AI Echocardiographic Screening of Cardiac Amyloidosis

Enrolling by invitation · Not applicable

Conditions studied: Cardiac Amyloidosis

In brief

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.

Key facts

Study ID

NCT06664866

Run by

Cedars-Sinai Medical Center

People needed

500

Starts

2024-10-28

Expected to finish

2027-11-01

Last updated by the study team

2026-07-22

Who can join

Age: 22 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

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

You may not qualify if…

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

Where it is running

• Cedars Sinai Medical Center — Los Angeles, California, United States
• Palo Alto Veteran Affairs Hospital — Palo Alto, California, United States
• Northwestern Medicine — Chicago, Illinois, United States
• Providence Heart and Vascular Institute — Portland, Oregon, United States

Full record on ClinicalTrials.gov

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