ECG imaging was performed in humans to reconstruct ventricular activation patterns and localize their excitation origins. The precision of the non-invasive reconstructions was evaluated against invasive measurements and found to be in line with the state-of-the-art literature. Statistics were produced for various excitation origins and reveal the beat-to-beat robustness of the imaging method.

This work provides methods to measure and analyze features of atrial electrograms - especially complex fractionated atrial electrograms (CFAEs) - mathematically. Automated classification of CFAEs into clinical meaningful classes is applied and the newly gained electrogram information is visualized on patient specific 3D models of the atria. Clinical applications of the presented methods showed that quantitative measures of CFAEs reveal beneficial information about the underlying arrhythmia.

Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This book presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF.

Catheter ablation is a major treatment for atrial tachycardias. Hereby, the precise monitoring of the lesion formation is an important success factor. This book presents computational, wet-lab, and clinical studies with the aim of evaluating the signal characteristics of the intracardiac electrograms (IEGMs) recorded around ablation lesions from different perspectives. The detailed analysis of the IEGMs can optimize the description of durable and complex lesions during the ablation procedure.