Preoperative Prediction of Subtype and Artificial Intelligence–Driven Endomicroscopy Detection of Advanced Neoplasia in Intraductal Papillary Mucinous Neoplasms

Background and Aims: Nongastric subtypes of branch duct (BD)-intraductal papillary mucinous neoplasms (IPMNs) are associated with high-grade dysplasia/invasive adenocarcinoma (HGD/IC) and disease progression. We evaluated preoperative prediction of gastric vs nongastric BD-IPMN subtypes and assessed a needle-based confocal laser endomicroscopy–guided artificial intelligence (nCLE-AI) algorithm for detecting HGD/IC in pathologist-reclassified BD-IPMNs. METHODS: Participants with resected BD-IPMNs were enrolled from prospective studies (2015-2024). Phase 1: lesions were reclassified by subtype and dysplasia grade through blinded pathologist review, with discordant cases receiving mucin immunostaining and consensus review. Phase 2: using this reclassified pathology data, preoperative clinical and morphological features were analyzed to predict BD-IPMN subtypes. Phase 3: nCLE-AI performance in detecting HGD/IC within reclassified gastric and nongastric BD-IPMNs was evaluated using preoperative endomicroscopy videos. RESULTS: Among 63 resected BD-IPMNs (mean diameter, 35.0 ± 10.1 mm), 38% were classified as HGD/IC. Phase 1: the interobserver agreement among pathologists for subtype classification was moderate (k = 0.52; 95% CI, 0.27-0.77). Phase 2: multivariable analysis of preoperative variables revealed that Kyoto high-risk stigmata (adjusted odds ratio [aOR], 11.568; p = 0.007), unifocal lesions (aOR, 8.354; p = 0.041), and lower body mass index (aOR, 1.37; p = 0.04) predicted nongastric subtype. Phase 3: the nCLE-AI algorithm using presurgical endomicroscopy imaging showed comparable sensitivity for detecting HGD/IC in nongastric and gastric IPMN subtypes (83% vs 82%; p = 0.92), but significantly higher specificity (100% vs 44%; p = 0.06) and accuracy (87% vs 53%; p < 0.02) in the nongastric subtype. CONCLUSION: Moderate interobserver variability in BD-IPMN subtype classification among pathologists highlights the need for immunohistochemistry and consensus review in challenging cases. Preoperative clinical variables can predict the nongastric subtype, which is associated with a less favorable prognosis. nCLE-AI shows improved performance in detecting HGD/IC in nongastric BD-IPMNs, where accurate risk stratification is particularly important due to the higher risk of progression.