An Artificial Intelligence System for ROSE of EUS-FNA Sample: a Prospective, Multicenter, Diagnostic Study.

Recruiting

• Conditions: The Malignant Lesions and Non-malignant Lesions of Pancreas, Bile Duct, Liver and Lymph Node

• Registration Number: NCT06718725
• Lead Sponsor: Qilu Hospital of Shandong University

Brief Summary

This is an observational study with a prospective, multicenter, disgnostic design. An artificial intelligence system named ROSE-AI system was developed using cytopathological slide images taken by microscope camera or smartphone of pancreas, bile duct, liver and lymph node, collected retrospectively from patients who underwent EUS-FNA and ROSE, and the perfo...

Detailed Description

Not available

Basic Information
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Recruitment & Eligibility
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Study & Design
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Trial Locations

Study Timeline

• Status Verified: 2024-09
• Study Start: 2024-09-01
• Study First Submitted: 2024-12-02
• Study First Submitted QC: 2024-12-02
• Last Update Submitted: 2024-12-02
• Study First Posted: 2024-12-05
• Last Update Posted: 2024-12-05
• Primary Completion: 2026-04
• Study Completion: 2026-04

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 236

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.

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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.

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Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
the accuracy, sensitivity and specificity of the ROSE-AI system in identifying malignant/non-malignant ROSE samples	During procedure	The primary outcome of the study is to evaluate the performance of the ROSE-AI system in identifying the malignant/non-malignant ROSE samples of pancreatic, bile duct, hepatic and lymph node based on both images taken by microscope camera and smartphone, and comparing the performance between the ROSE-AI system and endoscopists, cytopathologists.

Secondary Outcome Measures

Name	Time	Method
comparing the diagnostic performance between endoscopists with ROSE-AI system and without ROSE-AI system	During procedure	A cross-over human-AI contest using images of the prospective testing dataset will be performed. The diagnostic performance of endoscopists with ROSE-AI system and without ROSE-AI system will be evaluated.

Trial Locations

Locations (1)

Qilu Hospital of Shandong University; 🇨🇳 Jinan, Shandong, China