{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T03:40:51Z","timestamp":1792381251916,"version":"4.4.0"},"reference-count":24,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T00:00:00Z","timestamp":1792281600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T00:00:00Z","timestamp":1792281600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100003710","name":"Korea Health Industry Development Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003710","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Ultrasound Medicine"],"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To evaluate whether real\u2010time artificial intelligence (AI) breast ultrasound (US) can identify a subgroup of breast imaging reporting and data system (BI\u2010RADS) category 4A lesions without suspicious mammographic (MMG) findings in whom unnecessary biopsy may be safely avoided.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective analysis of single\u2010center biopsy registry included 641 consecutive US BI\u2010RADS 4A lesions that underwent vacuum\u2010assisted breast biopsy. Before conducting biopsy, the lesions were reassessed using a real\u2010time AI US system (CadAI\u2010B\u00ae), and MMG findings were classified as suspicious or non\u2010suspicious based on formal reports. Seven prespecified biopsy\u2010decision strategies were evaluated, including 3 AI\u2010only strategies, 3 mammography\u2010gated AI strategies, and the current standard strategy of biopsy all BI\u2010RADS 4A lesions. The primary outcomes were biopsy reduction rate, missed cancers, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy, with final pathology as the reference standard.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 641 cases of US BI\u2010RADS 4A lesions, 26 cases of malignancies (4.1%) were identified, including 14 cases of ductal carcinoma in situ (DCIS), 11 cases of invasive ductal carcinomas, and 1 case of apocrine carcinoma. AI reassigned 289 cases of lesions (45.1%) to BI\u2010RADS categories 1\u20133. AI\u2010only biopsy\u2010deferral strategies missed 30.8% and 38.5% of malignancies when biopsy was deferred for AI BI\u2010RADS \u22642 and \u22643 lesions, respectively, with DCIS accounting for most missed cancers. In contrast, among lesions without suspicious MMG findings, no malignancies were observed in AI BI\u2010RADS 1\u20133 lesions. The sequential strategy of deferring biopsy only for lesions with AI BI\u2010RADS \u22643 and non\u2010suspicious MMG findings reduced biopsies by 43.5% (279\/641) while maintaining 100.0% sensitivity (95% CI, 87.1\u2013100.0%) and increasing specificity to 45.4% (95% CI, 41.4\u201349.4%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Real\u2010time AI breast US alone could not safely support biopsy deferral in US BI\u2010RADS 4A lesions. However, after suspicious MMG findings had been excluded, AI identified a low\u2010risk subgroup in whom unnecessary biopsy could be substantially reduced without compromising cancer detection. These findings suggest that the clinical utility of real\u2010time AI breast US lies in patients without suspicious MMG findings. Prospective multicenter validation is warranted before clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jum.70439","type":"journal-article","created":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T03:14:32Z","timestamp":1792379672000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Defining the Clinical Indication for Real\u2010Time\n                    <scp>Artificial Intelligence\u2013Assisted<\/scp>\n                    Ultrasound in Breast Lesions with Low Suspicion of Malignancy"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1826-1690","authenticated-orcid":false,"given":"Jeeyeon","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Surgery, School of Medicine Kyungpook National University, Kyungpook National University Chilgok Hospital  Daegu Republic of 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Yong","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Surgery, School of Medicine Kyungpook National University, Kyungpook National University Chilgok Hospital  Daegu Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3589-5559","authenticated-orcid":false,"given":"Byeongju","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Surgery, School of Medicine Kyungpook National University, Kyungpook National University Chilgok Hospital  Daegu Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2880-6472","authenticated-orcid":false,"given":"Joon Suk","family":"Moon","sequence":"additional","affiliation":[{"name":"Department of Surgery, School of Medicine Kyungpook National University, Kyungpook National University Chilgok Hospital  Daegu Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai Lin","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Surgery, CHA Gangnam Medical Center CHA University  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,18]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.3348\/jksr.2022.0142"},{"key":"e_1_2_8_3_1","unstructured":"NewellMS DestounisSV LeungJWT DeMartiniWB LeeCH EbyPR.ACR BI\u2010RADS v2025 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