Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases

What this Trial Is About

Researchers are exploring the use of an artificial intelligence (AI) algorithm called EchoNet-LVH to improve detection of rare heart diseases such as cardiac amyloidosis and hypertrophic cardiomyopathy. These diseases can be difficult to distinguish using current clinical methods due to similar heart morphology, leading to misdiagnosis and delayed treatment. The study aims to evaluate how accurately this AI tool can identify patients who might benefit from additional screening for these conditions. The AI algorithm analyzes echocardiographic images to detect signs of left ventricular hypertrophy, low voltage, and other features suggestive of cardiac amyloidosis. When the AI identifies a high suspicion score, patients are referred to a specialty clinic for further evaluation, standard screening, and treatment as determined by physicians. This observational study follows patients based on the AI's assessment without assigning specific interventions. Participants will undergo routine echocardiography, with the AI algorithm generating a probability score for cardiac amyloidosis. Researchers will track the number of new diagnoses of cardiac amyloidosis and its subtypes over six months. The study monitors participant outcomes through standard care evaluations at specialty clinics. Total participation time varies depending on individual clinical follow-up and referral results.

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