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

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)

NCT Number	NCT07580456
Lead Sponsor	University Health Network, Toronto
Conditions	Point-of-care Ultrasound
Enrollment	30 participants
Start Date	2026-05-05
Primary Completion	2027-12-31 (estimated)
Study Completion	2027-12-31 (estimated)
Updated on ClinicalTrials.gov	2026-07-31