Abstract:

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and the total number of AF patients is constantly increasing. The mechanisms leading to and sustaining AF are not completely understood yet. Heterogeneities in atrial electrophysiology seem to play an important role in this context. Although some heterogeneities have been used in in-silico human atrial modeling studies, they have not been thoroughly investigated. In this study, the original electrophysiological (EP) models of Courtemanche et al., Nygren et al. and Maleckar et al. were adjusted to reproduce action potentials in 13 atrial regions. The parameter sets were validated against experimental action potential duration data and ECG data from patients with AV block. The use of the heterogeneous EP model led to a more synchronized repolarization sequence in a variety of 3D atrial anatomical models. Combination of the heterogeneous EP model with a model of persistent AF-remodeled electrophysiology led to a drastic change in cell electrophysiology. Simulated Ta-waves were significantly shorter under the remodeling. The heterogeneities in cell electrophysiology explain the previously observed Ta-wave effects. The results mark an important step toward the reliable simulation of the atrial repolarization sequence, give a deeper understanding of the mechanism of atrial repolarization and enable further clinical investigations.

Abstract:

Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the current efforts of clinical atrial modeling in the euHeart project are summarized within the context of recent publications in this field. Model-based segmentation methods allow for the automatic generation of ready-to-simulate patient-specific anatomical models. EP models can be adapted to patient groups based on a-priori knowledge, and to the individual without significant further data acquisition. ECG and intracardiac data build the basis for excitation personalization. Information from late enhancement (LE) MRI can be used to evaluate the success of radio-frequency ablation (RFA) procedures and interactive virtual atria pave the way for RFA planning. Atrial modeling is currently in a transition from the sole use in basic research to future clinical applications. The proposed methods build the framework for model-based diagnosis and therapy evaluation and planning. Complex models allow to understand biophysical mechanisms and enable the development of simplified models for clinical applications.

Abstract:

Multiscale cardiac modeling has made great advances over the last decade. Highly detailed atrial models were created and used for the investigation of initiation and perpetuation of atrial fibrillation. The next challenge is the use of personalized atrial models in clinical practice. In this study, a framework of simple and robust tools is presented, which enables the generation and validation of patient-specific anatomical and electrophysiological atrial models. Introduction of rule-based atrial fiber orientation produced a realistic excitation sequence and a better correlation to the measured electrocardiograms. Personalization of the global conduction velocity lead to a precise match of the measured P-wave duration. The use of a virtual cohort of nine patient and volunteer models averaged out possible model-specific errors. Intra-atrial excitation conduction was personalized manually from left atrial local activation time maps. Inclusion of LE-MRI data into the simulations revealed possible gaps in ablation lesions. A fast marching level set approach to compute atrial depolarization was extended to incorporate anisotropy and conduction velocity heterogeneities and reproduced the monodomain solution. The presented chain of tools is an important step towards the use of atrial models for the patient-specific AF diagnosis and ablation therapy planing.

Abstract:

Numerical and patient-specific models of the human atrial anatomy and electrophysiology have a high potential to enhance our knowledge regarding pathological conditions and to increase the outcome of diagnosis and therapy. This chapter briefly describes the current state of the art in modeling of generalized human atria. Furthermore, the chapter demonstrates ways to personalize human atrial anatomy and electrophysiology based on a variety of measurement data from, e.g. late enhancement magnetic resonance imaging (MRI), patch clamp technique, intracardiac electrograms and body surface potential maps. Wherever patient data cannot be collected, patient-group specific behavior can be integrated. Some examples of the personalization process are described and the validation process is discussed together with future options for personalization, validation and application.

Abstract:

Abstract. Atrial fibrillation (AF) is the most common cardiac arrhyth- mia. Patient-specific computational modeling of the atria can provide a better understanding about mechanisms underlying the arrhythmia and will potentially be used for model-based ablation therapy evaluation and planning. Electrical excitation spreads from the left to the right atrium at discrete locations. The location of the muscular bridges cannot be determined from image data. In the present study, left atrial activation sources were manually identified in local activation time maps of 4 AF patients. This information was used to adjust rule-based placed intera- trial bridges in anatomical atrial models of the patients. Sinus rhythm simulations showed a better qualitative agreement to the measured left atrial activation patterns after the adjustment of the bridges. For one patient, the simulated body surface potential (BSP) pattern after the adjustment correlated better to measured BSP maps. The results show that the fusion of intracardiac electrical measurements of early left atrial activation can be used to refine patient atria models with information of the myocardial structure which cannot be imaged. In future, such personalized atrial models may be used to support EP interventions.

Abstract:

Cardiac computer modeling can help to gain a deeper insight into the physiological processes of the heart. In this work we present a new electromechanical modeling framework which allows to simulate the contraction of the atria in a model of the whole heart with realistic bound- ary conditions. For the active tension development (TD) we used a model, which was originally developed to describe the TD of the ventricles. However, TD in the atria differs significantly from that of the ventricles. On that account, we adapted the TD model to the measurement data of the atria. The modeling framework allows to obtain a realistic motion of the atria during the contraction cycle.

Abstract:

This book targets three fields of computational multi-scale cardiac modeling. First, advanced models of the cellular atrial electrophysiology and fiber orientation are introduced. Second, novel methods to create patient-specific models of the atria are described. Third, applications of personalized models in basic research and clinical practice are presented. The results mark an important step towards the patient-specific model-based atrial fibrillation diagnosis, understanding and treatment.