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Starting soon Not applicable

Validation of Joint-AI in Diagnosing Pancreatic Solid Lesions

NCT06753318 · tracked via the Priya Life Science China tracker
Phase
Not applicable
Started
2025-01
Last updated
2024-12-31

Condition(s) studied

Pancreatic CancerPancreatitisPancreatic Neuroendocine Neoplasms (pNETs)Autoimmune PancreatitisSolid Pseudopapillary Neoplasm of the Pancreas

Investigational drug(s) / intervention(s)

The assistance of the Joint-AI modelThe assistance of the interpretable Joint-AI model

The assistance of the Joint-AI model: Predictions given by the Joint-AI model will be provided to the endoscopists during their diagnosis

The assistance of the interpretable Joint-AI model: Predictions given by the Joint-AI model and the results of the interpretability analysis will be provided to the endoscopists during their diagnosis

Study summary

This clinical trial aims to learn if a multimodal artificial intelligence (AI) model can enhance the diagnosis of pancreatic solid lesions. The main questions it aims to answer are:

1. Does the AI model enhance the diagnostic performance of endoscopists in diagnosing pancreatic solid lesions?
2. Does the addition of interpretability analysis further improve the diagnostic performance of the assisted endoscopists? Researchers will compare the diagnostic performance of endoscopists with or without the assistance of the AI model.

Participants will:

1. Their clinical data will be prospectively collected.
2. They will be randomized to the AI-assist group and the conventional diagnosis group.

Eligibility

Sex
ALL
Min age
18 Years
Max age
—
Healthy volunteers
No
Inclusion Criteria: * Imaging examinations (MRI, CT, B-ultrasound) show a solid mass in the pancreas, which requires endoscopic ultrasound guided-fine needle aspiration/biopsy (EUS-FNA/B) to clarify the nature of the lesion in patients. * Written consent provided Exclusion Criteria: * Age under 18 years old

Primary outcome measure(s)

  • Rate of correct diagnostic classification with assistance of the Joint-AI Model — Through study completion, an average of 1 year
    The rate of correct diagnoses in discriminating pancreatic cancer from other non-cancer lesions, determined by comparing endoscopist diagnosis assisted by the Joint-AI model against the final histopathological diagnosis (reference standard).
  • Rate of correct diagnostic classification with assistance of the Interpretable Joint-AI Model — Through study completion, an average of 1 year
    The rate of correct diagnoses in discriminating pancreatic cancer from other non-cancer lesions, determined by comparing endoscopist assessments assisted by the Interpretable Joint-AI model against the final histopathological diagnosis (reference standard)

Trial sites (1)

FacilityCityRegionStatus
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan Hubei
Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT06753318 on ClinicalTrials.gov ↗ ← All trials in China