New Algorithm Allows for Better Heart Surgery

The researchers simulated electrical activity during normal sinus rhythm and ectopic pacing to analyze how atrial excitation was reflected in alteration to the P-wave morphology (PWM). The researchers thus created an ECG map that detects the origin of the heart defect, reducing the amount of time some patients need to spend in surgery.

The researchers found that during sinus rhythm, the simulated P-waves of 12 and 64 leads ECG and body-surface potential (BSP) dipole direction show strong agreement with experimental data. Marked changes in PWM were associated with ectopic atrial activity, with some areas of the torso being more sensitive to specific activity than others. The success rate of the algorithm was 93%, correctly identifying the origin of the problems in 75 out of 80 simulations, a much better rate than current technology. The study was published on January 8, 2015, in PLoS Computational Biology.

“The standard way we do electrocardiograms does not provide sufficient information to enable medical professionals to focus in clearly to the area of concern,” said lead author, Professor of Biological Physics Henggui Zhang, PhD. “What we have come up with here is a significant improvement over previous techniques. Using this new algorithm ECG map can help diagnose the location of cardiac disorder in a way which is better for the patients and more cost effective for health services.”

ECG body surface mapping (BSM) is a technique that uses multiple electrocardiography leads to detect electrical activity. The use of multiple leads can result in improved diagnostic accuracy compared to that of the standard 12-lead ECG. Currently there are no BSM ECG devices with 80 or more leads commercially available in the United States.

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