Simulated transcatheter aortic valve deformation: A parametric study on the impact of leaflet geometry on valve peak stress

A review of polymeric heart valves leaflet geometric configuration and structural optimization

Valvular heart disease (VHD) is a major cause of loss of physical function, quality of life and longevity, and its prevalence is growing worldwide due to increased survival rates and an aging population. The most common treatment for VHD is surgical heart valve replacement with mechanical heart valves (MHVs) and bioprosthetic heart valves (BHVs), but with different limitations. Polymeric heart valves (PHVs) exhibit promising material properties, valve dynamics and biocompatibility, representing the most feasible alternative to existing artificial heart valves. However, inadequate fatigue performance remains a critical obstacle to their clinical translation. In this case, geometry and material design are essential to obtain the best mechanical properties of the PHV. In this study, we summarized the effects of optimal design of PHVs from geometrical configuration optimization (valve height, thickness and design curve) and structural material optimization (anisotropy, fiber reinforcement, variable thickness, microstructure and asymmetric optimization), and selected the parameters including Effective Orifice Area (EOA), Regurgitant fraction (RF), and Stress Distribution to compare the performance of valves. It would provide the theoretical support for the optimal design of PHVs.

Cardiac valve scaffold design: Implications of material properties and geometric configuration on performance and mechanics

Development of tissue engineered scaffolds for cardiac valve replacement is nearing clinical translation. While much work has been done to characterize mechanical behavior of native and bioprosthetic valves, and incorporate those data into models improving valve design, similar work for degradable valve scaffolds is lacking. This is particularly important given the implications mechanics have on short-term survival and long-term remodeling. As such, this study aimed to characterize spatially-resolved strain profiles on the leaflets of degradable polymeric valve scaffolds, manipulating common design features such as material stiffness by blending poly(carbonate urethane)urea with stiffer polymers, and geometric configuration, modeled after either a clinically-used valve design (Mk1 design) or an anatomically "optimized" design (Mk2 design). It was shown that material stiffness plays a significant role in overall valve performance, with the stiffest valve groups showing asymmetric and incomplete opening during systole. However, the geometric configuration had a significantly greater effect on valve performance as well as strain magnitude and distribution. Major findings in the strain maps included systolic strains having overall higher strain magnitudes than diastole, and peak radial-direction strain concentrations in the base region of Mk1 valves during systole, with a significant mitigation of radial strain in Mk2 valves. The high tunability of tissue engineered scaffolds is a great advantage for valve design, and the results reported here indicate that design parameters have significant and unequal impact on valve performance and mechanics.

Perfect prosthetic heart valve: generative design with machine learning, modeling, and optimization

Majority of modern techniques for creating and optimizing the geometry of medical devices are based on a combination of computer-aided designs and the utility of the finite element method This approach, however, is limited by the number of geometries that can be investigated and by the time required for design optimization. To address this issue, we propose a generative design approach that combines machine learning (ML) methods and optimization algorithms. We evaluate eight different machine learning methods, including decision tree-based and boosting algorithms, neural networks, and ensembles. For optimal design, we investigate six state-of-the-art optimization algorithms, including Random Search, Tree-structured Parzen Estimator, CMA-ES-based algorithm, Nondominated Sorting Genetic Algorithm, Multiobjective Tree-structured Parzen Estimator, and Quasi-Monte Carlo Algorithm. In our study, we apply the proposed approach to study the generative design of a prosthetic heart valve (PHV). The design constraints of the prosthetic heart valve, including spatial requirements, materials, and manufacturing methods, are used as inputs, and the proposed approach produces a final design and a corresponding score to determine if the design is effective. Extensive testing leads to the conclusion that utilizing a combination of ensemble methods in conjunction with a Tree-structured Parzen Estimator or a Nondominated Sorting Genetic Algorithm is the most effective method in generating new designs with a relatively low error rate. Specifically, the Mean Absolute Percentage Error was found to be 11.8% and 10.2% for lumen and peak stress prediction respectively. Furthermore, it was observed that both optimization techniques result in design scores of approximately 95%. From both a scientific and applied perspective, this approach aims to select the most efficient geometry with given input parameters, which can then be prototyped and used for subsequent in vitro experiments. By proposing this approach, we believe it will replace or complement CAD-FEM-based modeling, thereby accelerating the design process and finding better designs within given constraints. The repository, which contains the essential components of the study, including curated source code, dataset, and trained models, is publicly available at https://github.com/ViacheslavDanilov/generative_design.

Effects of leaflet curvature and thickness on the crimping stresses in transcatheter heart valve

With the current advances and expertise in biomedical device technologies, transcatheter heart valves (THVs) have been drawing significant attention. Various studies have been carried out on their durability and damage by dynamic loading in operational conditions. However, very few numerical investigations have been conducted to understand the effects of leaflet curvature and thickness on the crimping stresses which arise during the surgical preparation processes. In order to contribute to the current state of the art, a full heart valve model was presented, the leaflet curvature and thickness of which were then parameterized so as to understand the stress generation as a result of the crimping procedure during the surgical preparations. The results show that the existence of stresses is inevitable during the crimping procedure, which is a reduction factor for valve durability. Especially, stresses on the leaflets at the suture sites connected with the skirt were deduced to be critical and may result in leaflet ruptures after THV implantation.

A review of numerical simulation in transcatheter aortic valve replacement decision optimization

BACKGROUND

Recent trials indicated a further expansion of clinical indication of transcatheter aortic valve replacement to younger and low-risk patients. Factors related to longer-term complications are becoming more important for use in these patients. Accumulating evidence indicates that numerical simulation plays a significant role in improving the outcome of transcatheter aortic valve replacement. Understanding mechanical features' magnitude, pattern, and duration is a topic of ongoing relevance.

METHODS

We searched the PubMed database using keywords such as "transcatheter aortic valve replacement" and "numerical simulation" and reviewed and summarized relevant literature.

FINDINGS

This review integrated recently published evidence into three subtopics: 1) prediction of transcatheter aortic valve replacement outcomes through numerical simulation, 2) implications for surgeons, and 3) trends in transcatheter aortic valve replacement numerical simulation.

INTERPRETATIONS

Our study offers a comprehensive overview of the utilization of numerical simulation in the context of transcatheter aortic valve replacement, and highlights the advantages, potential challenges from a clinical standpoint. The convergence of medicine and engineering plays a pivotal role in enhancing the outcomes of transcatheter aortic valve replacement. Numerical simulation has provided evidence of potential utility for tailored treatments.

A Doppler-exclusive non-invasive computational diagnostic framework for personalized transcatheter aortic valve replacement

Given the associated risks with transcatheter aortic valve replacement (TAVR), it is crucial to determine how the implant will affect the valve dynamics and cardiac function, and if TAVR will improve or worsen the outcome of the patient. Effective treatment strategies, indeed, rely heavily on the complete understanding of the valve dynamics. We developed an innovative Doppler-exclusive non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics in patients with aortic stenosis in both pre- and post-TAVR status. Clinical Doppler pressure was reduced by TAVR (52.2 ± 20.4 vs. 17.3 ± 13.8 [mmHg], p < 0.001), but it was not always accompanied by improvements in valve dynamics and left ventricle (LV) hemodynamics metrics. TAVR had no effect on LV workload in 4 patients, and LV workload post-TAVR significantly rose in 4 other patients. Despite the group level improvements in maximum LV pressure (166.4 ± 32.2 vs 131.4 ± 16.9 [mmHg], p < 0.05), only 5 of the 12 patients (41%) had a decrease in LV pressure. Moreover, TAVR did not always improve valve dynamics. TAVR did not necessarily result in a decrease (in 9 out of 12 patients investigated in this study) in major principal stress on the aortic valve leaflets which is one of the main contributors in valve degeneration and, consequently, failure of heart valves. Diastolic stresses increased significantly post-TAVR (34%, 109% and 81%, p < 0.001) for each left, right and non-coronary leaflets respectively. Moreover, we quantified the stiffness and material properties of aortic valve leaflets which correspond with the reduced calcified region average stiffness among leaflets (66%, 74% and 62%; p < 0.001; N = 12). Valve dynamics post-intervention should be quantified and monitored to ensure the improvement of patient conditions and prevent any further complications. Improper evaluation of biomechanical valve features pre-intervention as well as post-intervention may result in harmful effects post-TAVR in patients including paravalvular leaks, valve degeneration, failure of TAVR and heart failure.

An ultrasound-exclusive non-invasive computational diagnostic framework for personalized cardiology of aortic valve stenosis

Aortic stenosis (AS) is an acute and chronic cardiovascular disease and If left untreated, 50% of these patients will die within two years of developing symptoms. AS is characterized as the stiffening of the aortic valve leaflets which restricts their motion and prevents the proper opening under transvalvular pressure. Assessments of the valve dynamics, if available, would provide valuable information about the patient's state of cardiac deterioration as well as heart recovery and can have incredible impacts on patient care, planning interventions and making critical clinical decisions with life-threatening risks. Despite remarkable advancements in medical imaging, there are no clinical tools available to quantify valve dynamics invasively or noninvasively. In this study, we developed a highly innovative ultrasound-based non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics (e.g. transient 3-D distribution of stress and displacement, 3-D deformed shape of leaflets, geometric orifice area and angular positions of leaflets) for patients with AS at no risk to the patients. Such a diagnostic tool considers the local valve dynamics and the global circulatory system to provide a platform for testing the intervention scenarios and evaluating their effects. We used clinical data of 12 patients with AS not only to validate the proposed framework but also to demonstrate its diagnostic abilities by providing novel analyses and interpretations of clinical data in both pre and post intervention states. We used transthoracic echocardiogram (TTE) data for the developments and transesophageal echocardiography (TEE) data for validation.

Application of compression optical coherence elastography for characterization of human pericardium: A pilot study

The recent impressive progress in Compression Optical Coherence Elastography (C-OCE) demonstrated diverse biomedical applications, comprising ophthalmology, oncology, etc. High resolution of C-OCE enables spatially resolved characterization of elasticity of rather thin (thickness < 1 mm) samples, which previously was impossible. Besides Young's modulus, C-OCE enables obtaining of nonlinear stress-strain dependences for various tissues. Here, we report the first application of C-OCE to nondestructively characterize biomechanics of human pericardium, for which data of conventional tensile tests are very limited and controversial. C-OCE revealed pronounced differences among differently prepared pericardium samples. Ample understanding of the influence of chemo-mechanical treatment on pericardium biomechanics is very important because of rapidly growing usage of own patients' pericardium for replacement of aortic valve leaflets in cardio-surgery. The figure demonstrates differences in the tangent Young's modulus after glutaraldehyde-induced cross-linking for two pericardium samples. One sample was over-stretched during the preparation, which caused some damage to the tissue.

Design consideration of a novel polymeric transcatheter heart valve through computational modeling

Transcatheter heart valve replacement is becoming a more routine procedure, and this is further supported by positive outcomes from studies involving low-risk patients. Nevertheless, the lack of long-term transcatheter heart valve (TAV) durability is still one of the primary concerns. As a result, more research has been focused on improving durability through various methods such as valve design, computational modeling, and material selection. Recent advancements in polymeric valve fabrication showed that linear low-density polyethylene (LLDPE) could be used as leaflet material for transcatheter heart valves. In this paper, a parametric study of computational simulations showed stress distribution on the leaflets of LLDPE-TAV under diastolic load, and the results were used to improve the stent design. The in silico experiment also tested the effect of shock absorbers in terms of valve durability. The results demonstrated that altering specific stent angles can significantly lower peak stress on the leaflets (13.8 vs. 6.07 MPa). Implementing two layers of shock absorbers further reduces the stress value to 4.28 MPa. The pinwheeling index was assessed, which seems to correlate with peak stress. Overall, the parametric study and the computational method can be used to analyze and improve valve durability.

In silico modelling of aortic valve implants - predicting in vitro performance using finite element analysis

The competing structural and hemodynamic considerations in valve design generally require a large amount of in vitro hydrodynamic and durability testing during development, often resulting in inefficient "trial-and-error" prototyping. While in silico modelling through finite element analysis (FEA) has been widely used to inform valve design by optimising structural performance, few studies have exploited the potential insight FEA could provide into critical hemodynamic performance characteristics of the valve. The objective of this study is to demonstrate the potential of FEA to predict the hydrodynamic performance of tri-leaflet aortic valve implants obtained during development through in vitro testing. Several variations of tri-leaflet aortic valves were designed and manufactured using a synthetic polymer and hydrodynamic testing carried out using a pulsatile flow rig according to ISO 5840, with bulk hydrodynamic parameters measured. In silico models were developed in tandem and suitable surrogate measures were investigated as predictors of the hydrodynamic parameters. Through regression analysis, the in silico parameters of leaflet coaptation area, geometric orifice area and opening pressure were found to be suitable indicators of experimental in vitro hydrodynamic parameters: regurgitant fraction, effective orifice area and transvalvular pressure drop performance, respectively.

Local and global growth and remodeling in calcific aortic valve disease and aging

Aging and calcific aortic valve disease (CAVD) are the main factors leading to aortic stenosis. Both processes are accompanied by growth and remodeling pathways that play a crucial role in aortic valve pathophysiology. Herein, a computational growth and remodeling (G&R) framework was developed to investigate the effects of aging and calcification on aortic valve dynamics. Particularly, an algorithm was developed to couple the global growth and stiffening of the aortic valve due to aging and the local growth and stiffening due to calcification with the aortic valve transient dynamics. The aortic valve dynamics during baseline were validated with available data in the literature. Subsequently, the changes in aortic valve dynamic patterns during aging and CAVD progression were studied. The results revealed the patterns in geometric orifice area reduction and an increase in the valve stress during local and global growth and remodeling of the aortic valve. The proposed algorithm provides a framework to couple mechanobiology models of disease growth with tissue-scale transient structural mechanics models to study the biomechanical changes during cardiovascular disease growth and aging.

Parameterization, geometric modeling, and isogeometric analysis of tricuspid valves

Approximately 1.6 million patients in the United States are affected by tricuspid valve regurgitation, which occurs when the tricuspid valve does not close properly to prevent backward blood flow into the right atrium. Despite its critical role in proper cardiac function, the tricuspid valve has received limited research attention compared to the mitral and aortic valves on the left side of the heart. As a result, proper valvular function and the pathologies that may cause dysfunction remain poorly understood. To promote further investigations of the biomechanical behavior and response of the tricuspid valve, this work establishes a parameter-based approach that provides a template for tricuspid valve modeling and simulation. The proposed tricuspid valve parameterization presents a comprehensive description of the leaflets and the complex chordae tendineae for capturing the typical three-cusp structural deformation observed from medical data. This simulation framework develops a practical procedure for modeling tricuspid valves and offers a robust, flexible approach to analyze the performance and effectiveness of various valve configurations using isogeometric analysis. The proposed methods also establish a baseline to examine the tricuspid valve's structural deformation, perform future investigations of native valve configurations under healthy and disease conditions, and optimize prosthetic valve designs.

Biomechanical Identification of High-Risk Patients Requiring Permanent Pacemaker After Transcatheter Aortic Valve Replacement

BACKGROUND

Cardiac conduction disturbance requiring new permanent pacemaker implantation (PPI) is an important complication of TAVR that has been associated with increased mortality. It is extremely challenging to optimize the valve size alone to prevent a complete atrioventricular block (AVB).

METHODS

In this study, we randomly took 48 patients who underwent TAVR and had been followed for at least 2 years to assess the risk of AVB. CT images of 48 patients with TAVR were analyzed using three-dimensional (3D) anatomical models of the aortic valve apparatus. The stresses were formulated according to loading force and tissue properties. Support vector regression (SVR) was used to model the relationship between AVB risk and biomechanical stresses. To avoid AVB, overlapping regions on the prosthetic valve where AV bundle passes will be removed as cylindrical sector with the angle θ. Thus, the optimization of the valve shape will be predicted with the joint optimization of the θ and valve size R.

RESULTS

The average AVB risk prediction accuracy was 83.33% in the range from 0.8-0.85 with 95% CI for all cases; specifically, 85.71% for Group A (no AVB), and 80.0% for Group B (undergoing AVB after the TAVR).

CONCLUSIONS

This model can estimate the optimal valve size and shape to avoid the risk of AVB after TAVR. This optimization may eliminate the excessive stresses to keep the normal function of both AV bundle and valve leaflets, leading to a favorable clinical outcome. The combination of biomechanical properties and machine learning method substantially improved prediction of surgical results.

Combining statistical shape modeling, CFD, and meta-modeling to approximate the patient-specific pressure-drop across the aortic valve in real-time

BACKGROUND

Advances in medical imaging, segmentation techniques, and high performance computing have stimulated the use of complex, patient-specific, three-dimensional Computational Fluid Dynamics (CFD) simulations. Patient-specific, CFD-compatible geometries of the aortic valve are readily obtained. CFD can then be used to obtain the patient-specific pressure-flow relationship of the aortic valve. However, such CFD simulations are computationally expensive, and real-time alternatives are desired.

AIM

The aim of this work is to evaluate the performance of a meta-model with respect to high-fidelity, three-dimensional CFD simulations of the aortic valve.

METHODS

Principal component analysis was used to build a statistical shape model (SSM) from a population of 74 iso-topological meshes of the aortic valve. Synthetic meshes were created with the SSM, and steady-state CFD simulations at flow-rates between 50 and 650 mL/s were performed to build a meta-model. The meta-model related the statistical shape variance, and flow-rate to the pressure-drop.

RESULTS

Even though the first three shape modes account for only 46% of shape variance, the features relevant for the pressure-drop seem to be captured. The three-mode shape-model approximates the pressure-drop with an average error of 8.8% to 10.6% for aortic valves with a geometric orifice area below 150 mm² . The proposed methodology was least accurate for aortic valve areas above 150 mm² . Further reduction to a meta-model introduces an additional 3% error.

CONCLUSIONS

Statistical shape modeling can be used to capture shape variation of the aortic valve. Meta-models trained by SSM-based CFD simulations can provide an estimate of the pressure-flow relationship in real-time.

In-vitro characterization of self-expandable textile transcatheter aortic valves

OBJECTIVE

This study aims at assessing the global dynamic behavior, closing energy and turbulence characteristics of self-expandable textile (inclined and straight yarn) transcatheter aortic valves (TAV) versus bioprosthetic TAVs.

METHODS

Two self-expandable textile TAVs one with inclined yarn textile and another with straight yarn textile leaflets were assessed in a pulse duplicator and compared with a self-expandable commercial bioprosthetic TAV under physiological pressure and flow. Particle Image Velocimetry and high-speed imaging were performed. Effective orifice areas (EOA), leakage fractions (LF), Pinwheeling indices (PI), closing energy (E), viscous shear stresses (VSS) and Reynolds shear stresses (RSS) were calculated.

RESULTS

(a) EOAs and LFs were 2.27 ± 0.03 cm2, 31.7 ± 0.6%; 2.25 ± 0.08 cm2, 26.6 ± 0.7%; and 1.63 ± 0.01 cm2, 29.1 ± 1.25% for inclined textile, bioprosthetic and straight textile TAV respectively (p < 0.0001). (b) Following same order, PIs were significantly different going from 1.16 ± 0.21%, 8.48 ± 0.8% and 8.865 ± 0.58% with the exception of CoreValve and straight yarn valve (p = 0.37); (c) E is lowest for straight textile TAV (0.0024 ± 0.0017 J), followed by bioprosthetic valve (0.00259 ± 0.0011 J) and then 45° Oriented Yarn Valve (0.00334 ± 0.03 J) (d) At peak systole, the highest RSS distribution was with the Straight textile TAV reaching up to 330Pa. The bioprosthetic TAV shows the smallest range with RSS reaching around 230Pa and the inclined textile TAV up to 280Pa. VSS limits were comparable among the 3 valves ranging between 5.2Pa and 5.7Pa.

CONCLUSION

Hemodynamic similarities were found between the textile self-expandable valves and the bioprosthetic valve. This study constitutes another step towards showing the potential that textile valves have to become an alternative for the biological ones.

A Deep Learning Framework for Design and Analysis of Surgical Bioprosthetic Heart Valves

Bioprosthetic heart valves (BHVs) are commonly used as heart valve replacements but they are prone to fatigue failure; estimating their remaining life directly from medical images is difficult. Analyzing the valve performance can provide better guidance for personalized valve design. However, such analyses are often computationally intensive. In this work, we introduce the concept of deep learning (DL) based finite element analysis (DLFEA) to learn the deformation biomechanics of bioprosthetic aortic valves directly from simulations. The proposed DL framework can eliminate the time-consuming biomechanics simulations, while predicting valve deformations with the same fidelity. We present statistical results that demonstrate the high performance of the DLFEA framework and the applicability of the framework to predict bioprosthetic aortic valve deformations. With further development, such a tool can provide fast decision support for designing surgical bioprosthetic aortic valves. Ultimately, this framework could be extended to other BHVs and improve patient care.

Mechanical considerations for polymeric heart valve development: Biomechanics, materials, design and manufacturing

The native human heart valve leaflet contains a layered microstructure comprising a hierarchical arrangement of collagen, elastin, proteoglycans and various cell types. Here, we review the various experimental methods that have been employed to probe this intricate microstructure and which attempt to elucidate the mechanisms that govern the leaflet's mechanical properties. These methods include uniaxial, biaxial, and flexural tests, coupled with microstructural characterization techniques such as small angle X-ray scattering (SAXS), small angle light scattering (SALS), and polarized light microscopy. These experiments have revealed complex elastic and viscoelastic mechanisms that are highly directional and dependent upon loading conditions and biochemistry. Of all engineering materials, polymers and polymer-based composites are best able to mimic the tissue-level mechanical behavior of the native leaflet. This similarity to native tissue permits the fabrication of polymeric valves with physiological flow patterns, reducing the risk of thrombosis compared to mechanical valves and in some cases surpassing the in vivo durability of bioprosthetic valves. Earlier work on polymeric valves simply assumed the mechanical properties of the polymer material to be linear elastic, while more recent studies have considered the full hyperelastic stress-strain response. These material models have been incorporated into computational models for the optimization of valve geometry, with the goal of minimizing internal stresses and improving durability. The latter portion of this review recounts these developments in polymeric heart valves, with a focus on mechanical testing of polymers, valve geometry, and manufacturing methods.

A Proof of Concept Study of Using Machine-Learning in Artificial Aortic Valve Design: From Leaflet Design to Stress Analysis

Artificial heart valves, used to replace diseased human heart valves, are life-saving medical devices. Currently, at the device development stage, new artificial valves are primarily assessed through time-consuming and expensive benchtop tests or animal implantation studies. Computational stress analysis using the finite element (FE) method presents an attractive alternative to physical testing. However, FE computational analysis requires a complex process of numeric modeling and simulation, as well as in-depth engineering expertise. In this proof of concept study, our objective was to develop machine learning (ML) techniques that can estimate the stress and deformation of a transcatheter aortic valve (TAV) from a given set of TAV leaflet design parameters. Two deep neural networks were developed and compared: the autoencoder-based ML-models and the direct ML-models. The ML-models were evaluated through Monte Carlo cross validation. From the results, both proposed deep neural networks could accurately estimate the deformed geometry of the TAV leaflets and the associated stress distributions within a second, with the direct ML-models (ML-model-d) having slightly larger errors. In conclusion, although this is a proof-of-concept study, the proposed ML approaches have demonstrated great potential to serve as a fast and reliable tool for future TAV design.

On the Modeling of Patient-Specific Transcatheter Aortic Valve Replacement: A Fluid-Structure Interaction Approach

PURPOSE

Transcatheter aortic valve replacement (TAVR) is a minimally invasive treatment for high-risk patients with aortic diseases. Despite its increasing use, many influential factors are still to be understood and require continuous investigation. The best numerical approach capable of reproducing both the valves mechanics and the hemodynamics is the fluid-structure interaction (FSI) modeling. The aim of this work is the development of a patient-specific FSI methodology able to model the implantation phase as well as the valve working conditions during cardiac cycles.

METHODS

The patient-specific domain, which included the aortic root, native valve and calcifications, was reconstructed from CT images, while the CAD model of the device, metallic frame and pericardium, was drawn from literature data. Ventricular and aortic pressure waveforms, derived from the patient's data, were used as boundary conditions. The proposed method was applied to two real clinical cases, which presented different outcomes in terms of paravalvular leakage (PVL), the main complication after TAVR.

RESULTS

The results confirmed the clinical prognosis of mild and moderate PVL with coherent values of regurgitant volume and effective regurgitant orifice area. Moreover, the final release configuration of the device and the velocity field were compared with postoperative CT scans and Doppler traces showing a good qualitative and quantitative matching.

CONCLUSION

In conclusion, the development of realistic and accurate FSI patient-specific models can be used as a support for clinical decisions before the implantation.

Effect of cyclic deformation on xenogeneic heart valve biomaterials

Glutaraldehyde-fixed bovine pericardium is currently the most popular biomaterial utilized in the creation of bioprosthetic heart valves. However, recent studies indicate that glutaraldehyde fixation results in calcification and structural valve deterioration, limiting the longevity of bioprosthetic heart valves. Additionally, glutaraldehyde fixation renders the tissue incompatible with constructive recipient cellular repopulation, remodeling and growth. Use of unfixed xenogeneic biomaterials devoid of antigenic burden has potential to overcome the limitations of current glutaraldehyde-fixed biomaterials. Heart valves undergo billion cycles of opening and closing throughout the patient’s lifetime. Therefore, understanding the response of unfixed tissues to cyclic loading is crucial to these in a heart valve leaflet configuration. In this manuscript we quantify the effect of cyclic deformation on cycle dependent strain, structural, compositional and mechanical properties of fixed and unfixed tissues. Glutaraldehyde-fixed bovine pericardium underwent marked cyclic dependent strain, resulting from significant changes in structure, composition and mechanical function of the material. Conversely, unfixed bovine pericardium underwent minimal strain and maintained its structure, composition and mechanical integrity. This manuscript demonstrates that unfixed bovine pericardium can withstand cyclic deformations equivalent to 6 months of in vivo heart valve leaflet performance.

Mechanics of the Tricuspid Valve-From Clinical Diagnosis/Treatment, In-Vivo and In-Vitro Investigations, to Patient-Specific Biomechanical Modeling

Proper tricuspid valve (TV) function is essential to unidirectional blood flow through the right side of the heart. Alterations to the tricuspid valvular components, such as the TV annulus, may lead to functional tricuspid regurgitation (FTR), where the valve is unable to prevent undesired backflow of blood from the right ventricle into the right atrium during systole. Various treatment options are currently available for FTR; however, research for the tricuspid heart valve, functional tricuspid regurgitation, and the relevant treatment methodologies are limited due to the pervasive expectation among cardiac surgeons and cardiologists that FTR will naturally regress after repair of left-sided heart valve lesions. Recent studies have focused on (i) understanding the function of the TV and the initiation or progression of FTR using both in-vivo and in-vitro methods, (ii) quantifying the biomechanical properties of the tricuspid valve apparatus as well as its surrounding heart tissue, and (iii) performing computational modeling of the TV to provide new insight into its biomechanical and physiological function. This review paper focuses on these advances and summarizes recent research relevant to the TV within the scope of FTR. Moreover, this review also provides future perspectives and extensions critical to enhancing the current understanding of the functioning and remodeling tricuspid valve in both the healthy and pathophysiological states.

Evaluation of transcatheter heart valve biomaterials: Computational modeling using bovine and porcine pericardium

OBJECTIVE

The durability of bioprosthetic heart valve (BHV) devices, commonly made of bovine (BP) and porcine (PP) pericardium tissue, is partly limited by device calcification and tissue degeneration, which has been associated with pathological levels of mechanical stress. This study investigated the impacts of BP and PP tissues with different thicknesses and tissue mechanical properties in BHV applications.

METHODS

Second Harmonic Generation (SHG) imaging was employed to visualize the collagen fibers on each side of the pericardium. Structural constitutive modeling that incorporates collagen fiber distribution obtained from multiphoton microscopy for each tissue type were derived to characterize the corresponding biaxial mechanical testing data collected in a previous study. The models were verified through finite element (FE) simulations of the biaxial test and implemented in valve closing simulations.

RESULTS

Smooth side collagen fibers were found to correlate with the mechanical response. BHVs with adult (ABP) and calf (CBP) BP tissues had lower maximum principal stresses than those with PP and fetal (FBP) BP tissues. Collagen fiber orientation along the circumferential axis resulted in lower maximum principal stresses and more uniform and symmetric stress distributions throughout the valve.

CONCLUSIONS

The use of PP and FBP tissue resulted in higher peak stresses than ABP and CBP tissues in the given valve design. Additionally, ensuring collagen fiber orientation along the circumferential axis led to lower maximum stresses felt by the valve leaflets, which could also improve BHV durability.

Collagen fibre orientation and dispersion govern ultimate tensile strength, stiffness and the fatigue performance of bovine pericardium

The durability of bovine pericardium leaflets employed in bioprosthetic heart valves (BHVs) can significantly limit the longevity of heart valve prostheses. Collagen fibres are the dominant load bearing component of bovine pericardium, however fibre architecture within leaflet geometries is not explicitly controlled in the manufacture of commercial devices. Thus, the purpose of this study was to ascertain the influence of pre-determined collagen fibre orientation and dispersion on the mechanical performance of bovine pericardium. Three tissue groups were tested in uniaxial tension: cross-fibre tissue (XD); highly dispersed fibre-orientations (HD); or preferred-fibre tissue (PD). Both the XD and PD tissue were tested under cyclic loading at 1.5 Hz and a stress range of 2.7 MPa. The results of the static tensile experiments illustrated that collagen fibre orientation and degree of alignment significantly influenced the material's response, whereby, there was a statistically significant decrease in material properties between the XD groups and both the PD and HD groups for ultimate tensile strength and stiffness (p < 0.01). Furthermore, HD tissue had a stiffness of approximately 58% of the PD group, and XD tissue had a stiffness of approximately 18% of the PD group. The dynamic behaviour of the XD and PD groups was extremely distinct; for example a Weibull analysis indicated that the 50% probability of failure in specimens with fibres orientated perpendicular (XD) to the loading direction occurred at 375 cycles. Due to this failure, XD specimens survived on average less than 20% of the cycles completed by those in which fibres were aligned along the loading direction (PD). The results from this study indicate that fibre architecture is a significant factor in determining static strength and fatigue life in bovine pericardium, and thus must be incorporated in the design process to improve future device durability.

Stented valve dynamic behavior induced by polyester fiber leaflet material in transcatheter aortic valve devices

OBJECTIVE

This study aims at assessing the global dynamic behavior, elastic deformability, closing energy and turbulence of rigid versus deformable stented (RS vs DS) valve systems with deformable and rigid textile materials (DT vs RT) through studying the stent-valve interaction compared to a bioprosthetic material in transcatheter aortic valves (TAV).

METHODS

Three 19 mm stented textile TAV designs (RS-DT, RS-RT and DS-RT) with different stent and leaflet properties were tested and compared with a control bioprosthetic TAV (RS-DB) in a left heart simulator flow loop under physiological pressure and flow. Particle Image Velocimetry and high speed imaging were performed. Pressure gradients (PG), leakage fractions (LF), Pinwheeling indices (PI), closing energy (E) and Reynolds shear stresses (RSS) were calculated.

RESULTS

(a) PGs and LFs were 11.86 ± 0.51 mmHg, 11.70 ± 0.34%; 8.84 ± 0.40 mmHg, 29.80 ± 0.76%; 11.59 ± 0.12 mmHg, 14.23 ± 1.64%; and 7.05 ± 0.09 mmHg, 12.08 ± 0.45% % for RS-DB, RS-DT, RS-RT and DS-RT respectively. (b) PIs were 15.79 ± 2.34%, 4.36 ± 0.84%, 2.47 ± 0.51% and 2.03 ± 0.33% for RS-DB, RS-DT, RS-RT and DS-RT respectively. (c) E is lowest for DS-RT (0.0010 ± 0.0002 J) followed by RS-RT (0.0017 ± 0.0002 J), RS-DB (0.0023 ± 0.0004 J) and highest with RS-DT (0.0036 ± 0.0007 J). (d) At peak systole lowest RSS was obtained with RS-DT (87.82 ± 0.58 Pa) and highest with DS-RT (122.98 ± 1.87 Pa).

CONCLUSION

PGs, LFs, PIs and E were improved with DS-RT compared to other textile TAVs and RS-DB. Despite achieving more RSS than the rest of TAVs, DS-RT still falls within the same range of RSS produced by the other 2 valves and control exceeding the threshold for platelet activation.

Stent and leaflet stresses in 26-mm, third-generation, balloon-expandable transcatheter aortic valve

OBJECTIVES

Transcatheter aortic valve replacement has proven successful in treating intermediate-risk, high-risk, and inoperable patients with severe aortic stenosis. Third-generation, balloon-expandable transcatheter aortic valves were developed with an outer sealing skirt to reduce paravalvular leakage. As transcatheter aortic valve replacement use expands, long-term durability questions remain. Valve design influences durability, where regions of increased leaflet stress are vulnerable to early degeneration. However, third-generation transcatheter aortic valve stresses are unknown. Our goals were to determine the stent and leaflet stresses of third-generation, balloon-expandable transcatheter aortic valves.

METHODS

The commercial 26-mm Edwards SAPIEN 3 valve (Edwards Lifesciences, Inc, Irvine, Calif) underwent high-resolution micro-computed tomography scanning to develop a precise 3-dimensional geometric mesh of the stent and valve. Leaflet material properties were obtained from surgical bioprostheses, and stent material properties were based on cobalt-chromium. Simulations of systemic pressure loading were performed, and stress was calculated using finite element analyses.

RESULTS

At diastole, maximum and minimum principal stresses on transcatheter aortic valve leaflets were 2.7 MPa and -0.47 MPa, respectively. Peak leaflet stresses were observed at upper leaflet commissures, at their connection to the stent. Maximum and minimum principal stresses for the stent were 38.2 MPa and -44.4 MPa, respectively, at 80 mm Hg and were located just below the commissural stent.

CONCLUSIONS

Stress analysis of the 26-mm SAPIEN 3 valve using exact geometry from high-resolution scans demonstrated that peak stresses for both transcatheter aortic valve stent and leaflets were present at commissural tips where leaflets were attached. These regions would be most likely to initiate degeneration. The Dacron skirt had minimal effect on stresses on leaflets and stent.

Simulated Transcatheter Aortic Valve Flow: Implications of Elliptical Deployment and Under-Expansion at the Aortic Annulus

Clinical use of transcatheter aortic valves (TAVs) has been associated with abnormal deployment, including oval deployment and under-expansion when placed into calcified aortic annuli. In this study, we performed an integrated computational and experimental investigation to quantify the impact of abnormal deployment at the aortic annulus on TAV hemodynamics. A size 23 mm generic TAV computational model, developed and published previously, was subjected to elliptical deployment at the annulus with eccentricity levels up to 0.68 and to under-expansion of the TAV at the annulus by up to 25%. The hemodynamic performance was quantified for each TAV deployment configuration. TAV opening geometries were fabricated using stereolithography and then subjected to steady forward flow testing in accordance with ISO-5840. Centerline pressure profiles were compared to validate the computational model. Our findings show that slight ellipticity of the TAV may not lead to degeneration of hydrodynamic performance. However, under large ellipticity, increases in transvalvular pressure gradients were observed. Under-expanded deployment has a much greater negative effect on the TAV hemodynamics compared with elliptical deployment. The maximum turbulent viscous shear stress (TVSS) values were found to be significantly larger in under-expanded TAVs. Although the maximum value of TVSS was not large enough to cause hemolysis in all cases, it may cause platelets activation, especially for under-expanded deployments.

A framework for designing patient-specific bioprosthetic heart valves using immersogeometric fluid-structure interaction analysis

Numerous studies have suggested that medical image derived computational mechanics models could be developed to reduce mortality and morbidity due to cardiovascular diseases by allowing for patient-specific surgical planning and customized medical device design. In this work, we present a novel framework for designing prosthetic heart valves using a parametric design platform and immersogeometric fluid-structure interaction (FSI) analysis. We parameterize the leaflet geometry using several key design parameters. This allows for generating various perturbations of the leaflet design for the patient-specific aortic root reconstructed from the medical image data. Each design is analyzed using our hybrid arbitrary Lagrangian-Eulerian/immersogeometric FSI methodology, which allows us to efficiently simulate the coupling of the deforming aortic root, the parametrically designed prosthetic valves, and the surrounding blood flow under physiological conditions. A parametric study is performed to investigate the influence of the geometry on heart valve performance, indicated by the effective orifice area and the coaptation area. Finally, the FSI simulation result of a design that balances effective orifice area and coaptation area reasonably well is compared with patient-specific phase contrast magnetic resonance imaging data to demonstrate the qualitative similarity of the flow patterns in the ascending aorta.

Computational methods for the aortic heart valve and its replacements

INTRODUCTION

Replacement with a prosthetic device remains a major treatment option for the patients suffering from heart valve disease, with prevalence growing resulting from an ageing population. While the most popular replacement heart valve continues to be the bioprosthetic heart valve (BHV), its durability remains limited. There is thus a continued need to develop a general understanding of the underlying mechanisms limiting BHV durability to facilitate development of a more durable prosthesis. In this regard, computational models can play a pivotal role as they can evaluate our understanding of the underlying mechanisms and be used to optimize designs that may not always be intuitive. Areas covered: This review covers recent progress in computational models for the simulation of BHV, with a focus on aortic valve (AV) replacement. Recent contributions in valve geometry, leaflet material models, novel methods for numerical simulation, and applications to BHV optimization are discussed. This information should serve not only to infer reliable and dependable BHV function, but also to establish guidelines and insight for the design of future prosthetic valves by analyzing the influence of design, hemodynamics and tissue mechanics. Expert commentary: The paradigm of predictive modeling of heart valve prosthesis are becoming a reality which can simultaneously improve clinical outcomes and reduce costs. It can also lead to patient-specific valve design.

Characterization of mechanical properties of pericardium tissue using planar biaxial tension and flexural deformation

Flexure is an important mode of deformation for native and bioprosthetic heart valves. However, mechanical characterization of bioprosthetic leaflet materials has been done primarily through planar tensile testing. In this study, an integrated experimental and computational cantilever beam bending test was performed to characterize the flexural properties of glutaraldehyde-treated bovine and porcine pericardium of different thicknesses. A strain-invariant based structural constitutive model was used to model the pericardial mechanical behavior quantified through the bending tests of this study and the planar biaxial tests previously performed. The model parameters were optimized through an inverse finite element (FE) procedure in order to describe both sets of experimental data. The optimized material properties were implemented in FE simulations of transcatheter aortic valve (TAV) deformation. It was observed that porcine pericardium TAV leaflets experienced significantly more flexure than bovine when subjected to opening pressurization, and that the flexure may be overestimated using a constitutive model derived from purely planar tensile experimental data. Thus, modeling of a combination of flexural and biaxial tensile testing data may be necessary to more accurately describe the mechanical properties of pericardium, and to computationally investigate bioprosthetic leaflet function and design.