An Artificial Intelligence System for Multimodal, Multi-class Diagnosing Solid Pancreatic Lesions Based on Endoscopic Ultrasound

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorQilu Hospital of Shandong University

About this trial

The aim of this study is to validate an artificial intelligence system named iEUS-SPL(intelligent endoscopic ultrasound system-solid pancreatic lesion) for detecting and multimodal, multi-class diagnosing solid pancreatic lesions during endoscopic ultrasound(EUS) examination.

Eligibility criteria

Qualifiers

Patients aged ≥18 years scheduled for EUS with suspected solid pancreatic lesions based on clinical symptoms, medical history, laboratory tests or radiological examinations agree to participate in the research and be able to sign informed consent.

Patients with no prior history of treatment for pancreatic lesions.

Disqualifiers

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.

Trial design

Treatments tested in this trial

  • iEUS-SPL(intelligent endoscopic ultrasound system-pancreatic solid lesion)

Treatment groups

383 Participants
are divided into 1 treatment group

Sponsors and collaborators

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