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

Huang,Anqian; Zhu,Luoxi; Tan,Yanjuan; Liu,Jian; Xiang,Jingjing; Zhu,Qingqing; Bao,Lingyun

doi:10.3892/ol.2016.4924

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
View Affiliations

Affiliations: Department of Ultrasound, The First People's Hospital of Hangzhou, Affiliated Hangzhou Hospital of Nanjing Medical University, Hangzhou 310006, P.R. China, Department of Breast Surgery, The First People's Hospital of Hangzhou, Affiliated Hangzhou Hospital of Nanjing Medical University, Hangzhou 310006, P.R. China, Department of Pathology, The First People's Hospital of Hangzhou, Affiliated Hangzhou Hospital of Nanjing Medical University, Hangzhou 310006, P.R. China
Published online on: July 29, 2016 https://doi.org/10.3892/ol.2016.4924
Pages: 2481-2484
Copyright: © Huang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

The present is a retrospective study examining the use of automated breast volume scanner (ABVS) for guiding breast conservation surgery in ductal carcinoma in situ (DCIS). A total of 142 patients with pathologically confirmed DCIS were initially included in the study. The patients underwent preoperative examination by conventional ultrasound and by ABVS. The BI‑RADS category system was used to identify benign and malignant lesions, after which breast conservation surgery was performed, and the therapeutic effects were compared. DCIS lesions were found in each quadrant of the breasts. Typical symptoms included: Duct ectasia and filling in 23 cases, mass (mainly solid, occasionally cystic, with or without calcification) in 38 cases, hypoechoic area (with or without calcification) in 33 cases, calcifications (simple) in 23 cases, and architectural distortion in 17 cases. In addition, 110 cases (82.1%) were detected as grade ≥4 according to the BI‑RADS category, and 92 cases (68.7%) were considered malignant lesions following conventional ultrasound scanning. The detection rate of ABVS was significantly higher than that of conventional ultrasound (χ2=268.000, P<0.001). The average tumor diameter was 2.5±0.8 cm using ABVS and 2.0±0.9 cm using conventional ultrasound (the former being significantly higher than the latter; t=6.325, P=0.034). Eight patients (5.6%) had recurrences of the cancer, and the tumor diameter in the 8 patients was significantly larger using ABVS as compared to conventional ultrasound. In the diagnosis of DCIS, ABVS was superior to conventional ultrasound scanner in guiding breast conservation surgery and predicting recurrence. However, large-scale studies are required for confirmation of the findings.

View Figures

View References

1	Yang WT and Zhu XZ: The introduction of 2012 WHO classification of tumours of the breast. Zhonghua Bing Li Xue Za Zhi. 42:78–80. 2013.(In Chinese). PubMed/NCBI
2	Si W, Li Y, Han Y, Zhang F, Wang Y, Li Y, Linghu RX, Zhang X and Yang J: epidemiological and clinicopathological trends of breast cancer in Chinese patients during 1993 to 2013: A retrospective study. Medicine (Baltimore). 94:e8202015. View Article : Google Scholar : PubMed/NCBI
3	Bok SK, Jeon Y and Hwang PS: Ultrasonographic evaluation of the effects of progressive resistive exercise in breast cancer-related lymphedema. Lymphat Res Biol. 14:18–24. 2016. View Article : Google Scholar : PubMed/NCBI
4	Wojcinski S, Farrokh A, Hille U, Wiskirchen J, Gyapong S, Soliman AA, Degenhardt F and Hillemanns P: The automated breast volume scanner (ABVS): Initial experiences in lesion detection compared with conventional handheld B-mode ultrasound: A pilot study of 50 cases. Int J Womens Health. 3:337–346. 2011. View Article : Google Scholar : PubMed/NCBI
5	Shen WC, Chang RF and Moon WK: Computer aided classifications system for breast ultrasound based on Breast Imaging Reporting and Data System (BI-RADS). Ultrasound Med Biol. 33:1688–1698. 2007. View Article : Google Scholar : PubMed/NCBI
6	Wöhrle NK, Hellerhoff K, Notohamiprodjo M, Reiser MF and Clevert DA: Automated breast volume scanner (ABVS): A new approach for breast imaging. Radiologe. 50:973–981. 2010.(In German). View Article : Google Scholar : PubMed/NCBI
7	Tozaki M, Isobe S, Yamaguchi M, Ogawa Y, Kohara M, Joo C and Fukuma E: Optimal scanning technique to cover the whole breast using an automated breast volume scanner. Jpn J Radiol. 28:325–328. 2010. View Article : Google Scholar : PubMed/NCBI
8	Shin HJ, Kim HH, Cha JH, Park JH, Lee KE and Kim JH: Automated ultrasound of the breast for diagnosis: Interobserver agreement on lesion detection and characterization. AJR Am J Roentgenol. 197:747–754. 2011. View Article : Google Scholar : PubMed/NCBI
9	Zhang Q, Hu B, Hu B and Li WB: Detection of breast lesions using an automated breast volume scanner system. J Int Med Res. 40:300–306. 2012. View Article : Google Scholar : PubMed/NCBI
10	Isobe S, Tozaki M, Yamaguchi M, Ogawa Y, Homma K, Satomi R, Saito M, Joo C and Fukuma E: Detectability of breast lesions under the nipple using an automated breast volume scanner: Comparison with handheld ultrasonography. Jpn J Radiol. 29:361–365. 2011. View Article : Google Scholar : PubMed/NCBI
11	Li N, Jiang YX, Zhu QL, Zhang J, Dai Q, Liu H, Yang Q, Wang HY, Lai XJ and Sun Q: Accuracy of an automated breast volume ultrasound system for assessment of the pre-operative extent of pure ductal carcinoma in situ: Comparison with a conventional handheld ultrasound examination. Ultrasound Med Biol. 39:2255–2263. 2013. View Article : Google Scholar : PubMed/NCBI
12	Kim YW, Kim SK, Youn HJ, Choi EJ and Jung SH: The clinical utility of automated breast volume scanner: A pilot study of 139 cases. J Breast Cancer. 16:329–334. 2013. View Article : Google Scholar : PubMed/NCBI
13	Golatta M, Franz D, Harcos A, Junkermann H, Rauch G, Scharf A, Schuetz F, Sohn C and Heil J: Interobserver reliability of automated breast volume scanner (ABVS) interpretation and agreement of ABVS findings with hand held breast ultrasound (HHUS), mammography and pathology results. Eur J Radiol. 82:e332–e336. 2013. View Article : Google Scholar : PubMed/NCBI
14	Garcia-Uribe A, Erpelding TN, Krumholz A, Ke H, Maslov K, Appleton C, Margenthaler JA and Wang LV: Dual-modality photoacoustic and ultrasound imaging system for noninvasive sentinel lymph node detection in patients with breast cancer. Sci Rep. 5:157482015. View Article : Google Scholar : PubMed/NCBI
15	Chen L, Chen Y, Diao XH, Fang L, Pang Y, Cheng AQ, Li WP and Wang Y: Comparative study of automated breast 3-D ultrasound and handheld B-mode ultrasound for differentiation of benign and malignant breast masses. Ultrasound Med Biol. 39:1735–1742. 2013. View Article : Google Scholar : PubMed/NCBI
16	Hao SY, Ou B, Li LJ, Peng YL, Wang Y, Liu LS, Xiao Y, Liu SJ, Wu CJ, Jiang YX, et al: Could ultrasonic elastography help the diagnosis of breast cancer with the usage of sonographic BI-RADS classification? Eur J Radiol. 84:2492–2500. 2015. View Article : Google Scholar : PubMed/NCBI
17	Giuliano V and Giuliano C: Improved breast cancer detection in asymptomatic women using 3D-automated breast ultrasound in mammographically dense breasts. Clin Imaging. 37:480–486. 2013. View Article : Google Scholar : PubMed/NCBI
18	Tozaki M and Fukuma E: Accuracy of determining preoperative cancer extent measured by automated breast ultrasonography. Jpn J Radiol. 28:771–773. 2010. View Article : Google Scholar : PubMed/NCBI