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SCOUT Echo-AI: Using AI to Detect Liver Disease

This study, called SCOUT Echo-AI, is looking at a new way to find liver diseases like MASLD (Metabolic Dysfunction-Associated Steatotic Liver Disease) and cirrhosis earlier. It uses artificial intelligence (AI) called EchoNet-Liver to review routine heart ultrasound scans (transthoracic echocardiograms or TTEs). If the AI spots signs of possible liver disease, it will alert doctors. The study wants to see how well this AI tool works to identify these conditions and if these alerts help patients get tested and treated sooner. We are looking to enroll about 2000 adults, aged 18 and older, who have had a recent TTE and were flagged by the AI as being at high risk for MASLD or cirrhosis. The main goal is to see how accurate the AI is at finding these liver conditions within 12 months of the AI notification.

Study design
This is a prospective, multicenter, open-label study with 2000 planned participants. It is designed to evaluate an AI-augmented screening approach.
What's involved
You would need to provide informed consent and be reachable for follow-up. The study will track if you receive confirmatory testing within 12 months of the AI identification.
Compensation
Not stated in the trial record.
Follow-up
Participants will be followed for up to 1 year after enrollment to assess the accuracy of the AI detection.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07216859

Screening Cardiometabolic Opportunities Using Transformative Echocardiography Artificial Intelligence (SCOUT Echo-AI)

Not Yet Recruiting
NAAges 18+InterventionalDiagnostic
Kaiser Permanente
~2,000 participants
Updated 2026-08-13 on ClinicalTrials.gov
What's tested:AI-Enabled Identification (EchoNet-Liver)

At a glance

Recruiting sites
0 of 6 listed sites are recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Positive Predictive Value (PPV) of the AI algorithm for detecting MASLD and/or cirrhosis confirmed within 12 months of AI identification.
Measured over From enrollment to end of follow up at 1 year.

Conditions

MASLD - Metabolic Dysfunction-Associated Steatotic Liver Disease
Cirrhosis

Explore related trials

CirrhosisNonalcoholic Fatty Liver Disease

NCT07216859

Where you'd take part

This study runs at 6 sites. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.

  • Cedars-Sinai Medical Center

    Los Angeles, Californiastudy coordinator listed

  • Kaiser Permanente

    Pleasanton, Californiastudy coordinator listed

  • Massachusetts General Hospital

    Boston, Massachusettsstudy coordinator listed

  • Northwestern Medicine

    Chicago, Illinoisstudy coordinator listed

  • Stanford Healthcare

    Palo Alto, Californiastudy coordinator listed

  • UCLA

    Los Angeles, Californiastudy coordinator listed

Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.

Who to contact

Alan Kwan
[email protected]
3104233475
Email the study team

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Eligibility criteria

Inclusion

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.

Exclusion

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).
Prior liver or kidney transplant.
Patient unwilling to undergo prospective testing for liver disease.

What this trial measures

  • Positive Predictive Value (PPV) of the AI algorithm for detecting MASLD and/or cirrhosis confirmed within 12 months of AI identification.From enrollment to end of follow up at 1 year.

    Numerator: Participants with clinician-confirmed diagnosis of later stage MASLD and/or cirrhosis after confirmatory evaluation. Denominator: * Participants with positive AI screen who were enrolled and evaluated. * The intervention is the clinician referral or referral testing workflow. The clinicians ultimately have discretion to avoid further downstream testing if pretest probability is felt to be too low. If a clinician determines no further testing is warranted despite high risk assessment by AI, the participant will be classified as a false positive (still counted in the denominator).