Conference Report: The FutuRE oF MinimalLy InvasivE GI and Capsule DiagnosTics (REFLECT), September 2025

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Authors: Alexandra Agache, Niels Gellert Olesen, Asta Slott Skifte, Jakob Frederik Frokjaer Justsen, Anastasios Koulaouzidis
Cited by: 1
References: 35

Abstract

Capsule endoscopy (CE) is evolving from a primarily small-bowel imaging modality into a broader diagnostic platform that increasingly incorporates artificial intelligence (AI), robotic technologies, biosensing capabilities, and decentralized models of care. The REFLECT symposium brought together an international, multidisciplinary audience of clinicians, engineers, scientists, and healthcare stakeholders to critically evaluate the present and future role of CE across a range of gastrointestinal (GI) applications, including inflammatory bowel disease, GI bleeding, coeliac disease, and colorectal cancer screening. Discussions explored the clinical impact of panenteric and colon capsule endoscopy, the potential of AI to enhance diagnostic performance and streamline workflows, innovations in capsule hardware, and the design of patient-centred diagnostic pathways. While conventional endoscopy continues to serve as the benchmark in many clinical scenarios, CE was recognized for its ability to improve access, acceptability, and scalability when deployed in appropriately selected populations. The symposium also identified key barriers to broader implementation, such as reinvestigation rates, absence of standardized quality indicators, limited real-world evidence for AI tools, and ongoing economic and environmental challenges. Overall, the meeting highlighted the importance of gradual, evidence-driven integration of CE, supported by robust validation, standardized metrics, close clinician-engineer collaboration, and meaningful incorporation of patient experience, to support the development of a safe, equitable, and sustainable pathway.

Fields of Study & Subjects

Gastrointestinal Bleeding Diagnosis and Treatment Colorectal Cancer Screening and Detection COVID-19 diagnosis using AI

Publication details

Journal / source
Diagnostics
Publisher
MDPI AG
Volume
16
Issue
9
Pages
1315–1315
Publication date
27 April 2026
Language
EN