Cardiac mesh morphing method for finite element modeling of heart failure with preserved ejection fraction

Weissmann, Jonathan; Charles, Christopher J.; Richards, A. Mark; Yap, Choon Hwai; Marom, Gil

doi:10.1016/j.jmbbm.2021.104937

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…The corresponding healthy configurations used in this study for evaluation were reconstructed from cardiac magnetic resonance imaging (cMRI) scans and pressures data, taken before the induction process. For all scenarios, corresponding FE cardiac models were developed by morphing the mesh of the Living Heart Porcine model (LHPM) [ 38 , 39 ], while retaining mesh topology and scaled material properties, to represent a healthy tissue in the healthy models and myocardial stiffening in the HFpEF models [ 33 , 40 ].…”

Section: Methodsmentioning

confidence: 99%

A numerical study of a left ventricular expander for heart failure with preserved ejection fraction

Weissmann,

Benoliel,

Yap

et al. 2023

R. Soc. open sci.

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Increased cardiac stiffness hinders proper left ventricular (LV) expansion, resulting in decreased volume and diastolic dysfunction. LV expanders are spring-like devices designed to improve diastolic function by facilitating mechanical outward expansion. Implantations in animals and humans have shown promising results, yet further evaluation is needed to assess a range of functions and the risk of use. In this computational study, the effectiveness and potential use of a generic LV expander were assessed by using previously generated finite-element models of induced heart failure with preserved ejection fraction (HFpEF). Following implantation, the treated models were compared to the corresponding untreated and healthy pre-induction models. The influence of device orientation and its material properties was also examined. Our results demonstrated a reduction in LV pressure and a volumetric improvement. Computed LV stresses have shown no gross irregularities. The device contributed to stress elevation during diastole while having a minor effect during systole, supporting a basic safety profile. This is the first study to use numerical analysis to assess LV expanders' performance on different HFpEF phenotypes. Improvement in heart function was demonstrated in both subjects, suggesting its potential use in various HFpEF manifestations, yet customization and optimal deployment are essential to improve heart performance.

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Section: Methodsmentioning

confidence: 99%

A numerical study of a left ventricular expander for heart failure with preserved ejection fraction

Weissmann,

Benoliel,

Yap

et al. 2023

R. Soc. open sci.

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“…For each pig model, the geometries of normal and HFpEF anatomies were reconstructed based on recordings before and after HF induction. The recordings were segmented at end diastole and were followed by smoothing with volume preservation (Weissmann et al, 2021). The living heart porcine model (LHPM; Simulia, Dassault Systèmes, Providence, RI, United States) (Baillargeon et al, 2014(Baillargeon et al, , 2017SIMULIA, 2016) was morphed based on the reconstructed geometries, using Abaqus solver (Simulia, Dassault Systèmes), to generate multiple FE models.…”

Section: Geometrical Modelingmentioning

confidence: 99%

“…The living heart porcine model (LHPM; Simulia, Dassault Systèmes, Providence, RI, United States) (Baillargeon et al, 2014(Baillargeon et al, , 2017SIMULIA, 2016) was morphed based on the reconstructed geometries, using Abaqus solver (Simulia, Dassault Systèmes), to generate multiple FE models. A detailed description of the algorithm can be found in our published work (Weissmann et al, 2021).…”

Section: Geometrical Modelingmentioning

confidence: 99%

“…The LHPM was used as a baseline mesh, and was morphed to generate cardiac models matching those of our animal models, both before and after induction of HFpEF. A previously developed mesh-morphing algorithm was used for this, which can accurately match imaged wall and septal thicknesses, and has the advantage of preserving fine structural details captured in the baseline mesh (Crick et al, 1998;Weissmann et al, 2021). For each model, long-and shortaxis cross sections in the initial healthy configuration and the post induction HF configuration are presented in Figure 3.…”

Section: Model Geometrymentioning

confidence: 99%

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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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“…This limits the spatiotemporal resolution of clinically available cardiac MR images in this young population. Deducing detailed three-dimensional models from these images is often time consuming and inconsistent [21]. Shape morphing can be an interesting technique to overcome some of these challenges.…”

Section: Introductionmentioning

confidence: 99%

Shape Morphing and Slice Shift Correction in Congenital Heart Defect Model Generation

Pentenga,

Stroh,

van Genuchten

et al. 2023

Lecture Notes in Computer Science

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Computational heart modeling is a promising approach for improving the prognosis of patients born with congenital heart defects. To create accurate physics-based digital cardiac twins of this population, it is crucial to accurately represent the highly diverse and unique subjectspecific heart geometry. In young pediatric patients, this is a challenging endeavor given the lack of high-spatial-resolution imaging data and the risk of slice misalignment. In this study, we set up a multistep shape morphing and slice correction approach to accommodate these challenges and establish a population of biventricular heart models for a variety of healthy, Fallot, and Fontan pediatric patients.

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Cardiac mesh morphing method for finite element modeling of heart failure with preserved ejection fraction

Cited by 7 publications

References 24 publications

A numerical study of a left ventricular expander for heart failure with preserved ejection fraction

A numerical study of a left ventricular expander for heart failure with preserved ejection fraction

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

Shape Morphing and Slice Shift Correction in Congenital Heart Defect Model Generation

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