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Multiscale Modeling of the Ventricles
This work is focused on different aspects within the loop of multiscale modeling: On the cellular level, effects of adrenergic regulation and the Long-QT syndrome have been investigated.On the organ level, a model for the excitation conduction system was developed and the role of electrophysiological heterogeneities was analyzed.On the torso level a dynamic model of a deforming heart was created and the effects of tissue conductivities on the solution of the forward problem were evaluated
Modeling Human Atrial Patho-Electrophysiology from Ion Channels to ECG - Substrates, Pharmacology, Vulnerability, and P-Waves
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.
Personalized Multi-Scale Modeling of the Atria: Heterogeneities, Fiber Architecture, Hemodialysis and Ablation Therapy
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.
Modified Mass-spring System for Physically Based Deformation Modeling
Mass-spring systems are considered the simplest and most intuitive of all deformable models. They are computationally efficient, and can handle large deformations with ease. But they suffer several intrinsic limitations. In this book a modified mass-spring system for physically based deformation modeling that addresses the limitations and solves them elegantly is presented. Several implementations in modeling breast mechanics, heart mechanics and for elastic images registration are presented.
Multiscale Modeling of Cardiac Electrophysiology: Adaptation to Atrial and Ventricular Rhythm Disorders and Pharmacological Treatment
Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface.AbstractEnglisch = Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface.
ECG Based Analysis of the Ventricular Repolarisation in the Human Heart
ECG recordings provide diagnostic relevant information on the de- and repolarisation sequences of the heart. A modification of the repolarisation sequence is assumed to cause Torsades de Pointes. Especially drug induced effects on the repolarisation processes are in focus, since some non-cardiac drugs have been associated with sudden cardiac death in the 1990s.The analysis of the ventricular repolarisation using a set of parameters depicting the morphology of the T-wave is introduced in this work. Therefore, new methods of fully automatic patient-specific QRS detection, beat classification and precise T-wave delineation are presented. Using these methods, medical studies are investigated regarding the modification of the T-wave by different compounds. Also the impact of the heart rate on the morphology of the T-wave is part of this research.The reliable identification of ventricular ectopic beats allows an analysis of the influence of these beats on subsequent heart beats. It turned out that the morphology of subsequent heart beats can significantly be changed. This might give new information on the proarrythmical risk of ventricular ectopic beats.
Multiscale Cohort Modeling of Atrial Electrophysiology : Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms
An early detection and diagnosis of atrial fibrillation sets the course for timely intervention to prevent potentially occurring comorbidities. Electrocardiogram data resulting from electrophysiological cohort modeling and simulation can be a valuable data resource for improving automated atrial fibrillation risk stratification with machine learning techniques and thus, reduces the risk of stroke in affected patients.
Characterizing Cardiac Electrophysiology during Radiofrequency Ablation : An Integrative Ex vivo, In silico, and In vivo Approach
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.
ECG Imaging of Ventricular Activity in Clinical Applications
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.
SAR Prediction and SAR Management for Parallel Transmit MRI
Parallel transmission enables control of the RF field in high-field Magnetic Resonance Imaging (MRI). However, the approach has also caused concerns about the specific absorption rate (SAR) in the patient body. The present work provides new concepts for SAR prediction. A novel approach for generating human body models is proposed, based on a water-fat separated MRI pre-scan. Furthermore, this work explores various approaches for SAR reduction.
