Recruiting

Observational Study

Sponsor:

University Health Network, Toronto

Code:

NCT07580456

Conditions

Point-of-care Ultrasound

Eligibility Criteria

Sex: All

Age: 18+

Healthy Volunteers: Accepted

Study Details

Brief 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

Study ID

NCT07580456

Start date

May 5, 2026

Status verified date

Apr, 2026

Completion date

Dec 31, 2027

Anticipated

Primary completion date

Dec 31, 2027

Anticipated

Eligibility Criteria

Eligibility Criteria

Sex: All

Age: 18+

Healthy Volunteers: Accepted

Inclusion Criteria:

A. Inclusion Criteria at the level of the participants

  • Participants must meet all the following inclusion criteria to be eligible for the study:

  • Aged ≥18 years
  • Any sex
  • Be healthy

B. Inclusion Criteria at the level of the input data • Transverse ultrasound images (10 sec clips) of the gastric antrum in the epigastric area that contain all these structures:

  • The edge of the left lobe of the liver
  • The gastric antrum
  • The pancreas
  • The aorta

Exclusion Criteria:

A. Exclusion Criteria at the level of the participants

  • Participants meeting any of the following exclusion criteria are ineligible for the study:

  • Previous gastro-esophageal surgery (e.g., gastric by-pass, sleeve gastrectomy, fundoplication, partial gastrectomy)
  • Allergy to any of the food that will be provided.

B. Exclusion Criteria at the level of the input data

• Ultrasound images (10 sec clips) where the gastric antrum cannot be positively identified.

Study Design

Enrollment

30 participants

Anticipated

Interventions and Outcome Measures

Primary outcome measure

  • To see the overall accuracy of the AI model [ Time Frame: Through study completion, an average of 2 years ]

Central Contacts and Locations

Central contacts

Jayanta Chowdhury, MBBS,MD

416-603-5800jayanta.chowdhury@uhn.ca

Locations

Toronto Western Hospital, University Health Network

Recruiting

Toronto, Ontario, Canada, M5T 2S8

Contacts

Jayanta Chowdhury

4166035800jayanta.chowdhury@uhn.ca

Principal Investigator:

Anahi Perlas, MD, FRCPC

More Information

Sponsor

University Health Network, Toronto

Last update posted

Jul 31, 2026

Last verified

Apr, 2026

Keywords

  • Artificial Intelligence
  • POCUS (Point-of-care ultrasound)
  • Ultrasound

Trial information was received from ClinicalTrials.gov and was last updated on 2026-09-10. This information was provided to ClinicalTrials.gov by University Health Network, Toronto on 2026-07-31.