Literature DB >> 21717306

Detectability of breast lesions under the nipple using an automated breast volume scanner: comparison with handheld ultrasonography.

Sachiko Isobe1, Mitsuhiro Tozaki, Miki Yamaguchi, Yukari Ogawa, Kanako Homma, Rie Satomi, Masahiro Saito, Chanwoong Joo, Eisuke Fukuma.   

Abstract

PURPOSE: The aims of this study were to investigate the visualization rate for the mammary gland under the nipple with automated breast ultrasonography (US) and to compare the detectability of breast lesions under the nipple with automated breast imaging and handheld US imaging.
MATERIALS AND METHODS: A total of 60 patients underwent automated breast US (ABVS; Siemens Medical Solutions, Mountain View, CA, USA) and handheld US. The scans of the four segments of the breast included sequential scans in the upper-outer (C), lower-outer (D), lower-inner (B), and upper-inner (A) regions.
RESULTS: The visualization rates for the mammary gland under the nipple were 72% (86/120 breasts) in A-scanning, 84% (101/120) in B-scanning, 78% (93/120) in C-scanning, and 80% (96/120) in D-scanning. Interscanning mode differences were statistically significant only for A-scanning and B-scanning (P = 0.02). Eventually, 98% (117/120 breasts) of the breasts examined were rated as "visualized." In 14 of the 15 patients with breast lesions under the nipple, the lesions were detectable with handheld US and the ABVS. In the other patient, the lesion was not detectable on handheld US but was detected on ABVS imaging.
CONCLUSION: ABVS imaging is by no means inferior to handheld US for detecting breast lesions under the nipple.

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Year:  2011        PMID: 21717306     DOI: 10.1007/s11604-010-0555-5

Source DB:  PubMed          Journal:  Jpn J Radiol        ISSN: 1867-1071            Impact factor:   2.374


  7 in total

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Journal:  Radiology       Date:  1999-11       Impact factor: 11.105

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Journal:  Radiology       Date:  1995-07       Impact factor: 11.105

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Authors:  S Raza; J K Baum
Journal:  Radiology       Date:  1997-04       Impact factor: 11.105

5.  Optimal scanning technique to cover the whole breast using an automated breast volume scanner.

Authors:  Mitsuhiro Tozaki; Sachiko Isobe; Miki Yamaguchi; Yukari Ogawa; Masami Kohara; Chanwoong Joo; Eisuke Fukuma
Journal:  Jpn J Radiol       Date:  2010-05-29       Impact factor: 2.374

6.  Breast disease: clinical application of US elastography for diagnosis.

Authors:  Ako Itoh; Ei Ueno; Eriko Tohno; Hiroshi Kamma; Hideto Takahashi; Tsuyoshi Shiina; Makoto Yamakawa; Takeshi Matsumura
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7.  Breast diseases: color Doppler US in differential diagnosis.

Authors:  D O Cosgrove; R P Kedar; J C Bamber; B al-Murrani; J B Davey; C Fisher; J A McKinna; W E Svensson; E Tohno; E Vagios
Journal:  Radiology       Date:  1993-10       Impact factor: 11.105

  7 in total
  8 in total

Review 1.  Diagnostic performance of the automated breast volume scanner: a systematic review of inter-rater reliability/agreement and meta-analysis of diagnostic accuracy for differentiating benign and malignant breast lesions.

Authors:  Zheying Meng; Cui Chen; Yitong Zhu; Shuling Zhang; Cong Wei; Bin Hu; Li Yu; Bing Hu; E Shen
Journal:  Eur Radiol       Date:  2015-04-28       Impact factor: 5.315

2.  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 3.  Characterisation of breast papillary neoplasm on automated breast ultrasound.

Authors:  Q-L Zhu; J Zhang; X-J Lai; H-Y Wang; M-S Xiao; Y-X Jiang
Journal:  Br J Radiol       Date:  2013-07-05       Impact factor: 3.039

4.  Fully automated lesion segmentation and visualization in automated whole breast ultrasound (ABUS) images.

Authors:  Chia-Yen Lee; Tzu-Fang Chang; Yi-Hong Chou; Kuen-Cheh Yang
Journal:  Quant Imaging Med Surg       Date:  2020-03

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.  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

7.  Diagnostic performance and inter-observer concordance in lesion detection with the automated breast volume scanner (ABVS).

Authors:  Sebastian Wojcinski; Samuel Gyapong; André Farrokh; Philipp Soergel; Peter Hillemanns; Friedrich Degenhardt
Journal:  BMC Med Imaging       Date:  2013-11-12       Impact factor: 1.930

8.  Evaluation of automated breast volume scanner for breast conservation surgery in ductal carcinoma in situ.

Authors:  Anqian Huang; Luoxi Zhu; Yanjuan Tan; Jian Liu; Jingjing Xiang; Qingqing Zhu; Lingyun Bao
Journal:  Oncol Lett       Date:  2016-07-29       Impact factor: 2.967

  8 in total

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