Patient-specific simulation of transcatheter aortic valve replacement: impact of deployment options on paravalvular leakage

Assessing post-TAVR cardiac conduction abnormalities risk using an electromechanically coupled beating heart

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

Computational hemodynamic indices to identify Transcatheter Aortic Valve Implantation degeneration

BACKGROUND AND OBJECTIVES

Structural Valve Deterioration (SVD) is the main limiting factor to the long-term durability of the bioprosthetic valves used for Transcatheter Aortic Valve Implantation (TAVI), a minimally invasive technique for the treatment of severe aortic stenosis. The aim of this retrospective study is to perform patient-specific computational analyses of blood dynamics shortly after TAVI to identify hemodynamic indices that correlate with a premature onset of SVD which is detected at 5-10 years long-term follow-up exam after TAVI.

METHODS

The study population comprises fourteen patients: seven cases with SVD at long-term follow-up were identified and seven cases without SVD were randomly extracted from the same cohort. Starting from pre-operative CT images, we created trustworthy post-TAVI scenarios by virtually inserting the bioprosthetic valve (stent and leaflets) and we qualitatively validated such virtual scenarios against post-TAVI CT scans, when available. We then performed numerical simulations imposing personalized inlet conditions based on patient-specific Echo Doppler cardiac output measurements and the numerical results were post-processed to identify suitable hemodynamics indices with the aim of discriminating between the SVD and non-SVD groups of patients. In particular, differences in terms of each individual index were evaluated using a Wilcoxon rank-sum test. Moreover, we defined three synthetic scores, based on suitably scaled hemodynamic indices of stress and vorticity, evaluated in different contexts: on the leaflets, in the ascending aorta, and in the whole domain.

RESULTS

We found that the hemodynamic index related to leaflets' OSI individually shows statistically significant differences (p=0.007) between the SVD and non-SVD groups. Moreover, our proposed synthetic scores are able to clearly isolate the SVD group both in a two-dimensional space given by the aorta and leaflets scores and by only considering the global synthetic score.

CONCLUSION

The results of this computational study suggest that blood dynamics may play an important role in creating the conditions that lead to SVD. Moreover, the proposed synthetic scores could provide further indications for clinicians in assessing and predicting TAVI valves' long-term performance.

Computational evaluation of interactive dynamics for a full transcatheter aortic valve device in a patient-specific aortic root

Transcatheter aortic valve implantation (TAVI) has become a key treatment for severe aortic stenosis, especially for patients unsuitable for surgery. Since its introduction in 2002, TAVI has advanced significantly due to improvements in imaging, operator skills, and device engineering. Despite these innovations, challenges in device sizing and positioning remain, complicating outcome predictions. Computational modelling is a powerful tool to aid TAVI device design and to understand its interactive behaviour with the aortic root during the deployment. Previous studies often simplified tissue properties, neglected patient-specific geometries or omitted crucial elements such as leaflets and fabric. This paper presents a numerical framework capable of simulating the whole crimping and deployment process of a full TAVI device in a patient-specific aortic root including the native leaflets and calcifications. We conduct a comprehensive investigation into the mechanical behaviour of the TAVI and its interactions with patient-specific aortic root through dynamic finite element analysis during the deployment process, with validation against experimental results. Additionally, we examined the influence of applied pressure during balloon inflation on the interactive dynamics of the entire model. The study concludes that selecting optimal balloon pressures is crucial for enhancing TAVI device performance and reducing complications. Numerical simulations demonstrate that appropriate balloon pressure ensures sufficient flow area and effective contact pressure between the TAVI and the aortic root, while minimising deformation and the risk of paravalvular leak.

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.

Probing the limits and capabilities of diffusion models for the anatomic editing of digital twins

Numerical simulations of cardiovascular device deployment within digital twins of patient-specific anatomy can expedite and de-risk the device design process. Nonetheless, the exclusive use of patient-specific data constrains the anatomic variability that can be explored. We study how Latent Diffusion Models (LDMs) can edit digital twins to create digital siblings. Siblings can serve as the basis for comparative simulations, which can reveal how subtle anatomic variations impact device deployment, and augment virtual cohorts for improved device assessment. Using a case example centered on cardiac anatomy, we study various methods to generate digital siblings. We specifically introduce anatomic variation at different spatial scales or within localized regions, demonstrating the existence of bias toward common anatomic features. We furthermore leverage this bias for virtual cohort augmentation through selective editing, addressing issues related to dataset imbalance and diversity. Our framework delineates the capabilities of diffusion models in synthesizing anatomic variation for numerical simulation studies.

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.

Robust automated calcification meshing for personalized cardiovascular biomechanics

Calcification has significant influence over cardiovascular diseases and interventions. Detailed characterization of calcification is thus desired for predictive modeling, but calcium deposits on cardiovascular structures are still often manually reconstructed for physics-driven simulations. This poses a major bottleneck for large-scale adoption of computational simulations for research or clinical use. To address this, we propose an end-to-end automated image-to-mesh algorithm that enables robust incorporation of patient-specific calcification onto a given cardiovascular tissue mesh. The algorithm provides a substantial speed-up from several hours of manual meshing to ~1 min of automated computation, and it solves an important problem that cannot be addressed with recent template-based meshing techniques. We validated our final calcified tissue meshes with extensive simulations, demonstrating our ability to accurately model patient-specific aortic stenosis and Transcatheter Aortic Valve Replacement. Our method may serve as an important tool for accelerating the development and usage of personalized cardiovascular biomechanics.

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.

Computational study of transcatheter aortic valve replacement based on patient-specific models-rapid surgical planning for self-expanding valves

Transcatheter aortic valve replacement (TAVR) is a minimally invasive interventional solution for treating aortic stenosis. The complex post-TAVR complications are associated with the type of valve implanted and the position of the implantation. The study aimed to establish a rapid numerical research method for TAVR to assess the performance differences of self-expanding valves released at various positions. It also aimed to calculate the risks of postoperative paravalvular leak and atrioventricular conduction block, comparing these risks to clinical outcomes to verify the method's effectiveness and accuracy. Based on medical images, six cases were established, including the aortic wall, native valve and calcification; one with a bicuspid aortic valve and five with tricuspid aortic valves. The parameters for the stent materials used by the patients were customized. High strain in the contact area between the stent and the valve annulus may lead to atrioventricular conduction block. Postoperatively, the self-expanding valve maintained a circular cross-section, reducing the risk of paravalvular leak and demonstrating favorable hemodynamic characteristics, consistent with clinical observations. The outcomes of the six simulations showed no significant difference in valve frame morphology or paravalvular leak risk compared to clinical results, thereby validating the numerical simulation process proposed for quickly selecting valve models and optimal release positions, aiding in TAVR preoperative planning based on patients'geometric characteristics.

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.

Computational Investigation of Vessel Injury Due to Catheter Tracking During Transcatheter Aortic Valve Replacement

Catheter reaction forces during transcatheter valve replacement (TAVR) may result in injury to the vessel or plaque rupture, triggering distal embolization or thrombosis. In vitro test methods represent the arterial wall using synthetic proxies to determine catheter reaction forces during tracking, but whether they can account for reaction forces within the compliant aortic wall tissue in vivo is unknown. Moreover, the role of plaque inclusions is not well understood. Computational approaches have predicted the impact of TAVR positioning, migration, and leaflet distortion, but have not yet been applied to investigate aortic wall reaction forces and stresses during catheter tracking. In this study, we investigate the role that catheter design and aorta and plaque mechanical properties have on the risk of plaque rupture during TAVR catheter delivery. We report that, for trackability testing, a rigid test model provides a reasonable estimation of the peak reaction forces experienced during catheter tracking within compliant vessels. We investigated the risk of rupture of both the aortic tissue and calcified plaques. We report that there was no risk of diseased aortic tissue rupture based on an accepted aortic tissue stress threshold (4.2 MPa). However, we report that both the aortic and plaque tissue exceed a rupture stress threshold (300 kPa) with and without the presence of stiff and soft plaque inclusions. We also highlight the potential risks associated with shorter catheter tips during catheter tracking and demonstrate that increasing the contact surface will reduce peak contact pressures experienced in the tissue.

On the necessity to include arterial pre-stress in patient-specific simulations of minimally invasive procedures

Transcatheter aortic valve implantation (TAVI) and thoracic endovascular aortic repair (TEVAR) are minimally invasive procedures for treating aortic valves and diseases. Finite element simulations have proven to be valuable tools in predicting device-related complications. In the literature, the inclusion of aortic pre-stress has not been widely investigated. It plays a crucial role in determining the biomechanical response of the vessel and the device-tissue interaction. This study aims at demonstrating how and when to include the aortic pre-stress in patient-specific TAVI and TEVAR simulations. A percutaneous aortic valve and a stent-graft were implanted in aortic models reconstructed from patient-specific CT scans. Two scenarios for each patient were compared, i.e., including and neglecting the wall pre-stress. The neglection of pre-stress underestimates the contact pressure of 48% and 55%, the aorta stresses of 162% and 157%, the aorta strains of 77% and 21% for TAVI and TEVAR models, respectively. The stent stresses are higher than 48% with the pre-stressed aorta in TAVI simulations; while, similar results are obtained in TEVAR cases. The distance between the device and the aorta is similar with and without pre-stress. The inclusion of the aortic wall pre-stress has the capability to give a better representation of the biomechanical behavior of the arterial tissues and the implanted device. It is suggested to include this effect in patient-specific simulations replicating the procedures.

Effect of Sinotubular Junction Size on TAVR Leaflet Thrombosis: A Fluid-Structure Interaction Analysis

TAVR has emerged as a standard approach for treating severe aortic stenosis patients. However, it is associated with several clinical complications, including subclinical leaflet thrombosis characterized by Hypoattenuated Leaflet Thickening (HALT). A rigorous analysis of TAVR device thrombogenicity considering anatomical variations is essential for estimating this risk. Clinicians use the Sinotubular Junction (STJ) diameter for TAVR sizing, but there is a paucity of research on its influence on TAVR devices thrombogenicity. A Medtronic Evolut® TAVR device was deployed in three patient models with varying STJ diameters (26, 30, and 34 mm) to evaluate its impact on post-deployment hemodynamics and thrombogenicity, employing a novel computational framework combining prosthesis deployment and fluid-structure interaction analysis. The 30 mm STJ patient case exhibited the best hemodynamic performance: 5.94 mmHg mean transvalvular pressure gradient (TPG), 2.64 cm2 mean geometric orifice area (GOA), and the lowest mean residence time (TR)-indicating a reduced thrombogenic risk; 26 mm STJ exhibited a 10 % reduction in GOA and a 35% increase in mean TPG compared to the 30 mm STJ; 34 mm STJ depicted hemodynamics comparable to the 30 mm STJ, but with a 6% increase in TR and elevated platelet stress accumulation. A smaller STJ size impairs adequate expansion of the TAVR stent, which may lead to suboptimal hemodynamic performance. Conversely, a larger STJ size marginally enhances the hemodynamic performance but increases the risk of TAVR leaflet thrombosis. Such analysis can aid pre-procedural planning and minimize the risk of TAVR leaflet thrombosis.

On the Material Constitutive Behavior of the Aortic Root in Patients with Transcatheter Aortic Valve Implantation

BACKGROUND

Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure used to treat patients with severe aortic valve stenosis. However, there is limited knowledge on the material properties of the aortic root in TAVI patients, and this can impact the credibility of computer simulations. This study aimed to develop a non-invasive inverse approach for estimating reliable material constituents for the aortic root and calcified valve leaflets in patients undergoing TAVI.

METHODS

The identification of material parameters is based on the simultaneous minimization of two cost functions, which define the difference between model predictions and cardiac-gated CT measurements of the aortic wall and valve orifice area. Validation of the inverse analysis output was performed comparing the numerical predictions with actual CT shapes and post-TAVI measures of implanted device diameter.

RESULTS

A good agreement of the peak systolic shape of the aortic wall was found between simulations and imaging, with similarity index in the range in the range of 83.7% to 91.5% for n.20 patients. Not any statistical difference was observed between predictions and CT measures of orifice area for the stenotic aortic valve. After TAVI simulations, the measurements of SAPIEN 3 Ultra (S3) device diameter were in agreement with those from post-TAVI angio-CT imaging. A sensitivity analysis demonstrated a modest impact on the S3 diameters when altering the elastic material property of the aortic wall in the range of inverse analysis solution.

CONCLUSIONS

Overall, this study demonstrates the feasibility and potential benefits of using non-invasive imaging techniques and computational modeling to estimate material properties in patients undergoing TAVI.

Analysis of fibrocalcific aortic valve stenosis: computational pre-and-post TAVR haemodynamics behaviours

Fibro-calcific aortic valve (AV) diseases are characterized by calcium growth or accumulation of fibrosis in the AV tissues. Fibrocalcific aortic stenosis (FAS) rises specifically in females, like calcification-induced aortic stenosis (CAS), may eventually necessitate valve replacement. Fluid-structure-interaction (FSI) computational models for severe CAS and FAS patients were developed using lattice Boltzmann method and multi-scale finite elements (FE). Three parametric AV models were introduced: pathology-free of non-calcified tri-and-bicuspid AVs with healthy collagen fibre network (CFN), a FAS model incorporated a thickened CFN with embedded small calcification volumes, and a CAS model employs healthy CFN with embedded high calcification volumes. The results indicate that the interaction between calcium deposits, adjacent tissue and fibres crucially influences haemodynamics and structural reactions. A fourth model of transcatheter aortic valve replacement (TAVR) post-procedure outcomes was created to study both CAS and FAS. TAVR-CAS had a higher maximum contact pressure and lower anchoring area than TAVR-FAS, making it prone to aortic tissue damage and migration. Finally, although the TAVR-CAS offered a larger opening area, its paravalvular leakage was higher. This may be attributed to a similar thrombogenicity potential characterizing both models. The computational framework emphasizes the significance of mechanobiology in FAS and underscores the requirement for tissue modelling at multiple scales.

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.

Mechanism of balloon burst during transcatheter aortic valve replacement pre-dilatation: Image observation and validation by finite element analysis

BACKGROUND

Balloon burst during transcatheter aortic valve replacement (TAVR) is serious complication. This study pioneers a novel approach by combining image observation and computer simulation validation to unravel the mechanism of balloon burst in a patient with bicuspid aortic valve (BAV) stenosis.

METHOD

A new computational model for balloon pre-dilatation was developed by incorporating the element failure criteria according to the Law of Laplace. The effects of calcification and aortic tissue material parameters, friction coefficients, balloon types and aortic anatomy classification were performed to validate and compare the expansion behavior and rupture mode of actual balloon.

RESULTS

Balloon burst was dissected into three distinct stages based on observable morphological changes. The mechanism leading to the complete transverse burst of the non-compliant balloon initiated at the folding edges, where contacted with heavily calcified masses at the right coronary sinus, resulting in high maximum principal stress. Local sharp spiked calcifications facilitated rapid crack propagation. The elastic moduli of calcification significantly influenced balloon expansion behavior and crack morphology. The simulation case of the calcific elastic modulus was set at 12.6 MPa could closely mirror clinical appearance of expansion behavior and crack pattern. Furthermore, the case of semi-compliant balloons introduced an alternative rupture mechanism as pinhole rupture, driven by local sharp spiked calcifications.

CONCLUSIONS

The computational model of virtual balloons could effectively simulate balloon dilation behavior and burst mode during TAVR pre-dilation. Further research with a larger cohort is needed to investigate the balloon morphology during pre-dilation by using this method to guide prosthesis sizing for potential favorable outcomes.

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.

Effect of Sinotubular Junction Size on TAVR Leaflet Thrombosis: A Fluid-structure Interaction Analysis

Purpose

TAVR has emerged as a standard approach for treating severe aortic stenosis patients. However, it is associated with several clinical complications, including subclinical leaflet thrombosis characterized by Hypoattenuated Leaflet Thickening (HALT). A rigorous analysis of TAVR device thrombogenicity considering anatomical variations is essential for estimating this risk. Clinicians use the Sinotubular Junction (STJ) diameter for TAVR sizing, but there is a paucity of research on its influence on TAVR devices thrombogenicity.

Methods

A Medtronic Evolut® TAVR device was deployed in three patient models with varying STJ diameters (26, 30, and 34mm) to evaluate its impact on post-deployment hemodynamics and thrombogenicity, employing a novel computational framework combining prosthesis deployment and fluid- structure interaction analysis.

Results

The 30 mm STJ patient case exhibited the best hemodynamic performance: 5.94 mmHg mean transvalvular pressure gradient (TPG), 2.64 cm 2 mean geometric orifice area (GOA), and the lowest mean residence time (T R ) - indicating a reduced thrombogenic risk; 26 mm STJ exhibited a 10 % reduction in GOA and a 35% increase in mean TPG compared to the 30 mm STJ; 34 mm STJ depicted hemodynamics comparable to the 30 mm STJ, but with a 6% increase in T R and elevated platelet stress accumulation.

Conclusion

A smaller STJ size impairs adequate expansion of the TAVR stent, which may lead to suboptimal hemodynamic performance. Conversely, a larger STJ size marginally enhances the hemodynamic performance but increases the risk of TAVR leaflet thrombosis. Such analysis can aid pre- procedural planning and minimize the risk of TAVR leaflet thrombosis.

Parametric analysis of transcatheter aortic valve replacement in transcatheter aortic valve replacement: evaluation of coronary flow obstruction

Transcatheter aortic valve replacement (TAVR) is increasingly being considered for use in younger patients having longer life expectancy than those who were initially treated. The TAVR-in-TAVR procedure represents an appealing strategy to treat failed transcatheter heart valves (THV) likely occurring in young patients. However, the permanent displacement of first THV can potentially compromise the coronary access and ultimately inhibit the blood flow circulation. The objective of this study was to use finite-element analysis (FEA) to quantify coronary flow in a patient who underwent TAVR-in-TAVR. A parametric investigation was carried out to determine the impact of both the implantation depth and device size on coronary flow for several deployment configurations. The FEAs consisted of first delivering the SAPIEN 3 Ultra THV and then positioning the Evolut PRO device. Findings indicates that high implantation depth and device undersize of the second THV could significantly reduce coronary flow to 20% of its estimated level before TAVR. Additionally, a positive correlation was observed between coronary flow and the valve-to-coronary distance (R = 0.86 and p = 0.032 for the left coronary artery, and R = 0.93 and p = 0.014 for the right coronary artery). This study demonstrated that computational modeling can provide valuable insights to improve the pre-procedural planning of TAVR-in-TAVR.

Calcium Fracture and Device Over Expansion in Transcatheter Aortic Valve Replacement for Bicuspid Aortic Valves

Transcatheter aortic valve replacement (TAVR) in patients with bicuspid aortic valve disease (BAV) has potential risks of under expansion and non-circularity which may compromise long-term durability. This study aims to investigate calcium fracture and balloon over expansion in balloon-expandable TAVs on the stent deformation with the aid of simulation. BAV patients treated with the SAPIEN 3 Ultra with pre- and post-TAVR CTs were analyzed (n = 8). Simulations of the stent deployment were performed (1) with baseline simulation allowing calcium fracture, (2) without allowable calcium fracture and (3) with balloon over expansion (1 mm larger diameter). When compared to post CT, baseline simulations had minimal error in expansion (2.5% waist difference) and circularity (3.0% waist aspect ratio difference). When compared to baseline, calcium fracture had insignificant impact on the expansion (- 0.5% average waist difference) and circularity (- 1.6% average waist aspect ratio difference). Over expansion had significantly larger expansion compared to baseline (15.4% average waist difference) but had insignificant impact on the circularity (- 0.5% waist aspect ratio difference). We conclude that stent deformation can be predicted with minimal error, calcium fracture has small differences on the final stent deformation except in extreme calcified cases, and balloon over expansion expands the waist closer to nominal values.

Latest Developments in Adapting Deep Learning for Assessing TAVR Procedures and Outcomes

Aortic valve defects are among the most prevalent clinical conditions. A severely damaged or non-functioning aortic valve is commonly replaced with a bioprosthetic heart valve (BHV) via the transcatheter aortic valve replacement (TAVR) procedure. Accurate pre-operative planning is crucial for a successful TAVR outcome. Assessment of computational fluid dynamics (CFD), finite element analysis (FEA), and fluid-solid interaction (FSI) analysis offer a solution that has been increasingly utilized to evaluate BHV mechanics and dynamics. However, the high computational costs and the complex operation of computational modeling hinder its application. Recent advancements in the deep learning (DL) domain can offer a real-time surrogate that can render hemodynamic parameters in a few seconds, thus guiding clinicians to select the optimal treatment option. Herein, we provide a comprehensive review of classical computational modeling approaches, medical imaging, and DL approaches for planning and outcome assessment of TAVR. Particularly, we focus on DL approaches in previous studies, highlighting the utilized datasets, deployed DL models, and achieved results. We emphasize the critical challenges and recommend several future directions for innovative researchers to tackle. Finally, an end-to-end smart DL framework is outlined for real-time assessment and recommendation of the best BHV design for TAVR. Ultimately, deploying such a framework in future studies will support clinicians in minimizing risks during TAVR therapy planning and will help in improving patient care.

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.

Fluid-structure interaction analysis of transcatheter aortic valve implantation

Transcatheter aortic valve implantation (TAVI) is a minimally invasive intervention for the treatment of severe aortic valve stenosis. The main cause of failure is the structural deterioration of the implanted prosthetic leaflets, possibly inducing a valvular re-stenosis 5-10 years after the implantation. Based solely on pre-implantation data, the aim of this work is to identify fluid-dynamics and structural indices that may predict the possible valvular deterioration, in order to assist the clinicians in the decision-making phase and in the intervention design. Patient-specific, pre-implantation geometries of the aortic root, the ascending aorta, and the native valvular calcifications were reconstructed from computed tomography images. The stent of the prosthesis was modeled as a hollow cylinder and virtually implanted in the reconstructed domain. The fluid-structure interaction between the blood flow, the stent, and the residual native tissue surrounding the prosthesis was simulated by a computational solver with suitable boundary conditions. Hemodynamical and structural indicators were analyzed for five different patients that underwent TAVI - three with prosthetic valve degeneration and two without degeneration - and the comparison of the results showed a correlation between the leaflets' structural degeneration and the wall shear stress distribution on the proximal aortic wall. This investigation represents a first step towards computational predictive analysis of TAVI degeneration, based on pre-implantation data and without requiring additional peri-operative or follow-up information. Indeed, being able to identify patients more likely to experience degeneration after TAVI may help to schedule a patient-specific timing of follow-up.

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.

Modelling blood flow in patients with heart valve disease using deep learning: A computationally efficient method to expand diagnostic capabilities in clinical routine

Introduction

The computational modelling of blood flow is known to provide vital hemodynamic parameters for diagnosis and treatment-support for patients with valvular heart disease. However, most diagnosis/treatment-support solutions based on flow modelling proposed utilize time- and resource-intensive computational fluid dynamics (CFD) and are therefore difficult to implement into clinical practice. In contrast, deep learning (DL) algorithms provide results quickly with little need for computational power. Thus, modelling blood flow with DL instead of CFD may substantially enhances the usability of flow modelling-based diagnosis/treatment support in clinical routine. In this study, we propose a DL-based approach to compute pressure and wall-shear-stress (WSS) in the aorta and aortic valve of patients with aortic stenosis (AS).

Methods

A total of 103 individual surface models of the aorta and aortic valve were constructed from computed tomography data of AS patients. Based on these surface models, a total of 267 patient-specific, steady-state CFD simulations of aortic flow under various flow rates were performed. Using this simulation data, an artificial neural network (ANN) was trained to compute spatially resolved pressure and WSS using a centerline-based representation. An unseen test subset of 23 cases was used to compare both methods.

Results

ANN and CFD-based computations agreed well with a median relative difference between both methods of 6.0% for pressure and 4.9% for wall-shear-stress. Demonstrating the ability of DL to compute clinically relevant hemodynamic parameters for AS patients, this work presents a possible solution to facilitate the introduction of modelling-based treatment support into clinical practice.

Mild Paravalvular Leak May Pose an Increased Thrombogenic Risk in Transcatheter Aortic Valve Replacement (TAVR) Patients-Insights from Patient Specific In Vitro and In Silico Studies

In recent years, the treatment of aortic stenosis with TAVR has rapidly expanded to younger and lower-risk patients. However, persistent thrombotic events such as stroke and valve thrombosis expose recipients to severe clinical complications that hamper TAVR's rapid advance. We presented a novel methodology for establishing a link between commonly acceptable mild paravalvular leak (PVL) levels through the device and increased thrombogenic risk. It utilizes in vitro patient-specific TAVR 3D-printed replicas evaluated for hydrodynamic performance. High-resolution µCT scans are used to reconstruct in silico FSI models of these replicas, in which multiple platelet trajectories are studied through the PVL channels to quantify thrombogenicity, showing that those are highly dependent on patient-specific flow conditions within the PVL channels. It demonstrates that platelets have the potential to enter the PVL channels multiple times over successive cardiac cycles, increasing the thrombogenic risk. This cannot be reliably approximated by standard hemodynamic parameters. It highlights the shortcomings of subjectively ranked PVL commonly used in clinical practice by indicating an increased thrombogenic risk in patient cases otherwise classified as mild PVL. It reiterates the need for more rigorous clinical evaluation for properly diagnosing thrombogenic risk in TAVR patients.

Impact of nickel-titanium super-elastic material properties on the mechanical performance of self-expandable transcatheter aortic valves

Self-expandable transcatheter aortic valves (TAVs) elastically resume their initial shape when implanted without the need for balloon inflation by virtue of the nickel-titanium (NiTi) frame super-elastic properties. Experimental findings suggest that NiTi mechanical properties can vary markedly because of a strong dependence on the chemical composition and processing operations. In this context, this study presents a computational framework to investigate the impact of the NiTi super-elastic material properties on the TAV mechanical performance. Finite element (FE) analyses of TAV implantation were performed considering two different TAV frames and three idealized aortic root anatomies, evaluating the device mechanical response in terms of pullout force magnitude exerted by the TAV frame and peak maximum principal stress within the aortic root. The widely adopted NiTi constitute model by Auricchio and Taylor (1997) was used. A multi-parametric sensitivity analysis and a multi-objective optimization of the TAV mechanical performance were conducted in relation to the parameters of the NiTi constitutive model. The results highlighted that: five NiTi material model parameters (E_A, σ_tL^S, σ_tU^S, σ_tU^E and σ_cL^S) are significantly correlated with the FE outputs; the TAV frame geometry and aortic root anatomy have a marginal effect on the level of influence of each NiTi material parameter; NiTi alloy candidates with pareto-optimal characteristics in terms of TAV mechanical performance can be successfully identified. In conclusion, the proposed computational framework supports the TAV design phase, providing information on the relationship between the super-elastic behavior of the supplied NiTi alloys and the device mechanical response.

Patient-Specific Immersed Finite Element-Difference Model of Transcatheter Aortic Valve Replacement

Transcatheter aortic valve replacement (TAVR) first received FDA approval for high-risk surgical patients in 2011 and has been approved for low-risk surgical patients since 2019. It is now the most common type of aortic valve replacement, and its use continues to accelerate. Computer modeling and simulation (CM&S) is a tool to aid in TAVR device design, regulatory approval, and indication in patient-specific care. This study introduces a computational fluid-structure interaction (FSI) model of TAVR with Medtronic's CoreValve Evolut R device using the immersed finite element-difference (IFED) method. We perform dynamic simulations of crimping and deployment of the Evolut R, as well as device behavior across the cardiac cycle in a patient-specific aortic root anatomy reconstructed from computed tomography (CT) image data. These IFED simulations, which incorporate biomechanics models fit to experimental tensile test data, automatically capture the contact within the device and between the self-expanding stent and native anatomy. Further, we apply realistic driving and loading conditions based on clinical measurements of human ventricular and aortic pressures and flow rates to demonstrate that our Evolut R model supports a physiological diastolic pressure load and provides informative clinical performance predictions.

Results of the Interlaboratory Computational Fluid Dynamics Study of the FDA Benchmark Blood Pump

Computational fluid dynamics (CFD) is widely used to simulate blood-contacting medical devices. To be relied upon to inform high-risk decision making, however, model credibility should be demonstrated through validation. To provide robust data sets for validation, researchers at the FDA and collaborators developed two benchmark medical device flow models: a nozzle and a centrifugal blood pump. Experimental measurements of the flow fields and hemolysis were acquired using each model. Concurrently, separate open interlaboratory CFD studies were performed in which participants from around the world, who were blinded to the measurements, submitted CFD predictions of each benchmark model. In this study, we report the results of the interlaboratory CFD study of the FDA benchmark blood pump. We analyze the results of 24 CFD submissions using a wide range of different flow solvers, methods, and modeling parameters. To assess the accuracy of the CFD predictions, we compare the results with experimental measurements of three quantities of interest (pressure head, velocity field, and hemolysis) at different pump operating conditions. We also investigate the influence of different CFD methods and modeling choices used by the participants. Our analyses reveal that, while a number of CFD submissions accurately predicted the pump performance for individual cases, no single participant was able to accurately predict all quantities of interest across all conditions. Several participants accurately predicted the pressure head at all conditions and the velocity field in all but one or two cases. Only one of the eight participants who submitted hemolysis results accurately predicted absolute plasma free hemoglobin levels at a majority of the conditions, though most participants were successful at predicting relative hemolysis levels between conditions. Overall, this study highlights the need to validate CFD modeling of rotary blood pumps across the entire range of operating conditions and for all quantities of interest, as some operating conditions and regions (e.g., the pump diffuser) are more challenging to accurately predict than others. All quantities of interest should be validated because, as shown here, it is possible to accurately predict hemolysis despite having relatively inaccurate predictions of the flow field.

Designing a Novel Asymmetric Transcatheter Aortic Valve for Stenotic Bicuspid Aortic Valves Using Patient-Specific Computational Modeling

Bicuspid aortic valve (BAV), the most common congenital heart malformation, is characterized by the presence of only two valve leaflets with asymmetrical geometry, resulting in elliptical systolic opening. BAV often leads to early onset of calcific aortic stenosis (AS). Following the rapid expansion of transcatheter aortic valve replacement (TAVR), designed specifically for treating conventional tricuspid AS, BAV patients with AS were initially treated "off-label" with TAVR, which recently gained FDA and CE regulatory approval. Despite its increasing use in BAV, pathological BAV anatomy often leads to complications stemming from mismatched anatomical features. To mitigate these complications, a novel eccentric polymeric TAVR valve incorporating asymmetrical leaflets was designed specifically for BAV anatomies. Computational modeling was used to optimize its asymmetric leaflets for lower functional stresses and improved hemodynamic performance. Deployment and flow were simulated in patient-specific BAV models (n = 6) and compared to a current commercial TAVR valve (Evolut R 29 mm), to assess deployment and flow parameters. The novel eccentric BAV-dedicated valve demonstrated significant improvements in peak systolic orifice area, along with lower jet velocity and wall shear stress (WSS). This feasibility study demonstrates the clinical potential of the first known BAV-dedicated TAVR design, which will foster advancement of patient-dedicated valvular devices.

Assessment of valve implantation in the descending aorta as an alternative for aortic regurgitation patients not treatable with conventional procedures

BACKGROUND

Aortic Regurgitation (AR) produces the entrance of an abnormal amount of blood in the left ventricle. This disease is responsible for high morbidity and mortality worldwide and may be caused by an aortic valve dysfunction. Surgical and transcatheter aortic valve replacement (TAVR) are the current options for treating AR. They have replaced older procedures such as Hufnagel's one. However, some physicians have reconsidered this procedure as a less aggressive alternative for patients not eligible for surgical or TAVR. Although Hufnagel suggested a 75% regurgitation reduction when a valve is placed in the descending aorta, a quantification of this value has not been reported.

METHODS

In this paper, CFD/FSI numerical simulation is conducted on an idealized geometry. We quantify the effect of placing a bileaflet mechanical heart valve in the descending aorta on a moderate-severe AR case. A three-element Windkessel model is employed to prescribe pressure outlet boundary conditions. We calculate the resulting flow rates and pressures at the aorta and first-generation vessels. Moreover, we evaluate several indices to assess the improvement due to the valve introduction.

RESULTS AND CONCLUSIONS

Regurgitation fraction (RF) is reduced from 37.5% (without valve) to 18.0% (with valve) in a single cardiac cycle. This reduction clearly shows the remarkable efficacy of the rescued technique. It will further ameliorate the left ventricle function in the long-term. Moreover, the calculations show that the implantation in that location introduces fewer incompatibilities' risks than a conventional one. The proposed methodology can be extended to any particular conditions (pressure waveforms/geometry) and is designed to assess usual clinical parameters employed by physicians.

Long-term prognostic impact of paravalvular leakage on coronary artery disease requires patient-specific quantification of hemodynamics

Transcatheter aortic valve replacement (TAVR) is a frequently used minimally invasive intervention for patient with aortic stenosis across a broad risk spectrum. While coronary artery disease (CAD) is present in approximately half of TAVR candidates, correlation of post-TAVR complications such as paravalvular leakage (PVL) or misalignment with CAD are not fully understood. For this purpose, we developed a multiscale computational framework based on a patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-structure interaction model to quantify metrics of global circulatory function, metrics of global cardiac function and local cardiac fluid dynamics in 6 patients. Based on our findings, PVL limits the benefits of TAVR and restricts coronary perfusion due to the lack of sufficient coronary blood flow during diastole phase (e.g., maximum coronary flow rate reduced by 21.73%, 21.43% and 21.43% in the left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)). Moreover, PVL may increase the LV load (e.g., LV load increased by 17.57% (N = 6)) and decrease the coronary wall shear stress (e.g., maximum wall shear stress reduced by 20.62%, 21.92%, 22.28% and 25.66% in the left main coronary artery (LMCA), left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)), which could promote atherosclerosis development through loss of the physiological flow-oriented alignment of endothelial cells. This study demonstrated that a rigorously developed personalized image-based computational framework can provide vital insights into underlying mechanics of TAVR and CAD interactions and assist in treatment planning and patient risk stratification in patients.

Validating In Silico and In Vitro Patient-Specific Structural and Flow Models with Transcatheter Bicuspid Aortic Valve Replacement Procedure

INTRODUCTION

Bicuspid aortic valve (BAV) is the most common congenital cardiac malformation, which had been treated off-label by transcatheter aortic valve replacement (TAVR) procedure for several years, until its recent approval by the Food and Drug Administration (FDA) and Conformité Européenne (CE) to treat BAVs. Post-TAVR complications tend to get exacerbated in BAV patients due to their inherent aortic root pathologies. Globally, due to the paucity of randomized clinical trials, clinicians still favor surgical AVR as the primary treatment option for BAV patients. While this warrants longer term studies of TAVR outcomes in BAV patient cohorts, in vitro experiments and in silico computational modeling can be used to guide the surgical community in assessing the feasibility of TAVR in BAV patients. Our goal is to combine these techniques in order to create a modeling framework for optimizing pre-procedural planning and minimize post-procedural complications.

MATERIALS AND METHODS

Patient-specific in silico models and 3D printed replicas of 3 BAV patients with different degrees of post-TAVR paravalvular leakage (PVL) were created. Patient-specific TAVR device deployment was modeled in silico and in vitro-following the clinical procedures performed in these patients. Computational fluid dynamics simulations and in vitro flow studies were performed in order to obtain the degrees of PVL in these models.

RESULTS

PVL degree and locations were consistent with the clinical data. Cross-validation comparing the stent deformation and the flow parameters between the in silico and the in vitro models demonstrated good agreement.

CONCLUSION

The current framework illustrates the potential of using simulations and 3D printed models for pre-TAVR planning and assessing post-TAVR complications in BAV patients.

Fragmentation of Different Calcification Growth Patterns in Bicuspid Valves During Balloon Valvuloplasty Procedure

This study focuses on the calcification development and routes of type-1 bicuspid aortic valves based on CT scans and the effect of the unique geometrical shapes of calcium deposits on their fragmentation under balloon valvuloplasty procedures. Towards this goal, the novel Reverse Calcification Technique (RCT), which can predict the calcification progression leading to the current state based on CT scans, is utilized for n = 26 bicuspid aortic valves patients. Two main calcification patterns of type-1 bicuspid aortic valves were identified; asymmetric and symmetric with either partial or full arcs and circles. Subsequently, a calcification fragmentation biomechanical model was introduced to study the balloon valvuloplasty procedure prior to transcatheter aortic valve replacement implantation that allows better device expansion. To achieve this goal, six representative stenotic bicuspid aortic valves of different calcification patterns were investigated. It was found that the distinct geometrical shape of the calcium deposits had a significant effect on the cracks' initiations. Full or partial circle deposits had stronger resistance to fragmentation and mainly remained intact, yet, arc-shaped pattern deposits resulted in multiple cracks in bottleneck regions. The proposed biomechanical computational models could help assess calcification fragmentation patterns toward improving treatment approaches in stenotic bicuspid aortic valve patients, particularly for the off-label use of transcatheter aortic valve replacement.

The native aortic valve reduces paravalvular leak in TAVR patients

Background: Paravalvular leak (PVL) is a frequent TAVR complication. Prospective identification of patients who are likely to develop PVL after TAVR would likely lead to improved outcomes. Prior studies have used geometric characteristics to predict the likelihood of PVL development, but prediction and quantification has not been done. One of the reasons is that it is difficult to predict the mechanical deformation of the native diseased aortic valve prior to implantation of the prosthetic valve, as existing calcifications likely contribute to the seal between the prosthetic valve and the aortic annulus. However, the relatively amount the native valve plays in preventing PVL is unknown.

Methods: A retrospective chart review was conducted identifying patients with mild or greater PVL. One patient who had substantial PVL was identified and a 3D printed (pre-TAVR) aortic root was created. Balloon-expandable TAVR stent frames were implanted within the 3D printed root and a new model was created. Using this geometry, computational fluid dynamics (CFD) simulations were done to quantify PVL. The PVL flow path was iteratively decreased to simulate the space occupied by a crushed native aortic valve and PVL was quantified.

Results: PVL was found to decrease as the space occupying the PVL area increased, demonstrating that the native aortic valve contributes to reducing regurgitation. CFD simulations demonstrated that within the patient analyzed, the native valve occupies between 3–40% of the PVL pathway.

Conclusion:A priori techniques that predict the development of post TAVR PVL should account for the native diseased valve as our simulations demonstrate that it plays a role in reducing PVL.

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.

Transcatheter aortic valve replacement for bicuspid aortic valve disease: does conventional surgery have a future?

Bicuspid aortic valve (BAV) disease is the most common form of congenital heart valve defect. It is associated with aortic stenosis (AS), aortic insufficiency, and aortopathy. Treatment of severe AS requires valve replacement which historically has been performed with surgical aortic valve replacement (SAVR). Recently, transcatheter aortic valve replacement (TAVR) has emerged as a promising alternative. However, increased rates of adverse outcomes following TAVR have been shown in BAV patients with high amounts of calcification. Comparison between TAVR and SAVR in low surgical risk BAV patients in a randomized trial has not been performed and TAVR for BAV long-term performance is unknown due to lack of clinical data. Due to the complexity of BAV anatomies and the significant knowledge gap from the lack of clinical data, SAVR still has many benefits over TAVR in low surgical risk BAV patients. It also remains common for BAV patients to have an aortopathy, which currently can be treated with surgical techniques. This review aims to outline BAV associated diseases and their treatment strategies, the main TAVR adverse outcomes associated with anatomically complex BAV patients, TAVR strategies for mitigating these risks and the current state of cutting-edge 3D printing and computer modeling screening methods that can provide otherwise unobtainable preoperative information during the BAV patient selection process for TAVR.

Patient-specific multi-scale design optimization of transcatheter aortic valve stents

BACKGROUND AND OBJECTIVE

Transcatheter aortic valve implantation (TAVI) has become the standard treatment for a wide range of patients with aortic stenosis. Although some of the TAVI post-operative complications are addressed in newer designs, other complications and lack of long-term and durability data on the performance of these prostheses are limiting this procedure from becoming the standard for heart valve replacements. The design optimization of these devices with the finite element and optimization techniques can help increase their performance quality and reduce the risk of malfunctioning. Most performance metrics of these prostheses are morphology-dependent, and the design and the selection of the device before implantation should be planned for each individual patient.

METHODS

In this study, a patient-specific aortic root geometry was utilized for the crimping and implantation simulation of 50 stent samples. The results of simulations were then evaluated and used for developing regression models. The strut width and thickness, the number of cells and patterns, the size of stent cells, and the diameter profile of the stent were optimized with two sets of optimization processes. The objective functions included the maximum crimping strain, radial strength, anchorage area, and the eccentricity of the stent.

RESULTS

The optimization process was successful in finding optimal models with up to 40% decrease in the maximum crimping strain, 261% increase in the radial strength, 67% reduction in the eccentricity, and about an eightfold increase in the anchorage area compared to the reference device.

CONCLUSIONS

The stents with larger distal diameters perform better in the selected objective functions. They provide better anchorage in the aortic root resulting in a smaller gap between the device and the surrounding tissue and smaller contact pressure. This framework can be used in designing patient-specific stents and improving the performance of these devices and the outcome of the implantation process.

Biomechanics of Transcatheter Aortic Valve Replacement Complications and Computational Predictive Modeling

Transcatheter aortic valve replacement (TAVR) is a rapidly growing field enabling replacement of diseased aortic valves without the need for open heart surgery. However, due to the nature of the procedure and nonremoval of the diseased tissue, there are rates of complications ranging from tissue rupture and coronary obstruction to paravalvular leak, valve thrombosis, and permanent pacemaker implantation. In recent years, computational modeling has shown a great deal of promise in its capabilities to understand the biomechanical implications of TAVR as well as help preoperatively predict risks inherent to device-patient-specific anatomy biomechanical interaction. This includes intricate replication of stent and leaflet designs and tested and validated simulated deployments with structural and fluid mechanical simulations. This review outlines current biomechanical understanding of device-related complications from TAVR and related predictive strategies using computational modeling. An outlook on future modeling strategies highlighting reduced order modeling which could significantly reduce the high time and cost that are required for computational prediction of TAVR outcomes is presented in this review paper. A summary of current commercial/in-development software is presented in the final section.

Structural Heart Valve Disease in the Era of Change and Innovation: The Crosstalk between Medical Sciences and Engineering

In recent years, both cardiology and cardiovascular surgery have witnessed an era of consistently evolving changes which have dramatically transformed the course and management of cardiovascular disease [...].

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.

On the Modeling of Transcatheter Therapies for the Aortic and Mitral Valves: A Review

Transcatheter aortic valve replacement (TAVR) has become a milestone for the management of aortic stenosis in a growing number of patients who are unfavorable candidates for surgery. With the new generation of transcatheter heart valves (THV), the feasibility of transcatheter mitral valve replacement (TMVR) for degenerated mitral bioprostheses and failed annuloplasty rings has been demonstrated. In this setting, computational simulations are modernizing the preoperative planning of transcatheter heart valve interventions by predicting the outcome of the bioprosthesis interaction with the human host in a patient-specific fashion. However, computational modeling needs to carry out increasingly challenging levels including the verification and validation to obtain accurate and realistic predictions. This review aims to provide an overall assessment of the recent advances in computational modeling for TAVR and TMVR as well as gaps in the knowledge limiting model credibility and reliability.

Computational Methods for Fluid-Structure Interaction Simulation of Heart Valves in Patient-Specific Left Heart Anatomies

Given the complexity of human left heart anatomy and valvular structures, the fluid–structure interaction (FSI) simulation of native and prosthetic valves poses a significant challenge for numerical methods. In this review, recent numerical advancements for both fluid and structural solvers for heart valves in patient-specific left hearts are systematically considered, emphasizing the numerical treatments of blood flow and valve surfaces, which are the most critical aspects for accurate simulations. Numerical methods for hemodynamics are considered under both the continuum and discrete (particle) approaches. The numerical treatments for the structural dynamics of aortic/mitral valves and FSI coupling methods between the solid Ωs and fluid domain Ωf are also reviewed. Future work toward more advanced patient-specific simulations is also discussed, including the fusion of high-fidelity simulation within vivo measurements and physics-based digital twining based on data analytics and machine learning techniques.

Treatment of Bicuspid Aortic Valve Stenosis with TAVR: Filling Knowledge Gaps Towards Reducing Complications

PURPOSE OF REVIEW

Bicuspid aortic valve (BAV) disease is the most common congenital heart defect worldwide. When severe, symptomatic aortic stenosis ensues, the treatment has increasingly become transcatheter aortic valve replacement (TAVR). The purpose of this review is to identify BAV classification and imaging methods, outline TAVR outcomes in BAV anatomy, and discuss how computational modeling can enhance TAVR treatment in BAV patients.

RECENT FINDINGS

TAVR use in BAV patients, when compared to use in tricuspid aortic valves, showed lower device success rate, and there remains no long-term randomized trial data. It has been reported that BAV patients with severe calcification increase the rate of complications. Additionally, the asymmetrical morphology of BAVs often results in asymmetric stent geometries which have implications for increased thrombosis risk and decreased durability. These adverse outcomes are currently very difficult to predict from routine pre-procedural imaging alone. Recently developed patient specific experimental and computational techniques have the potential to assist in filling knowledge gaps in the mechanisms of these complications and provide more information during preclinical planning for better TAVR selection in low surgical risk BAV patients. Efficacy of TAVR for irregular BAV anatomies remains concerning due to the lack of a long-term randomized trial data, their increased rate of short-term complications, and signs that long-term durability could be an issue. More knowledge on identifying which BAV anatomies are at greater risk for these adverse outcomes can potentially improve patient selection for TAVR versus SAVR in low surgical risk BAV patients.

A computational framework for post-TAVR cardiac conduction abnormality (CCA) risk assessment in patient-specific anatomy

BACKGROUND

Cardiac conduction abnormality (CCA)- one of the major persistent complications associated with transcatheter aortic valve replacement (TAVR) may lead to permanent pacemaker implantation. Localized stresses exerted by the device frame on the membranous septum (MS) which lies between the aortic annulus and the bundle of His, may disturb the cardiac conduction and cause the resultant CCA. We hypothesize that the area-weighted average maximum principal logarithmic strain (AMPLS) in the MS region can predict the risk of CCA following TAVR.

METHODS

Rigorous finite element-based modeling analysis was conducted in two patients (Balloon expandable TAVR recipients) to assess post-TAVR CCA risk. Following the procedure one of the patients required permanent pacemaker (PPM) implantation while the other did not (control case). Patient-specific aortic root was modeled, MS was identified from the CT image, and the TAVR deployment was simulated. Mechanical factors in the MS region such as logarithmic strain, contact force, contact pressure, contact pressure index (CPI) and their time history during the TAVR deployment; and anatomical factors such as MS length, implantation depth, were analyzed.

RESULTS

Maximum AMPLS (0.47 and 0.37, respectively), contact force (0.92 N and 0.72 N, respectively), and CPI (3.99 and 2.86, respectively) in the MS region were significantly elevated in the PPM patient as compared to control patient.

CONCLUSION

Elevated stresses generated by TAVR devices during deployment appear to correlate with CCA risk, with AMPLS in the MS region emerging as a strong predictor that could be used for preprocedural planning in order to minimize CCA risk.