AI Echocardiographic Screening of Cardiac Amyloidosis

Official title

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

Overview

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.

Interventions

• Diagnostic test EchoNet-LVH Assessment
  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.

Primary outcome measures

• Positive Predictive Value [Time frame: 1 year]

Secondary outcome measures (6)

• 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]

Eligibility criteria

Inclusion criteria

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

Exclusion criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

N/A

Model

Single group

Masking

Open label

Primary purpose

Diagnostic

Study locations

United States · 4 centers

• Cedars Sinai Medical Center — Los Angeles
• Palo Alto Veteran Affairs Hospital — Palo Alto
• Northwestern Medicine — Chicago
• Providence Heart and Vascular Institute — Portland

Identifiers

NCT: NCT06664866 · Study1720

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗