{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T06:16:23Z","timestamp":1789280183399,"version":"build-2803163510"},"reference-count":31,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T00:00:00Z","timestamp":1748217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Cancer Center Support Grant of the National Institutes of Health","award":["P30CA008748"],"award-info":[{"award-number":["P30CA008748"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Accurately determining HER2 status is essential for breast cancer treatment. We developed an AI-integrated in-house application for automated Dual bright-field (BF) in situ hybridization (ISH) analysis on whole slide images (WSIs), although optimal scanning conditions remain unclear. We evaluated scanners and optimized scanning protocols for clinical application. Ten de-identified invasive breast carcinoma cases, with HER2 immunohistochemistry and FISH results, were analyzed using three scanners and six scanning protocols. WSIs scanned by Scanner \u2018A\u2019 have 0.12 \u00b5m\/pixel with 0.95 NA (A1) and 1.2 NA (A2); Scanner \u2018B\u2019 have 0.08 \u00b5m\/pixel (B1); 0.17 \u00b5m\/pixel (B2); and 0.17 \u00b5m\/pixel with extended focus (1.4 \u00b5m step size and three layers) (B3); Scanner \u2018C\u2019 has 0.26 \u00b5m\/pixel (C1) resolution. Results showed scanning protocols A1, A2, B2, and B3 yielded HER2 gene amplification status and ASCO\/CAP ISH group results consistent with manual FISH as the ground truth. However, protocol C demonstrated poor concordance due to nuclei detection failure in six cases. The AI-integrated application achieved the best performance using scanning protocols with optimized resolutions of 0.12 \u00b5m\/pixel and 0.17 \u00b5m\/pixel with extended focus. This study highlights the importance of scanner selection in AI-based HER2 assessment and demonstrates that optimized scanning parameters enhance the accuracy and reliability of automated Dual BF ISH analysis.<\/jats:p>","DOI":"10.3390\/bioengineering12060569","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T08:12:47Z","timestamp":1748419967000},"page":"569","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Optimization of Scanning Protocol for AI-Integrated Assessment of HER2 Dual Bright-Field In-Situ Hybridization Application in Breast Cancer"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2306-5598","authenticated-orcid":false,"given":"Nilay","family":"Bakoglu Malinowski","sequence":"first","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"},{"name":"Department of Pathology, Faculty of Medicine, Istanbul Medipol University, 34214 Istanbul, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6152-4487","authenticated-orcid":false,"given":"Takashi","family":"Ohnishi","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4860-8499","authenticated-orcid":false,"given":"Emine","family":"Cesmecioglu","sequence":"additional","affiliation":[{"name":"Department of Pathology, Marmara University Research and Education Hospital, 34899 Istanbul, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dara S.","family":"Ross","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tetsuya","family":"Tsukamoto","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukako","family":"Yagi","sequence":"additional","affiliation":[{"name":"Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1038\/35052073","article-title":"Untangling the ErbB signalling network","volume":"2","author":"Yarden","year":"2001","journal-title":"Nat. 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