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Recruiting NCT06718725

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

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

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: ROSE-AI system.
Who it may be relevant to
Registry conditions: The Malignant Lesions and Non-malignant Lesions of Pancreas, Bile Duct, Liver and Lymph Node. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

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.

Overview

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.

Interventions

  • Diagnostic test ROSE-AI system
    The cytopathological slide images of the patients' ROSE samples will be identified by the ROSE-AI system.

Primary outcome measures

  • the accuracy, sensitivity and specificity of the ROSE-AI system in identifying malignant/non-malignant ROSE samples [Time frame: During procedure]
Secondary outcome measures (1)
  • comparing the diagnostic performance between endoscopists with ROSE-AI system and without ROSE-AI system [Time frame: During procedure]

Eligibility criteria

Inclusion criteria

  • the patient age ≥18 years accepted EUS-FNA+ROSE.
  • agree to participate in the research and be able to sign written informed consent.

Exclusion criteria

  • uncorrectable coagulopathy (PTT >50 seconds or INR >1.5) and/or uncorrectable thrombocytopenia (platelet count <50 × 109 /L).
  • patients who were too clinically ill to undergo an EUS examination.
  • lesions that were deemed inaccessible for EUS-guided sampling.
  • unsuccessful EUS-FNA (e.g., failure to obtain an adequate specimen, patient intolerance, intraoperative accidents, etc.).
  • Patients with unqualified ROSE smear.
  • Patients who underwent biopsy during EUS-FNA but did not receive a definitive pathological diagnosis or pathological report.
  • pregnancy.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model
Case-only

Study locations

China · 1 center
  • Qilu Hospital of Shandong University — Jinan

Identifiers

NCT: NCT06718725 · 2024SDU-QILU-1

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗