The aim of this study is to develop and validate an artificial intelligence system named iEUS-PCL (intelligent endoscopic ultrasound system-pancreatic cystic lesions） for detecting and multimodal, multi-class diagnosing pancreatic cystic lesions (PCL) during endoscopic ultrasound (EUS) examination.
Patients aged ≥18 years scheduled for EUS with suspected pancreatic cystic lesions based on clinical symptoms, medical history, laboratory tests or radiological examinations, and who agree to participate in the research and voluntarily sign the informed consent.
Patients with no prior history of treatment for pancreatic lesions.
Patients with absolute contraindications to EUS examination.
Pregnancy or lactating.
Uncorrectable coagulopathy (PTT>50 seconds or INR>1.5) and/or uncorrectable thrombocytopenia(platelet count<50×109/L).
Upper gastrointestinal obstruction.
Adult patients with suspected pancreatic cystic lesions undergoing EUS.
Cohort
Prospective
iEUS-PCL(intelligent endoscopic ultrasound system- pancreatic cystic lesion)
DeviceThe iEUS-PCL will automatically detect pancreatic cystic lesions and integrate the patients' EUS images, EUS features, clinical data and radiological imaging features to perform three classification tasks: 1. binary classification: benign/malignant lesions; 2. binary classification: mucinous/non-mucinous lesions; 3. four-category classification: intraductal papillary mucinous neoplasm/ mucinous cystic neoplasm/ serous cyst neoplasm/ pancreatic cyst.
The accuracy of iEUS-PCL for pancreatic cystic lesions
The primary outcome of the study is to evaluate the accuracy of the iEUS-PCL in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
The sensitivity of iEUS-PCL for pancreatic cystic lesions
The primary outcome of the study is to evaluate the sensitivity of the iEUS-PCL in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
The specificicy of iEUS-PCL for pancreatic cystic lesions
The primary outcome of the study is to evaluate the specificity of the iEUS-PCL in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
The postive predictive value of iEUS-PCL for pancreatic cystic lesions
The primary outcome of the study is to evaluate the postive predictive value of the iEUS-PCL in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
Comparison of the accuracy between iEUS-PCL and endosonographers
The secondary outcome of the study is to comparing the accuracy between iEUS-PCL and different-level endosonographers in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
Comparison of the sensitivity between iEUS-PCL and endosonographers
The secondary outcome of the study is to comparing the sensitivity between iEUS-PCL and different-level endosonographers in identifying in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
Comparison of the specificity between iEUS-PCL and endosonographers
The secondary outcome of the study is to comparing the specificity between iEUS-PCL and different-level endosonographers in identifying in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
Comparison of the postive predictive value between iEUS-PCL and endosonographers
The secondary outcome of the study is to comparing the postive predictive value between iEUS-PCL and different level endosonographers in identifying in identifying the pancreatic cystic lesions (benign/malignant; mucinous/non-mucinous; 4-category).
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Qilu Hospital of Shandong University
Lead sponsor
Liaocheng People's Hospital
Collaborator
Taian City Central Hospital
Collaborator
Qilu Hospital of Shandong University (Qingdao)
Collaborator
Binzhou People's Hospital
Collaborator
Shandong Provincial Hospital
Collaborator
The Affiliated Hospital of Qingdao University
Collaborator
Qianfoshan Hospital
Collaborator
Shengli Oilfield Hospital
Collaborator
Binzhou Medical University
Collaborator
