Virtual Breast Sonography. Results of Clinical Application
Abstract
The aim: to evaluate the diagnostic effectiveness the automated breast volume scanner (ABVS) ACUSON S2000 (Siemens, Germany). Material and methods: The volume data sets were collected from 97 patients and a database containing 27 women with no detectable lesions in multimodal examination (BI-RADS 1), 18 women with clearly benign lesions (BI-RADS2), and 29 women with known breast cancer (BI-RADS5) was created. An independent examiner evaluated all the ABVS data on a separate workstation without any prior knowledge of the patients’ histories. Results. The diagnostic accuracy for the experimental ABVS was estimated as 88%. The independent examiner detected all breast cancers in the volume data resulting in a calculated sensitivity of 100%. After the ABVS examination, there were a high number of requests for further examination in 66%. Over-diagnosis was estimated 24 %. Conclusion. The specificity was 40%. Given the fact that during the application of ABVS no breast cancer was missed - the ABVS must still be regarded as an experimental technique for breast ultrasound, which definitely needs to undergo further evaluation studies.
About the Authors
Olga Edmundovna Yakobs
PA. Herzen Moscow Oncology Research Institute
Russian Federation
Russian Federation
Andrey Dmitrievich Kaprin
PA. Herzen Moscow Oncology Research Institute
Russian Federation
Russian Federation
Nadezhda Ivanovna Rozhkova
PA. Herzen Moscow Oncology Research Institute
Russian Federation
Russian Federation
Michail L’vovich Mazo
PA. Herzen Moscow Oncology Research Institute
Russian Federation
Russian Federation
Sergey Yurjevich Mikushin
“Gazprom” Clinic
Russian Federation
Russian Federation
References
1. Лучевая диагностика в маммологии: Руководство для врачей; Под ред. Н.И. Рожковой. М.: СИМК, 2013. 121 с.
2. Цифровая маммологическая клиника. Современные технологии; Под ред. Н.И. Рожковой. М.: СИМК, 2012. 157 с.
3. Maturo V.G., Zusmer N.R., Gilson A.J. et al. Ultrasound of the whole breast utilizing a dedicated automated breast scanner. Radiology. 1980; 137: 457-463.
4. Egan R.L., Egan K.L. Automated water-pathfull-breast sonography: correlation with histology of 176 solid lesions. Am. J. Roentgenol. 1984; 143: 499-507.
5. Wenkel E., Heckmann M., Heinrich M. et al. Automated breast ultrasound: lesion detection and BI-RADS classification - a pilot study. Rofo. 2008; 180: 804-808.
6. Kelly K.M., Dean J., Lee S.J., Comulada W.S. Breast cancer detection: radiologists' performance using mammography with and without automated whole-breast ultrasound. Eur. Radiol. 2010; 20: 2557-2564.
7. Wojcinski S., Farrokh A., Hille U. et al. 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. 2011; 3: 337-346.
8. Wang Z.L., Xu J.H., Li J.L. et al. Comparison of automated breast volume scanning to hand-held ultrasound and mammography. Radiol. Med. 2012; 117 (8): 1287-1293.
9. Kim H., Cha J.H., Oh H.Y. et al. Comparison of conventional and automated breast volume ultrasound in the description and characterization of solid breast masses based on BI-RADS features. J. Breast Cancer. 2013; 16 (3): 329-334.
10. Маммология: Национальное руководство; Под ред. В.П. Харченко, Н.И. Рожковой. М.: ГЭОТАР-Медиа, 2009. 324 с.
11. Mendelson E.B., Baum J.K., Berg W.A. et al. BI-RADS: Ultrasound. In: Breast Imaging Reporting and Data System: ACR BI-RADS - Breast Imaging Atlas. Eds D'Orsi C.J., Mendelson E.B., Ikeda D.M. et al. Reston, VA: American College of Radiology, 2003. 345 p.
12. Kusano A.S., Trichopoulos D., Terry K.L. et al. A prospective study of breast size and premenopausal breast cancer incidence. Int. J. Cancer. 2006; 118: 2031-2034.
13. Wright M.C. Graphical analysis of bra size calculation procedures. Int. J. Cloth. Sci. Technol. 2002; 14: 41-45.
14. Chae E.Y., Shin H.J., Kim H.J. Diagnostic performance of automated breast ultrasound as a replacement for a handheld second-lookultrasound for breast lesions detected initially on magnetic resonance imaging. Ultrasound Med. Biol. 2013; 39 (12): 2246-2254.
15. Wojcinski S., Gyapong S., Farrokh A. et al. Diagnostic performance and inter-observer concordance in lesion detection with the automated breast volume scanner (ABVS). BMC Med. Imaging. 2013; 13: 36.
16. Chen L., Chen Y., Diao X.H. Comparative study of automated breast 3-D ultrasound and handheld B-mode ultrasound for differentiation of benign and malignant breast masses. Ultrasound Med. Biol. 2013; 39 (10): 1735-1742.
17. Skaane P., Gullien R., Eben E.B. Interpretation of automated breast ultrasound (ABUS) with and without knowledge of mammography: a reader performance study. Acta Radiol. 2014 Mar 28; [Epub ahead of print].
18. Prosch H., Halbwachs C., Strobl C. Automated breast ultrasound vs. handheld ultrasound: BI-RADS classification, duration of the examination and patient comfort. Ultraschall Med. 2011; 32 (5): 504-510.
19. Kim Y.W., Kim S.K., Youn H.J. et al. The clinical utility оf automated breast volume scanner: a pilot study of 139 cases. J. Breast Cancer. 2013; 16 (3): 329-334.
Review
For citations:
Yakobs O.E., Kaprin A.D., Rozhkova N.I., Mazo M.L., Mikushin S.Yu. Virtual Breast Sonography. Results of Clinical Application. Medical Visualization. 2014;(2):22-32. (In Russ.)
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