AbstractsComputer Science

The purpose of this contribution is to evaluate the feasibility, potential benefits and costs associated with generalizing and improving finite element formulations used to model, analyze and simulate the theoretical and practical operation and efficacy of internal myocardium defibrillation systems. The first goal of this contribution is to develop an anatomically accurate finite element model of the myocardium for the computational analysis and simulation of cardiac function. This work clarifies the critical characteristics required to produce accurate, reliable, and easily adaptable computational models for the human heart. This will provide a functional database for next generation biomedical computational analysis and simulation, for patient-specific determination of human heart health. More importantly, it will allow for the early and non-invasive detection of heart disease, along with the simulated prototyping and evaluation of proposed therapeutic treatments and surgical interventions. Towards this ultimate objective, the key components provided by this work are twofold: the generation of a finite element model for the left ventricle alone based on structured shape transformation mapping methods, and the patient-specific multilayered finite element model based on extracted raw data from medical images. The latter method is significantly advanced over the current state-of-the-art; it is constructed based on a self-consistent set of modular isoparametric second-order sub-domain structures, which facilitate both compatible anisotropic tissue modelling capabilities and integrity-preserving model adaptability. The main objective of this contribution is to investigate and evaluate the impact of modelling the directional aspects of the anisotropic electrical conductivity properties of the myocardium tissues, blood, and the immediate surrounding regions within the computational formulations used to model, analyze and predict the overall efficacy of internal myocardium defibrillation, in terms of electrode placement, size, and applied voltage profiles for both isolated healthy and infarcted hearts. Full tensor anisotropy formulations representing a variety of increasingly detailed conductivity models for representing the myocardium tissue layers and fiber bundles are considered and evaluated against simpler models. To incorporate the myocardial anisotropy properties into the computational models, the mapping technique based on the iterative closest point algorithm was used to fit the available myocardial fiber and sheet raw data for the computational model. Computational tests confirm that including the anisotropic nature of the myocardium can play a significant role in computing the excitations required for the internal defibrillation electrodes. It is shown that isotropic tissue models can overestimate defibrillation efficacy. In addition, results indicate the potential sensitivity of the predicated Defibrillation Threshold (DFT) results with respect to the electrode placement, regardless of the model used. It is…