artificial intelligence-based early screening of pancreatic cancer and high risk tracing (esprit-ai)

Conditions: Pancreatic Cancer; Diabetes; Familial Pancreatic Cancer; Pancreatic Cystic Neoplasm; Chronic Pancreatitis; Hereditary Pancreatitis

Summary: pancreatic cancer is one of the most fatal malignancies with a 5-year survival rate of only \~6%\[1\]. the reasons for this high mortality rate can be attributed to several factors, of which perhaps the most important is delayed diagnosis due to vague symptoms and consequently missed opportunities for surgical resection. therefore, the ability to detect pancreatic cancer at an early, more curable stage is urgently needed. identifying risk factors and biomarkers of early pancreatic cancer could facilitate screening for individuals at higher than average risk and expedite the diagnosis in individuals with symptoms and substantially improve an individual's chance of surviving the disease. thus, the investigators propose this longitudinal study entitled, "artificial intelligence-based early screening of pancreatic cancer and high risk tracing (esprit-ai)" in order to generate clinical data sets and bank serial blood specimens of high risk individuals.

the study is being run by a team of dedicated physicians and researchers, led by jin gang, md, director of department of general surgery of shanghai changhai hospital. the trial will include individuals with new-onset diabetes (diagnosed within the past 3 year), familial pancreatic cancer, inherited syndromes associated with pancreatic cancer (including hereditary pancreatitis, familial atypical multiple mole and melanoma syndrome, hereditary nonpolyposis colon cancer, peutz-jeghers syndrome, hereditary breast and ovarian cancer syndromes, etc), pancreatic cystic neoplasm (including ipmn, mcn) as well as chronic pancreatitis. participants will undergo annual laboratory tests and high-resolution mri/ct examinations of the pancreas. any suspicious lesions will be further examined by endoscopic ultrasound (eus). if pancreatic cancer or a pre-cancerous lesion is identified, the individual will be referred for surgery. we will also be collecting a blood sample from all participants for dna isolation. clinical data and biological specimens contained in this study may be used for a wide variety of future related studies to the cause, diagnosis, outcome and treatment of pancreatic cancer.

Eligibility criteria:
inclusion criteria: * subject is able and willing to provide informed consent and sign an informed consent form. * subject or authorized representative must be willing to complete a detailed questionnaire. * subject must meet one of the following criteria: 1. new onset diabetes (diagnosed within the past 3 years) 2. familial pancreatic cancer 3. inherited syndromes associated with pancreatic cancer (including hereditary pancreatitis, familial atypical multiple mole and melanoma syndrome, hereditary nonpolyposis colon cancer, peutz-jeghers syndrome, hereditary breast and ovarian cancer syndromes, etc) 4. pancreatic cystic neoplasm (including ipmn, mcn) 5. chronic pancreatitis exclusion criteria: * subject has been diagnosed with pancreatic cancer or other malignant tumors in the last 5 years; * subject has any medical condition that contraindicates high-resolution mri or ct; * subject cannot be followed up or is participating in other clinical trials.

Keywords: screening early diagnosis artificial intelligence pancreatic cancer