AI reviews heart ultrasounds to find fatty liver disease early
Tests AI screening of heart ultrasounds to find liver disease in adults.
Key facts
- Who runs it
- Kaiser Permanente
- Where
- Boston, Chicago, Los Angeles, Palo Alto, and Pleasanton, United StatesSee the 6 sites
- Trial code
- Registry title
- Screening Cardiometabolic Opportunities Using Transformative Echocardiography Artificial Intelligence (SCOUT Echo-AI)
- Status
- Not yet recruiting
- People taking part
- 2,000 people, planned
- Starts
- 1 Jan 2028
- Expected to end
- 1 Nov 2028
- Type of study
- Interventional
- Treatments tested
- AI-Enabled Identification (EchoNet-Liver)
- Record updated
- 13 August 2026
Who can take part
AI summary
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adults who had a routine heart ultrasound (echocardiogram) that an AI tool flagged as high risk for fatty liver disease (MASLD) or cirrhosis.
- Age
- 18 years or older
- Sex
- All sexes can join.
- Disease stage
- Flagged as high risk for MASLD and/or cirrhosis by the AI model after a routine heart ultrasound. No confirmed stage is required.
- Earlier treatment
- No prior treatment is required. A prior liver or kidney transplant means a person cannot join.
- Biomarker or test result
- A high-risk result from the AI model, above a set threshold, on a recent routine transthoracic echocardiogram.
Main reasons for not taking part
- Cannot consent or communicate
- In hospice, or life expectancy too short for extra tests
- Urgent illness needing immediate treatment first, such as acute decompensation
- Prior liver or kidney transplant
- Unwilling to have testing for liver disease
The registry criteria, word for word
Show all 8 criteriaShow less
Who can take part
- Adults ≥18 years
- Underwent routine TTE within site defined recent timeframe and flagged as high risk for MASLD and/or cirrhosis by the AI model using pre specified threshold
- Able to provide informed consent; reachable for follow up
Who cannot take part
- Prior liver or kidney transplant
- Patient unwilling to undergo prospective testing for liver disease
- Inability to consent or communicate
- Enrollment in hospice or life expectancy so limited that additional evaluation would not be appropriate per clinician judgment
- Clinical circumstances where immediate alternative diagnostic pathways supersede study procedures (e.g., acute decompensation requiring urgent management)
Where in United States
- Massachusetts General HospitalBoston, United StatesContact: Long NguyenNot yet recruiting
- Northwestern MedicineChicago, United StatesContact: Faraz Ahmad - Site PI, MDNot yet recruiting
- Cedars-Sinai Medical CenterLos Angeles, United StatesContact: Alan KwanNot yet recruiting
- UCLALos Angeles, United StatesContact: Alex Sandhu, MDNot yet recruiting
- Stanford HealthcarePalo Alto, United StatesContact: Paul Cheng - Site PINot yet recruiting
- Kaiser PermanentePleasanton, United StatesContact: Andrew Ambrosy - Site PI, MDNot yet recruiting
About the trial
What the trial wants to find out
The goal of this prospective, multicenter, open-label, blinded end-point pragmatic study is to evaluate an artificial intelligence (AI)-augmented echocardiography screening approach for early detection of metabolic dysfunction associated steatotic liver disease (MASLD) and/or cirrhosis, in patients undergoing routine transthoracic echocardiograms (TTEs).
Read full original descriptionShow less
The main question it aims to answer is to:
1. Evaluate notification responsiveness and rates of confirmatory testing for patients identified as high risk for having liver disease to determine whether optimized notifications increase timely confirmatory testing and treatment initiation versus standard of care assessment. 2. Compare time to diagnosis, treatment uptake, and clinical outcomes (hospitalizations, incident ASCVD, mortality) between cohorts identified as high risk by the AI algorithm and comparison groups to determine whether AI guided screening shortens time to diagnosis and increases appropriate treatment.
The group in the trial
- AI Notification (EchoNet-Liver-Flagged patients)Treatment being tested
Participants whose prior transthoracic echocardiograms are flagged by an AI model (EchoNet-Liver) as high risk for MASLD and/or cirrhosis, a notification is delivered to the primary treating clinician, or undergoes a structured diagnostic workflow for standard of care at their site.
Treatment: AI-Enabled Identification (EchoNet-Liver)
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?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorData and sources
- Registry record
- Listed on ClinicalTrials.gov.
- Official title
- Screening Cardiometabolic Opportunities Using Transformative Echocardiography Artificial Intelligence (SCOUT Echo-AI)
- Plain-language title
- AI reviews heart ultrasounds to find fatty liver disease earlyGenerated from the registry record. The registry title is the official one.
- AI summary
- From the trial's eligibility criteria. Read by machine on 12 November 2026.
- Record updated
- 13 August 2026