Using AI to improve rapid diagnosis of pancreatic and bile duct lesions
An Artificial Intelligence System for Rapid Onsite Cytologic Pathology Evaluation（ROSE） of Endoscopic Ultrasound-guided Fine-needle Aspiration (EUS-FNA) Sample: a Prospective, Multicenter, Diagnostic Study.
This study is testing a new AI system to see if it can help doctors quickly and accurately diagnose pancreatic and bile duct problems during certain medical procedures.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 236 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Qilu Hospital of Shandong University Academic / other |
| Locations | 1 site (Jinan, Shandong) |
| Trial ID | NCT06718725 on ClinicalTrials.gov |
What this trial studies
This observational study evaluates an artificial intelligence system called ROSE-AI, designed to assist endoscopists in performing rapid on-site cytopathology evaluations during endoscopic ultrasound fine-needle aspiration (EUS-FNA). The study collects cytopathological slide images from patients who have undergone EUS-FNA and rapid on-site evaluation (ROSE) to validate the performance of the ROSE-AI system. By comparing the diagnostic capabilities of the ROSE-AI system with those of cytopathologists and endoscopists, the study aims to enhance diagnostic accuracy and efficiency in identifying malignant and non-malignant lesions of the pancreas, bile duct, liver, and lymph nodes.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 and older who are undergoing EUS-FNA with ROSE.
Not a fit: Patients with uncorrectable coagulopathy, severe illness, or inaccessible lesions for EUS-guided sampling may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could significantly improve the speed and accuracy of diagnosing pancreatic and bile duct lesions, leading to better patient outcomes.
How similar studies have performed: While the use of AI in cytopathology is an emerging field, this specific application of AI for rapid on-site evaluation during EUS-FNA is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. the patient age ≥18 years accepted EUS-FNA+ROSE. 2. agree to participate in the research and be able to sign written informed consent. Exclusion Criteria: 1. uncorrectable coagulopathy (PTT \>50 seconds or INR \>1.5) and/or uncorrectable thrombocytopenia (platelet count \<50 × 109 /L). 2. patients who were too clinically ill to undergo an EUS examination. 3. lesions that were deemed inaccessible for EUS-guided sampling. 4. unsuccessful EUS-FNA (e.g., failure to obtain an adequate specimen, patient intolerance, intraoperative accidents, etc.). 5. Patients with unqualified ROSE smear. 6. Patients who underwent biopsy during EUS-FNA but did not receive a definitive pathological diagnosis or pathological report. 7. pregnancy.
Where this trial is running
Jinan, Shandong
- Qilu Hospital of Shandong University — Jinan, Shandong, China (Recruiting)
Study contacts
- Study coordinator: Zhen Li
- Email: qilulizhen@sdu.edu.cn
- Phone: 18560086106
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.