Early Detection and Risk Monitoring of Pancreatic Cancer Using Artificial Intelligence A Study Involving High-Risk Groups and Advanced Imaging Techniques

What this Trial Is About

Pancreatic cancer is a highly fatal disease with a low 5-year survival rate due to delayed diagnosis from vague symptoms. This research aims to identify risk factors and biomarkers for early pancreatic cancer detection to improve screening in high-risk individuals. The study focuses on groups including those with new-onset diabetes, familial pancreatic cancer, inherited syndromes, pancreatic cystic neoplasms, and chronic pancreatitis. It is a longitudinal observational study led by Dr. Jin Gang at Shanghai Changhai Hospital. Participants are grouped based on specific risk factors such as recent diabetes diagnosis, family history, or pancreatic conditions. They will undergo yearly questionnaires, laboratory tests, and high-resolution MRI or CT scans of the pancreas. Suspicious findings will be further examined using endoscopic ultrasound. Blood samples will be collected for DNA analysis. If cancer or precancerous lesions are found, surgical referral will be made. The study also collects clinical data and biological specimens for future related research. During the study, participants will have annual lab tests and imaging to monitor pancreatic health. Any suspicious lesions trigger additional specialized imaging. Researchers will track pancreatic cancer incidence and hazard ratios over five years, along with survival time and diagnostic yield. The study includes follow-up and data collection to understand early detection and outcomes. Participation duration and monitoring span up to five years, with data used to improve early diagnosis and treatment strategies for pancreatic cancer.

Artificial Intelligence-based Early Screening of Pancreatic Cancer and High Risk Tracing (ESPRIT-AI)