The impact of balloon-expandable transcatheter aortic valve replacement on concomitant mitral regurgitation: a comprehensive computational analysis

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.

The effect of balloon-expandable stent and self-expanding stent on changes in mitral annular motion after aortic valve replacement in patients with aortic stenosis

OBJECTIVES

The purpose of this study was to evaluate the effect of decalcification and existence of stent at the aortic annulus on mitral annular motion after surgery.

METHODS

Patients receiving Inspiris (Edwards, CA, USA, n = 117), Intuity (Edwards, n = 36), Perceval (Corcym, London, UK, n = 36), Evolut (Medtronics, MN, USA, n = 81) and Sapien 3 (Edwards, n = 250) were included in the study. Mitral annular motion was evaluated by E', using tissue doppler imaging.

RESULTS

After surgery, a significant increase in E' was observed in patients receiving Inspiris (Before: 4.2 ± 1.21 cm/s vs. Discharge: 5.0 ± 1.23 cm/s, p < 0.001). Mid-term echocardiogram performed at 11.8 ± 2.2 months after the surgery, showed a significant increase in E' in patients receiving Inspiris (Before: 4.2 ± 1.21 cm/s vs. Mid-term: 5.2 ± 1.20 cm/s, p < 0.001) and Perceval (Before: 3.9 ± 1.34 cm/s vs. Mid-term: 4.5 ± 1.24 cm/s, p = 0.008). Univariable analysis showed a higher increase in E' in patients with decalcified annulus compared to those without decalcified annulus (Decalcification: 0.15 ± 1.321 cm/s vs. No Decalcification: 0.66 ± 1.420 cm/s, p < 0.001). Multivariable analysis showed that balloon-expandable stent (β = - 0.6960, p < 0.001) and self-expanding stent (r = - 0.3592, p = 0.042) were independent limiting factors for an increase in E' at discharge. However, balloon-expandable stent (β = - 0.8382, p < 0.001), and not self-expanding stent (β = - 0.3682, p = 0.089), was a remaining independent factor associated with E' at mid-term follow-up.

CONCLUSIONS

Decalcification was associated with improvement in E' after surgery. Balloon-expandable stent was an independent limiting factor for improvement in E' up to 1 year after the surgery, while self-expanding stent was not a significant factor after 1 year.

Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning

Automated volumetric meshing of patient-specific heart geometry can help expedite various biomechanics studies, such as post-intervention stress estimation. Prior meshing techniques often neglect important modeling characteristics for successful downstream analyses, especially for thin structures like the valve leaflets. In this work, we present DeepCarve (Deep Cardiac Volumetric Mesh): a novel deformation-based deep learning method that automatically generates patient-specific volumetric meshes with high spatial accuracy and element quality. The main novelty in our method is the use of minimally sufficient surface mesh labels for precise spatial accuracy and the simultaneous optimization of isotropic and anisotropic deformation energies for volumetric mesh quality. Mesh generation takes only 0.13 seconds/scan during inference, and each mesh can be directly used for finite element analyses without any manual post-processing. Calcification meshes can also be subsequently incorporated for increased simulation accuracy. Numerous stent deployment simulations validate the viability of our approach for large-batch analyses. Our code is available at https://github.com/danpak94/Deep-Cardiac-Volumetric-Mesh.

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.

Echocardiographic Evaluation after Transcatheter Aortic Valve Implantation: A Comprehensive Review

Transcatheter aortic valve implantation (TAVI) is an increasingly popular treatment option for patients with severe aortic stenosis. Recent advancements in technology and imaging tools have significantly contributed to the success of TAVI procedures. Echocardiography plays a pivotal role in the evaluation of TAVI patients, both before and after the procedure. This review aims to provide an overview of the most recent technical advancements in echocardiography and their use in the follow-up of TAVI patients. In particular, the focus will be on the examination of the influence of TAVI on left and right ventricular function, which is frequently accompanied by other structural and functional alterations. Echocardiography has proven to be key also in detecting valve deterioration during extended follow-up. This review will provide valuable insights into the technical advancements in echocardiography and their role in the follow-up of TAVI patients.

Quantification of mitral regurgitation after transcatheter edge-to-edge repair: Comparison of echocardiography and patient-specific in silico models

BACKGROUND

Doppler echocardiographic (echo) assessment of residual mitral regurgitation (MR) after transcatheter edge-to-edge repair (TEER) is challenging and often subjective. This study aimed to evaluate the accuracy and feasibility of standardized quantitative echo methods for assessment of MR severity after MitraClip repair by comparing measurements against a reference MR severity obtained from patient-specific in silico models.

METHODS

Post-procedure hemodynamics were simulated under five different MitraClip configurations in previously validated patient-specific in silico models for the treatment of functional MR. The residual regurgitant volume was calculated as in clinical practice using four quantitative virtual echo methods: pulsed Doppler, volumetric, proximal isovelocity surface area (PISA) and vena contracta area (VCA). Multiple permutations were performed for each method. Virtual echo MR results were evaluated against reference MR values directly extracted from the 5 patient-specific in silico models.

RESULTS

The echo methods with the greatest accuracy were the three-dimensional (3D) volumetric method (r = 0.957, bias -0.8 ± 1.2 ml, p = 0.01), the 3D VCA method wherein velocity time integrals were evaluated for each jet assessed (r = 0.919, bias -1.5 ± 1.7 ml, p = 0.03), and the 3D PISA method integrating surface areas throughout systole (r = 0.98, bias -2.0 ± 0.9 ml, p = 0.003). The pulsed Doppler and 2D volumetric methods had technical limitations that may result in a high underestimation or overestimation of the MR severity after TEER. In the case of multiple regurgitant jets, a more accurate MR assessment was obtained when all significant jets were evaluated.

CONCLUSIONS

Clinically, the 3D volumetric, 3D VCA and 3D PISA methods gave the most accurate MR quantification after TEER. Three-dimensional echo technologies harbor the potential of becoming the non-invasive imaging tool of choice for MR quantification after complex transcatheter mitral interventions.

Deep Learning for Computational Hemodynamics: A Brief Review of Recent Advances

Computational fluid dynamics (CFD) modeling of blood flow plays an important role in better understanding various medical conditions, designing more effective drug delivery systems, and developing novel diagnostic methods and treatments. However, despite significant advances in computational technology and resources, the expensive computational cost of these simulations still hinders their transformation from a research interest to a clinical tool. This bottleneck is even more severe for image-based, patient-specific CFD simulations with realistic boundary conditions and complex computational domains, which make such simulations excessively expensive. To address this issue, deep learning approaches have been recently explored to accelerate computational hemodynamics simulations. In this study, we review recent efforts to integrate deep learning with CFD and discuss the applications of this approach in solving hemodynamics problems, such as blood flow behavior in aorta and cerebral arteries. We also discuss potential future directions in the field. In this review, we suggest that incorporating physiologic understandings and underlying fluid mechanics laws in deep learning models will soon lead to a paradigm shift in the development novel non-invasive computational medical decisions.

Clinical Impact of Computational Heart Valve Models

This paper provides a review of engineering applications and computational methods used to analyze the dynamics of heart valve closures in healthy and diseased states. Computational methods are a cost-effective tool that can be used to evaluate the flow parameters of heart valves. Valve repair and replacement have long-term stability and biocompatibility issues, highlighting the need for a more robust method for resolving valvular disease. For example, while fluid-structure interaction analyses are still scarcely utilized to study aortic valves, computational fluid dynamics is used to assess the effect of different aortic valve morphologies on velocity profiles, flow patterns, helicity, wall shear stress, and oscillatory shear index in the thoracic aorta. It has been analyzed that computational flow dynamic analyses can be integrated with other methods to create a superior, more compatible method of understanding risk and compatibility.

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.

The Technological Basis of a Balloon-Expandable TAVR System: Non-occlusive Deployment, Anchorage in the Absence of Calcification and Polymer Leaflets

Leaflet durability and costs restrict contemporary trans-catheter aortic valve replacement (TAVR) largely to elderly patients in affluent countries. TAVR that are easily deployable, avoid secondary procedures and are also suitable for younger patients and non-calcific aortic regurgitation (AR) would significantly expand their global reach. Recognizing the reduced need for post-implantation pacemakers in balloon-expandable (BE) TAVR and the recent advances with potentially superior leaflet materials, a trans-catheter BE-system was developed that allows tactile, non-occlusive deployment without rapid pacing, direct attachment of both bioprosthetic and polymer leaflets onto a shape-stabilized scallop and anchorage achieved by plastic deformation even in the absence of calcification. Three sizes were developed from nickel-cobalt-chromium MP35N alloy tubes: Small/23 mm, Medium/26 mm and Large/29 mm. Crimp-diameters of valves with both bioprosthetic (sandwich-crosslinked decellularized pericardium) and polymer leaflets (triblock polyurethane combining siloxane and carbonate segments) match those of modern clinically used BE TAVR. Balloon expansion favors the wing-structures of the stent thereby creating supra-annular anchors whose diameter exceeds the outer diameter at the waist level by a quarter. In the pulse duplicator, polymer and bioprosthetic TAVR showed equivalent fluid dynamics with excellent EOA, pressure gradients and regurgitation volumes. Post-deployment fatigue resistance surpassed ISO requirements. The radial force of the helical deployment balloon at different filling pressures resulted in a fully developed anchorage profile of the valves from two thirds of their maximum deployment diameter onwards. By combining a unique balloon-expandable TAVR system that also caters for non-calcific AR with polymer leaflets, a powerful, potentially disruptive technology for heart valve disease has been incorporated into a TAVR that addresses global needs. While fulfilling key prerequisites for expanding the scope of TAVR to the vast number of patients of low- to middle income countries living with rheumatic heart disease the system may eventually also bring hope to patients of high-income countries presently excluded from TAVR for being too young.

Comparative computational analysis of PASCAL and MitraClip implantation in a patient-specific functional mitral regurgitation model

Transcatheter mitral leaflet approximation with MitraClip has proven to be a viable treatment option for heart failure patients with functional mitral regurgitation (MR). PASCAL is a similar clip device, but it has design features that differentiate it from MitraClip. The effects of the different clip designs are largely unknown. In this study, using a patient-specific, mitral valve-left ventricle heart model, we performed finite-element (FE) simulations to provide a head-to-head comparison of the post-operative effects that PASCAL and MitraClip have on mitral valve (MV) geometry and biomechanics in a functional MR patient. The two devices were modeled as approximations of the real devices, and three implantation configurations were simulated for each device. The results showed that for this patient case, PASCAL caused less MV deformation than MitraClip. Additionally, PASCAL implantation reduced the stresses and strains in the MV leaflets compared to pre-repair conditions, while MitraClip implantation caused them to increase. Although complete coaptation was not achieved, both devices improved leaflet coaptation and were viable MR treatment options. The FE simulations in this study can be used to quantify biomechanics involved in clip treatments and improve our understanding of complex interactions between human hosts and percutaneous clip devices.

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

Background

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

Methods

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

Results

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

Conclusions

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

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

One of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

A Simplified In Silico Model of Left Ventricular Outflow in Patients After Transcatheter Mitral Valve Replacement with Anterior Leaflet Laceration

In silico modeling has been proposed as a tool to simulate left ventricular (LV) outflow tract (LVOT) obstruction in patients undergoing transcatheter mitral valve replacement (TMVR). This study validated a simplified approach to simulate LV outflow hemodynamics in the setting of TMVR with anterior leaflet laceration, a clinical technique used to mitigate the risk of LVOT obstruction. Personalized, 3-dimensional computational fluid dynamics models were developed from computed tomography images of six patients who underwent TMVR with anterior leaflet laceration. LV outflow hemodynamics were simulated using the patient-specific anatomy and the peak systolic flow rate as boundary conditions. The peak outflow velocity, a clinically relevant hemodynamic metric, was extracted from each simulation (v_sim-peak) and compared with the clinical measurement from Doppler echocardiography (v_clin-peak) for validation. In silico models were successfully developed and implemented for all patients. The pre-processing time was 2 h per model and the simulation could be completed within 3 h. In three patients, the lacerated anterior leaflet exposed open cells of the transcatheter valve to flow. Good agreement was obtained between v_sim-peak and v_clin-peak (r = 0.97, p < 0.01) with average discrepancies of 5 ± 2% and 14 ± 1% for patients with exposed and unexposed cells of the transcatheter valve, respectively. The proposed in silico modeling paradigm therefore simulated LV outflow hemodynamics in a time-efficient manner and demonstrated good agreement with clinical measurements. Future studies should investigate the ability of this paradigm to support clinical applications.

Fluid-Structure Interaction Analyses of Biological Systems Using Smoothed-Particle Hydrodynamics

Due to the inherent complexity of biological applications that more often than not include fluids and structures interacting together, the development of computational fluid-structure interaction models is necessary to achieve a quantitative understanding of their structure and function in both health and disease. The functions of biological structures usually include their interactions with the surrounding fluids. Hence, we contend that the use of fluid-structure interaction models in computational studies of biological systems is practical, if not necessary. The ultimate goal is to develop computational models to predict human biological processes. These models are meant to guide us through the multitude of possible diseases affecting our organs and lead to more effective methods for disease diagnosis, risk stratification, and therapy. This review paper summarizes computational models that use smoothed-particle hydrodynamics to simulate the fluid-structure interactions in complex biological systems.

Performance of high conformability vs. high radial force devices in the virtual treatment of TAVI patients with bicuspid aortic valve

OBJECTIVE

Transcatheter Aortic Valve Implantation (TAVI) is a consolidated procedure showing a low operative risk and excellent long-term outcomes in patients with aortic stenosis. Patients presenting a bicuspid aortic valve (BAV) often require valve replacement due to the highly calcific nature of the aortic leaflets. However, BAV patients have usually been contraindicated for TAVI due to their complex valve anatomy. The aim of this work was to compare the performance of devices featuring high conformability (HC) against those with high radial force (HRF).

METHODS

Four BAV patients undergoing TAVI were retrospectively selected. The aortic roots including the native leaflets and calcifications were reconstructed from pre-operative Computed Tomography scans. In each patient, both HC and HRF devices were virtually implanted using Finite Element Analysis simulations. After implantation, paravalvular orifice area, von Mises stress distribution, root contact area, and device eccentricity were calculated.

RESULTS

Simulations showed good agreement with intraoperative imaging. In 3 out of 4 patients, the HRF device resulted in a lower paravalvular area than the HC. Stress distribution was also more homogeneously distributed in the HRF group as compared with the HC group. Despite their lower adaptability, HRF devices showed consistently higher stent-root contact area.

CONCLUSION

HRF devices showed improved results with respect to HC valves after being deployed in BAV anatomies. We hypothesize that the ability to reshape the annulus is the major determinant of success in this subgroup of patients featuring highly calcified leaflets.

In silico approaches for transcatheter aortic valve replacement inspection

Introduction: Increasing applications of transcatheter aortic valve replacement (TAVR) to treat high- or medium-risk patients with aortic diseases have been proposed in recent years. Despite its increasing use, many influential factors are still to be understood. Furthermore, innovative applications of TAVR such as in bicuspid aortic valves or in low-risk patients are emerging in clinical use. Numerical analyses are increasingly used to reproduce clinical treatments. The future trends in this area are foreseen for in silico trials and personalized medicine. Areas covered: This review paper analyzes the recent years (Jan 2018 - Aug 2020) of in silico studies simulating the behavior of transcatheter aortic valves with emphasis on the addressed clinical question and the used modeling strategies. The manuscripts are firstly classified based on their clinical hypothesis. A second classification is based on the adopted modeling approach in terms of patient domain, device modeling, and inclusion or exclusion of the fluid domain. Expert opinion: The TAVR can be virtually performed in numerous vessel geometries and with different devices. This versatility allows a rapid evaluation of the feasibility of different implantation approaches for specific patients, and patient populations, resulting in faster and safer introduction or optimization of new treatments or devices.

Computer simulations of transapical mitral valve repair with neochordae implantation: Clinical implications

OBJECTIVES

Transapical beating heart neochordae implantation is an innovative mitral valve repair technique that has demonstrated promising clinical results in patients with primary mitral regurgitation. However, as clinical experience continues to increase, neochordae implantation criteria have not been fully standardized. The aim of this study was to investigate the biomechanical effects of selecting an antero-lateral apical access site compared with a postero-lateral site, and suboptimal neochordae length compared with optimal suture length, on restoring physiologic left heart dynamics.

METHODS

Transapical neochordae implantation using 3 and 4 sutures was computer simulated under 3 posterior mitral leaflet prolapse conditions: isolated P2, multiscallop P2/P3 and multiscallop P2/P1. Physiologic, pre- and postrepair left heart dynamics were evaluated using a fluid-structure interaction modeling framework.

RESULTS

Despite the absence of residual mitral regurgitation in all postrepair models with optimal neochordae length, selecting an antero-lateral apical entry site for the treatment of P2/P3 prolapse generated a significant increase (>80%) in neochordae tension and P2 peak stress, with respect to a postero-lateral entry site. During isolated P2 prolapse repair, although neochordae overtension by 5% led to minimal hemodynamic changes in the regurgitant volume compared with using an optimal suture length, a significant increase in systolic and diastolic neochordae tension (>300%) and posterior leaflet average stress (70%-460%) was quantified. On the other hand, neochordae undertension by 5% led to worsening of regurgitation severity.

CONCLUSIONS

This parametric computer study represents a further step toward an improved understanding of the biomechanical outcomes of transapical neochordae technologies.

A Comprehensive Engineering Analysis of Left Heart Dynamics After MitraClip in a Functional Mitral Regurgitation Patient

Percutaneous edge-to-edge mitral valve (MV) repair using MitraClip has been recently established as a treatment option for patients with heart failure and functional mitral regurgitation (MR), which significantly expands the number of patients that can be treated with this device. This study aimed to quantify the morphologic, hemodynamic and structural changes, and evaluate the biomechanical interaction between the MitraClip and the left heart (LH) complex of a heart failure patient with functional MR using a fluid-structure interaction (FSI) modeling framework. MitraClip implantation using lateral, central and double clip positions, as well as combined annuloplasty procedures were simulated in a patient-specific LH model that integrates detailed anatomic structures, incorporates age- and gender-matched non-linear elastic material properties, and accounts for mitral chordae tethering. Our results showed that antero-posterior distance, mitral annulus spherecity index, anatomic regurgitant orifice area, and anatomic opening orifice area decreased by up to 28, 39, 52, and 71%, respectively, when compared to the pre-clip model. MitraClip implantation immediately decreased the MR severity and improved the hemodynamic profile, but imposed a non-physiologic configuration and loading on the mitral apparatus, with anterior and posterior leaflet stress significantly increasing up to 210 and 145% during diastole, respectively. For this patient case, while implanting a combined central clip and ring resulted in the highest reduction in the regurgitant volume (46%), this configuration also led to mitral stenosis. Patient-specific computer simulations as used here can be a powerful tool to examine the complex device-host biomechanical interaction, and may be useful to guide device positioning for potential favorable clinical outcomes.

The Impact of Self-Expandable Transcatheter Aortic Valve Replacement on Concomitant Functional Mitral Regurgitation: A Comprehensive Engineering Analysis

Background

Mitral regurgitation (MR) is present in a large proportion of patients who undergo transcatheter aortic valve replacement (TAVR). However, existing clinical data on the impact of TAVR on early post-procedural MR severity are contradictory. Using a comprehensive computational engineering methodology, this study aimed to evaluate quantitatively the structural and hemodynamic impact of TAVR on aortic-mitral continuity and MR severity in a rigorously developed and validated patient-specific left heart (LH) computer model with aortic stenosis and concomitant functional MR.

Methods

TAVR procedure was virtually simulated using a self-expandable valve (SEV) at three implantation heights. Pre- and post-TAVR LH dynamics as well as intra-operative biomechanics were analyzed.

Results

No significant differences in early MR improvement (<10%) were noted at the three implantation depths when compared to the pre-TAVR state. The high deployment model resulted in the highest stress in the native aortic leaflets, lowest stent-tissue contact force, highest aortic-mitral angle, and highest MR reduction for this patient case. When comparing SEV vs. balloon-expandable valve (BEV) performance at an optimal implantation height, the SEV gave a higher regurgitant volume ⋅ than the pre-TAVR model (40.49 vs 37.59 ml), while the BEV model gave the lowest regurgitant volume (33.84 vs 37.59 ml).

Conclusions

Contact force, aortic-mitral angle, and valve annuli compression were identified as possible mechanistic parameters that may suggest avenues for acute MR improvement. Albeit a single patient parametric study, it is our hope that such detailed engineering analysis could shed some light into the underlying biomechanical mechanisms of TAVR impact on MR.

Transapical mitral valve repair with neochordae implantation: FSI analysis of neochordae number and complexity of leaflet prolapse

Transapical mitral valve repair with neochordae implantation is a relatively new minimally invasive technique to treat primary mitral regurgitation. Quantifying the complex biomechanical interaction and interdependence between the left heart structures and the neochordae during this procedure is technically challenging. The aim of this parametric computational study is to investigate the immediate effects of neochordae number and complexity of leaflet prolapse on restoring physiologic left heart dynamics after optimal transapical neochordae repair procedures. Neochordae implantation using three and four sutures was modeled under three clinically relevant prolapse conditions: isolated P2, multi-scallop P2/P3, and multi-scallop P2/P1. A fluid-structure interaction (FSI) modeling framework was used to evaluate the left heart dynamics under baseline, prerepair, and postrepair states. Despite immediate restoration of leaflet coaptation and no residual mitral regurgitation in all postrepair models, the average and peak stresses in the repaired scallop(s) increased >40% and >100%, respectively, compared with the baseline state. Additionally, anterior mitral leaflet marginal chordae tension increased >30%, while posterior mitral leaflet chordae tension decreased at least 30%. No marked differences in hemodynamic performance, in native and neochordae forces, and in leaflet stress were found when implanting three or four sutures. We report, to our knowledge, the first set of time-dependent in silico FSI human neochordae tension measurements during transapical neochordae repair. This work represents a further step towards an improved understanding of the biomechanical outcomes of minimally invasive mitral valve repair procedures.

Comparative quantification of primary mitral regurgitation by computer modeling and simulated echocardiography

Clinical investigations have demonstrated that mitral regurgitation (MR) quantification using echocardiography (echo) may significantly underestimate or overestimate the regurgitant volume, especially for two-dimensional (2D) echo. Computer modeling and simulated echo were conducted to evaluate the fundamental assumptions in the echo quantification of primary MR that is due to posterior mitral leaflet prolapse. The theoretical flaw of the proximal isovelocity surface area (PISA) method originates from the assumption that the MR flow rate is the product of the isovelocity surface area and aliasing velocity, which is only valid when the velocity vectors are perpendicular to the isovelocity surface. Other factors such as the Doppler angle effect, the view planes of 2D echo, and the single time instant of PISA were also analyzed. We find that the hemielliptic PISA method gives the smallest error for moderate and severe MR cases compared with other PISA methods. Compared with the PISA method, the volumetric technique (VT) is theoretically more robust. By considering correction factors that are caused by nonflat velocity profiles and the closing volume of the aortic valve, the accuracy of the VT method can be significantly improved. The corrected volumetric technique provides more accurate results compared with the PISA methods, especially for mild MR.NEW & NOTEWORTHY We evaluate the accuracy of common echocardiography techniques for the quantification of primary mitral regurgitations using computer modeling. The hemielliptic proximal isovelocity surface area (PISA) method gives the smallest error (within 15%) for moderate and severe mitral regurgitation cases compared with other PISA methods. The volumetric method is theoretically more robust than the PISA method. The accuracy of the volumetric method can be improved by a correction factor around 0.7 because of the nonflat velocity profiles and the closing volume of the aortic valve.

A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

Numerical analysis methods including finite element analysis (FEA), computational fluid dynamics (CFD), and fluid-structure interaction (FSI) analysis have been used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, for patient-specific computational analysis, complex procedures are usually required to set-up the models, and long computing time is needed to perform the simulation, preventing fast feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed deep neural networks (DNNs) to directly estimate the steady-state distributions of pressure and flow velocity inside the thoracic aorta. After training on hemodynamic data from CFD simulations, the DNNs take as input a shape of the aorta and directly output the hemodynamic distributions in one second. The trained DNNs are capable of predicting the velocity magnitude field with an average error of 1.9608% and the pressure field with an average error of 1.4269%. This study demonstrates the feasibility and great potential of using DNNs as a fast and accurate surrogate model for hemodynamic analysis of large blood vessels.