AI System to Detect and Diagnose Pancreatic Cystic Lesions During Endoscopic Ultrasound
Official title: An Artificial Intelligence System for Multimodal, Multi-class Diagnosis of Pancreatic Cystic Lesions Based on Endoscopic Ultrasonography
Run by Qilu Hospital of Shandong University · NCT07543263 · Data updated 2026-11-12
A multicenter study tests an AI system called iEUS-PCL to help detect and differentiate pancreatic cystic lesions in real time during endoscopic ultrasound.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 176 (estimated) |
| Sponsor | Qilu Hospital of Shandong University Academic / other |
| Locations | 1 site (Jinan, Shandong) |
| Status | Recruiting |
| Started | April 20, 2026 |
| Main results expected | June 30, 2028 |
| Study ends | June 30, 2028 |
| Registry record updated | November 5, 2026 |
| Trial ID | NCT07543263 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (18+) scheduled for EUS with suspected pancreatic cystic lesions who have no prior treatment for pancreatic lesions and who provide informed consent.
✕Probably not a fit
Patients with absolute contraindications to EUS, pregnancy, uncorrectable coagulopathy, or other exclusion criteria may not benefit from this study.
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 multicenter, prospective cohort study that aims to develop and validate iEUS-PCL, an AI system that uses multimodal data from endoscopic ultrasound to detect pancreatic cystic lesions and provide differential diagnoses. The model is trained on retrospectively collected EUS images, features, clinical data, and radiologic data, and its diagnostic performance will be evaluated prospectively on real-time EUS videos and compared to endosonographers. The study will assess accuracy in detection and multi-class classification of PCLs, with outcomes benchmarked against clinician performance. Eligible participants are adults scheduled for EUS for suspected pancreatic cysts, with specified exclusions. The lead sponsor is Qilu Hospital of Shandong University, with several collaborating centers in Shandong Province, China.
Why it matters
Potential benefit: If successful, iEUS-PCL could improve the accuracy and speed of diagnosing pancreatic cystic lesions during EUS, potentially guiding management decisions.
How similar studies have gone: This approach combines AI with endoscopic imaging and has shown promise in prior pilot studies, but real-time multicenter validation for PCLs is still under investigation.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. 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. 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
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Qilu Hospital of Shandong University
Jinan, Shandong, China Recruiting
Study contacts
- Study coordinator: Zhen Li
- Email: qilulizhen@sdu.edu.cn
- Phone: 86+18560086106
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
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AI-guided diagnosis and management of pancreatic cysts using endoscopic ultrasound
This project will test an AI tool that uses EUS images plus CT/MRI and lab data to help doctors tell mucinous from non-mucinous pancreatic cysts and guide care for adults with pancreatic cystic lesions.
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.