ClinicalTrials.gov record NCT06664866
AI Echocardiographic Screening of Cardiac Amyloidosis
Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases (EchoNet-Screening)
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.
An interventional diagnostic study using an existing AI algorithm (EchoNet-LVH) to flag echocardiograms suspicious for cardiac amyloidosis. Flagged charts are reviewed by site cardiac amyloidosis experts; eligible patients who consent will be followed and referred to those experts. The study measures how often flagged patients are later confirmed to have cardiac amyloidosis and tracks diagnosis timing and clinical outcomes over one year.
What it is studying. The study tests how well the EchoNet-LVH algorithm identifies echocardiograms that lead to confirmed cardiac amyloidosis diagnoses, with positive predictive value as the primary measure. It also measures time from echocardiogram to clinical diagnosis and counts of diagnoses, treatments, hospitalizations, and deaths within one year.
What the researchers hope to learn. To evaluate the diagnostic accuracy (positive predictive value) of EchoNet-LVH for detecting cardiac amyloidosis and to measure effects on time-to-diagnosis, number of diagnoses, treatment rates, hospitalizations, and deaths over one year.
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.
The EchoNet-LVH algorithm will review existing echocardiogram studies and flag those it deems suspicious for cardiac amyloidosis. Flagged cases will be chart-reviewed by each site's cardiac amyloidosis experts; patients judged appropriate will be contacted, asked to give consent, followed while in the study, and referred to see the cardiac amyloidosis specialist. The registry record does not list specific additional tests or invasive procedures performed by the study itself; it emphasizes chart review, consent, referral, and clinical follow-up to confirm diagnosis and track outcomes. The record states that about 100,000 echocardiograms will be screened by the algorithm to identify roughly 500 flagged patients.
How the study is structured. Interventional diagnostic, single-group study with no masking. EchoNet-LVH will screen large numbers of echocardiogram studies using a pre-set threshold; studies the algorithm flags are chart reviewed by site experts. Patients judged appropriate by experts may be contacted for consent, then followed and referred to the cardiac amyloidosis expert for clinical follow-up. Analyses compare outcomes among flagged participants with standard clinical-suspicion benchmarks described in the record.
Questions you could ask
These questions are suggestions for a conversation with the study team or your own clinician, not advice.
- The registry lists this study under Cardiac Amyloidosis. Does it apply to my diagnosis?
- 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 ATTRv amyloidosis
This trial is also listed on this site under wild-type ATTR amyloidosis.
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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