Fast Simulation of Mechanical Heterogeneity in the Electrically Asynchronous Heart Using the MultiPatch Module

Abstract

Cardiac electrical asynchrony occurs as a result of cardiac pacing or conduction disorders such as left bundle-branch block (LBBB). Electrically asynchronous activation causes myocardial contraction heterogeneity that can be detrimental for cardiac function. Computational models provide a tool for understanding pathological consequences of dyssynchronous contraction. Simulations of mechanical dyssynchrony within the heart are typically performed using the finite element method, whose computational intensity may present an obstacle to clinical deployment of patient-specific models. We present an alternative based on the CircAdapt lumped-parameter model of the heart and circulatory system, called the MultiPatch module. Cardiac walls are subdivided into an arbitrary number of patches of homogeneous tissue. Tissue properties and activation time can differ between patches. All patches within a wall share a common wall tension and curvature. Consequently, spatial location within the wall is not required to calculate deformation in a patch. We test the hypothesis that activation time is more important than tissue location for determining mechanical deformation in asynchronous hearts. We perform simulations representing an experimental study of myocardial deformation induced by ventricular pacing, and a patient with LBBB and heart failure using endocardial recordings of electrical activation, wall volumes, and end-diastolic volumes. Direct comparison between simulated and experimental strain patterns shows both qualitative and quantitative agreement between model fibre strain and experimental circumferential strain in terms of shortening and rebound stretch during ejection. Local myofibre strain in the patient simulation shows qualitative agreement with circumferential strain patterns observed in the patient using tagged MRI. We conclude that the MultiPatch module produces realistic regional deformation patterns in the asynchronous heart and that activation time is more important than tissue location within a wall for determining myocardial deformation. The CircAdapt model is therefore capable of fast and realistic simulations of dyssynchronous myocardial deformation embedded within the closed-loop cardiovascular system.

Predicting the Time Course of Ventricular Dilation and Thickening Using a Rapid Compartmental Model

“…Furthermore, it remains to be seen whether an approach similar to the one described here can handle the regional heterogeneity observed in hypertrophic cardiomyopathy or electrical dyssynchrony. Although intuition might suggest that such cases will require more geometrically sophisticated models, the 2-compartment model of infarction described here performed surprisingly well, and Walmsley et al have successfully reproduced many aspects of LV dyssynchrony using a multi-compartment model [34]. …”

Apresentação de Software para Pós-processamento de Curvas de Deformação Cardíaca: D-Station

“…Com isso, a curva de ECG não é mais necessária, e o programa torna-se compatível com o modelo matemático CircAdapt. Esse modelo associado ao MultiPatch Module, apresentado por Walmsley et al, 11 pode retornar curvas de strain correspondentes às simulações e os tempos de eventos mecânicos, sem sinais de ECG, como mostrado na Figura 6. Dessa forma, o software desenvolvido pode trabalhar com modelos cardíacos virtuais elaborados seguindo o trabalho de Walmsley et al [11][12][13][14] Possibilidade de aplicação de técnicas de aprendizado de máquina (Machine Learning) Machine learning consiste em uma área do campo da inteligência artificial capaz de processar problemas complexos de interação entre variáveis e fazer predições acuradas.…”

The Influence of Right Ventricular Afterload in Cardiac Resynchronization Therapy: A CircAdapt Study

“…Similarly, we adjusted the nonlinear stiffness exponent k and PH parameter p 0AV to meet different pressure conditions. This resulted in a total of about 80 combinations, for each of which we applied a homoestatic pressure-flow regulation algorithm [5] before performing the CRT ventricular activation pattern from [6]. The acute CRT response was observed by running 20 heart cycles without pressureflow adaptation.…”

“…Several studies have elaborated the acute CRT response due to various conditions via the multipatch module of Cir-cAdapt [3,4], a well-established tool that allows rapid simulation of the heart and circulatory system [5,6]. Recently, CircAdapt was also used in this context to test both mechanical dyssynchrony and RV contractility [7].…”