An Artificial Intelligence System for Multimodal, Multi-class Diagnosing Solid Pancreatic Lesions Based on Endoscopic Ultrasound

Recruiting now

Conditions studied: Endoscopic Ultrasound (EUS), Solid Pancreatic Lesion

In brief

The aim of this study is to validate an artificial intelligence system named iEUS-SPL(intelligent endoscopic ultrasound system-solid pancreatic lesion) for detecting and multimodal, multi-class diagnosing solid pancreatic lesions during endoscopic ultrasound(EUS) examination.

Key facts

Study ID

NCT07381192

Run by

Qilu Hospital of Shandong University

People needed

383

Starts

2025-09-01

Expected to finish

2028-06-30

Last updated by the study team

2026-02-02

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• Patients aged ≥18 years scheduled for EUS with suspected solid pancreatic lesions based on clinical symptoms, medical history, laboratory tests or radiological examinations agree to participate in the research and be able to sign 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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