Related Experiment Video
Updated: May 23, 2025
Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
Published on: April 11, 2025
Use of Artificial Intelligence Applied to Electrocardiogram for Diagnosis of Left Ventricular Systolic Dysfunction
Wilton Batista de Santana Júnior1, Marcelo M Pinto Filho1, Sandhi Maria Barreto1
1Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG - Brasil.
Insights
An artificial intelligence (AI) algorithm effectively detects left ventricular systolic dysfunction (LVSD) using electrocardiograms (ECG). This AI tool shows promise as a screening method for heart failure (HF).
Area of Science:
- Cardiology
- Artificial Intelligence
- Medical Diagnostics
Background:
- Heart failure (HF) is a significant cause of morbidity and mortality.
- Electrocardiograms (ECG) are accessible and cost-effective tools for evaluating HF.
- Left ventricular systolic dysfunction (LVSD) is a key indicator of HF.
Purpose of the Study:
- To assess an artificial intelligence (AI) algorithm's performance in detecting LVSD via ECG.
- To compare the AI algorithm's predictive power against major electrocardiographic alterations (MEA).
Main Methods:
- A diagnostic accuracy cross-sectional study using data from the ELSA-Brasil cohort.
- Participants with valid ECG and echocardiogram (ECHO) data were included.
- The AI algorithm estimated LVSD probability; the endpoint was ECHO-confirmed left ventricular ejection fraction (LVEF) <40%.
Main Results:
- The AI algorithm demonstrated high performance with an area under the ROC curve (AUC-ROC) of 0.947.
- Algorithm sensitivity was 0.690, specificity 0.976, and negative predictive value 0.996.
- Compared to MEA, the AI algorithm showed significantly better predictive power for LVSD.
Conclusions:
- The AI algorithm exhibits strong performance in identifying LVSD.
- This AI-powered ECG analysis can serve as a valuable screening tool for LVSD.
Background:
Heart failure (HF) is a disease associated with an important type of morbidity and mortality. The electrocardiogram (ECG), one of the tests used to evaluate HF, is low-cost and widely available.
Objective:
To evaluate the performance of an artificial intelligence (AI) algorithm applied to ECG to detect HF and compare it with the predictive power of major electrocardiographic alterations (MEA).
Methods:
This work is a diagnostic accuracy cross-sectional study. All participants were from the Longitudinal Study of Adult Health (Estudo Longitudinal da Saúde do Adulto - ELSA-Brasil) and presented a valid ECG and echocardiogram (ECHO). The algorithm estimated probability values for left ventricular systolic dysfunction (LVSD). The assessed endpoint was left ventricular ejection fraction (LVEF) <40% in the ECHO. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), negative likelihood ratio (LR-), and diagnostic odds ratio (DOR) were determined for both the algorithm and the MEA. The area under the ROC curve (AUC-ROC) for the algorithm was calculated.
Results:
In the analytical sample of 2,567 individuals, the prevalence of LVEF <40% was 1.13% (29 individuals). The values obtained for sensitivity, specificity, PPV, NPV, LR+, LR-, and DOR for the algorithm were 0.690, 0.976, 0.244, 0.996, 27.6, 0.32, and 88.74, respectively. For the MEA, the values were 0.172, 0.837, 0.012, 0.989, 1.09, 0.990, and 1.07, respectively. The AUC-ROC of the algorithm to predict the LVEF <40% was 0.947 (95% CI: 0.913 - 0.981).
Conclusion:
The AI algorithm performed well in detecting LVSD and can be used as a screening tool for LVSD.
Related Concept Videos
01:29Electrocardiogram
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
01:17Imaging Studies for Cardiovascular System I:Echocardiography
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion,...
01:28Electrocardiogram Fundamentals
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
01:25Correlation between ECG and Cardiac Cycle
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...