ArticleVirchows Archiv : an international journal of pathology2026
Toward a regional digital pathology network in Tuscany: current status and implementation roadmap.
Article in Virchows Archiv : an international journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
2 citing papers in PubMed.
- Practical considerations for pathologists when selecting digital pathology systems: an ESDIP guide.The Journal of pathology · 2026Review
- Conditional Acceptance and the Optimism-Knowledge Gap: A Scoping Review of Attitudes and Perceptions of Artificial Intelligence in Healthcare in Italy.Medical sciences (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
Abstract
Digital pathology (DP) is reshaping diagnostic workflows, offering enhanced accuracy, efficiency, and collaboration through high-resolution slide scanning, artificial intelligence (AI), and cloud-based infrastructure. In Tuscany, the adoption of DP is framed within a regionally integrated healthcare system composed of three local health authorities and four university hospitals, coordinated under a hub-and-spoke model. This structure supports the potential for widespread DP implementation, leveraging centralized expertise and shared digital infrastructure. A region-wide survey involving all public pathology centers in Tuscany confirmed that all institutions are already equipped with at least one whole slide scanner. Building on this foundation, the region has initiated a strategic transformation stepwise process to implement and progressively expand DP workflows. Key actions included the adoption of a common regional laboratory information system (LIS), the development of a centralized cloud repository ensuring secure data access, and the design of telepathology modules to enable remote consultations and second opinions. Dedicated training programs for technical staff and the progressive introduction of AI-assisted tools are also part of this roadmap, ensuring readiness for routine clinical integration. The benefits of DP in Tuscany are manifold: faster diagnostic turnaround, improved inter-institutional collaboration, standardized reporting, and opportunities for research and education. Integration of AI-assisted tools is expected to support routine diagnostics, especially in high-volume and complex cases. The regional network also creates a foundation for multi-omics integration and computational pathology research. To ensure successful implementation, the region adopted a phased, scalable approach backed by regulatory alignment and continuous professional development. A unified DP network with shared protocols and centralized resources will be crucial. Tuscany's experience may serve as a blueprint for other regions aiming to transition toward a digital, AI-powered pathology ecosystem aligned with the broader goals of precision medicine.
Indexed as
Identifiers
41603956What Socratic holds
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 Socratic graph.