ArticleVirchows Archiv : an international journal of pathology2025
Image analysis for bright-field HER2 in situ hybridization: validation for clinical use.
Article in Virchows Archiv : an international journal of pathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Computational methods, clinical evidence, and translational readiness for artificial intelligence for HER2 assessment using silver in situ hybridization (SISH).Breast cancer research : BCR · 2026Pooled it
- Artificial intelligence enhances cancer cell selection for HER2 gene amplification assessment in breast carcinoma.Virchows Archiv : an international journal of pathology · 2026Article
- BDNet: A Real-Time Biomedical Image Denoising Network with Gradient Information Enhancement Loss.Biosensors · 2026Article
- Digital pathology in tau research: A comparison of QuPath and HALO.Journal of neuropathology and experimental neurology · 2025Article
- Comparative Analysis of Equivocal (2+) and Positive (3+) HER2 Immunohistochemistry (IHC) and Bright-Field Dual-Color In Situ Hybridization (DISH) in Primary Breast Cancer From 1,307 Node-Positive Patients.Breast cancer : basic and clinical research · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present study was to develop and validate a quantitative image analysis (IA) algorithm to aid pathologists in assessing bright-field HER2 in situ hybridization (ISH) tests in solid cancers. A cohort of 80 sequential cases (40 HER2-negative and 40 HER2-positive) were evaluated for HER2 gene amplification with bright-field ISH. We developed an IA algorithm using the ISH Module from HALO software to automatically quantify HER2 and CEP17 copy numbers per cell as well as the HER2/CEP17 ratio. We observed a high correlation of HER2/CEP17 ratio, an average of HER2 and CEP17 copy number per cell between visual and IA quantification (Pearson's correlation coefficient of 0.842, 0.916, and 0.765, respectively). IA was able to count from 124 cells to 47,044 cells (median of 5565 cells). The margin of error for the visual quantification of the HER2/CEP17 ratio and of the average of HER2 copy number per cell decreased from a median of 0.23 to 0.02 and from a median of 0.49 to 0.04, respectively, in IA. Curve estimation regression models showed that a minimum of 469 or 953 invasive cancer cells per case is needed to reach an average margin of error below 0.1 for the HER2/CEP17 ratio or for the average of HER2 copy number per cell, respectively. Lastly, on average, a case took 212.1 s to execute the IA, which means that it evaluates about 130 cells/s and requires 6.7 s/mm
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