Atrial Tissue Conductivity Estimation For Analysis of Atrial Fibrillation

Atrial Tissue Conductivity Estimation For Analysis of Atrial Fibrillation
Written by:Prof. Dr. Bianca Brundel

The Electrical Circuit of The Heart

Have you ever considered your heart as an electrical circuit? That is how we,  electrical engineers at TU Delft, look at the heart.

To us, Atrial Fibrillation (AF) is a fault in the heart circuit and the first step in finding faults on a circuit is to perform some measurements and try to make a model.

Using high resolution electrode arrays, our colleagues in Erasmus MC measure the electrical signals of the heart surface during open chest surgeries. Next, using these recorded signals, we aim to point out defective tissue which may cause development of AF.

A Complete Heartbeat

In our heart’s right upper chamber, there is a group of cells called the sinus node, which produces an electrical impulse that initiates each heartbeat.

This electrical impulse then, travels through both atria from cell to cell on a normal electrical conduction pathway causing both atria to contract simultaneously and pump the blood to the lower chambers (ventricles).

Next, the impulse reaches the atrioventricular node, slows down there, and then travels through the lower chambers.

Finally, the impulse makes the lower chambers contract in order to pump the blood to our body or our lungs. This is a complete and normal heartbeat.

What Happens During AF?

During AF, the upper chambers of our heart experience chaotic electrical signals. This happens because of complex electrical conduction disorders in the heart tissue called “electropathology”.

As a result, the electrical impulse of the sinus node breaks into small impulses going through irregular paths, causing small contraction instead of a simultaneous big contraction.

This increases the risk of blood clots and stroke. These small impulses bombard the atrioventricular node, causing the lower chambers to beat faster.

Our analysis of the electrical signal, which has been recorded directly from the heart surface using high resolution electrode arrays, has shown promising results in determining the level of electropathology in tissue.

Our hypothesis at TU Delft Circuit and Systems (CAS) group, is that by exploiting electropathology we are able to develop a novel diagnostic test to predict AF onset and its early progression.

In order to achieve this, we aim to develop signal processing algorithms to automatically estimate underlying tissue parameters, especially tissue conductivity.

What Is Tissue Conductivity?

Conductivity plays an important role in dynamics and functional connections in the tissue. In simple words: it determines the tissue’s ability to allow the transport of an electric charge. This is an area with small conductivity and slows down the electrical propagation in the tissue.

Similarly, an area with an almost zero conductivity, a “conduction block”, cannot transport any electrical charge, therefore the wave should either make a detour around the block or if it is not possible, it will eventually stop.

This complicates the electrical propagation in the tissue and results in the chaotic propagations observed in patients with AF.  The estimation of this hidden parameter is thus essential in the diagnosis and staging of the disease.

Future Research of Conductivity Maps

So far, we have had promising results in overcoming the challenges in tissue conductivity estimation. We can provide patients specific conductivity maps for small patches in the atrium.

Furthermore, we can use these maps to simulate and regenerate the electrical propagation. In the future we hope to improve our proposed approach for a more robust estimation of complex conductivity maps and to develop a patient specific physiological model of the whole atrium. This can potentially be used as a diagnostic tool that can be used in clinical setup for early recognition of AF.

Moreover, they can be used for testing and determining appropriate treatments by guiding cardiologist through ablation therapies.

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