Hereditary Colorectal Cancer Syndromes: Small Bowel Cancer Risk and Endoscopic Surveillance Strategies.

Background

Hereditary colorectal cancer syndromes, including familial adenomatous polyposis (FAP), Lynch syndrome (LS), and Peutz-Jeghers syndrome (PJS), are associated with an increased risk of small bowel cancer (SBC). Due to the low incidence and non-specific presentation of SBC, effective surveillance strategies are essential for early detection and management. This review aims to evaluate and compare current endoscopic techniques for small bowel surveillance in these patients.

Methods

A comprehensive review was conducted using peer-reviewed studies sourced from PubMed. Various endoscopic modalities, including capsule endoscopy (CE), device-assisted enteroscopy (DAE), and intraoperative enteroscopy (IOE), were assessed for their diagnostic yield, safety, and clinical utility. Surveillance recommendations of the different syndromes were also examined.

Results

CE offers high sensitivity but lacks histological sampling capability. DAE, including double-balloon enteroscopy (DBE) and single-balloon enteroscopy (SBE), enables direct visualization, biopsy, and therapeutic interventions, albeit with greater procedural complexity. In FAP, duodenal surveillance follows the Spigelman classification to stratify cancer risk, while jejunal and ileal polyps remain less studied. LS patients have an increased SBC risk, warranting tailored endoscopic approaches. In PJS, surveillance aims to mitigate intussusception risks and allow early malignancy detection.

Conclusions

Optimized surveillance strategies in hereditary colorectal cancer syndromes require a multimodal approach, integrating advanced endoscopic techniques with genetic risk stratification. Centralized care in tertiary centers improves outcomes by ensuring standardized surveillance protocols and enhancing early cancer detection. Artificial intelligence (AI) applied to CE and DAE is shaping promising prospects for the future surveillance of small bowel polyps by enhancing diagnostic accuracy and reducing the duration of the diagnostic process. Further research should investigate AI-assisted imaging and molecular biomarkers to optimize screening strategies.