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.

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.

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Key information

Conditions

Pancreatic Disease Digestive System Diseases Pancreatic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Department of Gastroenterolog, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, Shanghai Municipality, China

Who can participate

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

ROSE-AI diagnostic system

Device

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 capture corresponding traditional light microscope RGB images. After the imaging was completed, all specimens were returned to the endoscopic centers from which they originated. Using the RGB images as input, an artificial intelligence algorithm was developed to assist in differentiating solid pancreatic lesions.

Primary outcomes

Accuracy

Time frame: through study completion, an average of 2 years

Accuracy = (TP + TN) / (TP + FP + FN + TN)

Sponsors and collaborators

Lead sponsor

Ruijin Hospital

Other

Collaborators

Affiliated Hospital of Jiangnan University
Fudan University
Jiangyin People's Hospital
Second Affiliated Hospital of Soochow University
Shanghai 10th People's Hospital
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
The Third Xiangya Hospital of Central South University

Registry information

Official study 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

Important dates

Study start: 2024
Primary completion: 2027
Study completion: 2027
First posted: Feb 13, 2025
Registry last updated: Feb 13, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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