Desynchronization Strain Patterns and Contractility in Left Bundle Branch Block through Computer Model Simulation

Abstract

Left bundle branch block (LBBB) is associated with specific septal-to-lateral wall activation patterns which are strongly influenced by the intrinsic left ventricular (LV) contractility and myocardial scar localization. The objective of this study was to propose a computational-model-based interpretation of the different patterns of LV contraction observed in the case of LBBB and preserved contractility or myocardial scarring. Two-dimensional transthoracic echocardiography was used to obtain LV volumes and deformation patterns in three patients with LBBB: (1) a patient with non-ischemic dilated cardiomyopathy, (2) a patient with antero-septal myocardial scar, and (3) a patient with lateral myocardial scar. Scar was confirmed by the distribution of late gadolinium enhancement with cardiac magnetic resonance imaging (cMRI). Model parameters were evaluated manually to reproduce patient-derived data such as strain curves obtained from echocardiographic apical views. The model was able to reproduce the specific strain patterns observed in patients. A typical septal flash with pre-ejection shortening, rebound stretch, and delayed lateral wall activation was observed in the case of non-ischemic cardiomyopathy. In the case of lateral scar, the contractility of the lateral wall was significantly impaired and septal flash was absent. In the case of septal scar, septal flash and rebound stretch were also present as previously described in the literature. Interestingly, the model was also able to simulate the specific contractile properties of the myocardium, providing an excellent localization of LV scar in ischemic patients. The model was able to simulate the electromechanical delay and specific contractility patterns observed in patients with LBBB of ischemic and non-ischemic etiology. With further improvement and validation, this technique might be a useful tool for the diagnosis and treatment planning of heart failure patients needing CRT.

Model-based analysis of myocardial strains in left bundle branch block

“…The lateral hypocontractility case is characterized by a modification of the LV activation pattern and is associated with a significant reduction in lateral wall strain and a diminution of the septal rebound stretch. The simulations could be related to Aalen et al [6] experimental results, where LBBB was induced in dogs with or without LV scar and previous results of our team [35].…”

“…These parameter modifications could be done independently on each segment at the same time. As performed in Owashi et al [35], model parameters were adjusted manually in order to reproduce characteristic strain patterns for a healthy subject and three patients with typical LBBB.…”

“…Therefore, a novel method is proposed, based on the patientspecific identification of a multi-segment model of LVs and RVs coupled to atria, systemic, and pulmonary circulations [33,34]. Recently, our team article has proposed an interpretation of the different patterns of LV contraction observed in different cases of LBBB, based on a manual evaluation of the model parameters of three patients with LBBB [35]. Interestingly, this model took into account not only the electrical activation delay of each segment but also the differences in regional contractility, which are known to largely contribute to strain morphology and global cardiac mechanics.…”

Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy—Benchmark Analysis with Finite-Element Methods in Experimental Data

“…Additionally, the parameter optimization schemes used by all participants of the CRT-Epiggy19 challenge were not taking advantage of recent technological advances such as the use of deep learning algorithms [55,56], variational approaches [57], reduced-order models [58,59] or GPUbased architectures [60], which allows for the exploration of a larger space of parameter solutions at reduced computational times. Moreover, cardiac multi-physical models should provide more realistic simulations, allowing for the inclusion of hemodynamic factors and improving the adjustment of CRT configuration through flow ratios [61], perfusion models [17], lumped models of the whole cardiovascular circulation [18] or with a complete torso [20].…”

“…The interested reader is referred to Niederer et al [15] and Lee et al [16] for comprehensive reviews on computational models in cardiology and specific to LBBB and CRT, respectively. More recently, some studies have focused on CRT response optimization through electromechanical models including coronary perfusion [17], or myocardial strains with a complete cardiovascular system, adding both atria as well as systemic and pulmonary circulations [18]. Other studies particularly investigate lead placement.…”