AI Echocardiographic Screening of Cardiac Amyloidosis
- Conditions
- Cardiac Amyloidosis
- Registration Number
- NCT06664866
- Lead Sponsor
- Cedars-Sinai Medical Center
- Brief 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. 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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ENROLLING_BY_INVITATION
- Sex
- All
- Target Recruitment
- 500
- Patients receiving an echocardiogram that is determined to be suspicious by EchoNet-LVH
- Patients that decline consent
- Patients receiving an echocardiogram that is determined to be not suspicious by EchoNet-LVH
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Primary Outcome Measures
Name Time Method Positive Predictive Value 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).
- Secondary Outcome Measures
Name Time Method Time to Diagnosis from Echocardiogram Study to Clinical Diagnosis 1 year 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.
Number of Patients that Receive Treatment for CA 1 year Number of Cardiac Amyloidosis Diagnoses 1 year Number of Participants with All Cause Death 1 year Number of Participants with All Cause Hospitalization 1 year Number of Participants with Heart Failure Hospitalization 1 year defined as needing IV diuretics or BNP higher than baseline or ICD9/10 code
Trial Locations
- Locations (4)
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