Abstract:

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, afflicting around 1-2% of the population. Although more than half of the AF-attacks are not even noticed by the patients, it is associated with a 5-fold increased risk of stroke and can be life threatening in combination with ischemic strokes. Furthermore the risk of death due to AF-related strokes is doubled [1]. One of the causes for atrial fibrillation or cardiac arrhythmia in general can be re-entry. This phenomenon occurs in diseased or damaged tissue, when excitation conduction is delayed. In this case excitation does not follow its designated path anymore whereby muscle contraction gets out of sync, which consequent- ly leads to a decrease in blood delivery rate. Effective treatment e.g. by radiofrequency ablation needs proper information about the location of those areas. Conduction velocity (CV) provides an important quantity in identifying potential reetrant circuits and thus the position of the diseased tissue zones [2].In this thesis a novel point-based approach for conduction velocity estimation was tested. Therefore several simulation experiments, varying surface-to-volume ratio and intracel- lular conductivity were made using a tetrahedron model of an atrial tissue strip. The impact of different conduction velocities on the extracellular potential was investigated by analyzing specific characteristics of the voltage curves like amplitude, signalwidth or slope within the recorded unipolar electrograms. Furthermore analytic functions for each marker were approximated and tested upon reliability towards noise and electrode di- stance from the tissue surface. While both amplitude and signalwidth generated almost no estimation error facing white gaussian noise above 125 dB signal-to-noise-ratio (SNR), only signalwidth could withstand the effect of rising electrode distance with tolerable va- lues below 25% error for all distances. The major deviation was recorded within the first 2 mm of electrode distance, hence for further tests with clinical data the boundaries should definitely set below 2 mm and above 125 dB SNR, while using signalwidth-estimation. Successful tests with clinical data are yet to make.