ClinicalTrials.gov record NCT06664866

AI Echocardiographic Screening of Cardiac Amyloidosis

Record copied from ClinicalTrials.gov: Oct 10, 2026AI summaries generated: Sep 17, 2026

Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases (EchoNet-Screening)

StatusEnrolling by invitationThe study enrols only people the study team invites, for example patients already at a particular clinic. It is not open to the public.
Study typeInterventionalA study in which researchers assign participants to one or more interventions, such as a drug, procedure, device, behavioural programme or other approach, to measure their effects.
Age22 years old and older
SexAll
LocationUnited States
AI summaryWhat this study is about, in plain languageShow ▾Hide ▴

AI-written from the registry record, not the study's own wording. May contain errors or omissions. Check the registry text on this page and the original record ↗ before acting on it.

This diagnostic study uses an AI algorithm (EchoNet-LVH) to review routine echocardiograms and flag studies suspicious for cardiac amyloidosis. Flagged cases are reviewed by site cardiac-amyloidosis experts; eligible patients who consent are followed and referred for clinical evaluation. The main measure is the proportion of flagged, consented patients who are confirmed to have cardiac amyloidosis.

What it is studying. Whether the EchoNet-LVH algorithm can identify patients with cardiac amyloidosis from routine echocardiograms (measured as positive predictive value). The study will also look at timing to diagnosis and counts of diagnoses, treatments, hospitalizations, and deaths among flagged patients.

What the researchers hope to learn. Measure the positive predictive value of EchoNet-LVH for detecting cardiac amyloidosis and compare it with standard clinical suspicion. Assess time from echocardiogram to clinical diagnosis. Count subsequent cardiac-amyloidosis diagnoses, treatments, hospitalizations, and deaths within the study period.

What this study is about

The study's own summary, as published on ClinicalTrials.gov. Underlined terms have a short explanation.

Recent advances in machine learning and image processing techniques have shown that machine learning models can identify features unrecognized by human experts and accurately assess common measurements made in clinical practice. Echocardiography is the most common form of cardiac imaging and is routinely and frequently used for diagnosis. However, there is often subjectivity and heterogeneity in interpretation. Artificial intelligence (AI)'s ability for precision measurement and detection is important in both disease screening as well as diagnosis of cardiovascular disease. Cardiac amyloidosis (CA) is a rare, underdiagnosed disease with targeted therapies that reduce morbidity and increase life expectancy. However, CA is frequently overlooked and confused with heart failure with preserved ejection fraction. Some estimates suggest that CA can be as prevalence as 1% in a general population, with even higher prevalence in patients with left ventricular hypertrophy, heart failure, and other cardiac symptoms that might prompt echocardiography. AI guided disease screening workflows have been proposed for rare diseases such as cardiac amyloidosis and other diseases with relatively low prevalence but significant human impact with targeted therapies when detected early. This is an area particularly suitable for AI as there are multiple mimics where diseases like hypertrophic cardiomyopathy, cardiac amyloidosis, aortic stenosis, and other phenotypes might visually be similar but can be distinguished by AI algorithms. The investigators have developed an algorithm, termed EchoNet-LVH, to identify cardiac hypertrophy and identify patients who would benefit from additional screening for cardiac amyloidosis.

Interventions being studied

Being studied in this trial does not mean the treatment or procedure is approved or available for this condition.

Diagnostic test
  • EchoNet-LVH Assessment

Eligibility

The criteria exactly as listed on ClinicalTrials.gov. Only the study team can say whether they apply to you.

Inclusion criteria

  • Patients receiving an echocardiogram that is determined to be suspicious by EchoNet-LVH

Exclusion criteria

  • Patients that decline consent
  • Patients receiving an echocardiogram that is determined to be not suspicious by EchoNet-LVH

Study description and what participation involves

The registry record has no detailed description beyond the summary above.

AI summaryWhat participation may involve, in plain languageShow ▾Hide ▴

AI-written from the registry record, not the study's own wording. May contain errors or omissions. Check the registry text on this page and the original record ↗ before acting on it.

Your existing echocardiogram will be automatically reviewed by the EchoNet-LVH algorithm. If the study algorithm flags your scan, site CA experts will review your chart and, if appropriate, contact you to obtain consent. Consented participants are followed in the study, referred to a CA expert, and have clinical information collected about diagnosis, time to diagnosis, treatments, hospitalizations, and deaths (outcomes tracked for about 1 year). The registry does not specify additional invasive study procedures beyond clinical follow-up and referral.

How the study is structured. Automated AI review of large numbers of echocardiograms will flag studies deemed suspicious. Flagged records are chart-reviewed by each site's cardiac-amyloidosis experts; those judged appropriate are contacted for consent, followed in a single group, and referred for clinical workup. The AI algorithm and its pre-set threshold are fixed for the study. There is no masking.

Questions you could ask

These questions are suggestions for a conversation with the study team or your own clinician, not advice.

  • The registry says participants are enrolled by invitation. Who decides who is invited, and how?
  • The listed sites are in United States. Is any of them reachable for me, and does the study help with travel?
  • Which of the eligibility criteria would need to be checked with tests before I could join?

More on wild-type ATTR amyloidosis

This trial is also listed on this site under ATTRv amyloidosis.

Clinical trials121 trials listed for wild-type ATTR amyloidosisEvery trial the registry lists for wild-type ATTR amyloidosis, with recruitment status, phase and sites, updated from ClinicalTrials.gov.See all trials →Research updatesWhat changed in wild-type ATTR amyloidosis researchLatest monthly update: September 2026. Includes: Frailty and support needs. New research summarized each month in plain language, with links to every source paper.Read the latest update →

Important dates

Study start
Oct 28, 2024
Primary completion
Nov 1, 2026 (estimated)
Study completion
Nov 1, 2027 (estimated)
Target enrollment
500 participants (estimated)
Last updated on registry
Jul 22, 2026
Data verified
Oct 10, 2026

Sponsor and research team

The lead sponsor funds and oversees the trial. A pharmaceutical or biotech company sponsor typically means the study is testing that company's drug or device; a hospital, university, or government agency usually indicates investigator-initiated or publicly funded research.

Lead sponsor
Cedars-Sinai Medical Center
Principal investigator
Lily Stern, Assistant Professor
Cedars-Sinai Medical Center
Collaborators
  • Palo Alto Veteran Affairs Hospital
  • Providence Heart & Vascular Institute
  • Northwestern Medicine

Participating sites (4)

  • Cedars Sinai Medical Center

    Los Angeles, California, 90034 · United States

  • Palo Alto Veteran Affairs Hospital

    Palo Alto, California, 94304 · United States

  • Northwestern Medicine

    Chicago, Illinois, 60190 · United States

  • Providence Heart and Vascular Institute

    Portland, Oregon, 97225 · United States

Terms used on this page · explanations by MedicalUpdates.ai

Echocardiography
An ultrasound scan of the heart. A transesophageal echocardiogram is done through a probe passed into the food pipe for a closer view.
life expectancy
Some studies require that, in the investigator's judgement, a participant is likely to live long enough to complete the study period. It is a study requirement, not a prediction about any individual.
Inclusion Criteria
The conditions a person must meet to be considered for the study, for example a confirmed diagnosis, an age range or a test result.
Exclusion Criteria
The conditions that rule a person out even if they meet the inclusion criteria, for example other illnesses, certain medicines or pregnancy.

The study record on this page is reproduced from ClinicalTrials.gov, a database of the U.S. National Library of Medicine, where it was submitted by the study sponsor. MedicalUpdates.ai does not own this content, is not affiliated with or endorsed by ClinicalTrials.gov, NIH, or the U.S. Government, and does not verify the record. Plain-language notes, the glossary and the questions above are added by this site; text in the boxes marked "AI summary" was written by an AI model and may contain errors. Registry records change over time. Check the original record for the current version and discuss eligibility or participation with a qualified healthcare professional.

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