Cardiac AmyloidosisNCT06664866
AI Echocardiographic Screening of Cardiac Amyloidosis
A study testing EchoNet-LVH Assessment in people with Cardiac Amyloidosis, run by Cedars-Sinai Medical Center at 4 sites in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 22 years and older
- Conditions the study is for
- Cardiac Amyloidosis
- What is being tested?
- EchoNet-LVH Assessment
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 500 participants
- Where
- 4 sitesUnited States
- Study dates
- 28 Oct 2024to 1 Nov 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 22 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Patients receiving an echocardiogram that is determined to be suspicious by EchoNet-LVH
Who cannot join
- Patients that decline consent
- Patients receiving an echocardiogram that is determined to be not suspicious by EchoNet-LVH
Trial locations and contacts
4 sites in 1 country. Contact the study team or a site near you to ask about taking part.
United States4 sites
Northwestern Medicine
Chicago, Illinois, 60190
Cedars Sinai Medical Center
Los Angeles, California, 90034
Palo Alto Veteran Affairs Hospital
Palo Alto, California, 94304
Providence Heart and Vascular Institute
Portland, Oregon, 97225
About this study
Official title: Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases (EchoNet-Screening)
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.
- Conditions
- Cardiac Amyloidosis
- Being tested
- EchoNet-LVH Assessment
- Medical subject headings
- Amyloid Neuropathies, Familial
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
EchoNet-LVH AssessmentDiagnostic test
The AI algorithm is previously described (Duffy et al. JAMA Cardiology 2022) and will remain unchanged throughout the course of the study. A pre-determined threshold based on prior experiments and analysis has been decided prior to the study. From each site, approximately 100,000 echocardiogram studies will be reviewed by EchoNet-LVH for approximately 500 patients to be flagged.
| Study group | Role | What they receive |
|---|---|---|
| Suspicious by EchoNet-LVH Algorithm | Experimental | Each potential participant identified by automated AI-enhanced echocardiogram review will be chart reviewed by each site's CA experts for appropriateness of enrollment and clinican suspicion for CA. Based on the judgement of CA experts, potential participants that meet eligibility criteria will be called to be consented, followed in the study, and referred to see the CA expert. Receives: Diagnostic Test: EchoNet-LVH Assessment |
What is being measured
The primary outcome is the main question the study is designed to answer.
Positive Predictive Value
- Among patients that screening positive and consented to the trial, the proportion of patients that subsequently are confirmed to have CA upon clinical follow-up.
- Statistical Analysis: Fisher's exact (two-sided) for superiority Comparison with PPV of standard clinical suspicion (PPV of all comers that receive Tc-99m PYP/HDP imaging scan or other clinical diagnosis).
Measured: 1 year
Secondary outcomes (6)
Time to Diagnosis from Echocardiogram Study to Clinical Diagnosis
Statistical Analysis: Cox proportional hazards test with comparison with of Study population vs. comparison with Patients with echocardiogram study showing at least moderate left ventricular hypertrophy by human interpretation.
Measured: 1 year
Number of Patients that Receive Treatment for CA
Measured: 1 year
Number of Cardiac Amyloidosis Diagnoses
Measured: 1 year
Number of Participants with All Cause Death
Measured: 1 year
Number of Participants with All Cause Hospitalization
Measured: 1 year
Number of Participants with Heart Failure Hospitalization
defined as needing IV diuretics or BNP higher than baseline or ICD9/10 code
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Oct 2024
- Study start28 Oct 2024
- Primary completion1 Nov 2026 (estimated)
- Study completion1 Nov 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Cardiac AmyloidosisStudies of the same condition, open and under way.
- More trials run by Cedars-Sinai Medical CenterThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cedars-Sinai Medical Center
- Sponsor type
- University, hospital or other
- Collaborators
- Palo Alto Veteran Affairs Hospital, Providence Heart & Vascular Institute, Northwestern Medicine
- Responsible party
- Principal investigator, Lily Stern, Cedars-Sinai Medical Center
- Investigators
- Lily Stern, MD, Principal investigator, Cedars-Sinai Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06664866
- Sponsor's protocol ID
- Study1720
- Status last verified
- Jul 2026
- First submitted
- 28 Oct 2024
- Last updated
- 22 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 22 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases (EchoNet-Screening)
- ClinicalTrials.gov ID
- NCT06664866
- Acronym / sponsor ID
- Study1720
- Conditions
- Cardiac Amyloidosis
- Study type
- Interventional
- Recruitment status
- Enrolling by invitation
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Cedars-Sinai Medical CenterUniversity, hospital or other
- Collaborators
- Palo Alto Veteran Affairs Hospital, Providence Heart & Vascular Institute, Northwestern Medicine
- Study start
- 28 Oct 2024 (actual)
- Primary completion
- 1 Nov 2026 (estimated)
- Study completion
- 1 Nov 2027 (estimated)
- First posted
- 30 Oct 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Suspicious by EchoNet-LVH Algorithm | Experimental | Diagnostic Test: EchoNet-LVH AssessmentEach potential participant identified by automated AI-enhanced echocardiogram review will be chart reviewed by each site's CA experts for appropriateness of enrollment and clinican suspicion for CA. Based on the judgement of CA experts, potential participants that meet eligibility criteria will be called to be consented, followed in the study, and referred to see the CA expert. |
Who may qualify
- Ages
- 22 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Patients receiving an echocardiogram that is determined to be suspicious by EchoNet-LVH
Key exclusion criteria (2 listed)
- Patients that decline consent
- Patients receiving an echocardiogram that is determined to be not suspicious by EchoNet-LVH
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| EchoNet-LVH AssessmentThe AI algorithm is previously described (Duffy et al. JAMA Cardiology 2022) and will remain unchanged throughout the course of the study. A pre-determined threshold based on prior experiments and analysis has been decided prior to the study. From each site, approximately 100,000 echocardiogram studies will be reviewed by EchoNet-LVH for approximately 500 patients to be flagged. | Diagnostic test | Suspicious by EchoNet-LVH Algorithm |
Primary outcome
Positive Predictive Value
Time frame: 1 year
1. Among patients that screening positive and consented to the trial, the proportion of patients that subsequently are confirmed to have CA upon clinical follow-up. 2. Statistical Analysis: Fisher's exact (two-sided) for superiority Comparison with PPV of standard clinical suspicion (PPV of all comers that receive Tc-99m PYP/HDP imaging scan or other clinical diagnosis).
6 secondary outcomes
Time to Diagnosis from Echocardiogram Study to Clinical Diagnosis
Time frame: 1 year
Number of Patients that Receive Treatment for CA
Time frame: 1 year
Number of Cardiac Amyloidosis Diagnoses
Time frame: 1 year
Number of Participants with All Cause Death
Time frame: 1 year
Number of Participants with All Cause Hospitalization
Time frame: 1 year
Number of Participants with Heart Failure Hospitalization
Time frame: 1 year
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Jul 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Lily Stern, MD principal investigator
Cedars-Sinai Medical Center
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing EchoNet-LVH Assessment in people with Cardiac Amyloidosis, run by Cedars-Sinai Medical Center at 4 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: enrolling by invitation, as of the sponsor's last update on 22 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Positive Predictive Value (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Jul 2026.