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A Comparative Study of the Diagnostic Performance of Evaluating Breast Masses for Breast Surgeons versus S-DetectTM(Samsung Medison Co., Ltd, Seoul, Korea)
J Surg Ultrasound 2019;6:58-63
Published online November 30, 2019
© 2019 The Korean Surgical Ultrasound Society

Haram Kim, Eiyoung Kwon, Youngsam Park, Eunhye Choi, Mijin Kim, Cheolseung Kim

Department of Surgery, Presbyterian Medical Center, Jeonju, Korea
Correspondence to: Cheolseung Kim
Department of Surgery, Presbyterian Medical Center, 365 Seowon-ro, Wansan-gu, Jeonju 54987, Korea
Tel: +82-63-230-1408
Fax: +82-63-230-1409
E-mail: cskimmd@hotmail.com
Received August 9, 2019; Revised October 7, 2019; Accepted November 1, 2019.
Journal of Surgical Ultrasound is an Open Access Journal. All articles are distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Purpose: Ultrasonography is widely used for examining breast mass. We used the Breast Imaging-Reporting and Data System (BI-RADS) to characterize breast lesions found on ultrasonography. Among various ultrasound techniques, we used S-DetectTM (Samsung Medison Co., Ltd, Seoul, Korea), which supports the morphological analysis of breast masses found according to BI-RADS. In addition, we compared the breast surgeons’ categorization of breast masses with that by S-DetectTM.
Methods: Breast surgeons evaluated the breast masses found using ultrasonography between April 2016 and December 2016. A total of 139 masses, which were categorized as BI-RADS 3 or 4, from 112 patients were reevaluated by S-DetectTM before performing vacuum-assisted resection or surgical excision.
Results: Of the 139 masses, 118 were benign tumors and 21 were malignant tumors. With regard to the diagnostic performance, the sensitivity of categorization was 95% for breast surgeons, but the sensitivity was relatively lower for S-detectTM (85%). However, the specificity and accuracy of S-detectTM were 70.6% and 74.1%, respectively, which were higher than those values obtained from breast surgeons (18.5% and 30.9%, respectively).
Conclusion: S-detectTM can be used by breast surgeons as a diagnostic aid when evaluating and diagnosing breast masses found on ultrasonography.
Keywords : Breast, Ultrasonography, Computer-assisted diagnosis, Artificial intelligence


November 2019, 6 (2)