Predictive modeling of defibrillation using hexahedral and tetrahedral finite element models: recent advances

Abstract

ICD implants may be complicated by body size and anatomy. One approach to this problem has been the adoption of creative, extracardiac implant strategies using standard ICD components. Because data on safety or efficacy of such ad hoc implant strategies is lacking, we have developed imagebased finite element models (FEMs) to compare electric fields and expected defibrillation thresholds (DFTs) using standard and novel electrode locations. In this paper, we review recently published studies by our group using such models, and progress in meshing strategies to improve efficiency and visualization. Our preliminary observations predict that they may be large changes in DFTs with clinically relevant variations of electrode placement. Extracardiac ICDs of various lead configurations are predicted to be effective in both children and adults. This approach may aid both ICD development and patient-specific optimization of electrode placement, but the simplified nature of current models dictates further development and validation prior to clinical or industrial utilization.

Subject-specific, multiscale simulation of electrophysiology: a software pipeline for image-based models and application examples

“…(d(i-iii)) Slices of the heart model with colour indicating the electric potential from a simulation of ischaemia in the subject-specific geometric model. the relative comparisons in the defibrillation study seem to show the same trends across all the different age (and size) models, suggesting that patient-specific modelling may not be needed (Triedman et al 2008). On the other hand, we see substantial influence from factors such as the presence of bowel gas on the absolute values of defibrillation potential, which would argue in favour of patient-specific modelling.…”

“…At this point, the proof to support this premise is incomplete, although intuition would suggest it to be true. For example, the relative comparisons in the defibrillation study seem to show the same trends across all the different age (and size) models, suggesting that patient-specific modelling may not be needed ( Triedman et al . 2008 ).…”

Lattice Cleaving: A Multimaterial Tetrahedral Meshing Algorithm with Guarantees

“…The second simulation is used for modeling the effects of EEG source on a human skull [17]. The third simulation used is for modeling ICD placement for defibrillation in children and adults [46]. …”

Anti-arrhythmic strategies for atrial fibrillation

“…Although the use of computational models to terminate fibrillation has been reviewed elsewhere (Schotten et al 2012; Triedman et al 2008), computations can continue to add value to clinical practice of electrical cardioversion in AF. One recent study employed an anatomically realistic computer model of human atria and torso to investigate the relationship between esophageal electric fields and atrial defibrillation thresholds, and found that starting with a clinically established electrode placement protocol and making small translational shifts in position has the potential to increase the probability of successful cardioversion on the first shock (Fitch & de Jongh Curry 2015).…”