The primary objective is to construct a multimodal AI model (Cyst-AI) based on EUS images and clinical data such as imaging features(CT or MRI) and laboratory tests to assist endoscopists in the diagnosis of pancreatic cystic lesions(PCLs), mainly differentiating mucinous from non-mucinous lesions.
The secondary objective is to evaluate the model's effectiveness in risk stratification and clinical management for patients with PCLs.
Patients whose EUS results indicates pancreatic cystic or cystoid lesions;
Mucinous lesions: including mucinous cystic neoplasm (MCN), intraductal papillary mucinous neoplasm (IPMN);
Non-mucinous lesions: including pancreatic pseudocyst, serous cystic neoplasm (SCN), cystic neuroendocrine tumor (cNET).
Patients whose age is less than 18 years old;
Patients who have undergone pancreatic surgery before the EUS examination;
Patients who have received chemotherapy and radiotherapy for pancreatic tumors before the EUS examination;
Pathological results indicate that pancreatic lesions are metastatic lesions from other sites;