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

Assessment of myocardial strain patterns in patients with left bundle branch block using cardiac magnetic resonance

Recently, a classification with four types of septal longitudinal strain patterns was described using echocardiography, suggesting a pathophysiological continuum of left bundle branch block (LBBB)-induced left ventricle (LV) remodeling. The aim of this study was to assess the feasibility of classifying these strain patterns using cardiovascular magnetic resonance (CMR), and to evaluate their association with LV remodeling and myocardial scar. Single center registry included LBBB patients with septal flash (SF) referred to CMR to assess the cause of LV systolic dysfunction. Semi-automated feature-tracking cardiac resonance (FT-CMR) was used to quantify myocardial strain and detect the four strain patterns. A total of 115 patients were studied (age 66 ± 11 years, 57% men, 28% with ischemic heart disease). In longitudinal strain analysis, 23 patients (20%) were classified in stage LBBB-1, 37 (32.1%) in LBBB-2, 25 (21.7%) in LBBB-3, and 30 (26%) in LBBB-4. Patients at higher stages had more prominent septal flash, higher LV volumes, lower LV ejection fraction, and lower absolute strain values (p < 0.05 for all). Late gadolinium enhancement (LGE) was found in 55% of the patients (n = 63). No differences were found between the strain patterns regarding the presence, distribution or location of LGE. Among patients with LBBB, there was a good association between strain patterns assessed by FT-CMR analysis and the degree of LV remodeling and LV dysfunction. This association seems to be independent from the presence and distribution of LGE.

The saga of dyssynchrony imaging: Are we getting to the point

Cardiac resynchronisation therapy (CRT) has an established role in the management of patients with heart failure, reduced left ventricular ejection fraction (LVEF &lt; 35%) and widened QRS (&gt;130 msec). Despite the complex pathophysiology of left ventricular (LV) dyssynchrony and the increasing evidence supporting the identification of specific electromechanical substrates that are associated with a higher probability of CRT response, the assessment of LVEF is the only imaging-derived parameter used for the selection of CRT candidates.

This review aims to (1) provide an overview of the evolution of cardiac imaging for the assessment of LV dyssynchrony and its role in the selection of patients undergoing CRT; (2) highlight the main pitfalls and advantages of the application of cardiac imaging for the assessment of LV dyssynchrony; (3) provide some perspectives for clinical application and future research in this field.

Conclusion

the road for a more individualized approach to resynchronization therapy delivery is open and imaging might provide important input beyond the assessment of LVEF.

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

Computational models of cardiac electrophysiology are promising tools for reducing the rates of non-response patients suitable for cardiac resynchronization therapy (CRT) by optimizing electrode placement. The majority of computational models in the literature are mesh-based, primarily using the finite element method (FEM). The generation of patient-specific cardiac meshes has traditionally been a tedious task requiring manual intervention and hindering the modeling of a large number of cases. Meshless models can be a valid alternative due to their mesh quality independence. The organization of challenges such as the CRT-EPiggy19, providing unique experimental data as open access, enables benchmarking analysis of different cardiac computational modeling solutions with quantitative metrics. We present a benchmark analysis of a meshless-based method with finite-element methods for the prediction of cardiac electrical patterns in CRT, based on a subset of the CRT-EPiggy19 dataset. A data assimilation strategy was designed to personalize the most relevant parameters of the electrophysiological simulations and identify the optimal CRT lead configuration. The simulation results obtained with the meshless model were equivalent to FEM, with the most relevant aspect for accurate CRT predictions being the parameter personalization strategy (e.g., regional conduction velocity distribution, including the Purkinje system and CRT lead distribution).