AI Tool Predicts Heart Pumping Function Using Scans and Body Composition
Studies an AI model combining heart ultrasound and body measurements in adults with heart failure.
Plain-language title generated from the registry record
Registry title: AI-based Prediction of Cardiac Function Using Echocardiography and Body Composition Data (ECHO-FIT Study)
Key facts
- Where
- Yŏngin, South KoreaSee the site
Where in South Korea
- Yongin Severance HospitalYŏngin, South KoreaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Yonsei University
- Trial code
- NCT06811519
- Record updated
- 4 March 2025
- Original description
This prospective observational study (ECHO-FIT Study) aims to develop and validate a predictive model for cardiac function, particularly left ventricular ejection fraction (LVEF), by integrating echocardiographic measurements with body composition data obtained from the QCCUNIQ BC 720 device.Read full original descriptionShow less
AI-based Prediction of Cardiac Function Using Echocardiography and Body Composition Data (ECHO-FIT Study)
This prospective observational study (ECHO-FIT Study) aims to develop and validate a predictive model for cardiac function, particularly left ventricular ejection fraction (LVEF), by integrating echocardiographic measurements with body composition data obtained from the QCCUNIQ BC 720 device.
The study plans to enroll 2,000 adult participants, comprising 1,000 individuals with normal LVEF (≥50%) and 1,000 with heart failure (LVEF <50%), all of whom will undergo standard-of-care echocardiography and body composition analysis.
By analyzing the relationships between key echocardiographic parameters (such as LVEF and diastolic function) and body composition measures (including fat mass, skeletal muscle mass, and total body water), we will develop a non-invasive prediction model capable of identifying individuals at higher risk of cardiac dysfunction.
This innovative approach has the potential to enhance early detection and personalized management of heart failure, reduce dependence on resource-intensive diagnostic procedures, and ultimately improve patient outcomes.
Inclusion: Aged 20 years or older; Undergoing a standard echocardiographic examination; Providing consent to undergo body composition analysis; Signing the informed consent form to voluntarily participate in the study.
Exclusion: Having a physical or mental condition that makes it impossible to conduct an echocardiogram or perform body composition analysis; Deemed inappropriate for study participation by the researcher (e.g., unable to cooperate).