Simulation of transcatheter aortic valve implantation: a patient-specific finite element approach

Finite Element Analysis of Evolut Transcatheter Heart Valves: Effects of Aortic Geometries and Valve Sizes on Post-TAVI Wall Stresses and Deformations

Background/Objectives: For transcatheter aortic valve implantation (TAVI) therapy, a catheter-guided crimped valve is deployed into the aortic root. Valve types such as Edwards balloon-expandable valves and Medtronic self-expandable valves come in different sizes and are chosen based on patient-specific aortic anatomy, including aortic root diameter measurement. Complications may arise due to variations in anatomical characteristics and the implantation procedure, making pre-implantation assessment important for predicting complications. Methods: Computational modeling, particularly finite element analysis (FEA), has become popular for assessing wall stresses and deformations in TAVI. In this study, a finite element model including the aorta, native leaflets, and TAVI device was used to simulate procedures and assess patient-specific wall stresses and deformations. Results: Using the Medtronic Evolut R valve, we simulated TAVI for 14 patients to analyze the effects of geometrical variations on structural stresses. Virtual TAVIs with different valve sizes were also simulated to study the influence of TAV size on stresses. Our results show that variations in aortic wall geometries and TAV sizes significantly influence wall stresses and deformations. Conclusions: Our study is one of the first comprehensive FEA investigations of aortic geometrical variations and valve sizes on post-TAVI stresses, demonstrating the non-linear relationship between aortic dimensions, TAV sizes, and wall stresses.

Material modeling and recent findings in transcatheter aortic valve implantation simulations

BACKGROUND AND OBJECTIVE

Transcatheter aortic valve implantation (TAVI) has significantly transformed the management of aortic valve (AV) diseases, presenting a minimally invasive option compared to traditional surgical valve replacement. Computational simulations of TAVI become more popular and offer a detailed investigation by employing patient-specific models. On the other hand, employing accurate material modeling procedures and applying basic modeling steps are crucial to determining reliable numerical results. Therefore, this review aims to outline the basic modeling approaches for TAVI, focusing on material modeling and geometry extraction, as well as summarizing the important findings from recent computational studies to guide future research in the field.

METHODS

This paper explains the basic steps and important points in setting up and running TAVI simulations. The material properties of the leaflets, valves, stents, and tissues utilized in TAVI simulations are provided, along with a comprehensive explanation of the geometric extraction methods employed. The differences between the finite element analysis, computational fluid dynamics, and fluid-structure interaction approaches are pointed out and the important aspects of TAVI modeling are described by elucidating the recent computational studies.

RESULTS

The results of the recent findings on TAVI simulations are summarized to demonstrate its powerful potential. It is observed that the material properties of aortic tissues and components of implanted valves should be modeled realistically to determine accurate results. For patient-specific AV geometries, incorporating calcific deposits on the leaflets is essential for ensuring the accuracy of computational findings. The results of numerical TAVI simulations indicate the significance of the selection of optimal valves and precise deployment within the appropriate anatomical position. These factors collectively contribute to the effective functionality of the implanted valve.

CONCLUSIONS

Recent studies in the literature have revealed the critical importance of patient-specific modeling, the selection of accurate material models, and bio-prosthetic valve diameters. Additionally, these studies emphasize the necessity of precise positioning of bio-prosthetic valves to achieve optimal performance in TAVI, characterized by an increased effective orifice area and minimal paravalvular leakage.

Effect of bioprosthetic leaflet anisotropy on stent dynamics of Transcatheter Aortic Valve Replacement devices

The assessment of stent fatigue in Transcatheter Aortic Valve Replacement (TAVR) systems is critical for the design of next-generation devices, both in vitro and in vivo. The mechanical properties of the bioprosthetic heart valves (BHVs) have a significant impact on the fatigue life of the metallic stent and thus must be taken into consideration when evaluating new TAVR device designs. This study aims to investigate the relationship between BHV anisotropic behaviour and the asymmetric deflections of the stent frame observed during in vitro testing. An explicit dynamics finite element model of the nitinol stent with attached bioprosthetic valve leaflets was developed to evaluate the deflections of the TAVR device under haemodynamic loading. Our results demonstrate that pericardium behaviour plays a dominant role in determining stent frame deflection. The anisotropic behaviour of the leaflets, resulting from collagen fibre orientation, affects the extent of deflection encountered by each commissure of the frame. This leads to asymmetric variation in frame deflection that can influence the overall fatigue life of the nitinol stent. This study highlights the importance of considering both the flexible nature of the metallic stent as well as the leaflet anisotropic behaviour in the design and fatigue assessment of TAVR systems.

Parameterization, algorithmic modeling, and fluid-structure interaction analysis for generative design of transcatheter aortic valves

Heart valves play a critical role in maintaining proper cardiovascular function in the human heart; however, valve diseases can lead to improper valvular function and reduced cardiovascular performance. Depending on the extent and severity of the valvular disease, replacement operations are often required to ensure that the heart continues to operate properly in the cardiac system. Transcatheter aortic valve replacement (TAVR) procedures have recently emerged as a promising alternative to surgical replacement approaches because the percutaneous methods used in these implant operations are significantly less invasive than open heart surgery. Despite the advantages of transcatheter devices, the precise deployment, proper valve sizing, and stable anchoring required to securely place these valves in the aorta remain challenging even in successful TAVR procedures. This work proposes a parametric modeling approach for transcatheter heart valves (THVs) that enables flexible valvular development and sizing to effectively generate existing and novel valve designs. This study showcases two THV configurations that are analyzed using an immersogeometric fluid-structure interaction (IMGA FSI) framework to demonstrate the influence of geometric changes on THV performance. The proposed modeling framework illustrates the impact of these features on THV behavior and indicates the effectiveness of parametric modeling approaches for enhancing THV performance and efficacy in the future.

A fast in silico model for preoperative risk assessment of paravalvular leakage

In silico simulations can be used to evaluate and optimize the safety, quality, efficacy and applicability of medical devices. Furthermore, in silico modeling is a powerful tool in therapy planning to optimally tailor treatment for each patient. For this purpose, a workflow to perform fast preoperative risk assessment of paravalvular leakage (PVL) after transcatheter aortic valve replacement (TAVR) is presented in this paper. To this end, a novel, efficient method is introduced to calculate the regurgitant volume in a simplified, but sufficiently accurate manner. A proof of concept of the method is obtained by comparison of the calculated results with results obtained from in vitro experiments. Furthermore, computational fluid dynamics (CFD) simulations are used to validate more complex stenosis scenarios. Comparing the simplified leakage model to CFD simulations reveals its potential for procedure planning and qualitative preoperative risk assessment of PVL. Finally, a 3D device deployment model and the efficient leakage model are combined to showcase the application of the presented leakage model, by studying the effect of stent size and the degree of stenosis on the regurgitant volume. The presented leakage model is also used to visualize the leakage path. To generalize the leakage model to a wide range of clinical applications, further validation on a large cohort of patients is needed to validate the accuracy of the model's prediction under various patient-specific conditions.

Reduced Order Modeling for Real-Time Stent Deformation Simulations of Transcatheter Aortic Valve Prostheses

Computational modeling can be a critical tool to predict deployment behavior for transcatheter aortic valve replacement (TAVR) in patients with aortic stenosis. However, due to the mechanical complexity of the aortic valve and the multiphysics nature of the problem, described by partial differential equations (PDEs), traditional finite element (FE) modeling of TAVR deployment is computationally expensive. In this preliminary study, a PDEs-based reduced order modeling (ROM) framework is introduced for rapidly simulating structural deformation of the Medtronic Evolut R valve stent frame. Using fifteen probing points from an Evolut model with parametrized loads enforced, 105 FE simulations were performed in the so-called offline phase, creating a snapshot library. The library was used in the online phase of the ROM for a new set of applied loads via the proper orthogonal decomposition-Galerkin (POD-Galerkin) approach. Simulations of small radial deformations of the Evolut stent frame were performed and compared to full order model (FOM) solutions. Linear elastic and hyperelastic constitutive models in steady and unsteady regimes were implemented within the ROM. Since the original POD-Galerkin method is formulated for linear problems, specific methods for the nonlinear terms in the hyperelastic case were employed, namely, the Discrete Empirical Interpolation Method. The ROM solutions were in strong agreement with the FOM in all numerical experiments, with a speed-up of at least 92% in CPU Time. This framework serves as a first step toward real-time predictive models for TAVR deployment simulations.

Computational study of the balloon dilation steps on transcatheter aortic valve replacement

Balloon dilation is a commonly used assistant method in transcatheter aortic valve replacement (TAVR) and plays an important role during valve implantation procedure. The balloon dilation steps need to be fully considered in TAVR numerical simulations. This study aims to establish a TAVR simulation procedure with two different balloon dilation steps to analyze the impact of balloon dilation on the results of TAVR implantation. Two cases of aortic stenosis were constructed based on medical images. An implantation simulation procedure with self-expandable valve was established, and multiple models including different simulation steps such as balloon pre-dilation and balloon post-dilation were constructed to compare the different effects on vascular stress, stent morphology and paravalvular leakage. Results show that balloon pre-dilation of TAVR makes less impact on post-operative outcomes, while post-dilation can effectively improve the implantation morphology of the stent, which is beneficial to the function and durability of the valve. It can effectively improve the adhesion of the stent and reduce the paravalvular leakage volume more than 30% after implantation. However, balloon post-dilation may also lead to about 20% or more increased stress on the aorta and increase the risk of damage. The balloon dilation makes an important impact on the TAVR outcomes. Balloon dilation needs to be fully considered during pre-operative analysis to obtain a better clinical result.

Calibration of the Mechanical Boundary Conditions for a Patient-Specific Thoracic Aorta Model Including the Heart Motion Effect

OBJECTIVE

We propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect.

METHODS

We first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI. A rigid-wall fluid-dynamic simulation is performed to derive the time-varying wall pressure field. We build the finite element model considering patient-specific material properties and imposing the derived pressure field and the motion at the annulus boundary. The calibration, which involves the zero-pressure state computation, is based on purely structural simulations. After obtaining the vessel boundaries from the cine-MRI sequences, an iterative procedure is performed to minimize the distance between them and the corresponding boundaries derived from the deformed structural model. A strongly-coupled fluid-structure interaction (FSI) analysis is finally performed with the tuned parameters and compared to the purely structural simulation.

RESULTS AND CONCLUSION

The calibration with structural simulations allows to reduce maximum and mean distances between image-derived and simulation-derived boundaries from 8.64 mm to 6.37 mm and from 2.24 mm to 1.83 mm, respectively. The maximum root mean square error between the deformed structural and FSI surface meshes is 0.19 mm. This procedure may prove crucial for increasing the model fidelity in replicating the real aortic root kinematics.

Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed Tomography

BACKGROUND

To propose a deep learning architecture for automatically detecting the complex structure of the aortic annulus plane using cardiac computed tomography (CT) for transcatheter aortic valve replacement (TAVR).

METHODS

This study retrospectively reviewed consecutive patients who underwent TAVR between January 2017 and July 2020 at a tertiary medical center. Annulus Detection Permuted AdaIN network (ADPANet) based on a three-dimensional (3D) U-net architecture was developed to detect and localize the aortic annulus plane using cardiac CT. Patients (N = 72) who underwent TAVR between January 2017 and July 2020 at a tertiary medical center were enrolled. Ground truth using a limited dataset was delineated manually by three cardiac radiologists. Training, tuning, and testing sets (70:10:20) were used to build the deep learning model. The performance of ADPANet for detecting the aortic annulus plane was analyzed using the root mean square error (RMSE) and dice similarity coefficient (DSC).

RESULTS

In this study, the total dataset consisted of 72 selected scans from patients who underwent TAVR. The RMSE and DSC values for the aortic annulus plane using ADPANet were 55.078 ± 35.794 and 0.496 ± 0.217, respectively.

CONCLUSION

Our deep learning framework was feasible to detect the 3D complex structure of the aortic annulus plane using cardiac CT for TAVR. The performance of our algorithms was higher than other convolutional neural networks.

PyTorch-FEA: Autograd-enabled finite element analysis methods with applications for biomechanical analysis of human aorta

BACKGROUND AND OBJECTIVES

Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed.

METHODS

In this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance.

RESULTS

We applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.

CONCLUSIONS

We have presented PyTorch-FEA, a new library of FEA code and methods, representing a new approach to develop FEA methods to forward and inverse problems in solid mechanics. PyTorch-FEA eases the development of new inverse methods and enables a natural integration of FEA and DNNs, which will have numerous potential applications.

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.

Biomechanical performance of the Bicaval Transcatheter System for the treatment of severe tricuspid regurgitation

Introduction: Tricuspid regurgitation (TR) is a relatively common valvular disease, which can result from structural abnormalities of any anatomic part of the tricuspid valve. Severe TR is linked to congestive heart failure and hemodynamic impairment, resulting in high mortality when repaired by elective surgery. This study was undertaken to quantify the structural and hemodynamic performance of the novel Transcatheter Bicaval Valves System (TricValve) percutaneously implanted in the superior vena cava (SVC) and inferior vena cava (IVC) of two patients with severe TR and venous congestion. Methods: After developing the SVC and IVC device models, the contact pressure exerted on the vena cava wall was obtained by computational analysis. Both smoothed-particle hydrodynamics (SPH) and computational fluid dynamics were carried out to quantify caval reflux in the right atrium and the pressure field of pre- and post-TricValve scenarios, respectively. Results: Analysis of contact pressure highlighted the main anchoring area of the SVC device occurring near the SVC device belly, while the IVC device exerted pronounced forces in the device's proximal and distal parts. SPH-related flow velocities revealed the absence of caval reflux, and a decrease in time-averaged pressure was observed near the SVC and IVC after TricValve implantation. Discussion: Findings demonstrated the potential of computational tools for enhancing our understanding of the biomechanical performance of structural tricuspid valve interventions and improving the way we design next-generation transcatheter therapies to treat the tricuspid valve with heterotopic caval valve implantation.

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.

PyTorch-FEA: Autograd-enabled Finite Element Analysis Methods with Applications for Biomechanical Analysis of Human Aorta

Motivation

Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed.

Methods

In this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance.

Results

We applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.

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.

Biomechanics of Transcatheter Aortic Valve Implant

Transcatheter aortic valve implantation (TAVI) has grown exponentially within the cardiology and cardiac surgical spheres. It has now become a routine approach for treating aortic stenosis. Several concerns have been raised about TAVI in comparison to conventional surgical aortic valve replacement (SAVR). The primary concerns regard the longevity of the valves. Several factors have been identified which may predict poor outcomes following TAVI. To this end, the lesser-used finite element analysis (FEA) was used to quantify the properties of calcifications which affect TAVI valves. This method can also be used in conjunction with other integrated software to ascertain the functionality of these valves. Other imaging modalities such as multi-detector row computed tomography (MDCT) are now widely available, which can accurately size aortic valve annuli. This may help reduce the incidence of paravalvular leaks and regurgitation which may necessitate further intervention. Structural valve degeneration (SVD) remains a key factor, with varying results from current studies. The true incidence of SVD in TAVI compared to SAVR remains unclear due to the lack of long-term data. It is now widely accepted that both are part of the armamentarium and are not mutually exclusive. Decision making in terms of appropriate interventions should be undertaken via shared decision making involving heart teams.

Comparison of Balloon-Expandable Valve and Self-Expandable Valve in Transcatheter Aortic Valve Replacement: A Patient-Specific Numerical Study

Transcatheter aortic valve replacement (TAVR) is a minimally invasive strategy for the treatment of aortic stenosis. The complex post-operative complications of TAVR were related to the type of implanted prosthetic valve, and the deep mechanism of this relationship may guide the clinical pre-operative planning. The purpose of this study was to develop a numerical method of TAVR to compare the outcome difference between balloon-expandable valve and self-expandable valve and predict the post-operative results. A complete patient-specific aortic model was reconstructed. Two prosthetic valves (balloon-expandable valve and self-expandable valve) were introduced to simulate the implantation procedure, and post-procedural function was studied with fluid-structure interaction method, respectively. Results showed similar stress distribution for two valves, but higher peak stress for balloon-expandable valve model. Compared with the self-expandable valve, the balloon-expandable valve was associated with a better circular cross-section and smaller paravalvular gaps area. Hemodynamic parameters like cardiac output, mean transvalvular pressure difference and effective orifice area (EOA) of the balloon-expandable valve model were better than those of the self-expandable valve model. Significant outcome difference was found for two prosthetic valves. Balloon-expandable valve may effectively decrease the risk and degree of post-operative paravalvular leak, while self-expandable valve was conducive to lower stroke risk due to lower aortic stress. The numerical TAVR simulation process may become an assistant tool for prosthesis selection in pre-operative planning and post-operative prediction.

Improving transcatheter aortic valve interventional predictability via fluid-structure interaction modelling using patient-specific anatomy

Transcatheter aortic valve replacement (TAVR) is now a standard treatment for high-surgical-risk patients with severe aortic valve stenosis. TAVR is being explored for broader indications including degenerated bioprosthetic valves, bicuspid valves and for aortic valve (AV) insufficiency. It is, however, challenging to predict whether the chosen valve size, design or its orientation would produce the most-optimal haemodynamics in the patient. Here, we present a novel patient-specific evaluation framework to realistically predict the patient's AV performance with a high-fidelity fluid-structure interaction analysis that included the patient's left ventricle and ascending aorta (AAo). We retrospectively evaluated the pre- and post-TAVR dynamics of a patient who underwent a 23 mm TAVR and evaluated against the patient's virtually de-calcified AV serving as a hypothetical benchmark. Our model predictions were consistent with clinical data. Stenosed AV produced a turbulent flow during peak-systole, while aortic flow with TAVR and de-calcified AV were both in the laminar-to-turbulent transitional regime with an estimated fivefold reduction in viscous dissipation. For TAVR, dissipation was highest during early systole when valve deformation was the greatest, suggesting that an efficient valve opening may reduce energy loss. Our study demonstrates that such patient-specific modelling frameworks can be used to improve predictability and in the planning of AV interventions.

Leaflet Stresses During Full Device Simulation of Crimping to 6 mm in Transcatheter Aortic Valve Implantation, TAVI

BACKGROUND

With continuing growth in transcatheter aortic valve implantation for the treatment of a failing aortic valve, there is increasing interest in prosthetic valve durability and the potential damage caused to leaflets by stress. Whilst most available research into the computational prediction of leaflet stresses using finite element analysis, FEA, has focussed on variations during dynamic loading, very little appears to have been reported for the impact of crimping, even though awareness of this effect is widespread. Potentially, this has been due to the difficulty of performing full model simulations of crimping to clinically meaningful diameters.

METHOD

A full model comprising a self-expanding frame, skirt and leaflets has been developed and crimped to a final diameter of 6 mm. A detailed description is provided of the FEA setup, emphasising the importance of the skirt definition needed to successfully crimp to this small diameter. Then, an analysis of leaflet folding and stresses is presented, particularly with respect to the differences produced between leaflet thicknesses of 0.20, 0.25 and 0.30 mm and for bioprosthetic and polymeric leaflet material models.

RESULTS

In all cases, peak stresses occurred close to the modelled suture lines joining the leaflets and the skirt and high stresses were also present along axially aligned folds in the leaflets. Stresses were lower for the polymeric leaflets.

CONCLUSION

Successful simulation of crimping requires a finely resolved skirt mesh. Leaflet stresses during crimping are dependent on leaflet thickness, material properties and the ratio of leaflet volume to the available volume inside the crimped valve.

Simple 2-dimensional anatomic model to predict the risk of coronary obstruction during transcatheter aortic valve replacement

OBJECTIVE

In this study, a 2-dimensional (2D) index relying on preprocedural computed tomography (CT) data was developed to evaluate the risk of coronary obstruction during transcatheter aortic valve replacement (TAVR) procedures.

METHODS

Anatomic measurements from pre-TAVR CT scans were collected in 28 patients among 600 who were flagged as high risk (defined as meeting coronary artery height, h, <14 mm and/or sinus of Valsalva diameter, SOVd, <30 mm) for coronary obstruction. A geometric model derived from these anatomic measurements was used to predict the post-TAVR native cusp apposition relative to the coronary ostium. The distance from the cusp to the coronary ostium, DLC2D, was measured from the geometric model and indexed with the coronary artery diameter, d, to yield a fractional obstruction measure, DLC2D/d.

RESULTS

Twenty-three of 28 high-risk patients successfully underwent TAVR without coronary obstruction, of whom 1 had coronary obstruction and 4 were deemed non-TAVR candidates. DLC2D/d differed significantly between the 2 groups (P < .0018), but neither h nor SOVd did (P > .32). The optimal sensitivity and specificity for DLC2D/d were 85% and occurred at a cutoff of 0.45. The optimal sensitivity and specificity of h and SOVd in this high-risk group were only 60% and 40%, respectively, for cutoffs of h = 10 mm and SOVd = 30.5 mm.

CONCLUSIONS

The 2D geometric model derived in this study shows promise for identifying patients with low-lying coronary ostium and/or small SOVd that may be safely treated with TAVR. DLC2D/d is more predictive of obstruction or poor TAVR candidacy compared with h and SOVd.

Effect of Valve Height on the Opening and Closing Performance of the Aortic Valve Under Aortic Root Dilatation

Patients with aortic valve disease can suffer from valve insufficiency after valve repair surgery due to aortic root dilatation. The paper investigates the effect of valve height (Hv) on the aortic valve opening and closing in order to select the appropriate range of Hv for smoother blood flow through the aortic valve and valve closure completely in the case of continuous aortic root dilatation. A total of 20 parameterized three-dimensional models of the aortic root were constructed following clinical surgical guidance. Aortic annulus diameter (DAA) was separately set to 26, 27, 28, 29, and 30 mm to simulate aortic root dilatation. H_V value was separately set to 13.5, 14, 14.5, and 15 mm to simulate aortic valve alterations in surgery. Time-varying pressure loads were applied to the valve, vessel wall of the ascending aorta, and left ventricle. Then, finite element analysis software was employed to simulate the movement and mechanics of the aortic root. The feasible design range of the valve size was evaluated using maximum stress, geometric orifice area (GOA), and leaflet contact force. The results show that the valve was incompletely closed when H_V was 13.5 mm and D_AA was 29 or 30 mm. The GOA of the valve was small when H_V was 15 mm and D_AA was 26 or 27 mm. The corresponding values of the other models were within the normal range. Compared with the model with an H_V of 14 mm, the model with an H_V of 14.5 mm could effectively reduce maximum stress and had relatively larger GOA and less change in contact force. As a result, valve height affects the performance of aortic valve opening and closing. Smaller H_V is adapted to smaller D_AA and vice versa. When H_V is 14.5 mm, the valve is well adapted to the dilatation of the aortic root to enhance repair durability. Therefore, more attention should be paid to H_V in surgical planning.

Transcatheter Heart Valve Implantation in Bicuspid Patients with Self-Expanding Device

Bicuspid aortic valve (BAV) patients are conventionally not treated by transcathether aortic valve implantation (TAVI) because of anatomic constraint with unfavorable outcome. Patient-specific numerical simulation of TAVI in BAV may predict important clinical insights to assess the conformability of the transcathether heart valves (THV) implanted on the aortic root of members of this challenging patient population. We aimed to develop a computational approach and virtually simulate TAVI in a group of n.6 stenotic BAV patients using the self-expanding Evolut Pro THV. Specifically, the structural mechanics were evaluated by a finite-element model to estimate the deformed THV configuration in the oval bicuspid anatomy. Then, a fluid–solid interaction analysis based on the smoothed-particle hydrodynamics (SPH) technique was adopted to quantify the blood-flow patterns as well as the regions at high risk of paravalvular leakage (PVL). Simulations demonstrated a slight asymmetric and elliptical expansion of the THV stent frame in the BAV anatomy. The contact pressure between the luminal aortic root surface and the THV stent frame was determined to quantify the device anchoring force at the level of the aortic annulus and mid-ascending aorta. At late diastole, PVL was found in the gap between the aortic wall and THV stent frame. Though the modeling framework was not validated by clinical data, this study could be considered a further step towards the use of numerical simulations for the assessment of TAVI in BAV, aiming at understanding patients not suitable for device implantation on an anatomic basis.

Transcatheter aortic valve replacement in bicuspid valves: The synergistic effects of eccentric and incomplete stent deployment

Bicuspid aortic valve is a congenital cardiac anomaly and common etiology of aortic stenosis. Given the positive outcomes of transcatheter aortic valve replacement (TAVR) in low-risk patients, TAVR will become more prevalent in the future in the treatment of severe bicuspid valve stenosis. However, asymmetrical bicuspid valve anatomy and calcification can prevent the circular and complete expansion of transcatheter aortic valves (TAVs). In previous studies, examining the impact of elliptical TAV deployment on leaflet stress distribution, asymmetric expansion of balloon-expandable intra-annular devices was studied up to an ellipticity index (long/short TAV diameter) of 1.4. However, such a high degree of eccentricity has not been observed in clinical studies with balloon-expandable devices. High degrees of stent eccentricity have been observed in self-expanding TAVs, such as CoreValve. However, CoreValve is a supra-annular device, and it was not clear if eccentric and incomplete stent deployment at the annulus would alter leaflet stress and strain distributions. This study aimed to assess the effects of eccentric and incomplete stent deployment of CoreValves in bicuspid aortic valves and compare the results to that of SAPIEN 3. Leaflet stress distribution and leaflet kinematics of 26-mm CoreValve and 26-mm SAPIEN 3 devices in bicuspid valves were obtained in a range that was observed in previous clinical studies. The results indicated that elliptical and incomplete stent deployment of TAVs increase leaflet stress and impair leaflet kinematics. The changes were more pronounced in CoreValve than SAPIEN 3. Increased leaflet stress can reduce long-term valve durability, and impaired leaflet kinematics can potentially increase blood stasis on the TAV leaflets. The study provides complementary insights into the mechanics of TAVs in bicuspid aortic valves.

CoreValve vs. Sapien 3 Transcatheter Aortic Valve Replacement: A Finite Element Analysis Study

Aim: to investigate the factors implied in the development of postoperative complications in both self-expandable and balloon-expandable transcatheter heart valves by means of finite element analysis (FEA). Materials and methods: FEA was integrated into CT scans to investigate two cases of postoperative device failure for valve thrombosis after the successful implantation of a CoreValve and a Sapien 3 valve. Data were then compared with two patients who had undergone uncomplicated transcatheter heart valve replacement (TAVR) with the same types of valves. Results: Computational biomechanical modeling showed calcifications persisting after device expansion, not visible on the CT scan. These calcifications determined geometrical distortion and elliptical deformation of the valve predisposing to hemodynamic disturbances and potential thrombosis. Increased regional stress was also identified in correspondence to the areas of distortion with the associated paravalvular leak. Conclusion: the use of FEA as an adjunct to preoperative imaging might assist patient selection and procedure planning as well as help in the detection and prevention of TAVR complications.

Effect of percutaneous aortic valve position on stress map in ascending aorta: A fluid-structure interaction analysis

Transcatheter aortic valve implantation (TAVI) is an increasingly widespread procedure. Although this intervention is indicated for high and low surgical risk patients, some issues still remain, such as prosthesis positioning optimization in the aortic annulus. Coaxial positioning of the percutaneous prosthesis influences directly on the aortic wall stress map. The determination of the mechanical stress that acts on the vascular endothelium resulting from blood flow can be considered an important task, since TAVI positioning can lead to unfavorable hemodynamic patterns, resulting in changes in parietal stress, such as those found in post-stenotic dilatation region. This research aims to investigate the influence of the prosthetic valve inclination angle in the mechanical stresses acting in the ascending aortic wall. Aortic compliance and blood flow during cardiac cycle were numerically obtained using fluid structure interaction. The aortic model was developed through segmentation of a computed tomography image of a specific patient submitted to TAVI. When compared to standard position (coaxiality match between the prosthesis and the aortic annulus), the inclination of 4° directed to the left main coronary artery decreased the aortic wall area with high values of wall shear stress and pressure. Coaxial positioning optimization of percutaneous aortic prosthesis may decrease the high mechanical stress area. These changes may be important to reduce the aortic remodeling process, vascular calcification or even the prosthesis half-life. Computational fluid dynamics makes room for personalized medicine, with manufactured prosthesis tailored to each patient.

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.

3D Printing, Computational Modeling, and Artificial Intelligence for Structural Heart Disease

Structural heart disease (SHD) is a new field within cardiovascular medicine. Traditional imaging modalities fall short in supporting the needs of SHD interventions, as they have been constructed around the concept of disease diagnosis. SHD interventions disrupt traditional concepts of imaging in requiring imaging to plan, simulate, and predict intraprocedural outcomes. In transcatheter SHD interventions, the absence of a gold-standard open cavity surgical field deprives physicians of the opportunity for tactile feedback and visual confirmation of cardiac anatomy. Hence, dependency on imaging in periprocedural guidance has led to evolution of a new generation of procedural skillsets, concept of a visual field, and technologies in the periprocedural planning period to accelerate preclinical device development, physician, and patient education. Adaptation of 3-dimensional (3D) printing in clinical care and procedural planning has demonstrated a reduction in early-operator learning curve for transcatheter interventions. Integration of computation modeling to 3D printing has accelerated research and development understanding of fluid mechanics within device testing. Application of 3D printing, computational modeling, and ultimately incorporation of artificial intelligence is changing the landscape of physician training and delivery of patient-centric care. Transcatheter structural heart interventions are requiring in-depth periprocedural understanding of cardiac pathophysiology and device interactions not afforded by traditional imaging metrics.

Using Discrete Multiphysics Modelling to Assess the Effect of Calcification on Hemodynamic and Mechanical Deformation of Aortic Valve

This study proposes a 3D particle-based (discrete) multiphysics approach for modelling calcification in the aortic valve. Different stages of calcification (from mild to severe) were simulated, and their effects on the cardiac output were assessed. The cardiac flow rate decreases with the level of calcification. In particular, there is a critical level of calcification below which the flow rate decreases dramatically. Mechanical stress on the membrane is also calculated. The results show that, as calcification progresses, spots of high mechanical stress appear. Firstly, they concentrate in the regions connecting two leaflets; when severe calcification is reached, then they extend to the area at the basis of the valve.

Pre-Operative Modeling of Transcatheter Mitral Valve Replacement in a Surgical Heart Valve Bioprosthesis

Obstruction of the left ventricular outflow tract (LVOT) is a common complication of transcatheter mitral valve replacement (TMVR). This procedure can determine an elongation of an LVOT (namely, the neo-LVOT), ultimately portending hemodynamic impairment and patient death. This study aimed to understand the biomechanical implications of LVOT obstruction in a patient who underwent TMVR using a transcatheter heart valve (THV) to repair a failed bioprosthetic heart valve. We first reconstructed the heart anatomy and the bioprosthetic heart valve to virtually implant a computer-aided-design (CAD) model of THV and evaluate the neo-LVOT area. A numerical simulation of THV deployment was then developed to assess the anchorage of the THV to the bioprosthetic heart valve as well as the resulting Von Mises stress at the mitral annulus and the contract pressure among implanted bioprostheses. Quantification of neo-LVOT and THV deployment may facilitate more accurate predictions of the LVOT obstruction in TMVR and help clinicians in the optimal choice of the THV size.

Modeling risk of coronary obstruction during transcatheter aortic valve replacement

OBJECTIVE

In this study we aimed to evaluate risk of coronary obstruction during transcatheter aortic valve replacement and develop improved criteria based on computational modeling.

METHODS

Patient specific 3-dimensional models were constructed and validated for 28 patients out of 600 patients who were flagged as high risk for coronary obstruction (defined as meeting coronary ostium height < 14 mm and/or sinus of Valsalva diameter [SOVd] < 30 mm). The models consisted finite element analysis to predict the post- transcatheter aortic valve replacement native cusp apposition relative to the coronary ostium and were validated in vitro. The distance from cusp to coronary ostium (DLC) was derived from the 3-dimensional models and indexed with the coronary artery diameter to yield a fractional obstruction measure (DLC/d).

RESULTS

Twenty-two out of 28 high-risk patients successfully underwent transcatheter aortic valve replacement without coronary obstruction and 6 did not. DLC/d between the 2 groups was significantly different (P < .00078), whereas neither coronary ostium height nor SOVd were significantly different (P > .32). A cutoff of DLC/d < 0.7 was predictive with 100% sensitivity and 95.7% specificity. The optimal sensitivity and specificity of coronary ostium height and SOVd in this high-risk group was only 60% and 40%, respectively, for cutoff coronary ostium height of 10 mm and SOVd of 30.5 mm.

CONCLUSIONS

Three-dimensional modeling has the potential to enable more patients to be safely treated with transcatheter aortic valve replacement who have a low-lying coronary ostium or small SOVd. DLC/d is more predictive of obstruction than coronary ostium height and SOVd.

A biomechanical model of the pathological aortic valve: simulation of aortic stenosis

Aortic stenosis (AS) disease is a narrowing of the aortic valve (AV) opening which reduces blood flow from the heart causing several health complications. Although a lot of work has been done in AV simulations, most of the efforts have been conducted regarding healthy valves. In this article, a new three-dimensional patient-specific biomechanical model of the valve, based on a parametric formulation of the stenosis that permits the simulation of different degrees of pathology, is presented. The formulation is based on a double approach: the first one is done from the geometric point of view, reducing the effective ejection area of the AV by joining leaflets using a zipper effect to sew them; the second one, in terms of functionality, is based on the modification of AV tissue properties due to the effect of calcifications. Both healthy and stenotic valves were created using patient-specific data and results of the numerical simulation of the valve function are provided. Analysis of the results shows a variation in the first principal stress, geometric orifice area, and blood velocity which were validated against clinical data. Thus, the possibility to create a pipeline which allows the integration of patient-specific data from echocardiographic images and iFR studies to perform finite elements analysis is proved.

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.

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.

Numerical Parametric Study of Paravalvular Leak Following a Transcatheter Aortic Valve Deployment Into a Patient-Specific Aortic Root

Paravalvular leak (PVL) is a relatively frequent complication after transcatheter aortic valve replacement (TAVR) with increased mortality. Currently, there is no effective method to pre-operatively predict and prevent PVL. In this study, we developed a computational model to predict the severity of PVL after TAVR. Nonlinear finite element (FE) method was used to simulate a self-expandable CoreValve deployment into a patient-specific aortic root, specified with human material properties of aortic tissues. Subsequently, computational fluid dynamics (CFD) simulations were performed using the post-TAVR geometries from the FE simulation, and a parametric investigation of the impact of the transcatheter aortic valve (TAV) skirt shape, TAV orientation, and deployment height on PVL was conducted. The predicted PVL was in good agreement with the echocardiography data. Due to the scallop shape of CoreValve skirt, the difference of PVL due to TAV orientation can be as large as 40%. Although the stent thickness is small compared to the aortic annulus size, we found that inappropriate modeling of it can lead to an underestimation of PVL up to 10 ml/beat. Moreover, the deployment height could significantly alter the extent and the distribution of regurgitant jets, which results in a change of leaking volume up to 70%. Further investigation in a large cohort of patients is warranted to verify the accuracy of our model. This study demonstrated that a rigorously developed patient-specific computational model can provide useful insights into underlying mechanisms causing PVL and potentially assist in pre-operative planning for TAVR to minimize PVL.

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.

The Impact of Size and Position of a Mechanical Expandable Transcatheter Aortic Valve: Novel Insights Through Computational Modelling and Simulation

Transcatheter aortic valve implantation has become an established procedure to treat severe aortic stenosis. Correct device sizing/positioning is crucial for optimal outcome. Lotus valve sizing is based upon multiple aortic root dimensions. Hence, it often occurs that two valve sizes can be selected. In this study, patient-specific computer simulation is adopted to evaluate the influence of Lotus size/position on paravalvular aortic regurgitation (AR) and conduction abnormalities, in patients with equivocal aortic root dimensions. First, simulation was performed in 62 patients to validate the model in terms of predicted AR and conduction abnormalities using postoperative echocardiographic, angiographic and ECG-based data. Then, two Lotus sizes were simulated at two positions in patients with equivocal aortic root dimensions. Large valve size and deep position were associated with higher contact pressure, while only large size, not position, significantly reduced the predicted AR. Despite general trends, simulations revealed that optimal device size/position is patient-specific.

Biomechanical modeling of transcatheter aortic valve replacement in a stenotic bicuspid aortic valve: deployments and paravalvular leakage

Calcific aortic valve disease (CAVD) is characterized by stiffened aortic valve leaflets. Bicuspid aortic valve (BAV) is the most common congenital heart disease. Transcatheter aortic valve replacement (TAVR) is a treatment approach for CAVD where a stent with mounted bioprosthetic valve is deployed on the stenotic valve. Performing TAVR in calcified BAV patients may be associated with post-procedural complications due to the BAV asymmetrical structure. This study aims to develop refined computational models simulating the deployments of Evolut R and PRO TAVR devices in a representative calcified BAV. The paravalvular leakage (PVL) was also calculated by computational fluid dynamics simulations. Computed tomography scan of severely stenotic BAV patient was acquired. The 3D calcium deposits were generated and embedded inside a parametric model of the BAV. Deployments of the Evolut R and PRO inside the calcified BAV were simulated in five bioprosthesis leaflet orientations. The hypothesis of asymmetric and elliptic stent deployment was confirmed. Positioning the bioprosthesis commissures aligned with the native commissures yielded the lowest PVL (15.7 vs. 29.5 mL/beat). The Evolut PRO reduced the PVL in half compared with the Evolut R (15.7 vs. 28.7 mL/beat). The proposed biomechanical computational model could optimize future TAVR treatment in BAV patients. Graphical abstract.

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex procedures to set up and long computing times to obtain final simulation results, preventing prompt feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed a deep learning (DL) model to directly estimate the stress distributions of the aorta. The DL model was designed and trained to take the input of FEA and directly output the aortic wall stress distributions, bypassing the FEA calculation process. The trained DL model is capable of predicting the stress distributions with average errors of 0.492% and 0.891% in the Von Mises stress distribution and peak Von Mises stress, respectively. This study marks, to our knowledge, the first study that demonstrates the feasibility and great potential of using the DL technique as a fast and accurate surrogate of FEA for stress analysis.

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.

Principles of TAVR valve design, modelling, and testing

INTRODUCTION

Transcatheter aortic valve replacement (TAVR) has emerged as an effective minimally-invasive alternative to surgical valve replacement in medium- to high-risk, elderly patients with calcific aortic valve disease and severe aortic stenosis. The rapid growth of the TAVR devices market has led to a high variety of designs, each aiming to address persistent complications associated with TAVR valves that may hamper the anticipated expansion of TAVR utility.

AREAS COVERED

Here we outline the challenges and the technical demands that TAVR devices need to address for achieving the desired expansion, and review design aspects of selected, latest generation, TAVR valves of both clinically-used and investigational devices. We further review in detail some of the up-to-date modeling and testing approaches for TAVR, both computationally and experimentally, and additionally discuss those as complementary approaches to the ISO 5840-3 standard. A comprehensive survey of the prior and up-to-date literature was conducted to cover the most pertaining issues and challenges that TAVR technology faces.

EXPERT COMMENTARY

The expansion of TAVR over SAVR and to new indications seems more promising than ever. With new challenges to come, new TAV design approaches, and materials used, are expected to emerge, and novel testing/modeling methods to be developed.

Pre-procedural fit-testing of TAVR valves using parametric modeling and 3D printing

BACKGROUND

Successful transcatheter aortic valve replacement (TAVR) requires an understanding of how a prosthetic valve will interact with a patient's anatomy in advance of surgical deployment. To improve this understanding, we developed a benchtop workflow that allows for testing of physical interactions between prosthetic valves and patient-specific aortic root anatomy, including calcified leaflets, prior to actual prosthetic valve placement.

METHODS

This was a retrospective study of 30 patients who underwent TAVR at a single high volume center. By design, the dataset contained 15 patients with a successful annular seal (defined by an absence of paravalvular leaks) and 15 patients with a sub-optimal seal (presence of paravalvular leaks) on post-procedure transthoracic echocardiogram (TTE). Patients received either a balloon-expandable (Edwards Sapien or Sapien XT, n = 15), or a self-expanding (Medtronic CoreValve or Core Evolut, n = 14, St. Jude Portico, n = 1) valve. Pre-procedural computed tomography (CT) angiograms, parametric geometry modeling, and multi-material 3D printing were utilized to create flexible aortic root physical models, including displaceable calcified valve leaflets. A 3D printed adjustable sizing device was then positioned in the aortic root models and sequentially opened to larger valve sizes, progressively flattening the calcified leaflets against the aortic wall. Optimal valve size and fit were determined by visual inspection and quantitative pressure mapping of interactions between the sizer and models.

RESULTS

Benchtop-predicted "best fit" valve size showed a statistically significant correlation with gold standard CT measurements of the average annulus diameter (n = 30, p < 0.0001 Wilcoxon matched-pairs signed rank test). Adequateness of seal (presence or absence of paravalvular leak) was correctly predicted in 11/15 (73.3%) patients who received a balloon-expandable valve, and in 9/15 (60%) patients who received a self-expanding valve. Pressure testing provided a physical map of areas with an inadequate seal; these corresponded to areas of paravalvular leak documented by post-procedural transthoracic echocardiography.

CONCLUSION

We present and demonstrate the potential of a workflow for determining optimal prosthetic valve size that accounts for aortic annular dimensions as well as the active displacement of calcified valve leaflets during prosthetic valve deployment. The workflow's open source framework offers a platform for providing predictive insights into the design and testing of future prosthetic valves.

Patient-specific simulation of guidewire deformation during transcatheter aortic valve implantation

Transcatheter aortic valve implantation is a recent mini-invasive procedure to implant an aortic valve prosthesis. Prosthesis positioning in transcatheter aortic valve implantation appears as an important aspect for the success of the intervention. Accordingly, we developed a patient-specific finite element framework to predict the insertion of the stiff guidewire, used to position the aortic valve. We simulated the guidewire insertion for 2 patients based on their pre-operative CT scans. The model was designed to primarily predict the position and the angle of the guidewires in the aortic valve, and the results were successfully compared with intraoperative images. The present paper describes extensively the numerical model, which was solved by using the ANSYS software with an implicit resolution scheme, as well as the stabilization techniques which were used to overcome numerical instabilities. We performed sensitivity analysis on the properties of the guidewire (curvature angle, curvature radius, and stiffness) and the conditions of insertion (insertion force and orientation). We also explored the influence of the model parameters. The accuracy of the model was quantitatively evaluated as the distance and the angle difference between the simulated guidewires and the intraoperative ones. A good agreement was obtained between the model predictions and intraoperative views available for 2 patient cases. In conclusion, we showed that the shape of the guidewire in the aortic valve was mainly determined by the geometry of the patient's aorta and by the conditions of insertion (insertion force and orientation).