NCT06718725

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

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.

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 236 (estimated)
• Sponsor: Qilu Hospital of Shandong University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

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 performance of ROSE-AI system was validated in the datasets collected prospectively.This study aims to assist endoscopists in conducting rapid on-site cytopathology evaluations during EUS-FNA without the presence of cytopathologists. In addition, the diagnostic field was compared between the cytopathologists and ROSE-AI system, endoscopists with or without ROSE-AI system.

Conditions

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

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	ROSE-AI system	The cytopathological slide images of the patients' ROSE samples will be identified by the ROSE-AI system.

Timeline

• Start date: 2024-09-01
• Primary completion: 2026-04-01
• Completion: 2026-04-01
• First posted: 2024-12-05
• Last updated: 2024-12-05

Locations

1 site across 1 country: China