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Content archived on 2024-06-18

Optimization of noninvasive assessment of the substrate for atrial fibrillation

Final Report Summary - ASAF (Optimization of noninvasive assessment of the substrate for atrial fibrillation)

Atrial fibrillation (AF) is a condition in which the atria, the upper chambers of the heart, contract in an uncoordinated fashion. AF reduces pumping efficiency and causes an irregular heart rate that cannot adapt anymore to the body’s demands. AF is caused by a malfunction of the electrical activation mechanism that orchestrates the contraction of the heart. In a normal heart this activation is generated at regular intervals in a single location, called the sinus node, and from there spreads over the atria. In AF, the activation can run in circles, resulting in a chaotic and irregular contraction. Moreover, AF maintains and aggravates itself by causing structural changes. Treatment options depend on the disease stage. Our purpose is to develop better diagnostic methods to identify the stage of AF in individual patients. We conducted this project to develop a computer model of the heart that could help us to better understand the relation between the stage of AF and the characteristics of the electrocardiogram (ECG) measured on the skin of the patient.
The structural remodeling process that maintains AF causes heterogeneous changes in the atrial tissue’s capacity to propagate the electrical activation. Therefore, the complexity of the propagating activation wavefront could be a measure of the disease stage. It would be desirable to assess this complexity from the ECG measured at the body surface. We hypothesized that more complex conduction patterns in the atria generate more complex potential patterns on the body surface. The purpose of our project was to find and validate measures for the complexity of ECG signals that correlate well with the complexity of wavefront propagation in the atria. To achieve this, we developed a large-scale computer model of the human atria with which we could accurately simulate the atrial activation pattern and the electrical signals (ECG and local electrograms) that result from it.

We have built an anatomical model of the atria that accurately represents the structural inhomogeneities that are present even in the healthy atria, and that allows pathological changes in the structure to be represented. Notably, the model includes a clear representation of the thin atrial wall and the thicker muscle bundles that are invariably present. With this model we simulated the electrical activation mechanism of the atria based on the transmembrane ionic currents in the atrial muscle cells. From the results we computed the ECG together with electrograms in the atria (which can be measured with endocardial catheters in real patients) as well as electrograms in the esophagus (which can also be measured in patients using a special probe).

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