ArticleJournal of pathology informatics2025
An international study of stain variability in histopathology using qualitative and quantitative analysis.
Article in Journal of pathology informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- A guide for the deployment, validation, and accreditation of clinical digital pathology tools.Journal of pathology informatics · 2026Article
- The Missing Millions: Building Cancer Pathology Artificial Intelligence for Safety Net Populations.Mayo Clinic proceedings. Digital health · 2026Review
- Artificial Intelligence-Powered Histopathology in Stem Cell Research: Bridging Morphology, Function, and Omics.Current issues in molecular biology · 2026Review
- A protocol for evaluating robustness to H&E staining variation in computational pathology models.Journal of pathology informatics · 2026Article
- Assessing the Effects of a 3-Dimensional (3D) Pathology Tissue-Processing Workflow on Downstream Molecular Analyses.Laboratory investigation; a journal of technical methods and pathology · 2026Article
- Hardware-Attentive Programmable Fourier Ptychography Enables Task-Adaptive Label-Free Virtual Staining.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Virtual Evaluation of Hematoxylin & Eosin via Digital Pathology Survey (VEED) Project: Results from a Non-Inferiority Study of a Tabs-Based Staining Method.Diagnostics (Basel, Switzerland) · 2026Article
- Quantitative Histomorphometric Analysis of Collagen Bundles in Masson's Trichrome Stained Rat (Health science reports · 2026Article
- Staining normalization in histopathology: Method benchmarking using multicenter dataset.Scientific reports · 2026Article
- Manganese as a Cofactor in the Immunity of Mycobacterium tuberculosis Infection.Current microbiology · 2025Article
- Translating Features to Findings: Deep Learning for Melanoma Subtype Prediction.Dermatopathology (Basel, Switzerland) · 2025Review
- Lightweight self supervised learning framework for domain generalization in histopathology.Scientific reports · 2025Article
- Histopathological evaluation of abdominal aortic aneurysms with deep learning.Diagnostic pathology · 2025Article
- An Efficient Organoid Cutting Method for Long-Term Culture and High-Throughput Analyses.Tissue engineering and regenerative medicine · 2025Article
- Artificial Intelligence in Placental Pathology: New Diagnostic Imaging Tools in Evolution and in Perspective.Journal of imaging · 2025Review
- Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hematoxylin and eosin (H&E) staining accounts for over 80% of slides stained worldwide. Although routinely used, there are high levels of variation between labs due to different staining methods. Staining is a pivotal part of slide preparation, but quality control is largely subjective, with overall clinical assurance provided by external quality assessment (EQA) services, underpinned by expert assessment. Digital pathology offers the potential to provide objective quantification of stain, through color analysis, to augment EQA assessment. This large-scale study evaluated H&E staining in 247 international labs participating in the UK NEQAS CPT EQA programme. Tissue sections were circulated to each lab to stain using their routine H&E staining protocol. The slides were reviewed by independent expert UK NEQAS CPT assessors, and quantitative digital analysis was conducted, comprising of H&E color deconvolution and color difference determination (ΔE). Most labs (69%) achieved an EQA score indicating good or excellent staining, with high inter-observer concordance to support this (92.5% within one mark of each other). H&E color difference, ΔE, showed 60% of labs were within 2 ΔE of the mean, which is considered as only perceptible through close observation. There was little correlation found between H&E intensity and assessor score, however, the H&E intensity ratio indicated a trend with assessor score suggesting there may be an optimal stain relationship that should be investigated further. The presented hybrid analysis combines expert analysis with objective data. This has the potential to inform upon optimal tissue staining and allows us to consider quantitative standards of H&E staining in pathology practice.
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