# The Augmented Cytopathologist: A Conceptual Exploratory Narrative Review on Immersive and Vision–Language Models Tools in Digital Pathology

**Authors:** Enrico Giarnieri, Andrea Lastrucci, Alberto Ricci, Pierdonato Bruno, Daniele Giansanti

PMC · DOI: 10.3390/jimaging12030100 · 2026-02-26

## TL;DR

This paper explores how immersive technologies and AI copilots could support cytopathologists in training and diagnostics, suggesting a future where these tools enhance rather than replace professionals.

## Contribution

Introduces the concept of the 'augmented cytopathologist' by exploring the combined use of immersive tools and vision-language models in digital pathology.

## Key findings

- Immersive tools and VLMs can support cytopathology training and workflow efficiency.
- Combined use of these technologies offers perceptual and cognitive augmentation for professionals.
- Adoption should be incremental and governed to ensure responsible use.

## Abstract

Emerging digital technologies, including immersive environments (VR/AR/XR) and Vision–Language Models (VLMs), have the potential to reshape digital pathology and medical imaging. While immersive tools can enhance spatial visualization and procedural training, VLM-based copilots offer cognitive and workflow support. Their combined impact on cytopathology remains largely conceptual and preclinical. This Conceptual Exploratory Narrative Review (CENR) examines how immersive technologies and VLM-based copilots may jointly influence cytopathologists’ professional workflow, training, and diagnostic processes, introducing the notion of the “augmented cytopathologist.” A structured exploratory approach integrated peer-reviewed literature, position papers, preprints, gray literature (technical reports, white papers, conference abstracts, blogs), and cross-disciplinary perspectives. Database searches (PubMed, Web of Science, Scopus) confirmed a limited number of studies addressing immersive or AI-assisted cytopathology imaging. Thematic analysis focused on four conceptual dimensions: (1) technological capabilities and maturity; (2) workflow and educational applications; (3) professional implications and cytopathologist role; and (4) responsible use of LLMs and VLMs as supportive tools. This approach emphasizes interpretation of emerging trends over aggregation of empirical data, enabling conceptual synthesis of early-stage implementations and perspectives in the field. Immersive technologies facilitate three-dimensional visualization, procedural skill development, and collaborative engagement, whereas VLMs support report generation, literature retrieval, and decision guidance. Together, they offer a synergistic model for perceptual and cognitive augmentation. Key challenges include technical maturity, interoperability, workflow integration, regulatory compliance, and ethical oversight. Figures illustrate representative examples of (1) remote collaborative immersive evaluation and (2) integration of immersive visualization with VLM-based copilots, highlighting potential applications in training and workflow support. The CENR underscores the potential of combining immersive tools and AI copilots to support cytopathology, particularly for education, workflow efficiency, and cognitive augmentation. Adoption should be incremental and carefully governed, emphasizing augmentative rather than transformative use. Future research should focus on clinical validation, scalable integration, and regulatory and ethical frameworks to realize the concept of the augmented cytopathologist in practice.

## Full-text entities

- **Diseases:** VLMs (MESH:D014786), Cancer (MESH:D009369), fatigue (MESH:D005221), LLM (MESH:D007806), inflammatory (MESH:D007249), MR (MESH:D060085), anxiety (MESH:D001007), COVID-19 (MESH:D000086382), hallucination (MESH:D006212), injury to (MESH:D014947), lesion (MESH:D009059), WSI (MESH:C564543), pain (MESH:D010146)
- **Chemicals:** LLM (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13027800/full.md

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Source: https://tomesphere.com/paper/PMC13027800