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NCT07543263

An Artificial Intelligence System for Multimodal, Multi-class Diagnosis of Pancreatic Cystic Lesions Based on Endoscopic Ultrasonography

Sponsor: Qilu Hospital of Shandong University

View on ClinicalTrials.gov

Summary

The aim of this study is to develop and validate an artificial intelligence system named iEUS-PCL (intelligent endoscopic ultrasound system-pancreatic cystic lesions) for detecting and multimodal, multi-class diagnosing pancreatic cystic lesions (PCL) during endoscopic ultrasound (EUS) examination.

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

176

Start Date

2026-04-20

Completion Date

2028-06-30

Last Updated

2026-04-21

Healthy Volunteers

No

Interventions

DEVICE

iEUS-PCL(intelligent endoscopic ultrasound system- pancreatic cystic lesion)

The iEUS-PCL will automatically detect pancreatic cystic lesions and integrate the patients' EUS images, EUS features, clinical data and radiological imaging features to perform three classification tasks: 1. binary classification: benign/malignant lesions; 2. binary classification: mucinous/non-mucinous lesions; 3. four-category classification: intraductal papillary mucinous neoplasm/ mucinous cystic neoplasm/ serous cyst neoplasm/ pancreatic cyst.

Locations (1)

Qilu Hospital of Shandong University

Jinan, Shandong, China