NCT07463872

Management of Pancreatic Cystic Lesions Using Artificial Intelligence Based on EUS and Multimodal Data

A Multimodal Artificial Intelligence Model for Subtyping Diagnosis and Clinical Management of Pancreatic Cystic Lesions Based on Endoscopic Ultrasound and Clinical Information

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 500 (estimated)
• Sponsor: Huazhong University of Science and Technology · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The primary objective is to construct a multimodal AI model (Cyst-AI) based on EUS images and clinical data such as imaging features(CT or MRI) and laboratory tests to assist endoscopists in the diagnosis of pancreatic cystic lesions(PCLs), mainly differentiating mucinous from non-mucinous lesions. The secondary objective is to evaluate the model's effectiveness in risk stratification and clinical management for patients with PCLs.

Detailed description

With the development of medical imaging technology, the detection rate of pancreatic cystic lesions (PCLs) has been increasing notably. Although most cysts are benign, a considerable subset has the potential for malignant transformation. Clinical management is based on diagnosis and risk stratification. For PCLs，different diagnosis and risk stratification lead to entirely different clinical strategies and outcomes, which are closely related to the quality of life, economic burden, and psychological stress of patients. Endoscopic ultrasound (EUS) has played a crucial role in the further differential diagnosis of PCLs. Artificial intelligence (AI) has also shown great potential in clinical diagnosis and management. Thus, we plan to retrospectively collect patients' EUS imaging data, radiological and laboratory tests, and other clinical information to construct a model named Cyst-AI which integrates the function of diagnosis and clinical management, to assist in clinical decision-making.

Conditions

• Pancreatic Cystic Lesion
• Mucinous Cystadenoma of Pancreas
• Intraductal Papillary Mucinous Neoplasm of Pancreas
• Pseudocyst Pancreas
• Serous Cystadenoma
• Neuroendocrine Tumors, NET

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Cyst-AI model	The multi-center collected data will be divided into a training set, a validation set, and a test set for developing and testing the cyst-AI model.

Timeline

• Start date: 2025-01-01
• Primary completion: 2026-04-01
• Completion: 2026-06-01
• First posted: 2026-03-11
• Last updated: 2026-03-11

Locations

2 sites across 1 country: China