Automatic detection of spatial and dynamic heterogeneity of repolarization

Area of Science:

• Cardiology
• Biomedical Engineering
• Computational Medicine

Background:

• Ventricular repolarization heterogeneity increases risk of life-threatening arrhythmias.
• Heterogeneity manifests as spatial (beat-to-beat) and dynamic (sequence of beats) variations.
• Manual detection of repolarization heterogeneity is time-consuming and inaccurate.

Purpose of the Study:

• To develop and validate computer algorithms for automatic detection of repolarization dispersion and T-wave alternans.
• To assess the utility of these algorithms in distinguishing patients with Long QT syndrome from healthy controls.

Main Methods:

• Development of computer algorithms for automatic detection of repolarization dispersion and T-wave alternans.
• Utilized high-resolution (1,000 Hz) digital electrocardiogram (ECG) leads (X, Y, Z).
• Tested algorithms on 10 patients with idiopathic Long QT syndrome and 10 age-matched normal subjects.

Main Results:

• Long QT syndrome patients showed significantly higher repolarization dispersion (44 ± 11 ms) compared to controls (13 ± 6 ms) (P < .01).
• T-wave alternans index was significantly higher in Long QT syndrome patients (0.40 ± 0.37) versus controls (0.03 ± 0.06) (P < .01).
• Automatic detection provided objective and sensitive measures of repolarization heterogeneity.

Conclusions:

• Simultaneous assessment of spatial and dynamic repolarization heterogeneity offers novel insights into myocardial electrical recovery.
• Automated detection of repolarization dispersion and T-wave alternans is a practical method for evaluating repolarization heterogeneity.
• This approach may improve risk stratification for patients prone to ventricular arrhythmias.