.  Comparison between automated breast volume scanner (ABVS) versus hand-held ultrasound as a second look procedure after magnetic resonance imaging.

Authors:  Rossano Girometti; Martina Zanotel; Viviana Londero; Massimo Bazzocchi; Chiara Zuiani
Journal:  Eur Radiol       Date:  2017-01-24       Impact factor: 5.315

3.  Preliminary study of the technical limitations of automated breast ultrasound: from procedure to diagnosis.

Authors:  Maria Julia Gregório Calas; Fernanda Philadelpho Arantes Pereira; Leticia Pereira Gonçalves; Flávia Paiva Proença Lobo Lopes
Journal:  Radiol Bras       Date:  2020 Sep-Oct

4.  Automated breast volume scanner (ABVS) in assessing breast cancer size: A comparison with conventional ultrasound and magnetic resonance imaging.

Authors:  Rossano Girometti; Martina Zanotel; Viviana Londero; Anna Linda; Michele Lorenzon; Chiara Zuiani
Journal:  Eur Radiol       Date:  2017-10-10       Impact factor: 5.315

5.  Early prediction of pathological outcomes to neoadjuvant chemotherapy in breast cancer patients using automated breast ultrasound.

Authors:  Xinguang Wang; Ling Huo; Yingjian He; Zhaoqing Fan; Tianfeng Wang; Yuntao Xie; Jinfeng Li; Tao Ouyang
Journal:  Chin J Cancer Res       Date:  2016-10       Impact factor: 5.087

Review 6.  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

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.  Comparison of the background echotexture between automated breast ultrasound and handheld breast ultrasound.

Authors:  Jieun Kim; Eun Young Ko; Boo-Kyung Han; Eun Sook Ko; Ji Soo Choi; Ko Woon Park; Haejung Kim
Journal:  Medicine (Baltimore)       Date:  2022-07-08       Impact factor: 1.817

10.  A multicenter hospital-based diagnosis study of automated breast ultrasound system in detecting breast cancer among Chinese women.

Authors:  Xi Zhang; Xi Lin; Yanjuan Tan; Ying Zhu; Hui Wang; Ruimei Feng; Guoxue Tang; Xiang Zhou; Anhua Li; Youlin Qiao
Journal:  Chin J Cancer Res       Date:  2018-04       Impact factor: 5.087

  10 in total

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