Optimization of scanning protocol for AI-integrated assessment of HER2 Dual bright-field in-situ hybridization application in breast cancer Journal Article
| Authors: | Bakoglu Malinowski, N.; Ohnishi, T.; Cesmecioglu, E.; Ross, D. S.; Tsukamoto, T.; Yagi, Y. |
| Article Title: | Optimization of scanning protocol for AI-integrated assessment of HER2 Dual bright-field in-situ hybridization application in breast cancer |
| Abstract: | 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 'A' have 0.12 mu m/pixel with 0.95 NA (A1) and 1.2 NA (A2); Scanner 'B' have 0.08 mu m/pixel (B1); 0.17 mu m/pixel (B2); and 0.17 mu m/pixel with extended focus (1.4 mu m step size and three layers) (B3); Scanner 'C' has 0.26 mu m/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 mu m/pixel and 0.17 mu m/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. |
| Keywords: | artificial intelligence; breast carcinoma; whole slide image; dual bright-field in-situ hybridization; scanning protocol |
| Journal Title: | Bioengineering |
| Volume: | 12 |
| Issue: | 6 |
| ISSN: | 2306-5354 |
| Publisher: | MDPI |
| Date Published: | 2025-06-01 |
| Start Page: | 569 |
| Language: | English |
| ACCESSION: | WOS:001516258000001 |
| DOI: | 10.3390/bioengineering12060569 |
| PROVIDER: | wos |
| PMCID: | PMC12190017 |
| PUBMED: | 40564386 |
| Notes: | Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PubMed and PDF -- MSK corresponding author is Yukako Yagi -- MSK author Nilay Bakoglu is listed as 'Nilay Bakoglu Malinowski' on the original publication -- Source: Wos |
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