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

Recruiting now

Conditions studied: Point-of-care Ultrasound

In brief

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)

Key facts

Study ID
NCT07580456
Run by
University Health Network, Toronto
People needed
30
Starts
2026-05-05
Expected to finish
2027-12-31
Last updated by the study team
2026-07-31

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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