A compact matrix model for atrial electrograms for tissue conductivity estimation

Finding the hidden parameters of the cardiac electrophysiological model would help to gain more insight on the mechanisms underlying atrial fibrillation, and subsequently, facilitate the diagnosis and treatment of the disease in later stages. In this work, we aim to estimate tissue conductivity from recorded electrograms as an indication of tissue (mal)functioning. To do so, we first develop a simple but effective forward model to replace the computationally intensive reaction-diffusion equations governing the electrical propagation in tissue. Using the simplified model, we present a compact matrix model for electrograms based on conductivity. Subsequently, we exploit the simplicity of the compact model to solve the ill-posed inverse problem of estimating tissue conductivity. The algorithm is demonstrated on simulated data as well as on clinically recorded data. The results show that the model allows to efficiently estimate the conductivity map. In addition, based on the estimated conductivity, realistic electrograms can be regenerated demonstrating the validity of the model.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Circuits and System

Decoding atrial fibrillation:Personalized identification and quantification of electropathology

Electrophysiological mapping-guided ablation strategies targeting atrial fibrillation (AF) have improved considerably over the past few years. However, it remains a major challenge to design effective strategies for particularly persistent AF. This can be partially explained by the inadequate understanding of the mechanisms and electropathological substrate underlying AF. Progression of AF is accompanied by structural and electrical remodeling, resulting in complex electrical conduction disorders, which is defined as electropathology. The severity of electropathology thus defines the stage of AF and is a major determinant of the effectiveness of AF therapy. In this thesis, features of electrophysiological properties of atrial tissue have been explored, developed and quantified during normal sinus rhythm, programmed electrical stimulation and AF. In addition, inter- and intra-individual variation in these quantified parameters has been examined in patients with and without prior episodes of AF. The most suitable objective parameters will aid in the identification of patients at risk for early onset or progression of AF. Part I of this thesis focusses on quantified electrogram features related to electropathology. In part II, abnormalities in wavefront propagation due to heterogeneous conduction properties were explored. Part III focusses on identification of post-operative AF and the relation with electropathology. In part IV of this thesis, some clinical implications of high-resolution mapping during cardiac surgery and application of quantified electrophysiological features are discussed