Management of Pancreatic Cystic Lesions Using Artificial Intelligence Based on EUS and Multimodal… (NCT07463872) | Clinical Trial Compass
RecruitingNot Applicable
Management of Pancreatic Cystic Lesions Using Artificial Intelligence Based on EUS and Multimodal Data
China500 participantsStarted 2025-01-01
Plain-language 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.
Who can participate
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
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.
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
The performance of the diagnostic model in differentiating mucinous from non-mucinous PCLs
Timeframe: Within 3 months upon completion of the diagnostic model training.
2
The risk stratification performance of the clinical management model for mucinous PCLs
Timeframe: Within 3 months upon completion of the risk stratification model training.
Trial details
NCT IDNCT07463872
SponsorHuazhong University of Science and Technology