ArticleArchives of pathology & laboratory medicine2026
Interobserver Variability Across Whole-Slide Imaging Systems.
Article in Archives of pathology & laboratory medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Guidance for laboratory implementation, governance and continuous assurance of artificial intelligence in histopathology.Virchows Archiv : an international journal of pathology · 2026Review
- Comparative analysis of whole-slide scanner tissue detection algorithms: Implications for scan area, scan time, and file size in high-volume digital pathology workflows.Journal of pathology informatics · 2026Article
- Deployment of AI-driven automated quality control of whole-slide images in a large tertiary cancer center.Journal of pathology informatics · 2026Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Context.—: Digital pathology whole-slide images (WSIs) must be of adequate quality for use in diagnostics and the development of artificial intelligence algorithms. Inadequate slides should be re-scanned. There is insufficient data on what qualifies as WSI adequacy. Objective.—: To report on the degree of inter-cohort agreement when evaluating WSI quality and adequacy for use in primary diagnostics. Design.—: The 60 validation slides were scanned by 3 scanners (Leica GT450, Hamamatsu NanoZoomer S360, and Huron TissueScope iQ). The resulting 180 WSIs were independently evaluated on a quality pass or fail basis by 12 observers representing 4 staff members of the following: in-house attending physicians, fellows, and imaging technicians. The Cohen's kappa was calculated overall and within each cohort, and the acceptance rate was compared between cohorts. Results.—: For almost every cohort on each scanner, the Cohen's kappa was weak (0.21-0.4) or very poor (<0.2). Based on WSI pass rates, the data yielded different scanner rankings across cohorts, with the GT450, TissueScope iQ, and NanoZoomer S360 exhibiting the highest pass rates for technicians, fellows, and attendings, respectively. Conclusions.—: There is significant interobserver and inter-cohort variability in the rating of WSIs for suitability in diagnostic pathology. Setting uniform, reproducible standards is important for patient safety, creating a uniform level of care, efficiently re-scanning subpar slides, developing artificial intelligence models on images characteristic of those used in clinical practice, and accurately representing the quality of a scanner.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.