Validation of Joint-AI in Diagnosing Pancreatic Solid Lesions

Validation of a Multimodal Artificial Intelligence Model in in Diagnosing Pancreatic Solid Lesions: a Prospective, Multicenter, Randomized, Controlled Trial

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.

The investigators have previously developed a multimodal AI model (Joint-AI) based on endoscopic ultrasound images and clinical data to diagnose pancreatic solid lesions. This study aims to improve the Joint-AI model's performance with a prospectively collected dataset and validate it through a randomized controlled clinical trial.

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