AI-ECG for Predicting CMR-Defined Myocardial Injury in Acute Myocardial Infarction

Completed

Conditions studied: Acute Myocardial Infarction (AMI)

In brief

This retrospective, single-center external validation study evaluates whether two commercially approved artificial intelligence-enhanced electrocardiography (AI-ECG) algorithms (AiTiA LVSD and AiTiA MI; Medical AI Co., Ltd.), applied to a single pre-percutaneous coronary intervention (PCI) 12-lead ECG, predict cardiac magnetic resonance (CMR)-defined myocardial injury in patients with acute myocardial infarction (AMI). The primary endpoint is a large infarct (late gadolinium enhancement \>17.9% of left ventricular mass); secondary endpoints are CMR left ventricular ejection fraction (LVEF) ≤40% and microvascular obstruction (MVO).

Key facts

Study ID

NCT07751809

Run by

Yonsei University

People needed

461

Starts

2020-04-01

Expected to finish

2025-06-30

Last updated by the study team

2026-08-07

Who can join

Age: 19 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Acute myocardial infarction (STEMI or NSTEMI) undergoing PCI
• Subsequent cardiac magnetic resonance imaging performed
• Valid pre-PCI 12-lead ECG processable by both AI-ECG algorithms

You may not qualify if…

• Duplicate AMI enrollment
• Invalid ECG-CMR date linkage
• No valid pre-PCI 12-lead ECG processable by both algorithms

Where it is running

• Yongin Severance Hospital, Yonsei University College of Medicine — Yongin-si, Gyeonggi-do, South Korea

Full record on ClinicalTrials.gov

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