Sealing Behavior in Transcatheter Bicuspid and Tricuspid Aortic Valves Replacement Through Patient-Specific Computational Modeling.

Background: Patient-specific computer simulation of transcatheter aortic valve replacement (TAVR) can provide unique insights in device-patient interaction. Aims: This study was to compare transcatheter aortic valve sealing behavior in patients with bicuspid aortic valves (BAV) and tricuspid aortic valves (TAV) through patient-specific computational modeling. Methods: Patient-specific computer simulation was retrospectively performed with FEops HEARTguide for TAVR patients. Simulation output was compared with postprocedural computed tomography and echocardiography to validate the accuracy. Skirt malapposition was defined by a distance larger than 1 mm based on the predicted device-patient interaction by quantifying the distance between the transcatheter heart valve (THV) skirt and the surrounding anatomical regions. Results: In total, 43 patients were included in the study. Predicted and observed THV frame deformation showed good correlation (R 2 ≥ 0.90) for all analyzed measurements (maximum diameter, minimum diameter, area, and perimeter). The amount of predicted THV skirt malapposition was strongly linked with the echocardiographic grading of paravalvular leakage (PVL). More THV skirt malapposition was observed for BAV cases when compared to TAV cases (22.7 vs. 15.5%, p < 0.05). A detailed analysis of skirt malapposition showed a higher degree of malapposition in the interleaflet triangles section for BAV cases as compared to TAV patients (11.1 vs. 5.8%, p < 0.05). Conclusions: Patient-specific computer simulation of TAVR can accurately predict the behavior of the Venus A-valve. BAV patients are associated with more malapposition of the THV skirt as compared to TAV patients, and this is mainly driven by more malapposition in the interleaflet triangle region.

Towards patient-specific prediction of conduction abnormalities induced by transcatheter aortic valve implantation: a combined mechanistic modelling and machine learning approach.

Aims: Post-procedure conduction abnormalities (CA) remain a common complication of transcatheter aortic valve implantation (TAVI), highlighting the need for personalized prediction models. We used machine learning (ML), integrating statistical and mechanistic modelling to provide a patient-specific estimation of the probability of developing CA after TAVI. Methods and results: The cohort consisted of 151 patients with normal conduction and no pacemaker at baseline who underwent TAVI in nine European centres. Devices included CoreValve, Evolut R, Evolut PRO, and Lotus. Preoperative multi-slice computed tomography was performed. Virtual valve implantation with patient-specific computer modelling and simulation (CM&S) allowed calculation of valve-induced contact pressure on the anatomy. The primary composite outcome was new onset left or right bundle branch block or permanent pacemaker implantation (PPI) before discharge. A supervised ML approach was applied with eight models predicting CA based on anatomical, procedural and mechanistic data. CA occurred in 59% of patients (n = 89), more often after mechanical than first or second generation self-expanding valves (68% vs. 60% vs. 41%). CM&S revealed significantly higher contact pressure and contact pressure index in patients with CA. The best model achieved 83% accuracy (area under the curve 0.84) and sensitivity, specificity, positive predictive value, negative predictive value, and F1-score of 100%, 62%, 76%, 100%, and 82%. Conclusion: ML, integrating statistical and mechanistic modelling, achieved an accurate prediction of CA after TAVI. This study demonstrates the potential of a synergetic approach for personalizing procedure planning, allowing selection of the optimal device and implantation strategy, avoiding new CA and/or PPI.

Differences in clinical valve size selection and valve size selection for patient-specific computer simulation in transcatheter aortic valve replacement (TAVR): a retrospective multicenter analysis.

Valve size selection for transcatheter aortic valve replacement (TAVR) is currently based on cardiac CT-scan. At variance with patient-specific computer simulation, this does not allow the assessment of the valve-host interaction. We aimed to compare clinical valve size selection and valve size selection by an independent expert for computer simulation. A multicenter retrospective analysis of valve size selection by the physician and the independent expert in 141 patients who underwent TAVR with the self-expanding CoreValve or Evolut R. Baseline CT-scan was used for clinical valve size selection and for patient-specific computer simulation. Simulation results were not available for clinical use. Overall true concordance between clinical and simulated valve size selection was observed in 47 patients (33%), true discordance in 15 (11%) and ambiguity in 79 (56%). In 62 (44%, cohort A) one valve size was simulated whereas two valve sizes were simulated in 79 (56%, cohort B). In cohort A, concordance was 76% and discordance was 24%; a smaller valve size was selected for simulation in 10 patients and a larger in 5. In cohort B, a different valve size was selected for simulation in all patients in addition to the valve size that was used for TAVR. The different valve size concerned a smaller valve in 45 patients (57%) and a larger in 34 (43%). Selection of the valve size differs between the physician and the independent computer simulation expert who used the same source of information. These findings indicate that valve sizing in TAVR is still more intricate than generally assumed.

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

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

Optimization of a Transcatheter Heart Valve Frame Using Patient-Specific Computer Simulation.

PURPOSE: This study proposes a new framework to optimize the design of a transcatheter aortic valve through patient-specific finite element and fluid dynamics simulation. METHODS: Two geometrical parameters of the frame, the diameter at ventricular inflow and the height of the first row of cells, were examined using the central composite design. The effect of those parameters on postoperative complications was investigated by response surface methodology, and a Nonlinear Programming by Quadratic Lagrangian algorithm was used in the optimization. Optimal and initial devices were then compared in 12 patients. The comparison was made in terms of device performance [i.e., reduced contact pressure on the atrioventricular conduction system and paravalvular aortic regurgitation (AR)]. RESULTS: Results suggest that large diameters and high cells favor higher anchoring of the device within the aortic root reducing the contact pressure and favor a better apposition of the device to the aortic root preventing AR. Compared to the initial device, the optimal device resulted in almost threefold lower predicted contact pressure and limited AR in all patients. CONCLUSIONS: In conclusion, patient-specific modelling and simulation could help to evaluate device performance prior to the actual first-in-human clinical study and, combined with device optimization, could help to develop better devices in a shorter period.

Patient-specific computer simulation for transcatheter cardiac interventions: what a clinician needs to know.

Patient-specific computer simulation consists of the assessment of the interaction of the device with the host based on the integration of the detailed geometric and biomechanical properties of the device and host. Hence, it allows the prediction of valve performance (efficacy) and complications (safety) and may consequently help the physician to select the valve/device that best fits the individual patient, thereby improving outcome. There is currently little awareness and information in clinical medicine on patient-specific computer simulation. In this paper, we describe the technical background and a number of illustrations to illustrate how patient-specific computer simulation may be used for catheter-based treatment planning of acquired heart disease.

Patient-Specific Computer Simulation to Elucidate the Role of Contact Pressure in the Development of New Conduction Abnormalities After Catheter-Based Implantation of a Self-Expanding Aortic Valve.

BACKGROUND: The extent to which pressure generated by the valve on the aortic root plays a role in the genesis of conduction abnormalities after transcatheter aortic valve replacement (TAVR) is unknown. This study elucidates the role of contact pressure and contact pressure area in the development of conduction abnormalities after TAVR using patient-specific computer simulations. METHODS AND RESULTS: Finite-element computer simulations were performed to simulate TAVR of 112 patients who had undergone TAVR with the self-expanding CoreValve/Evolut R valve. On the basis of preoperative multi-slice computed tomography, a patient-specific region of the aortic root containing the atrioventricular conduction system was determined by identifying the membranous septum. Contact pressure and contact pressure index (percentage of area subjected to pressure) were quantified and compared in patients with and without new conduction abnormalities. Sixty-two patients (55%) developed a new left bundle branch block or a high-degree atrioventricular block after TAVR. Maximum contact pressure and contact pressure index (median [interquartile range]) were significantly higher in patients with compared with those without new conduction abnormalities (0.51 MPa [0.43-0.70 MPa] and 33% [22%-44%], respectively, versus 0.29 MPa [0.06-0.50 MPa] and 12% [1%-28%]). By multivariable regression analysis, only maximum contact pressure (odds ratio, 1.35; confidence interval, 1.1-1.7; P=0.01) and contact pressure index (odds ratio, 1.52; confidence interval, 1.1-2.1; P=0.01) were identified as independent predictors for conduction abnormalities, but not implantation depth. CONCLUSIONS: Patient-specific computer simulations revealed that maximum contact pressure and contact pressure index are both associated with new conduction abnormalities after CoreValve/Evolut R implantation and can predict which patient will have conduction abnormalities.

Fluid-Structure Interaction Simulation of Prosthetic Aortic Valves: Comparison between Immersed Boundary and Arbitrary Lagrangian-Eulerian Techniques for the Mesh Representation.

In recent years the role of FSI (fluid-structure interaction) simulations in the analysis of the fluid-mechanics of heart valves is becoming more and more important, being able to capture the interaction between the blood and both the surrounding biological tissues and the valve itself. When setting up an FSI simulation, several choices have to be made to select the most suitable approach for the case of interest: in particular, to simulate flexible leaflet cardiac valves, the type of discretization of the fluid domain is crucial, which can be described with an ALE (Arbitrary Lagrangian-Eulerian) or an Eulerian formulation. The majority of the reported 3D heart valve FSI simulations are performed with the Eulerian formulation, allowing for large deformations of the domains without compromising the quality of the fluid grid. Nevertheless, it is known that the ALE-FSI approach guarantees more accurate results at the interface between the solid and the fluid. The goal of this paper is to describe the same aortic valve model in the two cases, comparing the performances of an ALE-based FSI solution and an Eulerian-based FSI approach. After a first simplified 2D case, the aortic geometry was considered in a full 3D set-up. The model was kept as similar as possible in the two settings, to better compare the simulations' outcomes. Although for the 2D case the differences were unsubstantial, in our experience the performance of a full 3D ALE-FSI simulation was significantly limited by the technical problems and requirements inherent to the ALE formulation, mainly related to the mesh motion and deformation of the fluid domain. As a secondary outcome of this work, it is important to point out that the choice of the solver also influenced the reliability of the final results.