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

Sensitivity of Post-TAVR Hemodynamics to the Distal Aortic Arch Anatomy: A High-Fidelity CFD Study

PURPOSE

Patient-specific simulations of transcatheter aortic valve (TAV) using computational fluid dynamics (CFD) often rely on assumptions regarding proximal and distal anatomy due to the limited availability of high-resolution imaging away from the TAV site and the primary research focus being near the TAV. However, the influence of these anatomical assumptions on computational efficiency and resulting flow characteristics remains uncertain. This study aimed to investigate the impact of different distal aortic arch anatomies-some of them commonly used in literature-on flow and hemodynamics in the vicinity of the TAV using large eddy simulations (LES).

METHODS

Three aortic root anatomical configurations with four representative distal aortic arch types were considered in this study. The arch types included a 90-degree bend, an idealized distal aortic arch anatomy, a clipped version of the idealized distal aortic arch, and an anatomy extruded along the normal of segmented anatomical boundary. Hemodynamic parameters both instantaneous and time-averaged such as Wall Shear Stress (WSS), and Oscillatory Shear Index (OSI) were derived and compared from high-fidelity CFD data.

RESULTS

While there were minor differences in flow and hemodynamics across the configurations examined, they were generally not significant within our region of interest i.e., the aortic root. The choice of extension type had a modest impact on TAV hemodynamics, especially in the vicinity of the TAV with variations observed in local flow patterns and parameters near the TAV. However, these differences were not substantial enough to cause significant deviations in the overall flow and hemodynamic characteristics.

CONCLUSIONS

The results suggest that under the given configuration and boundary conditions, the type of outflow extension had a modest impact on hemodynamics proximal to the TAV. The findings contribute to a better understanding of flow dynamics in TAV configurations, providing insights for future studies in TAV-related experiments as well as numerical simulations. Additionally, they help mitigate the uncertainties associated with patient-specific geometries, offering increased flexibility in computational modeling.

In Vitro Comparison of a Closed and Semi-closed Leaflet Design for Adult and Pediatric Transcatheter Heart Valves

Transcatheter heart valve replacements (TVR) are mostly designed in a closed position (c) with leaflets coaptating. However, recent literature suggests fabricating valves in semi-closed (sc) position to minimize pinwheeling. With about 100,000 children in need of a new pulmonary valve each year worldwide, this study evaluates both geometrical approaches in adult as well as pediatric size and condition. Three valves of each geometry were fabricated in adult (30 mm) and pediatric (15 mm) size, using porcine pericardium. To evaluate performance, the mean transvalvular pressure gradient (TPG), effective orifice area (EOA), and regurgitation fraction (RF) were determined in three different annulus geometries (circular, elliptic, and tilted). For both adult-sized valve geometries, the TPG (TPGC = 2.326 ± 0.115 mmHg; TPGSC = 1.848 ± 0.175 mmHg)* and EOA (EOAC = 3.69 ± 0.255 cm2; EOASC = 3.565 ± 0.025 cm2)* showed no significant difference. Yet the RF as well as its fluctuation was significantly higher for valves with the closed geometry (RFC = 12.657 ± 7.669 %; RFSC = 8.72 ± 0.977 %)*. Recordings showed that the increased backflow was caused by pinwheeling due to a surplus of tissue material. Hydrodynamic testing of pediatric TVRs verified the semi-closed geometry being favourable. Despite the RF (RFC = 7.721 ± 0.348 cm2; RFSC = 5.172 ± 0.679 cm2), these valves also showed an improved opening behaviour ((TPGC = 20.929 ± 0.497 cm2; TPGSC = 15.972 ± 1.158 cm2); (EOAC = 0.629 ± 0.017 cm2; EOASC = 0.731 ± 0.026 cm2)). Both adult and pediatric TVR with semi-closed geometry show better fluiddynamic functionality compared to valves with a closed design due to less pinwheeling. Besides improved short-term functionality, less pinwheeling potentially prevents early valve degeneration and improves durability. *Results are representatively shown for a circular annulus geometry.

Current progress toward isogeometric modeling of the heart biophysics

In this paper, we review a powerful methodology to solve complex numerical simulations, known as isogeometric analysis, with a focus on applications to the biophysical modeling of the heart. We focus on the hemodynamics, modeling of the valves, cardiac tissue mechanics, and on the simulation of medical devices and treatments. For every topic, we provide an overview of the methods employed to solve the specific numerical issue entailed by the simulation. We try to cover the complete process, starting from the creation of the geometrical model up to the analysis and post-processing, highlighting the advantages and disadvantages of the methodology.

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.

Strategies for Development of Synthetic Heart Valve Tissue Engineering Scaffolds

The current clinical solutions, including mechanical and bioprosthetic valves for valvular heart diseases, are plagued by coagulation, calcification, nondurability, and the inability to grow with patients. The tissue engineering approach attempts to resolve these shortcomings by producing heart valve scaffolds that may deliver patients a life-long solution. Heart valve scaffolds serve as a three-dimensional support structure made of biocompatible materials that provide adequate porosity for cell infiltration, and nutrient and waste transport, sponsor cell adhesion, proliferation, and differentiation, and allow for extracellular matrix production that together contributes to the generation of functional neotissue. The foundation of successful heart valve tissue engineering is replicating native heart valve architecture, mechanics, and cellular attributes through appropriate biomaterials and scaffold designs. This article reviews biomaterials, the fabrication of heart valve scaffolds, and their in-vitro and in-vivo evaluations applied for heart valve tissue engineering.

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.

Functional mechanical behavior of the murine pulmonary heart valve

Genetically modified mouse models provide a versatile and efficient platform to extend our understanding of the underlying disease processes and evaluate potential treatments for congenital heart valve diseases. However, applications have been limited to the gene and molecular levels due to the small size of murine heart valves, which prohibits the use of standard mechanical evaluation and in vivo imaging methods. We have developed an integrated imaging/computational mechanics approach to evaluate, for the first time, the functional mechanical behavior of the murine pulmonary heart valve (mPV). We utilized extant mPV high resolution µCT images of 1-year-old healthy C57BL/6J mice, with mPVs loaded to 0, 10, 20 or 30 mmHg then chemically fixed to preserve their shape. Individual mPV leaflets and annular boundaries were segmented and key geometric quantities of interest defined and quantified. The resulting observed inter-valve variations were small and consistent at each TVP level. This allowed us to develop a high fidelity NURBS-based geometric model. From the resultant individual mPV geometries, we developed a mPV shape-evolving geometric model (SEGM) that accurately represented mPV shape changes as a continuous function of transvalvular pressure. The SEGM was then integrated into an isogeometric finite element based inverse model that estimated the individual leaflet and regional mPV mechanical behaviors. We demonstrated that the mPV leaflet mechanical behaviors were highly anisotropic and nonlinear, with substantial leaflet and regional variations. We also observed the presence of strong axial mechanical coupling, suggesting the important role of the underlying collagen fiber architecture in the mPV. When compared to larger mammalian species, the mPV exhibited substantially different mechanical behaviors. Thus, while qualitatively similar, the mPV exhibited important functional differences that will need to accounted for in murine heart valve studies. The results of this novel study will allow detailed murine tissue and organ level investigations of semi-lunar heart valve diseases.

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.

Analysis of the Effect of Thickness on the Performance of Polymeric Heart Valves

Polymeric heart valves (PHVs) are a promising and more affordable alternative to mechanical heart valves (MHVs) and bioprosthetic heart valves (BHVs). Materials with good durability and biocompatibility used for PHVs have always been the research focus in the field of prosthetic heart valves for many years, and leaflet thickness is a major design parameter for PHVs. The study aims to discuss the relationship between material properties and valve thickness, provided that the basic functions of PHVs are qualified. The fluid-structure interaction (FSI) approach was employed to obtain a more reliable solution of the effective orifice area (EOA), regurgitant fraction (RF), and stress and strain distribution of the valves with different thicknesses under three materials: Carbothane PC-3585A, xSIBS and SIBS-CNTs. This study demonstrates that the smaller elastic modulus of Carbothane PC-3585A allowed for a thicker valve (>0.3 mm) to be produced, while for materials with an elastic modulus higher than that of xSIBS (2.8 MPa), a thickness less than 0.2 mm would be a good attempt to meet the RF standard. What is more, when the elastic modulus is higher than 23.9 MPa, the thickness of the PHV is recommended to be 0.l-0.15 mm. Reducing the RF is one of the directions of PHV optimization in the future. Reducing the thickness and improving other design parameters are reliable means to reduce the RF for materials with high and low elastic modulus, respectively.

A parametric geometry model of the aortic valve for subject-specific blood flow simulations using a resistive approach

Cardiac valves simulation is one of the most complex tasks in cardiovascular modeling. Fluid-structure interaction is not only highly computationally demanding but also requires knowledge of the mechanical properties of the tissue. Therefore, an alternative is to include valves as resistive flow obstacles, prescribing the geometry (and its possible changes) in a simple way, but, at the same time, with a geometry complex enough to reproduce both healthy and pathological configurations. In this work, we present a generalized parametric model of the aortic valve to obtain patient-specific geometries that can be included into blood flow simulations using a resistive immersed implicit surface (RIIS) approach. Numerical tests are presented for geometry generation and flow simulations in aortic stenosis patients whose parameters are extracted from ECG-gated CT images.

Neural Network Approaches for Soft Biological Tissue and Organ Simulations

Given the functional complexities of soft tissues and organs, it is clear that computational simulations are critical in their understanding and for the rational basis for the development of therapies and replacements. A key aspect of such simulations is accounting for their complex, nonlinear, anisotropic mechanical behaviors. While soft tissue material models have developed to the point of high fidelity, in-silico implementation is typically done using the finite element (FE) method, which remains impractically slow for translational clinical time frames. As a potential path toward addressing the development of high fidelity simulations capable of performing in clinically relevant time frames, we review the use of neural networks (NN) for soft tissue and organ simulation using two approaches. In the first approach, we show how a NN can learn the responses for a detailed meso-structural soft tissue material model. The NN material model not only reproduced the full anisotropic mechanical responses but also demonstrated a considerable efficiency improvement, as it was trained over a range of realizable fibrous structures. In the second approach, we go a step further with the use of a physics-based surrogate model to directly learn the displacement field solution without the need for raw training data or FE simulation datasets. In this approach we utilize a finite element mesh to define the domain and perform the necessary integrations, but not the finite element method (FEM) itself. We demonstrate with this approach, termed neural network finite element (NNFE), results in a trained NNFE model with excellent agreement with the corresponding "ground truth" FE solutions over the entire physiological deformation range on a cuboidal myocardium specimen. More importantly, the NNFE approach provided a significantly decreased computational time for a range of finite element mesh sizes. Specifically, as the FE mesh size increased from 2744 to 175,615 elements, the NNFE computational time increased from 0.1108 s to 0.1393 s, while the "ground truth" FE model increased from 4.541 s to 719.9 s, with the same effective accuracy. These results suggest that NNFE run times are significantly reduced compared with the traditional large-deformation-based finite element solution methods. We then show how a nonuniform rational B-splines (NURBS)-based approach can be directly integrated into the NNFE approach as a means to handle real organ geometries. While these and related approaches are in their early stages, they offer a method to perform complex organ-level simulations in clinically relevant time frames without compromising accuracy.

Design of an aortic polymeric valve with asymmetric leaflets and evaluation of its performance by finite element method

BACKGROUND

The geometry of leaflets plays a significant role in prosthetic valves' (PVs) performance. Typically, natural aortic valves have three unequal leaflets, which differ in size. The present study aims to design an asymmetric tri-leaflet polymeric valve with one large and two small leaflets based on commissure lengths and leaflet eccentricities.

METHODS

Eccentricity was related to commissure lengths based on the deformation of the free margins for the fully-opened state of leaflets. The polystyrene-block-polyethylene-polypropylene-block-polystyrene polymer characterized the material properties of the leaflets. The Finite Element Method (FEM) was used to evaluate performance parameters, including maximum geometric orifice area (GOA), average GOA, maximum von Mises stress, and leaflet's coaptation surface area (CSA).

RESULTS

Asymmetric valves with no eccentricity provided a low level of GOA because the asymmetric form of small leaflets caused them to close faster than the large leaflet, leading to a sudden drop in the GOA during systole. As the radial curve tends towards a straight line, an undesirable coaptation occurs, and peak stress increases despite higher GOAs. A new radial curve consisting of two straight lines connected by an arc that provided 25.64 mm² coaptation surface area (CAS) and 117.54 mm² average GOA, was proposed to improve coaptation and GOA.

CONCLUSION

The radial curve of leaflets affects the valve's performance more than other geometric parameters. The combination of straight lines and arcs for radial curves was selected as the reference model for asymmetric valves with one large and two small leaflets.

Aortic Valve Leaflet Shape Synthesis With Geometric Prior From Surrounding Tissue

Even though the field of medical imaging advances, there are structures in the human body that are barely assessible with classical image acquisition modalities. One example are the three leaflets of the aortic valve due to their thin structure and high movement. However, with an increasing accuracy of biomechanical simulation, for example of the heart function, and extense computing capabilities available, concise knowledge of the individual morphology of these structures could have a high impact on personalized therapy and intervention planning as well as on clinical research. Thus, there is a high demand to estimate the individual shape of inassessible structures given only information on the geometry of the surrounding tissue. This leads to a domain adaptation problem, where the domain gap could be very large while typically only small datasets are available. Hence, classical approaches for domain adaptation are not capable of providing sufficient predictions. In this work, we present a new framework for bridging this domain gap in the scope of estimating anatomical shapes based on the surrounding tissue's morphology. Thus, we propose deep representation learning to not map from one image to another but to predict a latent shape representation. We formalize this framework and present two different approaches to solve the given problem. Furthermore, we perform a proof-of-concept study for estimating the individual shape of the aortic valve leaflets based on a volumetric ultrasound image of the aortic root. Therefore, we collect an ex-vivo porcine data set consisting of both, ultrasound volume images as well as high-resolution leaflet images, evaluate both approaches on it and perform an analysis of the model's hyperparameters. Our results show that using deep representation learning and domain mapping between the identified latent spaces, a robust prediction of the unknown leaflet shape only based on surrounding tissue information is possible, even in limited data scenarios. The concept can be applied to a wide range of modeling tasks, not only in the scope of heart modeling but also for all kinds of inassessible structures within the human body.

Effects of membrane and flexural stiffnesses on aortic valve dynamics: identifying the mechanics of leaflet flutter in thinner biological tissues

Valvular pathologies that induce deterioration in the aortic valve are a common cause of heart disease among aging populations. Although there are numerous available technologies to treat valvular conditions and replicate normal aortic function by replacing the diseased valve with a bioprosthetic implant, many of these devices face challenges in terms of long-term durability. One such phenomenon that may exacerbate valve deterioration and induce undesirable hemodynamic effects in the aorta is leaflet flutter, which is characterized by oscillatory motion in the biological tissues. While this behavior has been observed for thinner bioprosthetic valves, the specific underlying mechanics that lead to leaflet flutter have not previously been identified. This work proposes a computational approach to isolate the fundamental mechanics that induce leaflet flutter in thinner biological tissues during the cardiac cycle. The simulations in this work identify reduced flexural stiffness as the primary factor that contributes to increased leaflet flutter in thinner biological tissues, while decreased membrane stiffness and mass of the thinner tissues do not directly induce flutter in these valves. The results of this study provide an improved understanding of the mechanical tissue properties that contribute to flutter and offer significant insights into possible developments in the design of bioprosthetic tissues to account for and reduce the incidence of flutter.

Patient-Specific Quantification of Normal and Bicuspid Aortic Valve Leaflet Deformations from Clinically Derived Images

The clinical benefit of patient-specific modeling of heart valve disease remains an unrealized goal, often a result of our limited understanding of the in vivo milieu. This is particularly true in assessing bicuspid aortic valve (BAV) disease, the most common cardiac congenital defect in humans, which leads to premature and severe aortic stenosis or insufficiency (AS/AI). However, assessment of BAV risk for AS/AI on a patient-specific basis is hampered by the substantial degree of anatomic and functional variations that remain largely unknown. The present study was undertaken to utilize a noninvasive computational pipeline ( https://doi.org/10.1002/cnm.3142 ) that directly yields local heart valve leaflet deformation information using patient-specific real-time three-dimensional echocardiographic imaging (rt-3DE) data. Imaging data was collected for patients with normal tricuspid aortic valve (TAV, [Formula: see text]) and those with BAV ([Formula: see text] with fused left and right coronary leaflets and [Formula: see text] with fused right and non-coronary leaflets), from which the medial surface of each leaflet was extracted. The resulting deformation analysis resulted in, for the first time, quantified differences between the in vivo functional deformations of the TAV and BAV leaflets. Our approach was able to capture the complex, heterogeneous surface deformation fields in both TAV and BAV leaflets. We were able to identify and quantify differences in stretch patterns between leaflet types, and found in particular that stretches experienced by BAV leaflets during closure differ from those of TAV leaflets in terms of both heterogeneity as well as overall magnitude. Deformation is a key parameter in the clinical assessment of valvular function, and serves as a direct means to determine regional variations in structure and function. This study is an essential step toward patient-specific assessment of BAV based on correlating leaflet deformation and AS/AI progression, as it provides a means for assessing patient-specific stretch patterns.

Simulating the time evolving geometry, mechanical properties, and fibrous structure of bioprosthetic heart valve leaflets under cyclic loading

Currently, the most common replacement heart valve design is the 'bioprosthetic' heart valve (BHV), which has important advantages in that it does not require permanent anti-coagulation therapy, operates noiselessly, and has blood flow characteristics similar to the native valve. BHVs are typically fabricated from glutaraldehyde-crosslinked pericardial xenograft tissue biomaterials (XTBs) attached to a rigid, semi-flexible, or fully collapsible stent in the case of the increasingly popular transcutaneous aortic valve replacement (TAVR). While current TAVR assessments are positive, clinical results to date are generally limited to <2 years. Since TAVR leaflets are constructed using thinner XTBs, their mechanical demands are substantially greater than surgical BHV due to the increased stresses during in vivo operation, potentially resulting in decreased durability. Given the functional complexity of heart valve operation, in-silico predictive simulations clearly have potential to greatly improve the TAVR development process. As such simulations must start with accurate material models, we have developed a novel time-evolving constitutive model for pericardial xenograft tissue biomaterials (XTB) utilized in BHV (doi: 10.1016/j.jmbbm.2017.07.013). This model was able to simulate the observed tissue plasticity effects that occur in approximately in the first two years of in vivo function (50 million cycles). In the present work, we implemented this model into a complete simulation pipeline to predict the BHV time evolving geometry to 50 million cycles. The pipeline was implemented within an isogeometric finite element formulation that directly integrated our established BHV NURBS-based geometry (doi: 10.1007/s00466-015-1166-x). Simulations of successive loading cycles indicated continual changes in leaflet shape, as indicated by spatially varying increases in leaflet curvature. While the simulation model assumed an initial uniform fiber orientation distribution, anisotropic regional changes in leaflet tissue plastic strain induced a complex changes in regional fiber orientation. We have previously noted in our time-evolving constitutive model that the increases in collagen fiber recruitment with cyclic loading placed an upper bound on plastic strain levels. This effect was manifested by restricting further changes in leaflet geometry past 50 million cycles. Such phenomena was accurately captured in the valve-level simulations due to the use of a tissue-level structural-based modeling approach. Changes in basic leaflet dimensions agreed well with extant experimental studies. As a whole, the results of the present study indicate the complexity of BHV responses to cyclic loading, including changes in leaflet shape and internal fibrous structure. It should be noted that the later effect also influences changes in local mechanical behavior (i.e. changes in leaflet anisotropic tissue stress-strain relationship) due to internal fibrous structure resulting from plastic strains. Such mechanism-based simulations can help pave the way towards the application of sophisticated simulation technologies in the development of replacement heart valve technology.

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.

Fully coupled dynamic simulations of bioprosthetic aortic valves based on an embedded strategy for fluid-structure interaction with contact

AIMS

This work aims at presenting a fully coupled approach for the numerical solution of contact problems between multiple elastic structures immersed in a fluid flow. The key features of the computational model are (i) a fully coupled fluid-structure interaction with contact, (ii) the use of a fibre-reinforced material for the leaflets, (iii) a stent, and (iv) a compliant aortic root.

METHODS AND RESULTS

The computational model takes inspiration from the immersed boundary techniques and allows the numerical simulation of the blood-tissue interaction of bioprosthetic heart valves (BHVs) as well as the contact among the leaflets. First, we present pure mechanical simulations, where blood is neglected, to assess the performance of different material properties and valve designs. Secondly, fully coupled fluid-structure interaction simulations are employed to analyse the combination of haemodynamic and mechanical characteristics. The isotropic leaflet tissue experiences high-stress values compared to the fibre-reinforced material model. Moreover, elongated leaflets show a stress concentration close to the base of the stent. We observe a fully developed flow at the systolic stage of the heartbeat. On the other hand, flow recirculation appears along the aortic wall during diastole.

CONCLUSION

The presented FSI approach can be used for analysing the mechanical and haemodynamic performance of a BHV. Our study suggests that stresses concentrate in the regions where leaflets are attached to the stent and in the portion of the aortic root where the BHV is placed. The results from this study may inspire new BHV designs that can provide a better stress distribution.

On the shape and structure of the murine pulmonary heart valve

Murine animal models are an established standard in translational research and provides a potential platform for studying heart valve disease. To date, studies on heart valve disease using murine models have been hindered by a lack of appropriate methodologies due to their small scale. In the present study, we developed a multi-scale, imaging-based approach to extract the functional structure and geometry for the murine heart valve. We chose the pulmonary valve (PV) to study, due to its importance in congenital heart valve disease. Excised pulmonary outflow tracts from eleven 1-year old C57BL/6J mice were fixed at 10, 20, and 30 mmHg to simulate physiological loading. Micro-computed tomography was used to reconstruct the 3D organ-level PV geometry, which was then spatially correlated with serial en-face scanning electron microscopy imaging to quantify local collagen fiber distributions. From the acquired volume renderings, we obtained the geometric descriptors of the murine PV under increasing transvalvular pressures, which demonstrated remarkable consistency. Results to date suggest that the preferred collagen orientation was predominantly in the circumferential direction, as in larger mammalian valves. The present study represents a first step in establishing organ-level murine models for the study of heart valve disease.

Isogeometric finite element-based simulation of the aortic heart valve: Integration of neural network structural material model and structural tensor fiber architecture representations

The functional complexity of native and replacement aortic heart valves (AVs) is well known, incorporating such physical phenomenons as time-varying non-linear anisotropic soft tissue mechanical behavior, geometric non-linearity, complex multi-surface time varying contact, and fluid-structure interactions to name a few. It is thus clear that computational simulations are critical in understanding AV function and for the rational basis for design of their replacements. However, such approaches continued to be limited by ad-hoc approaches for incorporating tissue fibrous structure, high-fidelity material models, and valve geometry. To this end, we developed an integrated tri-leaflet valve pipeline built upon an isogeometric analysis framework. A high-order structural tensor (HOST)-based method was developed for efficient storage and mapping the two-dimensional fiber structural data onto the valvular 3D geometry. We then developed a neural network (NN) material model that learned the responses of a detailed meso-structural model for exogenously cross-linked planar soft tissues. The NN material model not only reproduced the full anisotropic mechanical responses but also demonstrated a considerable efficiency improvement, as it was trained over a range of realizable fibrous structures. Results of parametric simulations were then performed, as well as population-based bicuspid AV fiber structure, that demonstrated the efficiency and robustness of the present approach. In summary, the present approach that integrates HOST and NN material model provides an efficient computational analysis framework with increased physical and functional realism for the simulation of native and replacement tri-leaflet heart valves.

Computational investigation of left ventricular hemodynamics following bioprosthetic aortic and mitral valve replacement

The left ventricle of the heart is a fundamental structure in the human cardiac system that pumps oxygenated blood into the systemic circulation. Several valvular conditions can cause the aortic and mitral valves associated with the left ventricle to become severely diseased and require replacement. However, the clinical outcomes of such operations, specifically the postoperative ventricular hemodynamics of replacing both valves, are not well understood. This work uses computational fluid-structure interaction (FSI) to develop an improved understanding of this effect by modeling a left ventricle with the aortic and mitral valves replaced with bioprostheses. We use a hybrid Arbitrary Lagrangian-Eulerian/immersogeometric framework to accommodate the analysis of cardiac hemodynamics and heart valve structural mechanics in a moving fluid domain. The motion of the endocardium is obtained from a cardiac biomechanics simulation and provided as an input to the proposed numerical framework. The results from the simulations in this work indicate that the replacement of the native mitral valve with a tri-radially symmetric bioprosthesis dramatically changes the ventricular hemodynamics. Most significantly, the vortical motion in the left ventricle is found to reverse direction after mitral valve replacement. This study demonstrates that the proposed computational FSI framework is capable of simulating complex multiphysics problems and can provide an in-depth understanding of the cardiac mechanics.

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.

Influence of Patient-Specific Characteristics on Transcatheter Heart Valve Neo-Sinus Flow: An In Silico Study

Thrombosis in post-transcatheter aortic valve replacement (TAVR) patients has been correlated with flow stasis in the neo-sinus. This study investigated the effect of the post-TAVR geometry on flow stasis. Computed tomography angiography of 155 patients who underwent TAVR using a SAPIEN 3 were used to identify patients with and without thrombosis, and quantify thrombus volumes. Six patients with 23-mm SAPIEN 3 valves were then selected from the cohort and used to create patient-specific post-TAVR computational fluid dynamic models. Regions of flow stasis (%Vol_stasis, velocities below 0.05 m/s) were identified. The results showed that all post-TAVR anatomical measurements were significantly different in patients with and without thrombus, but only sinus diameter had a linear correlation with thrombus volume (r = 0.471, p = 0.008). A linear correlation was observed between %Vol_stasis and thrombus volume (r = 0.821, p = 0.007). The combination of anatomy and valve deployment created a unique geometry in each patient, which when combined with patient-specific cardiac output, resulted in distinct flow patterns. While parametric studies have shown individual anatomical or deployment metrics may relate to flow stasis, the combined effects of these metrics potentially contributes to the biomechanical environment promoting thrombosis, therefore hemodynamic studies of TAVR should account for these patient-specific factors.

Next-generation tissue-engineered heart valves with repair, remodelling and regeneration capacity

Valvular heart disease is a major cause of morbidity and mortality worldwide. Surgical valve repair or replacement has been the standard of care for patients with valvular heart disease for many decades, but transcatheter heart valve therapy has revolutionized the field in the past 15 years. However, despite the tremendous technical evolution of transcatheter heart valves, to date, the clinically available heart valve prostheses for surgical and transcatheter replacement have considerable limitations. The design of next-generation tissue-engineered heart valves (TEHVs) with repair, remodelling and regenerative capacity can address these limitations, and TEHVs could become a promising therapeutic alternative for patients with valvular disease. In this Review, we present a comprehensive overview of current clinically adopted heart valve replacement options, with a focus on transcatheter prostheses. We discuss the various concepts of heart valve tissue engineering underlying the design of next-generation TEHVs, focusing on off-the-shelf technologies. We also summarize the latest preclinical and clinical evidence for the use of these TEHVs and describe the current scientific, regulatory and clinical challenges associated with the safe and broad clinical translation of this technology.

Thinner biological tissues induce leaflet flutter in aortic heart valve replacements

Valvular heart disease has recently become an increasing public health concern due to the high prevalence of valve degeneration in aging populations. For patients with severely impacted aortic valves that require replacement, catheter-based bioprosthetic valve deployment offers a minimally invasive treatment option that eliminates many of the risks associated with surgical valve replacement. Although recent percutaneous device advancements have incorporated thinner, more flexible biological tissues to streamline safer deployment through catheters, the impact of such tissues in the complex, mechanically demanding, and highly dynamic valvular system remains poorly understood. The present work utilized a validated computational fluid-structure interaction approach to isolate the behavior of thinner, more compliant aortic valve tissues in a physiologically realistic system. This computational study identified and quantified significant leaflet flutter induced by the use of thinner tissues that initiated blood flow disturbances and oscillatory leaflet strains. The aortic flow and valvular dynamics associated with these thinner valvular tissues have not been previously identified and provide essential information that can significantly advance fundamental knowledge about the cardiac system and support future medical device innovation. Considering the risks associated with such observed flutter phenomena, including blood damage and accelerated leaflet deterioration, this study demonstrates the potentially serious impact of introducing thinner, more flexible tissues into the cardiac system.

Morphogeometric analysis for characterization of keratoconus considering the spatial localization and projection of apex and minimum corneal thickness point

This work evaluates changes in new morphogeometric indices developed considering the position of anterior and posterior corneal apex and minimum corneal thickness (MCT) point in keratoconus. This prospective comparative study included 440 eyes of 440 patients (age, 7-99 years): control (124 eyes) and keratoconus (KC) groups (316 eyes). Tomographic information (Sirius®, Costruzione Strumenti Oftalmici, Italy) was treated with SolidWorks v2013, creating the following morphogeometric parameters: geometric axis-apex line angle (GA-AP), geometric axis-MCT line angle (GA-MCT, apex line-MCT line angle (AP-MCT), and distances between apex and MCT points on the anterior (anterior AP-MCTd) and posterior corneal surface (posterior AP-MCTd). Statistically significant higher values of GA-AP, GA-MCT, AP-MCT and anterior AP-MCTd were found in the keratoconus group (p ≤ 0.001). Moderate significant correlations of corneal aberrations (r ≥ 0.587, p < 0.001) and corneal thickness parameters (r ≤ -0.414, p < 0.001) with GA-AP and AP-MCT were found. Anterior asphericity was found to be significantly correlated with anterior and posterior AP-MCTd (r ≥ 0.430, p < 0.001). Likewise, GA-AP and AP-MCT showed a good diagnostic ability for the detection of keratoconus, with optimal cutoff values of 9.61° (sensitivity 85.5%, specificity 80.3%) and 18.08° (sensitivity 80.5%, specificity 78.7%), respectively. These new morphogeometric indices allow a clinical characterization of the 3-D structural alteration occurring in keratoconus, with less coincidence in the spatial projection of the apex and MCT points of both corneal surfaces. Future studies should confirm the potential impact on the precision of these indices of the variability of posterior corneal surface measurements obtained with Scheimpflug imaging technology.

Fluid-Structure Interaction Models of Bioprosthetic Heart Valve Dynamics in an Experimental Pulse Duplicator

Computer modeling and simulation is a powerful tool for assessing the performance of medical devices such as bioprosthetic heart valves (BHVs) that promises to accelerate device design and regulation. This study describes work to develop dynamic computer models of BHVs in the aortic test section of an experimental pulse-duplicator platform that is used in academia, industry, and regulatory agencies to assess BHV performance. These computational models are based on a hyperelastic finite element extension of the immersed boundary method for fluid-structure interaction (FSI). We focus on porcine tissue and bovine pericardial BHVs, which are commonly used in surgical valve replacement. We compare our numerical simulations to experimental data from two similar pulse duplicators, including a commercial ViVitro system and a custom platform related to the ViVitro pulse duplicator. Excellent agreement is demonstrated between the computational and experimental results for bulk flow rates, pressures, valve open areas, and the timing of valve opening and closure in conditions commonly used to assess BHV performance. In addition, reasonable agreement is demonstrated for quantitative measures of leaflet kinematics under these same conditions. This work represents a step towards the experimental validation of this FSI modeling platform for evaluating BHVs.

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.

Immersogeometric fluid-structure interaction modeling and simulation of transcatheter aortic valve replacement

The transcatheter aortic valve replacement (TAVR) has emerged as a minimally invasive alternative to surgical treatments of valvular heart disease. TAVR offers many advantages, however, the safe anchoring of the transcatheter heart valve (THV) in the patients anatomy is key to a successful procedure. In this paper, we develop and apply a novel immersogeometric fluid-structure interaction (FSI) framework for the modeling and simulation of the TAVR procedure to study the anchoring ability of the THV. To account for physiological realism, methods are proposed to model and couple the main components of the system, including the arterial wall, blood flow, valve leaflets, skirt, and frame. The THV is first crimped and deployed into an idealized ascending aorta. During the FSI simulation, the radial outward force and friction force between the aortic wall and the THV frame are examined over the entire cardiac cycle. The ratio between these two forces is computed and compared with the experimentally estimated coefficient of friction to study the likelihood of valve migration.

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.

Immersed Methods for Fluid-Structure Interaction

Fluid-structure interaction is ubiquitous in nature and occurs at all biological scales. Immersed methods provide mathematical and computational frameworks for modeling fluid-structure systems. These methods, which typically use an Eulerian description of the fluid and a Lagrangian description of the structure, can treat thin immersed boundaries and volumetric bodies, and they can model structures that are flexible or rigid or that move with prescribed deformational kinematics. Immersed formulations do not require body-fitted discretizations and thereby avoid the frequent grid regeneration that can otherwise be required for models involving large deformations and displacements. This article reviews immersed methods for both elastic structures and structures with prescribed kinematics. It considers formulations using integral operators to connect the Eulerian and Lagrangian frames and methods that directly apply jump conditions along fluid-structure interfaces. Benchmark problems demonstrate the effectiveness of these methods, and selected applications at Reynolds numbers up to approximately 20,000 highlight their impact in biological and biomedical modeling and simulation.

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.

A patient-specific mass-spring model for biomechanical simulation of aortic root tissue during transcatheter aortic valve implantation

The success of transcatheter aortic valve implantation (TAVI) is highly dependent on the prediction of the interaction between the prosthesis and the aortic root anatomy. The simulation of the surgical procedure may be useful to guide artificial valve selection and delivery, nevertheless the introduction of simulation models into the clinical workflow is often hindered by model complexity and computational burden. To address this point, we introduced a patient-specific mass-spring model (MSM) with viscous damping, as a good trade-off between simulation accuracy and time-efficiency. The anatomical model consisted of a hexahedral mesh, segmented from pre-procedural patient-specific cardiac computer tomographic (CT) images of the aortic root, including valve leaflets and attached calcifications. Nodal forces were represented by linear-elastic springs acting on edges and angles. A fast integration approach based on the modulation of nodal masses was also tested. The model was validated on seven patients, comparing simulation results with post-procedural CT images with respect to calcification and aortic wall position. The validation showed that the MSM was able to predict calcification displacement with an average accuracy of 1.72 mm and 1.54 mm for the normal and fast integration approaches, respectively. Wall displacement root mean squared error after valve expansion was about 1 mm for both approaches, showing an improved matching with respect to the pre-procedural configuration. In terms of computational burden, the fast integration approach allowed a consistent reduction of the computational times, which decreased from 36 h to 21.8 min per 100 K hexahedra. Our findings suggest that the proposed linear-elastic MSM model may provide good accuracy and reduced computational times for TAVI simulations, fostering its inclusion in clinical routines.

Study of Morpho-Geometric Variables to Improve the Diagnosis in Keratoconus with Mild Visual Limitation

The validation of new methods for the diagnosis of incipient cases of Keratoconus (KC) with mild visual limitation is of great interest in the field of ophthalmology. During the asymmetric progression of the disease, the current diagnostic indexes do not record the geometric decompensation of the corneal curvature nor the variation of the spatial profile that occurs in singular points of the cornea. The purpose of this work is to determine the structural characterization of the asymmetry of the disease by using morpho-geometric parameters in KC eyes with mild visual limitation including using an analysis of a patient-specific virtual model with the aid of computer-aided design (CAD) tools. This comparative study included 80 eyes of patients classified as mild KC according to the degree of visual limitation and a control group of 122 eyes of normal patients. The metric with the highest area under the receiver operating characteristic (ROC) curve was the posterior apex deviation. The most prominent correlation was found between the anterior and posterior deviations of the thinnest point for the mild keratoconic cases. This new custom computational approach provides the clinician with a three-dimensional view of the corneal architecture when the visual loss starts to impair.

An anisotropic constitutive model for immersogeometric fluid-structure interaction analysis of bioprosthetic heart valves

This paper considers an anisotropic hyperelastic soft tissue model, originally proposed for native valve tissue and referred to herein as the Lee-Sacks model, in an isogeometric thin shell analysis framework that can be readily combined with immersogeometric fluid-structure interaction (FSI) analysis for high-fidelity simulations of bioprosthetic heart valves (BHVs) interacting with blood flow. We find that the Lee-Sacks model is well-suited to reproduce the anisotropic stress-strain behavior of the cross-linked bovine pericardial tissues that are commonly used in BHVs. An automated procedure for parameter selection leads to an instance of the Lee-Sacks model that matches biaxial stress-strain data from the literature more closely, over a wider range of strains, than other soft tissue models. The relative simplicity of the Lee-Sacks model is attractive for computationally-demanding applications such as FSI analysis and we use the model to demonstrate how the presence and direction of material anisotropy affect the FSI dynamics of BHV leaflets.