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Early Detection of Concealed Cardiac Amyloidosis Using AI-ECG and CT-Derived Extracellular Volume in Patients With Atrial Fibrillation
Sponsor: Samsung Medical Center
Summary
This study investigates the clinical efficacy of a non-invasive screening protocol using AI-ECG and CT-ECV analysis for cardiac amyloidosis. The study targets on atrial fibrillation(AF) patients with "red-flag" indicators. Participants are randomized 1:1 into either an early screening or usual care group. * Early screening group : AI- ECG and/or CT-ECV analysis + AF treatment * Usual care group : AF treatment Both groups followed for 2 years to compare CA detection rates and clinical outcomes.
Key Details
Gender
All
Age Range
19 Years - Any
Study Type
INTERVENTIONAL
Enrollment
500
Start Date
2026-05
Completion Date
2029-12-31
Last Updated
2026-05-05
Healthy Volunteers
No
Interventions
AI-ECG analysis
Artificial Intelligence-enhanced Electrocardiogram (AI-ECG), developed by Mayo Clinic, is gaining attention as a non-invasive screening tool. AI-ECG predicts myocardial amyloid deposition based on a standard 12-lead ECG with high accuracy, AUC 0.84(95% CI 0.82-0.86) In particular, it demonstrated superior performance with an AUC of 0.9 or higher in ECGs exhibiting low voltage or pseudo-infarction patterns, suggesting its potential to detect the disease even before structural changes become apparent.
CT-ECV analysis
Myocardial Extracellular Volume (CT-ECV) analysis using cardiac CT is a tissue characterization technique that can be easily added to conventional cardiac CT protocols, enabling the quantification of myocardial fibrosis or infiltrative diseases. Among 874 subjects who underwent coronary CT, 12.4% exhibited a CT-ECV of ≥ 35%, and cardiac amyloidosis was incidentally discovered in 14.3% of these individuals.
Atrial fibrillation treatment
Standard care and treatment in accordance with established AF guidelines.
Locations (1)
Samsung Medical Center
Seoul, Seoul, South Korea