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Recruiting NCT06824909

Endoscopic Ultrasound-guided Fine-needle Aspiration of Solid Pancreatic Lesions With Rapid Staining of Cytological Smears Followed by Whole Slide Scanning and Artificial Intelligence Diagnosis: A Prospective, Multicenter Study.

Observational Pancreatic Disease

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 diagnostic system.
Who it may be relevant to
Registry conditions: Pancreatic Disease. 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 →
Official title

内镜超声穿刺胰腺实性占位细胞涂片快速染色后全玻片扫描及人工智能诊断:一项前瞻性、多中心研究

Overview

The objective of this observational study is to investigate whether the self-developed whole slide scanning and artificial intelligence diagnostic system for pancreatic solid lesion puncture cytopathology (hereinafter referred to as the "Zhiying Shunxi" ROSE-AI diagnostic system) can promptly and accurately diagnose solid pancreatic lesions (SPLs). The main question it aims to answer is: By utilizing optical imaging technology to capture RGB images of Diff-Quik stained smears from pancreatic punctures, can the development of artificial intelligence algorithms assist in differentiating solid pancreatic space-occupying diseases (such as pancreatic ductal adenocarcinoma, pancreatic neuroendocrine tumors, and non-neoplastic benign lesions)? Researchers will compare the diagnoses of SPLs made by the ROSE-AI system with the actual pathological diagnoses of the SPLs themselves to determine whether the ROSE-AI system can effectively diagnose SPLs.

Interventions

  • Device ROSE-AI diagnostic system
    All samples were obtained due to the necessity for disease treatment and in accordance with routine clinical workflows. After the pathological diagnoses were confirmed by the pathology departments of the hospitals affiliated with the respective endoscopic centers, the eligible pancreatic puncture Diff-Quik stained smears were borrowed and transferred to Ruijin Hospital Affiliated to School of Medicine, Shanghai Jiao Tong University. There, the self-developed "Zhiying Shunxi" system was used to c

Primary outcome measures

  • Accuracy [Time frame: through study completion, an average of 2 years]

Eligibility criteria

Inclusion criteria

  • A dated and signed informed consent form A commitment to abide by the research procedures and cooperate throughout the entire study Subjects aged 18 and above, regardless of gender Diagnosis or suspicion of a solid pancreatic space-occupying lesion based on imaging studies (B-mode ultrasound, CT, or MRI)

Exclusion criteria

  • Unable or refusing to sign the informed consent form Unable to suspend anticoagulation/antiplatelet therapy Pregnant or lactating Having a mental illness or other medical conditions that are unsuitable for undergoing FNA/B biopsy Presence of coagulation disorders (PLT < 50 × 10\^3/μl, INR > 1.5) Pancreatic cystic lesions Non-diagnostic EUS-FNA/B specimens Having less than 8 microscopic fields of interest (ROI) in the digital pathology images of the entire Diff-Quik smear slide

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

Study design

Observational model
Cohort

Study locations

China · 2 centers
  • Ruijin Hospital, Shanghai Jiaotong University School of Medicine — Shanghai
  • Department of Gastroenterolog, Ruijin Hospital Affiliated to Shanghai Jiao Tong University — Shanghai

Identifiers

NCT: NCT06824909 · RuijinH2024574

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗