Optimization of cardiac resynchronization therapy based on a cardiac electromechanics-perfusion computational model

Fan, Lei; Choy, Jenny S.; Raissi, Farshad; Kassab, Ghassan S.; Lee, Lik Chuan

doi:10.1016/j.compbiomed.2021.105050

Cited by 10 publications

(11 citation statements)

References 83 publications

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“…Fourth, we assumed homogeneous contraction and did not consider electrophysiology in the model because the key goal here is to investigate the isolated effects of myofiber disarray and geometry on ventricular mechanics in HCM patients. Nevertheless, arrythmia and mechanical dyssynchrony can be present in HCM patients 82 and previous computer models 45,83 have shown that mechanical dyssynchrony (without myofiber disarray and geometrical remodeling) worsens the cardiac function (i.e., reduce LV pressure and stroke volume). Correspondingly, we expect the presence of mechanical dyssynchrony to exacerbate the adverse effects of myofiber disarray and ventricular geometrical remodeling in HCM as found here.…”

Section: Limitationmentioning

confidence: 98%

“…Correspondingly, we expect the presence of mechanical dyssynchrony to exacerbate the adverse effects of myofiber disarray and ventricular geometrical remodeling in HCM as found here. Future studies can apply computer models coupling cardiac electrophysiology and mechanics 44,45,84,85 to investigate the combined effects of mechanical dyssynchrony, geometrical remodeling and myofiber disarray. Fifth, beside asymmetric hypertrophy of the LV wall, HCM is also associated with abnormal mitral valve morphology and function (i.e., systolic anterior motion, SAM) that can contribute to obstruction of LVOT and mitral valve regurgitation [83][84][85] .…”

Section: Limitationmentioning

confidence: 99%

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Computational analysis of ventricular mechanics in hypertrophic cardiomyopathy patients

Mojumder

Fan

Nguyen

et al. 2023

Sci Rep

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Hypertrophic cardiomyopathy (HCM) is a genetic heart disease that is associated with many pathological features, such as a reduction in global longitudinal strain (GLS), myofiber disarray and hypertrophy. The effects of these features on left ventricle (LV) function are, however, not clear in two phenotypes of HCM, namely, obstructive and non-obstructive. To address this issue, we developed patient-specific computational models of the LV using clinical measurements from 2 female HCM patients and a control subject. Left ventricular mechanics was described using an active stress formulation and myofiber disarray was described using a structural tensor in the constitutive models. Unloaded LV configuration for each subject was first determined from their respective end-diastole LV geometries segmented from the cardiac magnetic resonance images, and an empirical single-beat estimation of the end-diastolic pressure volume relationship. The LV was then connected to a closed-loop circulatory model and calibrated using the clinically measured LV pressure and volume waveforms, peak GLS and blood pressure. Without consideration of myofiber disarray, peak myofiber tension was found to be lowest in the obstructive HCM subject (60 kPa), followed by the non-obstructive subject (242 kPa) and the control subject (375 kPa). With increasing myofiber disarray, we found that peak tension has to increase in the HCM models to match the clinical measurements. In the obstructive HCM patient, however, peak tension was still depressed (cf. normal subject) at the largest degree of myofiber disarray found in the clinic. The computational modeling workflow proposed here can be used in future studies with more HCM patient data.

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Section: Limitationmentioning

confidence: 98%

Section: Limitationmentioning

confidence: 99%

Computational analysis of ventricular mechanics in hypertrophic cardiomyopathy patients

Mojumder

Fan

Nguyen

et al. 2023

Sci Rep

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“…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].…”

Section: Limitations and Future Workmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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).

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“…Last, we assumed that homogeneous contraction of the heart in this study, and did not consider the presence of mechanical dyssynchrony that can occur in HCM [81]. Mechanical dyssynchrony can be considered in future studies using an electromechanics model [44], [45].…”

Section: Limitationmentioning

confidence: 99%

Computational Analysis of Ventricular Mechanics in Hypertrophic Cardiomyopathy Patients

Mojumder

Fan

Nguyen

et al. 2022

Preprint

Self Cite

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Hypertrophic cardiomyopathy (HCM) is a genetic heart disease that is associated with many pathological features, such as a reduction in global longitudinal strain (GLS), myofiber disarray and hypertrophy. The effects of these features on left ventricle (LV) function are, however, not clear in two phenotypes of HCM, namely, obstructive and non-obstructive. To address this issue, we developed patient specific computational models of the LV using clinical measurements of 2 female HCM patients and a control subject. Left ventricular mechanics was described using an active stress formulation and myofiber disarray was described using a structural tensor in the constitutive models. Unloaded LV configuration for each subject was first determined from their respective end-diastole LV geometries segmented from the cardiac magnetic resonance images, and an empirical single-beat estimation of the end-diastolic pressure volume relationship. The LV was then connected to a closed-loop circulatory model and calibrated using the clinically measured LV pressure and volume waveforms, peak GLS and blood pressure. Without consideration of myofiber disarray, peak myofiber tension was found to be lowest in the obstructive HCM subject (60 kPa), followed by the non-obstructive subject (242 kPa) and the control subject (375 kPa). With increasing myofiber disarray, we found that peak tension has to increase in the HCM models to match the clinical measurements. In the obstructive HCM patient, however, peak tension is still depressed (cf. normal subject) at the largest degree of myofiber disarray found in the clinic. The computational modeling workflow proposed here can be used in future studies with more HCM patient data.

show abstract

Optimization of cardiac resynchronization therapy based on a cardiac electromechanics-perfusion computational model

Cited by 10 publications

References 83 publications

Computational analysis of ventricular mechanics in hypertrophic cardiomyopathy patients

Computational analysis of ventricular mechanics in hypertrophic cardiomyopathy patients

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

Computational Analysis of Ventricular Mechanics in Hypertrophic Cardiomyopathy Patients

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