Atrial arrhythmias such as atrial fibrillation or atrial flutter are a large burden for both patients and health care systems worldwide. Changes in the atrial substrate are known to initiate and maintain the abnormal cardiac rhythm. However, the tools to deduce substrate properties from atrial electrograms are still unsatisfactory and require further investigation. The conduction velocity as one of the substrate properties of interest undergoes pathological remodeling in diseased tissue. Therefore, a conduction velocity map of high spatial resolution would be of great clinical benefit. In order to provide the latter, it is inevitable to support the algorithms for conduction velocity estimation with additional input parameters that can be extracted from patient specific atrial electrograms.
This project focusses on improving the estimation of conduction velocities at the atrial surface during repetitive cardiac rhythms. To this end, existing algorithms will be fine-tuned to patient specific and local conductive properties by extracting and estimating relevant parameters from clinical intraatrial electrograms. In particular, the detection of scars, the estimation of the signal to noise ratio and a measure for the temporal uncertainty of local activation times will be deduced, analyzed, and applied. Refined conduction velocity maps will be presented to our clinical partners.