AI tool to detect and classify solid pancreatic lesions during endoscopic ultrasound
Official title: An Artificial Intelligence System for Multimodal, Multi-class Diagnosing Solid Pancreatic Lesions Based on Endoscopic Ultrasound
Run by Qilu Hospital of Shandong University · NCT07381192 · Data updated 2026-11-12
This research will test an artificial intelligence tool called iEUS-SPL to find and classify solid pancreatic lesions in adults having endoscopic ultrasound.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 383 (estimated) |
| Sponsor | Qilu Hospital of Shandong University Academic / other |
| Locations | 1 site (Jinan, Shandong) |
| Status | Recruiting |
| Started | September 1, 2025 |
| Main results expected | June 30, 2028 |
| Study ends | June 30, 2028 |
| Registry record updated | February 2, 2026 |
| Trial ID | NCT07381192 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (≥18) scheduled for EUS for suspected solid pancreatic lesions who have not received prior treatment and can give informed consent are ideal candidates.
✕Probably not a fit
Patients with contraindications to EUS, pregnancy, uncorrectable bleeding disorders, prior pancreatic surgery or stents, or altered pancreatic anatomy are unlikely to benefit from participation.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a prospective observational cohort study validating iEUS-SPL, an AI system trained on retrospectively collected EUS images, clinical data, and imaging features to detect and multi-classify solid pancreatic lesions. The system will be tested in real-time during live EUS scanning videos from prospectively enrolled patients. Investigators will measure lesion detection rate and diagnostic performance compared with standard clinical findings and available pathology. The work is conducted at Qilu Hospital of Shandong University with collaborating regional hospitals.
Why it matters
Potential benefit: If successful, the system could help doctors find and identify pancreatic lesions more quickly and accurately during EUS, potentially reducing delays and unnecessary procedures.
How similar studies have gone: Previous AI work in EUS has shown promising diagnostic accuracy for pancreatic lesions, but real-time multimodal, multi-class systems like iEUS-SPL remain relatively novel and less validated.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. 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. 2. Patients with no prior history of treatment for pancreatic lesions. Exclusion Criteria: 1. Patients with absolute contraindications to EUS examination. 2. Pregnancy or lactating. 3. Uncorrectable coagulopathy(PTT\>50 seconds or INR\>1.5) and/or uncorrectable thrombocytopenia(platelet count\<50×109/L). 4. Upper gastrointestinal obstruction. 5. 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. 6. Patients who have undergone biliary/pancreatic duct stent placement. 7. Patients who refuse to sign the informed consent.
Where it's running
-
Qilu Hospital of Shandong University
Jinan, Shandong, China Recruiting
Study contacts
- Study coordinator: Zhen Li
- Email: qilulizhen@sdu.edu.cn
- Phone: 18560086106
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.