An international study of stain variability in histopathology using qualitative and quantitative analysis

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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Publication Details

Journal
Journal of Pathology Informatics
Published
2025-02-13
DOI
https://doi.org/10.1016/j.jpi.2025.100423
Citations
14
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
34.73

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article

An international study of stain variability in histopathology using qualitative and quantitative analysis

Catriona M. Dunn, Darren Treanor, D S Brettle, Chantell Hodgson et al.
14 citations
Journal of Pathology Informatics
AI in cancer detection
34.73
article

An international study of stain variability in histopathology using qualitative and quantitative analysis

Catriona M. Dunn, Darren Treanor, D S Brettle, Chantell Hodgson, Robert Hughes
article en
14 citations

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.

Journal of Pathology InformaticsVol. 17
Linköping University (SE), St Thomas' Hospital (GB), Leeds Teaching Hospitals NHS Trust (GB), Leeds Beckett University (GB)
UK Research and Innovation
Openalex Percentile: Top 0%
AI in cancer detection
34.73
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