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

NCT07580456 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 30

Last updated 2026-05-12

No results posted yet for this study

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)

Conditions

  • Point-of-care Ultrasound

Sponsors & Collaborators

  • University Health Network, Toronto

    lead OTHER

Principal Investigators

  • Anahi Perlas · University Health Network, Toronto

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-05-08
Primary Completion
2027-12-31
Completion
2027-12-31

Countries

  • Canada

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07580456 on ClinicalTrials.gov