AI-guided diagnosis and management of pancreatic cysts using endoscopic ultrasound

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

Researchers will retrospectively collect endoscopic ultrasound images, radiology (CT or MRI), laboratory results, and clinical records from patients with pancreatic cystic lesions seen at Tongji Hospital. They will train a multimodal artificial intelligence model called Cyst-AI to integrate imaging and clinical data to distinguish mucinous from non-mucinous cysts and to provide risk stratification. The model's outputs will be compared to pathological, clinical, and follow-up data to measure diagnostic and management concordance. The goal is to create a tool to assist endoscopists in decision-making about surveillance, further testing, or intervention.

Why it matters

Who can join: the full rules

Inclusion criteria:

* Patients whose EUS results indicates pancreatic cystic or cystoid lesions;
* Mucinous lesions: including mucinous cystic neoplasm (MCN), intraductal papillary mucinous neoplasm (IPMN);
* Non-mucinous lesions: including pancreatic pseudocyst, serous cystic neoplasm (SCN), cystic neuroendocrine tumor (cNET).

Exclusion criteria:

* Patients whose age is less than 18 years old;
* Patients who have undergone pancreatic surgery before the EUS examination;
* Patients who have received chemotherapy and radiotherapy for pancreatic tumors before the EUS examination;
* Pathological results indicate that pancreatic lesions are metastatic lesions from other sites;
* Patients whose EUS images or reports are missing;
* EUS image quality does not meet the requirements for review, such as blurry imaging or containing artifacts, biopsy needles, measuring scales, or other additional annotations that are not part of the original EUS image;
* Patients whose final diagnosis is unclear.

Where it's running

• Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
  Wuhan, Hubei, China Recruiting
• Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
  Wuhan, Hubei, China Not yet recruiting

Study contacts

• Study coordinator: Bin Cheng
• Email: b.cheng@tjh.tjmu.edu.cn
• Phone: 86-13986097542

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.