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Artificial intelligence in pediatric endoscopy for hereditary polyposis syndromes: promises and challenges
Kennedy Tham1, Nicholas Norris2, Srisindu Vellanki2
1Department of Pediatrics, University of Texas Southwestern School of Medicine.
Insights
Artificial intelligence (AI) shows promise for improving polyp detection and monitoring in children with hereditary polyposis syndromes. Further pediatric-specific research is needed for clinical use.
Area of Science:
- Gastroenterology
- Pediatric Endoscopy
- Artificial Intelligence in Medicine
Background:
- Hereditary polyposis syndromes necessitate lifelong endoscopic surveillance for children to prevent gastrointestinal complications.
- Current surveillance methods face challenges including variable lesion presentation and interobserver variability.
- The role of artificial intelligence (AI) in pediatric polyposis surveillance is not yet well-established.
Purpose of the Study:
- To review existing evidence on artificial intelligence (AI) in endoscopy.
- To explore potential applications of AI in the surveillance of pediatric hereditary polyposis syndromes.
Main Methods:
- Review of current literature on AI in adult and pediatric endoscopy.
- Analysis of AI's performance in lesion detection and review time reduction.
- Identification of potential AI applications for pediatric polyposis surveillance.
Main Results:
- AI improves adenoma detection rates and reduces missed lesions in adult colonoscopy, though direct cancer incidence reduction is unproven.
- AI demonstrates high sensitivity and efficiency in capsule endoscopy for lesion detection.
- Limited pediatric data exist, but early findings suggest AI feasibility for automated polyp detection, localization, and burden quantification in hereditary polyposis syndromes.
Conclusions:
- AI holds significant potential to enhance polyp detection, diagnostic accuracy, and monitoring in pediatric hereditary polyposis syndromes.
- Pediatric-specific datasets and robust validation studies are crucial for clinical implementation.
- AI can improve consistency and efficiency in lifelong surveillance for these patients.
Purpose Of Review:
Children with hereditary polyposis syndromes require long-term endoscopic surveillance to reduce risks of gastrointestinal complications: malignancy, bleeding, and obstruction, among others. However, surveillance remains challenging because of variable lesion distribution, subtle morphology, interobserver variability, and the burden of repeated procedures throughout the patient's lifetime. Artificial intelligence has transformed adult endoscopy, but its application in pediatric polyposis is less defined. This review summarizes current evidence and explores potential applications for children with hereditary polyposis syndromes.
Recent Findings:
In adult colonoscopy, meta-analyses and randomized trials demonstrate that artificial intelligence improves adenoma detection rates (ADR) and reduces missed lesions, though evidence linking these benefits to meaningful reductions in colorectal cancer incidence remains insufficient. In capsule endoscopy, artificial intelligence demonstrates high sensitivity for lesion detection while substantially reducing review time. Pediatric data remain limited, with no studies specific to hereditary polyposis syndromes, but early studies support feasibility. Potential applications include automated polyp detection, localization, burden quantification, and longitudinal comparisons across surveillance examinations.
Summary:
Artificial intelligence has significant potential to improve polyp detection, diagnostic consistency, accuracy, efficiency, and longitudinal disease monitoring in pediatric hereditary polyposis syndromes. Development of pediatric-specific datasets and prospective, multicenter, and outcome-driven validation studies will be essential before widespread clinical implementation.