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

An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation

In recent years, transcatheter edge-to-edge repair (TEER) has been widely adopted as an effective treatment for mitral regurgitation (MR). The aim of this study is to develop a personalized in silico model to predict the effect of edge-to-edge repair in advance to the procedure for each individual patient. For this purpose, we propose a combination of a valve deformation model for computing the mitral valve (MV) orifice area (MVOA) and a lumped parameter model for the hemodynamics, specifically mitral regurgitation volume (RVol). Although we cannot obtain detailed information on the three-dimensional flow field near the mitral valve, we can rapidly simulate the important medical parameters for the clinical decision support. In the present method, we construct the patient-specific pre-operative models by using the parameter optimization and then simulate the postoperative state by applying the additional clipping condition. The computed preclip MVOAs show good agreement with the clinical measurements, and the correlation coefficient takes 0.998. In addition, the MR grade in terms of RVol also has good correlation with the grade by ground truth MVOA. Finally, we try to investigate the applicability for the predicting the postclip state. The simulated valve shapes clearly show the well-known double orifice and the improvement of the MVOA, compared with the preclip state. Similarly, we confirmed the improved reverse flow and MR grade in terms of RVol. A total computational time is approximately 8 h by using general-purpose PC. These results obviously indicate that the present in silico model has good capability for the assessment of edge-to-edge repair.

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.

Patient-Specific Quantitative In-Vivo Assessment of Human Mitral Valve Leaflet Strain Before and After MitraClip Repair

PURPOSE

Mitral regurgitation (MR) is a highly prevalent and deadly cardiac disease characterized by improper mitral valve (MV) leaflet coaptation. Among the plethora of available treatment strategies, the MitraClip is an especially safe option, but optimizing its long-term efficacy remains an urgent challenge.

METHODS

We applied our noninvasive image-based strain computation pipeline [1] to intraoperative transesophageal echocardiography datasets taken from ten patients undergoing MitraClip repair, spanning a range of MR etiologies and MitraClip configurations. We then analyzed MV leaflet strains before and after MitraClip implementation to develop a better understanding of (1) the pre-operative state of human regurgitant MV, and (2) the MitraClip's impact on the MV leaflet deformations.

RESULTS

The MV pre-operative strain fields were highly variable, underscoring both the heterogeneity of the MR in the patient population and the need for patient-specific treatment approaches. Similarly, there were no consistent overall post-operative strain patterns, although the average A2 segment radial strain difference between pre- and post-operative states was consistently positive. In contrast, the post-operative strain fields were better correlated to their respective pre-operative strain fields than to the inter-patient post-operative strain fields. This quantitative result implies that the patient specific pre-operative state of the MV guides its post-operative deformation, which suggests that the post-operative state can be predicted using pre-operative data-derived modelling alone.

CONCLUSIONS

The pre-operative MV leaflet strain patterns varied considerably across the range of MR disease states and after MitraClip repair. Despite large inter-patient heterogeneity, the post-operative deformation appears principally dictated by the pre-operative deformation state. This novel finding suggests that though the variation in MR functional state and MitraClip-induced deformation were substantial, the post-operative state can be predicted from the pre-operative data alone. This study suggests that, with use of larger patient cohort and corresponding long-term outcomes, quantitative predictive factors of MitraClip durability can be identified.

Utilization of Engineering Advances for Detailed Biomechanical Characterization of the Mitral-Ventricular Relationship to Optimize Repair Strategies: A Comprehensive Review

The geometrical details and biomechanical relationships of the mitral valve-left ventricular apparatus are very complex and have posed as an area of research interest for decades. These characteristics play a major role in identifying and perfecting the optimal approaches to treat diseases of this system when the restoration of biomechanical and mechano-biological conditions becomes the main target. Over the years, engineering approaches have helped to revolutionize the field in this regard. Furthermore, advanced modelling modalities have contributed greatly to the development of novel devices and less invasive strategies. This article provides an overview and narrative of the evolution of mitral valve therapy with special focus on two diseases frequently encountered by cardiac surgeons and interventional cardiologists: ischemic and degenerative mitral regurgitation.

Machine learning used for simulation of MitraClip intervention: A proof-of-concept study

Introduction: Severe mitral regurgitation (MR) is a mitral valve disease that can lead to lifethreatening complications. MitraClip (MC) therapy is a percutaneous solution for patients who cannot tolerate surgical solutions. In MC therapy, a clip is implanted in the heart to reduce MR. To achieve optimal MC therapy, the cardiologist needs to foresee the outcomes of different scenarios for MC implantation, including the location of the MC. Although finite element (FE) modeling can simulate the outcomes of different MC scenarios, it is not suitable for clinical usage because it requires several hours to complete.

Methods: In this paper, we used machine learning (ML) to predict the outcomes of MC therapy in less than 1 s. Two ML algorithms were used: XGBoost, which is a decision tree model, and a feed-forward deep learning (DL) model. The MC location, the geometrical attributes of the models and baseline stress and MR were the features of the ML models, and the predictions were performed for MR and maximum von Mises stress in the leaflets. The parameters of the ML models were determined to achieve the minimum errors obtained by applying the ML models on the validation set.

Results: The results for the test set (not used during training) showed relative agreement between ML predictions and ground truth FE predictions. The accuracy of the XGBoost models were better than DL models. Mean absolute percentage error (MAPE) for the XGBoost predictions were 0.115 and 0.231, and the MAPE for DL predictions were 0.154 and 0.310, for MR and stress, respectively.

Discussion: The ML models reduced the FE runtime from 6 hours (on average) to less than 1 s. The accuracy of ML models can be increased by increasing the dataset size. The results of this study have important implications for improving the outcomes of MC therapy by providing information about the outcomes of MC implantation in real-time.

Effect of transcatheter edge-to-edge repair device position on diastolic hemodynamic parameters: An echocardiography-based simulation study

Background

Transcatheter edge-to-edge repair (TEER) has developed from innovative technology to an established treatment strategy of mitral regurgitation (MR). The risk of iatrogenic mitral stenosis after TEER is, however, a critical factor in the conflict of interest between maximal reduction of MR and minimal impairment of left ventricular filling. We aim to investigate systematically the impact of device position on the post treatment hemodynamic outcome by involving the patient-specific segmentation of the diseased mitral valve.

Materials and methods

Transesophageal echocardiographic image data of ten patients with severe MR (age: 57 ± 8 years, 20% female) were segmented and virtually treated with TEER at three positions by using a position based dynamics approach. Pre- and post-interventional patient geometries were preprocessed for computational fluid dynamics (CFD) and simulated at peak-diastole with patient-specific blood flow boundary conditions. Simulations were performed with boundary conditions mimicking rest and stress. The simulation results were compared with clinical data acquired for a cohort of 21 symptomatic MR patients (age: 79 ± 6 years, 43% female) treated with TEER.

Results

Virtual TEER reduces the mitral valve area (MVA) from 7.5 ± 1.6 to 2.6 ± 0.6 cm2. Central device positioning resulted in a 14% smaller MVA than eccentric device positions. Furthermore, residual MVA is better predictable for central than for eccentric device positions (R2 = 0.81 vs. R2 = 0.49). The MVA reduction led to significantly higher maximal diastolic velocities (pre: 0.9 ± 0.2 m/s, post: 2.0 ± 0.5 m/s) and pressure gradients (pre: 1.5 ± 0.6 mmHg, post: 16.3 ± 9 mmHg) in spite of a mean flow rate reduction by 23% due to reduced MR after the treatment. On average, velocities were 12% and pressure gradients were 25% higher with devices in central compared to lateral or medial positions.

Conclusion

Virtual TEER treatment combined with CFD is a promising tool for predicting individual morphometric and hemodynamic outcomes. Such a tool can potentially be used to support clinical decision making, procedure planning, and risk estimation to prevent post-procedural iatrogenic mitral stenosis.

Computational Analysis of Flow Structures in Turbulent Ventricular Blood Flow Associated With Mitral Valve Intervention

Cardiac disease and clinical intervention may both lead to an increased risk for thrombosis events due to a modified blood flow in the heart, and thereby a change in the mechanical stimuli of blood cells passing through the chambers of the heart. Specifically, the degree of platelet activation is influenced by the level and type of mechanical stresses in the blood flow. In this article we analyze the blood flow in the left ventricle of the heart through a computational model constructed from patient-specific data. The blood flow in the ventricle is modelled by the Navier-Stokes equations, and the flow through the mitral valve by a parameterized model which represents the projected opening of the valve. A finite element method is used to solve the equations, from which a simulation of the velocity and pressure of the blood flow is constructed. The intraventricular blood flow is complex, in particular in diastole when the inflow jet from the atrium breaks down into turbulent flow on a range of scales. A triple decomposition of the velocity gradient tensor is then used to distinguish between rigid body rotational flow, irrotational straining flow, and shear flow. The triple decomposition enables the separation of three fundamentally different flow structures, that each generates a distinct type of mechanical stimulus on the blood cells in the flow. We compare the results in a simulation where a mitral valve clip intervention is modelled, which leads to a significant modification of the intraventricular flow. Further, we perform a sensitivity study of the results with respect to the positioning of the clip. It was found that the shear in the simulation cases treated with clips increased more compared to the untreated case than the rotation and strain did. A decrease in valve opening area of 64% in one of the cases led to a 90% increase in rotation and strain, but a 150% increase in shear. The computational analysis opens up for improvements in models of shear-induced platelet activation, by offering an algorithm to distinguish shear from other modalities in intraventricular blood flow.

Effects of MitraClip Therapy on Mitral Flow Patterns and Vortex Formation: An In Vitro Study

MitraClip transcatheter edge-to-edge repair is used to treat mitral regurgitation (MR). While MR is reduced, diastolic left ventricular flows are altered. An in vitro left heart simulator was used to assess a porcine mitral valve in the native, MR, and MR plus MitraClip cases. Velocity, vorticity, and Reynolds shear stress (RSS) were quantified by particle image velocimetry. Peak velocity increased from 1.20 m/s for native to 1.30 m/s with MR. With MitraClip, two divergent jets of 1.18 and 0.61 m/s emerged. Higher vorticity was observed with MR than native and lessened with MitraClip. MitraClip resulted in shear layer formation and downstream vortex formation. Native RSS decreased from 33 Pa in acceleration to 29 Pa at peak flow, then increased to 31 Pa with deceleration. MR RSS increased from 27 Pa in acceleration to 40 Pa at peak flow to 59 Pa during deceleration. MitraClip RSS increased from 79 Pa in acceleration to 162 Pa during peak flow, then decreased to 45 Pa during deceleration. After MitraClip, two divergent jets of reduced velocity emerged, accompanied by shear layers and recirculation. Chaotic flow developed, resulting in elevated RSS magnitude and coverage. Findings help understand consequences of MitraClip on left ventricular flow dynamics.

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 impact of transcatheter edge-to-edge repair on mitral valve annular geometry

PURPOSE OF REVIEW

Mitral valve transcatheter edge-to-edge repair (TEER) is becoming increasingly common to treat severe mitral regurgitation. However, the lack of concomitant annuloplasty raises concerns regarding its durability. As a result, there is an emerging body of literature evaluating the impacts of TEER on mitral annular geometry. In this review, we summarize the most recent literature evaluating the impacts of TEER on annular geometry in the acute, intermediate and long-term. We also review the relationship between changes in annular geometry and clinical endpoints.

RECENT FINDINGS

Current evidence suggests that TEER acutely induces favourable changes in mitral annular size and shape, which may persist for at least up to 1 year. Few studies suggest that TEER-induced annular remodelling is associated with positive clinical outcomes.

SUMMARY

The current body of literature is sparse and limited to primarily small case series. Data from the surgical literature suggest that ringless edge-to-edge repair is associated with eventual failure. Unfortunately, few studies evaluate TEER-induced annular changes beyond the acute postprocedural phase. Future research needs to focus on and evaluate the significance of TEER-induced changes in annular dimensions in the long-term.

Invasive hemodynamics are equivocal for functional outcomes after MitraClip

Objectives

To evaluate invasive hemodynamics in assessing MC therapy success as well as evaluate its effectiveness as a predictor of functional outcomes.

Background

Mitral regurgitation grade is a poor predictor of functional outcomes after a MitraClip. There is a paucity of data on invasive hemodynamics as a predictor of outcomes.

Methods

Sixty-nine patients underwent MC between 2015 and 2018 at the University of Minnesota Medical Center and were retrospectively analyzed. Invasive hemodynamics were performed before and after device deployment with transesophageal echocardiographic guidance. Statistical analysis was performed using STATA version 16. Student's t test was used for continuous variables and Pearson's chi-squared test for categorical variables. Mann-Whitney test was performed for continuous variables where data were not normally distributed. Logistic and linear regression were used to investigate relationships between variables and outcomes.

Results

A total of 69 patients were included in the study. The mean age was 83 (75-87) years and 38 (55%) were male. Eighty-one percentage had >/= NYHA III symptoms. Eighty-seven percentage had severe MR. Pulmonary capillary wedge pressure was 20 (15-24). Overall, there was significant improvement in left atrial pressure including mean left atrial pressure index, MR, and NYHA class after MC (<.001). There was no significant association between invasive hemodynamics (including left atrial mean pressure index or its reduction rate) and functional outcomes (p = NS). MR grade was also not predictive of functional outcomes.

Conclusion

Left atrial pressure may not be a significant predictor of functional outcomes, and, in isolation, may not be an improvement over MR grade.

Mitral Valve Atlas for Artificial Intelligence Predictions of MitraClip Intervention Outcomes

Severe mitral regurgitation (MR) is a cardiac disease that can lead to fatal consequences. MitraClip (MC) intervention is a percutaneous procedure whereby the mitral valve (MV) leaflets are connected along the edge using MCs. The outcomes of the MC intervention are not known in advance, i.e., the outcomes are quite variable. Artificial intelligence (AI) can be used to guide the cardiologist in selecting optimal MC scenarios. In this study, we describe an atlas of shapes as well as different scenarios for MC implantation for such an AI analysis. We generated the MV geometrical data from three different sources. First, the patients' 3-dimensional echo images were used. The pixel data from six key points were obtained from three views of the echo images. Using PyGem, an open-source morphing library in Python, these coordinates were used to create the geometry by morphing a template geometry. Second, the dimensions of the MV, from the literature were used to create data. Third, we used machine learning methods, principal component analysis, and generative adversarial networks to generate more shapes. We used the finite element (FE) software ABAQUS to simulate smoothed particle hydrodynamics in different scenarios for MC intervention. The MR and stresses in the leaflets were post-processed. Our physics-based FE models simulated the outcomes of MC intervention for different scenarios. The MR and stresses in the leaflets were computed by the FE models for a single clip at different locations as well as two and three clips. Results from FE simulations showed that the location and number of MCs affect subsequent residual MR, and that leaflet stresses do not follow a simple pattern. Furthermore, FE models need several hours to provide the results, and they are not applicable for clinical usage where the predicted outcomes of MC therapy are needed in real-time. In this study, we generated the required dataset for the AI models which can provide the results in a matter of seconds.

A finite element model of the cardiac ventricles with coupled circulation: Biventricular mesh generation with hexahedral elements, airbags and a functional mockup interface to the circulation

INTRODUCTION

Finite element (FE) mechanics models of the heart are becoming more sophisticated. However, there is lack of consensus about optimal element type and coupling of FE models to the circulation. We describe biventricular (left (LV) and right (RV) ventricles) FE mechanics model creation using hexahedral elements, airbags and a functional mockup interface (FMI) to lumped-parameter models of the circulation.

METHODS

Cardiac MRI (CMR) was performed in two healthy volunteers and a single patient with ischemic heart disease (IHD). CMR images were segmented and surfaced, meshing with hexahedral elements was performed with a "thin butterfly with septum" topology. LV and RV inflow and outflow airbags were coupled to lumped-parameter circulation models with an FMI interface. Pulmonary constriction (PAC) and vena cava occlusion (VCO) were simulated and end-systolic pressure-volume relations (ESPVR) were calculated.

RESULTS

Mesh construction was prompt with representative contouring and mesh adjustment requiring 32 and 26 min Respectively. The numbers of elements ranged from 4104 to 5184 with a representative Jacobian of 1.0026 ± 0.4531. Agreement between CMR-based surfaces and mesh was excellent with root-mean-squared error of 0.589 ± 0.321 mm. The LV ESPVR slope was 3.37 ± 0.09 in volunteers but 2.74 in the IHD patient. The effect of PAC and VCO on LV ESPVR was consistent with ventricular interaction (p = 0.0286).

CONCLUSION

Successful co-simulation using a biventricular FE mechanics model with hexahedral elements, airbags and an FMI interface to lumped-parameter model of the circulation was demonstrated. Future studies will include comparison of element type and study of cardiovascular pathologies and device therapies.

Computational Analysis of Virtual Echocardiographic Assessment of Functional Mitral Regurgitation for Validation of Proximal Isovelocity Surface Area Methods

BACKGROUND

Mitral regurgitation (MR) quantification by the proximal isovelocity surface area (PISA) method remains challenging. Using computer models, the authors evaluated the accuracy of different PISA methods and quantified their errors.

METHODS

Five functional MR computer models of different geometric and tethering abnormalities were created, validated, and treated as phantom models, from which the reference values were directly obtained. Virtual two-dimensional (2D) PISA and three-dimensional (3D) PISA (both peak and integrated values) were performed on these phantom models. By comparing virtual PISA results with reference values, the accuracy of different PISA methods was evaluated, and their sources of errors were quantified.

RESULTS

Compared with reference values of regurgitant flow rate, excellent correlations were found for true PISA (r = 0.99, bias = 32.3 ± 35.3 mL/sec), 3D PISA (r = 0.97, bias = -24.4 ± 55.5 mL/sec), followed by multiplane 2D hemicylindrical PISA (r = 0.88, bias = -24.1 ± 85.4 mL/sec) and hemiellipsoidal PISA (r = 0.91, bias = -55.7 ± 96.6 mL/sec). Weaker correlations were found for single-plane 2D hemispherical PISA (parasternal long-axis: r = 0.71, bias = -77.6 ± 124.5 mL/sec; apical two-chamber: r = 0.69, bias = -52.0 ± 122.0 mL/sec; apical four-chamber: r = 0.82, bias = -65.5 ± 107.3 mL/sec). For regurgitant volume quantification, integrated PISA was more accurate than peak PISA. The bias of 3D PISA improved from -12.7 ± 7.8 mL (peak PISA) to -2.1 ± 5.3 mL (integrated PISA).

CONCLUSIONS

For functional MR quantification, 2D hemispherical PISA had significant underestimation, multiplane 2D hemiellipsoidal and hemicylindrical PISA showed improved accuracy, and 3D PISA was the most accurate. The PISA method is subject to both systematic underestimation due to the Doppler angle effect and systematic overestimation when regurgitant flow is not perpendicular to PISA contour. Integrated PISA is able to capture dynamic MR and is therefore more accurate than peak PISA. The sum of regurgitant flow rates is the most feasible way to perform integrated PISA.

State-of-the-art intra-procedural imaging for the mitral and tricuspid PASCAL Repair System

Advanced intra-procedural imaging techniques have been integral to technical and procedural success transcatheter devices. A novel leaflet approximation therapy, the PASCAL Transcatheter Valve Repair System (Edwards Lifesciences, Irvine, CA, USA) has demonstrated high procedural success, acceptable safety, and significant clinical improvement in patients with severe mitral and tricuspid regurgitation and has CE mark approval in Europe with pivotal trials underway in the USA. This review outlines the pre-procedural imaging views and advanced transoesophageal imaging protocols both mitral and tricuspid valve device implantation.

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.

In Vivo Image-Based 4D Modeling of Competent and Regurgitant Mitral Valve Dynamics

BACKGROUND

In vivo characterization of mitral valve dynamics relies on image analysis algorithms that accurately reconstruct valve morphology and motion from clinical images. The goal of such algorithms is to provide patient-specific descriptions of both competent and regurgitant mitral valves, which can be used as input to biomechanical analyses and provide insights into the pathophysiology of diseases like ischemic mitral regurgitation (IMR).

OBJECTIVE

The goal is to generate accurate image-based representations of valve dynamics that visually and quantitatively capture normal and pathological valve function.

METHODS

We present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE), an imaging modality used for pre-operative surgical planning of mitral interventions. The framework integrates groupwise multi-atlas label fusion and template-based medial modeling with Kalman filtering to generate quantitatively descriptive and temporally consistent models of valve dynamics.

RESULTS

The algorithm is evaluated on rt-3DE data series from 28 patients: 14 with normal mitral valve morphology and 14 with severe IMR. In these 28 data series that total 613 individual 3DE images, each 3D mitral valve segmentation is validated against manual tracing, and temporal consistency between segmentations is demonstrated.

CONCLUSIONS

Automated 4D image analysis allows for reliable non-invasive modeling of the mitral valve over the cardiac cycle for comparison of annular and leaflet dynamics in pathological and normal mitral valves. Future studies can apply this algorithm to cardiovascular mechanics applications, including patient-specific strain estimation, fluid dynamics simulation, inverse finite element analysis, and risk stratification for surgical treatment.