An Artificial Intelligence System for Multimodal, Multi-class Diagnosis of Pancreatic Cystic Lesions Based on Endoscopic Ultrasonography

Recruiting now

Conditions studied: Pancreatic Cystic Lesion (PCL)

In brief

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.

Key facts

Study ID

NCT07543263

Run by

Qilu Hospital of Shandong University

People needed

176

Starts

2026-04-20

Expected to finish

2028-06-30

Last updated by the study team

2026-08-10

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• 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.

You may not qualify if…

• 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.
• Patients who underwent surgical treatment or anatomical alterations of the pancreas due to lesions in other thoracic and/or abdominal organs, as well as patients with congenital anatomical abnormalities.
• Patients who have undergone biliary/pancreatic duct stent placement.
• Patients who refuse to sign the informed consent.

Where it is running

• Qilu Hospital of Shandong University — Jinan, Shandong, China (enrolling)

Full record on ClinicalTrials.gov

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