The aim of this study is to develop and validate an artificial intelligence system named iEUS-PCL (intelligent endoscopic ultrasound system-pancreatic cystic lesions） for detecting and multimodal, multi-class diagnosing pancreatic cystic lesions (PCL) during endoscopic ultrasound (EUS) examination.
Patients aged ≥18 years scheduled for EUS with suspected pancreatic cystic lesions based on clinical symptoms, medical history, laboratory tests or radiological examinations, and who agree to participate in the research and voluntarily sign the informed consent.
Patients with no prior history of treatment for pancreatic lesions.
Patients with absolute contraindications to EUS examination.
Pregnancy or lactating.
Uncorrectable coagulopathy (PTT>50 seconds or INR>1.5) and/or uncorrectable thrombocytopenia(platelet count<50×109/L).
Upper gastrointestinal obstruction.
Qilu Hospital of Shandong University
Lead sponsor
Liaocheng People's Hospital
Collaborator
Taian City Central Hospital
Collaborator
Qilu Hospital of Shandong University (Qingdao)
Collaborator
Binzhou People's Hospital
Collaborator
Shandong Provincial Hospital
Collaborator
The Affiliated Hospital of Qingdao University
Collaborator
Qianfoshan Hospital
Collaborator
Shengli Oilfield Hospital
Collaborator
Binzhou Medical University
Collaborator