MedPath

Artificial Inteligence in Endoscopic Ultrasound

Recruiting
Conditions
Pancreas Disease
Pancreatic Cancer
Pancreatic Cyst
Interventions
Device: Patients undergoing endoscopic ultrasound procedures
Registration Number
NCT06564571
Lead Sponsor
Orlando Health, Inc.
Brief Summary

The objective of the study is to determine if this artificial intelligence system is capable of detecting abnormalities in the pancreas that are identified by an endoscopist at endoscopic ultrasound procedures.

Detailed Description

Endoscopic Ultrasound (EUS) is an equipment where an ultrasound transducer is attached to the tip of the endoscope. When advanced to the stomach the organs outside such as the pancreas and liver can be visualized in great detail. This enables diagnosis of conditions such as pancreatic cancer. However, an endoscopist must undergo training to accurately interpret these ultrasound images.

The investigators are in the process of developing an artificial intelligence system that could potentially interpret EUS images. The objective of the study is to determine if this artificial intelligence system is capable of detecting abnormalities in the pancreas that are identified by an endoscopist at endoscopic ultrasound procedures. Such correlation if established will lead to possible development of an artificial intelligence platform that can diagnose pancreatic diseases. Such development will potentially minimize human error and decrease learning curve to gain proficiency in EUS.

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
1500
Inclusion Criteria
  • Age ≥ 18 years
  • Any patient undergoing endoscopic ultrasound examination
Exclusion Criteria
  • Age < 18 years

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
Patients undergoing endoscopic ultrasound proceduresPatients undergoing endoscopic ultrasound proceduresPatients will undergo endoscopic ultrasound procedures as planned. Abnormalities in the pancreas identified by the endoscopist during the endoscopic ultrasound examination will be correlated against those detected by the AI platform.
Primary Outcome Measures
NameTimeMethod
Rate of detection pancreatic abnormalities by AI1 day

Ability of AI to detect pancreatic abnormalities as identified by an endoscopist during EUS examination of the pancreas.

Secondary Outcome Measures
NameTimeMethod
Rate of detection pancreatic solid mass lesions by AI1 day

Ability of AI to detect pancreatic solid mass lesions as identified by an endoscopist during EUS examination of the pancreas.

Rate of detection pancreatic cystic lesions by AI1 day

Ability of AI to detect pancreatic cystic lesions as identified by an endoscopist during EUS examination of the pancreas.

Trial Locations

Locations (1)

Orlando Health

🇺🇸

Orlando, Florida, United States

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