AI-Guided Echocardiogram Screening to Detect Cardiac Amyloidosis and Related Heart Conditions

What this Trial Is About

Researchers are exploring the use of an artificial intelligence AI algorithm called EchoNet-LVH to improve the detection of cardiac hypertrophy and identify patients who may benefit from additional screening for cardiac amyloidosis and related rare heart diseases. This observational study aims to address limitations in current clinical assessments by using machine learning to recognize features in echocardiograms that might be missed or interpreted differently by human experts. The study uses the EchoNet-LVH AI algorithm to analyze echocardiographic images and generate a suspicion score for cardiac amyloidosis and hypertrophic cardiomyopathy. Patients who receive a high suspicion score from the AI will be referred to a specialty clinic for further standard care evaluation, screening, and potential treatment as decided by physicians. This approach seeks to enhance early and accurate disease identification through AI-guided screening. Participants undergo routine echocardiographic screening interpreted by the AI algorithm, which evaluates heart morphology. The main outcome measured is the number of new diagnoses of cardiac amyloidosis within six months, including subtypes like TTR and AL amyloidosis. Participants referred to specialty clinics will receive further assessments and standard care. The study is sponsored by Cedars-Sinai Medical Center and will continue through June 2027.

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