AI-Powered Precision Decision-Making for Pancreatic Diseases

Summary

This multicenter clinical trial evaluates an artificial intelligence (AI) system designed to assist in the diagnosis and management of pancreatic diseases. Using contrast-enhanced CT scans, the study compares the AI's recommendations against the decisions of experienced clinicians to verify the system's accuracy and safety in a real-world setting. Patients are categorized into three management groups: Intervention (surgery/treatment), Intensive Surveillance (close monitoring), or Routine Surveillance (standard follow-up). The primary goal is to determine if the AI system can reliably classify patients, reduce the risk of missing malignant lesions, and prevent unnecessary surgeries, thereby improving clinical decision-making for pancreatic conditions.

Conditions

• Pancreatic Cancer
• Diagnose Disease
• IPMN, Pancreatic
• Pancreatic Cystic Lesions
• Chronic Pancreatitis
• Pancreatic Neuroendocrine Tumor
• Acute Pancreatitis (AP)

Interventions

DIAGNOSTIC_TEST

Diagnosis by Artificial Intelligence model

To develop an artificial intelligence-based classification management system for pancreatic diseases, achieving automated and precise classification. Contrast-enhanced CT images from all study subjects will be analyzed by the AI system to generate classification results, categorizing patients into three groups: INTERVENTIOM, INTENSIVE SURVEILLANCE or ROUTINE SURVEILLANCE.

Sponsors & Collaborators

• The First Affiliated Hospital with Nanjing Medical University

  collaborator OTHER

• The Affiliated People's Hospital of Ningbo University

  collaborator OTHER_GOV

• The Second Affiliated Hospital of Jiaxing University

  collaborator OTHER

• Shanghai Changzheng Hospital

  collaborator OTHER

• Xinhua Hospital, Shanghai Jiao Tong University School of Medicine

  collaborator OTHER

• Shengjing Hospital

  collaborator OTHER

• Shanghai Fourth People's Hospital Tongji University

  collaborator OTHER

• The First Affiliated Hospital of Medical School of Zhejiang University

  collaborator UNKNOWN

• Shanghai Fudan University Cancer Center

  collaborator UNKNOWN

• Changhai Hospital

  lead OTHER

Eligibility

Min Age

18 Years

Max Age

80 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2026-03-01

Primary Completion

2029-10-31

Completion

2029-10-31

Countries

• China

Study Locations