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NOT YET RECRUITING
NCT07580456

AI for Gastric POCUS ( Point-of-care Ultrasound)

Sponsor: University Health Network, Toronto

View on ClinicalTrials.gov

Summary

The goal of this observational study is to train and test an AI (Artificial Intelligence)-based program to assist anesthesiologists in the interpretation of stomach ultrasound images and differentiate a "full" from an "empty" stomach. It is a healthy-volunteer study, where the participants will undergo ultrasound examination of their stomach at three different time points to visualize the stomach contents. These are at fasting state, after taking some solid food and after taking some water. Here, the participants will be randomized to receive one of five different types solid foods and one of five different volumes of water. The stomach ultrasound images will then be used to train and test the accuracy of the model to diagnose the type of stomach content (nothing vs. clear fluid vs. solid food)

Official title: Development of an Artificial Intelligence Algorithm to Enhance the Gastric Point-of-care Ultrasound. A Proof-of-concept Study.

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

30

Start Date

2026-05-08

Completion Date

2027-12-31

Last Updated

2026-05-12

Healthy Volunteers

Yes

Locations (1)

Toronto Western Hospital, University Health Network

Toronto, Ontario, Canada