Pancreatic Neuroendocine Neoplasms (pNETs)

The aim of this observational multicenter retrospective cohort study is to evaluate the differences in risk factors, prognosis, clinicopathological and metabolic characteristics between early-onset pancreatic neuroendocrine tumors (EO-PanNETs) and late-onset pancreatic neuroendocrine tumors (LO-PanNETs). The main questions it aims to answer are: Are there distinct clinical, pathological, and metabolic profiles in EO-PanNETs compared with LO-PanNETs? Do EO-PanNETs have different prognostic outcomes compared with LO-PanNETs? Researchers will compare EO-PanNET patients with LO-PanNET patients and with matched nonmalignant controls to assess differences in tumor characteristics and associated metabolic conditions. Participants will: Provide retrospective clinical, pathological, and metabolic data from hospital records. Have survival and recurrence outcomes assessed through follow-up data review.

This clinical trial aims to learn if a multimodal artificial intelligence (AI) model can enhance the diagnosis of pancreatic solid lesions. The main questions it aims to answer are: 1. Does the AI model enhance the diagnostic performance of endoscopists in diagnosing pancreatic solid lesions? 2. Does the addition of interpretability analysis further improve the diagnostic performance of the assisted endoscopists? Researchers will compare the diagnostic performance of endoscopists with or without the assistance of the AI model. Participants will: 1. Their clinical data will be prospectively collected. 2. They will be randomized to the AI-assist group and the conventional diagnosis group.