Patient-specific finite element analysis of heart failure and the impact of surgical intervention in pulmonary hypertension secondary to mitral valve disease

Heidari, Alireza; Elkhodary, Khalil I.; Pop, Cristina; Badran, Mohamed; Vali, Hojatollah; Abdel-Raouf, Yousof M A; Torbati, Saeed; Asgharian, Masoud; Steele, Russell; Kani, Iradj Mahmoudzadeh; Sheibani, Sara; Pouraliakbar, Hamidreza; Sadeghian, Hakimeh; Cecere, Renzo; Friedrich, Matthias G.; Tafti, Hossein Ahmadi

doi:10.1007/s11517-022-02556-6

Cited by 12 publications

(8 citation statements)

References 64 publications

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“…The computational cardiac biomechanics model was adapted from the Living Heart Human Project (version 2.1, Simulia, Dassault Systèmes) ( Baillargeon et al, 2014 ), previously used for biomechanical simulation studies by ( Genet et al, 2014 ; Sack et al, 2016a , b ; Genet et al, 2016 ; Sack et al, 2018b , a ; Peirlinck et al, 2018 ; Dabiri et al, 2018 ; Sahli Costabal et al, 2019 ; Dabiri et al, 2019b , a ; Peirlinck et al, 2021 ; Guan et al, 2020 ; Sack et al, 2020 ; Dabiri et al, 2020 ; Wisneski et al, 2020 ; Heidari et al, 2022 ; St. Pierre et al, 2022 ). The dynamic problem was solved in Abaqus 2020 (Simulia, Dassault Systèmes) using meshes of the LV with 160,000 linear tetrahedral elements with an average edge length of 1.8 ± 0.5 mm.…”

Section: Methodsmentioning

confidence: 99%

Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods

et al. 2022

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Simulations of cardiac electrophysiology and mechanics have been reported to be sensitive to the microstructural anisotropy of the myocardium. Consequently, a personalized representation of cardiac microstructure is a crucial component of accurate, personalized cardiac biomechanical models. In-vivo cardiac Diffusion Tensor Imaging (cDTI) is a non-invasive magnetic resonance imaging technique capable of probing the heart’s microstructure. Being a rather novel technique, issues such as low resolution, signal-to noise ratio, and spatial coverage are currently limiting factors. We outline four interpolation techniques with varying degrees of data fidelity, different amounts of smoothing strength, and varying representation error to bridge the gap between the sparse in-vivo data and the model, requiring a 3D representation of microstructure across the myocardium. We provide a workflow to incorporate in-vivo myofiber orientation into a left ventricular model and demonstrate that personalized modelling based on fiber orientations from in-vivo cDTI data is feasible. The interpolation error is correlated with a trend in personalized parameters and simulated physiological parameters, strains, and ventricular twist. This trend in simulation results is consistent across material parameter settings and therefore corresponds to a bias introduced by the interpolation method. This study suggests that using a tensor interpolation approach to personalize microstructure with in-vivo cDTI data, reduces the fiber uncertainty and thereby the bias in the simulation results.

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Section: Methodsmentioning

confidence: 99%

Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods

et al. 2022

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“…The material parameters (a, b, a f , b f , a s , b s , a fs , b fs ) were calibrated for the subject-specific anatomies and produced appropriate results for all models, as previously reported in the literature (Göktepe et al, 2011;Wang et al, 2013;Nikou et al, 2015;Genet et al, 2016;Dabiri et al, 2018;Peirlinck et al, 2019;Heidari et al, 2022). Table 4 lists the values of the eight calibrated passive material parameters for the two cases.…”

Section: Materials Parameter Estimationmentioning

confidence: 99%

Material property alterations for phenotypes of heart failure with preserved ejection fraction: A numerical study of subject-specific porcine models

Weissmann

Charles

Richards

et al. 2022

Front. Bioeng. Biotechnol.

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A substantial proportion of heart failure patients have a preserved left ventricular (LV) ejection fraction (HFpEF). This condition carries a high burden of morbidity and mortality and has limited therapeutic options. left ventricular pressure overload leads to an increase in myocardial collagen content, causing left ventricular stiffening that contributes to the development of heart failure patients have a preserved left ventricular ejection fraction. Although several heart failure patients have a preserved left ventricular ejection fraction models have been developed in recent years to aid the investigation of mechanical alterations, none has investigated different phenotypes of the disease and evaluated the alterations in material properties. In this study, two similar healthy swine were subjected to progressive and prolonged pressure overload to induce diastolic heart failure characteristics, providing a preclinical model of heart failure patients have a preserved left ventricular ejection fraction. Cardiac magnetic resonance imaging (cMRI) scans and intracardiac pressures were recorded before and after induction. In both healthy and disease states, a corresponding finite element (FE) cardiac model was developed via mesh morphing of the Living Heart Porcine model. The material properties were derived by calibrating to its passive and active behavior. The change in the passive behavior was predominantly isotropic when comparing the geometries before and after induction. Myocardial thickening allowed for a steady transition in the passive properties while maintaining tissue incompressibility. This study highlights the importance of hypertrophy as an initial compensatory response and might also pave the way for assessing disease severity.

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“…A dynamic high-fidelity Multiphysics model of a four-chamber adult male human heart ( Figure 1 ) (Baillargeon et al 2014), developed under the SIMULIA Living Heart Project (Dassault Systèmes, SIMULIA Corp.) has previously been used to study various cardiovascular diseases (Wisneski et al 2020; St Pierre, Peirlinck, and Kuhl 2022) including heart failure (Genet et al 2016; Costabal, Choy, et al 2019), arrhythmia (Sahli Costabal, Yao, and Kuhl 2018), effects of drug on treating these diseases (Costabal, Matsuno, et al 2019), and performance analysis of several cardiovascular procedures including TAVR (Ghosh et al 2020b), mitral valve repair (Galili, White Zeira, and Marom 2022; Heidari et al 2022; Pasta et al 2022), and left ventricular assistance device (Pasta et al 2022). In this study, this digital twin of the human heart was used to explore the interaction between the TAVR prosthesis and the conduction fibers both during the TAVR procedure and across three cardiac cycles subsequent to the procedure, in order to gain deeper insights into the mechanisms underlying the development of new conduction abnormalities at varying implantation depths and in the presence of pre-existing CCAs.…”

Section: Introductionmentioning

confidence: 99%

Assessing Post-TAVR Cardiac Conduction Abnormalities Risk Using a Digital Twin of a Beating Heart

Reza,

Kovarovic,

Bluestein

2024

Preprint

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Transcatheter aortic valve replacement (TAVR) has rapidly displaced surgical aortic valve replacement (SAVR). However, certain post-TAVR complications persist, with cardiac conduction abnormalities (CCA) being one of the major ones. The elevated pressure exerted by the TAVR stent onto the conduction fibers situated between the aortic annulus and the His bundle, in proximity to the atrioventricular (AV) node, may disrupt the cardiac conduction leading to the emergence of CCA. In his study, an in-silico framework was developed to assess the CCA risk, incorporating the effect of a dynamic beating heart and pre-procedural parameters such as implantation depth and preexisting cardiac asynchrony in the new onset of post-TAVR CCA. A self-expandable TAVR device deployment was simulated inside an electro-mechanically coupled beating heart model in five patient scenarios, including three implantation depths, and two preexisting cardiac asynchronies: (i) a right bundle branch block (RBBB) and (ii) a left bundle branch block (LBBB). Subsequently, several biomechanical parameters were analyzed to assess the post-TAVR CCA risk. The results manifested a lower cumulative contact pressure on the conduction fibers following TAVR for aortic deployment (0.018 MPa) compared to baseline (0.29 MPa) and ventricular deployment (0.52 MPa). Notably, the preexisting RBBB demonstrated a higher cumulative contact pressure (0.34 MPa) compared to the baseline and preexisting LBBB (0.25 MPa). Deeper implantation and preexisting RBBB cause higher stresses and contact pressure on the conduction fibers leading to an increased risk of post-TAVR CCA. Conversely, implantation above the MS landmark and preexisting LBBB reduces the risk.

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Patient-specific finite element analysis of heart failure and the impact of surgical intervention in pulmonary hypertension secondary to mitral valve disease

Cited by 12 publications

References 64 publications

Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods

Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods

Material property alterations for phenotypes of heart failure with preserved ejection fraction: A numerical study of subject-specific porcine models

Assessing Post-TAVR Cardiac Conduction Abnormalities Risk Using a Digital Twin of a Beating Heart

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