{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T10:09:50Z","timestamp":1790762990297,"version":"4.1.0"},"reference-count":23,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T00:00:00Z","timestamp":1724630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korea Medical Device Development","award":["RS-2020-KD000007"],"award-info":[{"award-number":["RS-2020-KD000007"]}]},{"name":"Korea Medical Device Development","award":["16-2020-0001"],"award-info":[{"award-number":["16-2020-0001"]}]},{"name":"SNUBH Research Fund","award":["RS-2020-KD000007"],"award-info":[{"award-number":["RS-2020-KD000007"]}]},{"name":"SNUBH Research Fund","award":["16-2020-0001"],"award-info":[{"award-number":["16-2020-0001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>This study aims to enhance breast cancer detection accuracy through an AI-driven ultrasound tool, Vis-BUS, developed by Barreleye Inc., Seoul, South Korea. Vis-BUS incorporates Lesion Detection AI (LD-AI) and Lesion Analysis AI (LA-AI), along with a Cancer Probability Score (CPS), to differentiate between benign and malignant breast lesions. A retrospective analysis was conducted on 258 breast ultrasound examinations to evaluate Vis-BUS\u2019s performance. The primary methods included the application of LD-AI and LA-AI to b-mode ultrasound images and the generation of CPS for each lesion. Diagnostic accuracy was assessed using metrics such as the Area Under the Receiver Operating Characteristic curve (AUROC) and the Area Under the Precision-Recall curve (AUPRC). The study found that Vis-BUS achieved high diagnostic accuracy, with an AUROC of 0.964 and an AUPRC of 0.967, indicating its effectiveness in distinguishing between benign and malignant lesions. Logistic regression analysis identified that \u2018Fatty\u2019 lesion density had an extremely high odds ratio (OR) of 27.7781, suggesting potential convergence issues. The \u2018Unknown\u2019 density category had an OR of 0.3185, indicating a lower likelihood of correct classification. Medium and large lesion sizes were associated with lower likelihoods of correct classification, with ORs of 0.7891 and 0.8014, respectively. The presence of microcalcifications showed an OR of 1.360. Among Breast Imaging-Reporting and Data System categories, category C5 had a significantly higher OR of 10.173, reflecting a higher likelihood of correct classification. Vis-BUS significantly improves diagnostic precision and supports clinical decision-making in breast cancer screening. However, further refinement is needed in areas like lesion density characterization and calcification detection to optimize its performance.<\/jats:p>","DOI":"10.3390\/diagnostics14171867","type":"journal-article","created":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T07:53:37Z","timestamp":1724658817000},"page":"1867","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Enhancing Breast Cancer Detection through Advanced AI-Driven Ultrasound Technology: A Comprehensive Evaluation of Vis-BUS"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0960-0198","authenticated-orcid":false,"given":"Hyuksool","family":"Kwon","sequence":"first","affiliation":[{"name":"Laboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea"},{"name":"Imaging Division, Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea"},{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seok Hwan","family":"Oh","sequence":"additional","affiliation":[{"name":"Laboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea"},{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"},{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7269-3959","authenticated-orcid":false,"given":"Myeong-Gee","family":"Kim","sequence":"additional","affiliation":[{"name":"Laboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea"},{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"},{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youngmin","family":"Kim","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guil","family":"Jung","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyeon-Jik","family":"Lee","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sang-Yun","family":"Kim","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyeon-Min","family":"Bae","sequence":"additional","affiliation":[{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"},{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"394","DOI":"10.3322\/caac.21492","article-title":"Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"68","author":"Bray","year":"2018","journal-title":"CA Cancer J. 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