The objective of this article is to present a set of methods for constructing realistic computational models of cardiac structure from high-resolution structural and diffusion tensor magnetic resonance images and to demonstrate the applicability of the models in simulation studies. The structural image is segmented to identify various regions such as normal myocardium, ventricles, and infarct. A finite element mesh is generated from the processed structural data, and fiber orientations are assigned to the elements. The Purkinje system, when visible, is modeled using linear elements that interconnect a set of manually identified points. The methods were applied to construct 2 different models; and 2 simulation studies, which demonstrate the applicability of the models in the analysis of arrhythmia and defibrillation, were performed. The models represent cardiac structure with unprecedented detail for simulation studies.

Background Low-voltage termination of VT and atrial fibrillation has shown promising results, however the mechanisms and full range of applications remain unexplored. Objective This study aimed to elucidate the mechanisms for low-voltage cardioversion and defibrillation, and to develop an optimal low-voltage defibrillation protocol. Methods We developed a detailed MRI-based computational model of the rabbit right ventricular wall. We applied multiple low-voltage far-field stimuli of various strengths (≤1 V/cm) and stimulation rates in VT and VF. Results Out of the five stimulation rates tested, stimuli applied at 16 or 88% of VT cycle length (CL) were most effective in cardioverting VT, the mechanism being consecutive excitable gap decreases. Stimuli given at 88% of VF CL defibrillated successfully, whereas a faster stimulation rate (16%) often failed because the fast stimuli did not capture enough tissue. In this model, defibrillation threshold (DFT) energy for multiple low-voltage stimuli at 88% VF CL was 0.58% of the DFT energy for a single strong biphasic shock. Based on the simulation results, a novel two-stage defibrillation protocol was proposed. The first stage converted VF into VT by applying low-voltage stimuli at times of maximal excitable gap, capturing large tissue volume and synchronizing depolarization; the second stage terminated VT. The energy required for successful defibrillation using this protocol was 57.42% of the energy for low-voltage defibrillation when stimulating at 88% CL. Conclusion A novel two-stage low-voltage defibrillation protocol using the excitable gap extent to time multiple stimuli defibrillated VF with the least energy by first converting VF into VT, then terminating VT.

Key points• Defibrillation is known to be less efficient in infarcted than in healthy hearts.• In a rabbit model of myocardial infarction, altered 3D distribution of virtual electrodes and propagation delay in the peri-infarct zone caused increased vulnerability to electric shocks in infarcted hearts.• The infarct scar alone -without the presence of a peri-infarct zone -did not cause an increase in vulnerability.• The results help us to understand the mechanisms of increased vulnerability and decreased defibrillation efficacy in infarcted hearts.Abstract Defibrillation efficacy is decreased in infarcted hearts, but the mechanisms by which infarcted hearts are more vulnerable to electric shocks than healthy hearts remain poorly understood. The goal of this study was to provide insight into the 3D mechanisms for the increased vulnerability to electric shocks in infarcted hearts. We hypothesized that changes in virtual electrode polarizations (VEPs) and propagation delay through the peri-infarct zone (PZ) were responsible. We developed a microanatomically detailed rabbit ventricular model with chronic myocardial infarction from magnetic resonance imaging and enriched the model with data from optical mapping experiments. We further developed a control model without the infarct. The simulation protocol involved apical pacing followed by biphasic shocks. Simulation results from both models were compared. The upper limit of vulnerability (ULV) was 8 V cm −1 in the infarction model and 4 V cm −1 in the control model. VEPs were less pronounced in the infarction model, providing a larger excitable area for postshock propagation but smaller transmembrane potential gradients to initiate new wavefronts. Initial post-shock transmural activation occurred at a later time in the infarction model, and the PZ served to delay propagation in subsequent beats. The presence of the PZ was found to be responsible for the increased vulnerability.

Key points• Implantable cardioverter-defibrillators (ICDs) with transvenous leads often cannot be implanted in a standard manner in paediatric and congenital heart defect (CHD) patients. Currently, there is no reliable approach to predict the optimal ICD placement in these patients.• A pipeline for constructing personalized, electrophysiological heart-torso models from clinical magnetic resonance imaging scans was developed and applied to a paediatric CHD patient.• Optimal ICD placement was determined using patient-specific simulations of the defibrillation process. In a patient with tricuspid valve atresia, two configurations with epicardial leads were found to have the lowest defibrillation threshold.• We demonstrated that determining extracellular potential ( e ) gradients during the shockwithout actually simulating defibrillation -was not sufficient to predict defibrillation success or failure.• Using the proposed methodology, the optimal ICD placement in paediatric/CHD patients can be predicted computationally, which could reduce defibrillation energy if the pipeline is used as part of ICD implantation planning.Abstract There is currently no reliable way of predicting the optimal implantable cardioverter-defibrillator (ICD) placement in paediatric and congenital heart defect (CHD) patients. This study aimed to: (1) develop a new image processing pipeline for constructing patient-specific heart-torso models from clinical magnetic resonance images (MRIs); (2) use the pipeline to determine the optimal ICD configuration in a paediatric tricuspid valve atresia patient; (3) establish whether the widely used criterion of shock-induced extracellular potential ( e ) gradients ≥5 V cm −1 in ≥95% of ventricular volume predicts defibrillation success. A biophysically detailed heart-torso model was generated from patient MRIs. Because transvenous access was impossible, three subcutaneous and three epicardial lead placement sites were identified along with five ICD scan locations. Ventricular fibrillation was induced, and defibrillation shocks were applied from 11 ICD configurations to determine defibrillation thresholds (DFTs). Two configurations with epicardial leads resulted in the lowest DFTs overall and were thus considered optimal. Three configurations shared the lowest DFT among subcutaneous lead ICDs. The e gradient criterion was an inadequate predictor of defibrillation success, as defibrillation failed in numerous instances even when 100% of the myocardium experienced such gradients. In conclusion, we have developed a new image processing pipeline and applied it to a CHD patient to construct the first active heart-torso model from clinical MRIs.

Cardiac defibrillation, as accomplished nowadays by automatic, implantable devices, constitutes the most important means of combating sudden cardiac death. Advancing our understanding towards a full appreciation of the mechanisms by which a shock interacts with the heart, particularly under diseased conditions, is a promising approach to achieve an optimal therapy. The aim of this article is to assess the current state-of-the-art in whole-heart defibrillation modelling, focusing on major insights that have been obtained using defibrillation models, primarily those of realistic heart geometry and disease remodelling. The article showcases the contributions that modelling and simulation have made to our understanding of the defibrillation process. The review thus provides an example of biophysically based computational modelling of the heart (i.e. cardiac defibrillation) that has advanced the understanding of cardiac electrophysiological interaction at the organ level, and has the potential to contribute to the betterment of the clinical practice of defibrillation.

The locAP algorithm is a valid and valuable tool for clinical practice in a cardiac electrophysiology laboratory. It could be shown that use of the locAP algorithm is favorable over the localizing algorithms that are in clinical use today.