Solving the Inverse Problem of Electrocardiography on the Endocardium Using a Single Layer Source.

Area of Science:

• Biomedical Engineering
• Computational Electrophysiology
• Medical Imaging

Background:

• Reconstructing cardiac electrical activity from body surface measurements (inverse problem of electrocardiography) remains challenging, especially for endocardial potentials.
• Existing methods struggle to achieve acceptable accuracy on the heart's inner surface.

Purpose of the Study:

• To present a novel numerical approach for enhancing the accuracy of endocardial electrical potential reconstruction.
• To leverage single layer densities on the myocardial surface for improved inverse problem solutions.

Main Methods:

• The study utilizes a solution representation based on electrical single layer densities on the myocardial surface.
• A conventional transfer matrix is split, revealing a regularizing component.
• The method was validated in-silico using realistic CT-based heart and torso geometries for ventricular pacing.

Main Results:

• The novel approach provides more accurate endocardial reconstructions compared to conventional potential-based methods with Tikhonov regularization.
• The single layer density representation offers a physiologically meaningful solution.
• A regularizing property was identified within a split component of the transfer matrix.

Conclusions:

• The proposed method significantly improves the accuracy of endocardial electrical activity reconstruction.
• Single layer densities offer a robust and potentially more stable representation for inverse electrocardiography problems.
• The uniform spatio-temporal behavior of single layer densities can be exploited for regularization.