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

In vitro bench testing using patient-specific 3D models for percutaneous pulmonary valve implantation with Venus P-valve

BACKGROUND

Due to the wide variety of morphology, size, and dynamics, selecting an optimal valve size and location poses great difficulty in percutaneous pulmonary valve implantation (PPVI). This study aimed to report our experience with in vitro bench testing using patient-specific three-dimensional (3D)-printed models for planning PPVI with the Venus P-valve.

METHODS

Patient-specific 3D soft models were generated using PolyJet printing with a compliant synthetic material in 15 patients scheduled to undergo PPVI between July 2018 and July 2020 in Central China Fuwai Hospital of Zhengzhou University.

RESULTS

3D model bench testing altered treatment strategy in all patients (100%). One patient was referred for surgery because testing revealed that even the largest Venus P-valve would not anchor properly. In the remaining 14 patients, valve size and/or implantation location was altered to avoid valve migration and/or compression coronary artery. In four patients, it was decided to change the point anchoring because of inverted cone-shaped right ventricular outflow tract (RVOT) ( n = 2) or risk of compression coronary artery ( n = 2). Concerning sizing, we found that an oversize of 2-5 mm suffices. Anchoring of the valve was dictated by the flaring of the in- and outflow portion in the pulmonary artery. PPVI was successful in all 14 patients (absence of valve migration, no coronary compression, and none-to-mild residual pulmonary regurgitation [PR]). The diameter of the Venus P-valve in the 3D simulation group was significantly smaller than that of the conventional planning group (36 [2] vs. 32 [4], Z = -3.77, P <0.001).

CONCLUSIONS

In vitro testing indicated no need to oversize the Venus P-valve to the degree recommended by the balloon-sizing technique, as 2-5 mm sufficed.

Physical and Computational Modeling for Transcatheter Structural Heart Interventions

Structural heart disease interventions rely heavily on preprocedural planning and simulation to improve procedural outcomes and predict and prevent potential procedural complications. Modeling technologies, namely 3-dimensional (3D) printing and computational modeling, are nowadays increasingly used to predict the interaction between cardiac anatomy and implantable devices. Such models play a role in patient education, operator training, procedural simulation, and appropriate device selection. However, current modeling is often limited by the replication of a single static configuration within a dynamic cardiac cycle. Recognizing that health systems may face technical and economic limitations to the creation of "in-house" 3D-printed models, structural heart teams are pivoting to the use of computational software for modeling purposes.

The Application of Precision Medicine in Structural Heart Diseases: A Step towards the Future

The personalized applications of 3D printing in interventional cardiology and cardiac surgery represent a transformative paradigm in the management of structural heart diseases. This review underscores the pivotal role of 3D printing in enhancing procedural precision, from preoperative planning to procedural simulation, particularly in valvular heart diseases, such as aortic stenosis and mitral regurgitation. The ability to create patient-specific models contributes significantly to predicting and preventing complications like paravalvular leakage, ensuring optimal device selection, and improving outcomes. Additionally, 3D printing extends its impact beyond valvular diseases to tricuspid regurgitation and non-valvular structural heart conditions. The comprehensive synthesis of the existing literature presented here emphasizes the promising trajectory of individualized approaches facilitated by 3D printing, promising a future where tailored interventions based on precise anatomical considerations become standard practice in cardiovascular care.

Assessing Post-TAVR Cardiac Conduction Abnormalities Risk Using a Digital Twin of a 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 his study, an in-silico framework was developed to assess the CCA risk, incorporating the effect of a dynamic beating heart and pre-procedural 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 electro-mechanically 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 baseline (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 baseline 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.

Preoperative computed tomography-imaging with patient-specific computer simulation in transcatheter aortic valve implantation: Design and rationale of the GUIDE-TAVI trial

BACKGROUND

Transcatheter aortic valve implantation (TAVI) is an established treatment option for patients with severe aortic valve stenosis, but is still associated with relatively high rates of pacemaker implantation and paravalvular regurgitation. Routine preoperative computed tomography (CT) combined with patient-specific computer modelling can predict the interaction between the TAVI device and the patient's unique anatomy, allowing physicians to assess the risk for paravalvular regurgitation and conduction disorders in advance to the procedure. The aim of this trial is to assess potential improvement in the procedural outcome of TAVI by applying CT-based patient-specific computer simulations in patients with suitable anatomy for TAVI.

METHODS

The GUIDE-TAVI trial is an international multicenter randomized controlled trial including patients accepted for TAVI by the Heart Team. Patients enrolled in the study will be randomized into 2 arms of each 227 patients. In patients randomized to the use of FEops HEARTGuide (FHG), patient-specific computer simulation with FHG is performed in addition to routine preoperative CT imaging and results of the FHG are available to the operator(s) prior to the scheduled intervention. In patients randomized to no use of FHG, only routine preoperative CT imaging is performed. The primary objective is to evaluate whether the use of FHG will reduce the incidence of mild to severe PVR, according to the Valve Academic Research Consortium 3. Secondary endpoints include the incidence of new conduction disorders requiring permanent pacemaker implantation, the difference between preoperative and final selected valve size, the difference between target and final implantation depth, change of preoperative decision, failure to implant valve, early safety composite endpoint and quality of life.

CONCLUSIONS

The GUIDE-TAVI trial is the first multicenter randomized controlled trial to evaluate the value of 3-dimensional computer simulations in addition to standard preprocedural planning in TAVI procedures.

Generation of synthetic aortic valve stenosis geometries for in silico trials

In silico trials are a promising way to increase the efficiency of the development, and the time to market of cardiovascular implantable devices. The development of transcatheter aortic valve implantation (TAVI) devices, could benefit from in silico trials to overcome frequently occurring complications such as paravalvular leakage and conduction problems. To be able to perform in silico TAVI trials virtual cohorts of TAVI patients are required. In a virtual cohort, individual patients are represented by computer models that usually require patient-specific aortic valve geometries. This study aimed to develop a virtual cohort generator that generates anatomically plausible, synthetic aortic valve stenosis geometries for in silico TAVI trials and allows for the selection of specific anatomical features that influence the occurrence of complications. To build the generator, a combination of non-parametrical statistical shape modeling and sampling from a copula distribution was used. The developed virtual cohort generator successfully generated synthetic aortic valve stenosis geometries that are comparable with a real cohort, and therefore, are considered as being anatomically plausible. Furthermore, we were able to select specific anatomical features with a sensitivity of around 90%. The virtual cohort generator has the potential to be used by TAVI manufacturers to test their devices. Future work will involve including calcifications to the synthetic geometries, and applying high-fidelity fluid-structure-interaction models to perform in silico trials.

Clinical value of CT-derived simulations of transcatheter-aortic-valve-implantation in challenging anatomies the PRECISE-TAVI trial

BACKGROUND

Preprocedural computed tomography planning improves procedural safety and efficacy of transcatheter aortic valve implantation (TAVI). However, contemporary imaging modalities do not account for device-host interactions.

AIMS

This study evaluates the value of preprocedural computer simulation with FEops HEARTguideTM on overall device success in patients with challenging anatomies undergoing TAVI with a contemporary self-expanding supra-annular transcatheter heart valve.

METHODS

This prospective multicenter observational study included patients with a challenging anatomy defined as bicuspid aortic valve, small annulus or severely calcified aortic valve. We compared the heart team's transcatheter heart valve (THV) planning decision based on (1) conventional multislice computed tomography (MSCT) and (2) MSCT imaging with FEops HEARTguideTM simulations. Clinical outcomes and THV performance were followed up to 30 days.

RESULTS

A total of 77 patients were included (median age 79.9 years (IQR 74.2-83.8), 42% male). In 35% of the patients, preprocedural planning changed after FEops HEARTguideTM simulations (change in valve size selection [12%] or target implantation height [23%]). A new permanent pacemaker implantation (PPI) was implanted in 13% and >trace paravalvular leakage (PVL) occurred in 28.5%. The contact pressure index (i.e., simulation output indicating the risk of conduction abnormalities) was significantly higher in patients with a new PPI, compared to those without (16.0% [25th-75th percentile 12.0-21.0] vs. 3.5% [25th-75th percentile 0-11.3], p < 0.01) The predicted PVL was 5.7 mL/s (25th-75th percentile 1.3-11.1) in patients with none-trace PVL, 12.7 (25th-75th percentile 5.5-19.1) in mild PVL and 17.7 (25th-75th percentile 3.6-19.4) in moderate PVL (p = 0.04).

CONCLUSION

FEops HEARTguideTM simulations may provide enhanced insights in the risk for PVL or PPI after TAVI with a self-expanding supra-annular THV in complex anatomies.

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.

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.

Ongoing experience with patient-specific computer simulation of transcatheter aortic valve replacement in bicuspid aortic valve

BACKGROUND

Transcatheter aortic valve replacement (TAVR) is increasingly being used to treat younger, lower-risk patients with bicuspid aortic valve (BAV). Patient-specific computer simulation may identify patients at risk for developing paravalvular regurgitation (PVR) and major conduction disturbance. Only limited prospective experience of this technology exist. We wished to describe our ongoing experience with patient-specific computer simulation.

METHODS

Patients who were referred for consideration of TAVR with a self-expanding transcatheter heart valve (THV) and had BAV identified on pre-procedural cardiac computed tomography imaging underwent patient-specific computer simulation. The computer simulations were reviewed by the Heart Team and used to guide surgical or transcatheter treatment approaches and to aid in THV sizing and positioning. Clinical outcomes were recorded.

RESULTS

Between May 2019 and May 2021, 16 patients with BAV were referred for consideration of TAVR with a self-expanding THV. Sievers Type 1 morphology was present in 15 patients and Type 0 in the remaining patient. Two patients were predicted to develop moderate-to-severe PVR with a TAVR procedure and these patients underwent successful surgical aortic valve replacement. In the remaining 14 patients, computer simulation was used to optimize THV sizing and positioning to minimise PVR and conduction disturbance. One patient with a low valve implantation depth developed moderate PVR and this complication was correctly predicted by the computer simulations. No patient required insertion of a new permanent pacemaker.

CONCLUSION

Patient-specific computer simulation may be used to guide the most appropriate treatment modality for patients with BAV. The usage of computer simulation to guide THV sizing and positioning was associated with favourable clinical outcomes.

Patient-Specific Numerical Simulations of Endovascular Procedures in Complex Aortic Pathologies: Review and Clinical Perspectives

The endovascular technique is used in the first line treatment in many complex aortic pathologies. Its clinical outcome is mostly determined by the appropriate selection of a stent-graft for a specific patient and the operator's experience. New tools are still needed to assist practitioners with decision making before and during procedures. For this purpose, numerical simulation enables the digital reproduction of an endovascular intervention with various degrees of accuracy. In this review, we introduce the basic principles and discuss the current literature regarding the use of numerical simulation for endovascular management of complex aortic diseases. Further, we give the future direction of everyday clinical applications, showing that numerical simulation is about to revolutionize how we plan and carry out endovascular interventions.

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.

Artificial Intelligence and Cardiovascular Risk Prediction: All That Glitters is not Gold

Artificial intelligence (AI) is a broad term referring to any automated systems that need 'intelligence' to carry out specific tasks. During the last decade, AI-based techniques have been gaining popularity in a vast range of biomedical fields, including the cardiovascular setting. Indeed, the dissemination of cardiovascular risk factors and the better prognosis of patients experiencing cardiovascular events resulted in an increase in the prevalence of cardiovascular disease (CVD), eliciting the need for precise identification of patients at increased risk for development and progression of CVD. AI-based predictive models may overcome some of the limitations that hinder the performance of classic regression models. Nonetheless, the successful application of AI in this field requires knowledge of the potential pitfalls of the AI techniques, to guarantee their safe and effective use in daily clinical practice. The aim of the present review is to summarise the pros and cons of different AI methods and their potential application in the cardiovascular field, with a focus on the development of predictive models and risk assessment tools.

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.

Application of cardiovascular 3-dimensional printing in Transcatheter aortic valve replacement

Transcatheter aortic valve replacement (TAVR) has been performed for nearly 20 years, with reliable safety and efficacy in moderate- to high-risk patients with aortic stenosis or regurgitation, with the advantage of less trauma and better prognosis than traditional open surgery. However, because surgeons have not been able to obtain a full view of the aortic root, 3-dimensional printing has been used to reconstruct the aortic root so that they could clearly and intuitively understand the specific anatomical structure. In addition, the 3D printed model has been used for the in vitro simulation of the planned procedures to predict the potential complications of TAVR, the goal being to provide guidance to reasonably plan the procedure to achieve the best outcome. Postprocedural 3D printing can be used to understand the depth, shape, and distribution of the stent. Cardiovascular 3D printing has achieved remarkable results in TAVR and has a great potential.

Patient-Specific Computer Simulation to Predict Conduction Disturbance With Current-Generation Self-Expanding Transcatheter Heart Valves

Background

Patient-specific computer simulation may predict the development of conduction disturbance following transcatheter aortic valve replacement (TAVR). Validation of the computer simulations with current-generation devices has not been undertaken.

Methods

A retrospective study was performed on patients who had undergone TAVR with a current-generation self-expanding transcatheter heart valve (THV). Preprocedural computed tomography imaging was used to create finite element models of the aortic root. Procedural contrast angiography was reviewed, and finite element analysis performed using a matching THV device size and implantation depth. A region of interest corresponding to the atrioventricular bundle and proximal left bundle branch was identified. The percentage of this area (contact pressure index [CPI]) and maximum contact pressure (CPMax) exerted by THV were recorded. Postprocedural electrocardiograms were reviewed, and major conduction disturbance was defined as the development of persistent left bundle branch block or high-degree atrioventricular block.

Results

A total of 80 patients were included in the study. THVs were 23- to 29-mm Evolut PRO (n = 53) and 34-mm Evolut R (n = 27). Major conduction disturbance occurred in 27 patients (33.8%). CPI (28.3 ± 15.8 vs. 15.6 ± 11.2%; p < 0.001) and CPMax (0.51 ± 0.20 vs. 0.36 ± 0.24 MPa; p = 0.008) were higher in patients who developed major conduction disturbance. CPI (area under the receiver operating characteristic curve [AUC], 0.74; 95% CI, 0.63-0.86; p < 0.001) and CPMax (AUC, 0.69; 95% CI, 0.57-0.81; p = 0.006) demonstrated a discriminatory power to predict the development of major conduction disturbance.

Conclusions

Patient-specific computer simulation may identify patients at risk for conduction disturbance after TAVR with current-generation self-expanding THVs.

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.

Pooled-Analysis of Association of Sievers Bicuspid Aortic Valve Morphology With New Permanent Pacemaker and Conduction Abnormalities After Transcatheter Aortic Valve Replacement

Background

Studies on the association of Sievers bicuspid aortic valve (BAV) morphology with conduction disorders after transcatheter aortic valve replacement (TAVR) have not reached consensus.

Methods

We here performed a pooled-analysis to explore whether Sievers type 1 BAV morphology increased the risk of post-TAVR conduction abnormalities and permanent pacemaker implantation (PPI) compared to type 0. Systematic literature searches through EMBASE, Medline, and Cochrane databases were concluded on 1 December 2021. The primary endpoint was post-TAVR new PPI and pooled as risk ratios (RRs) and 95% confidence intervals (CIs). Conduction abnormalities as the secondary endpoint were the composites of post-TAVR PPI and/or new-onset high-degree of atrial-ventricle node block and left-bundle branch block. Studies that reported incidence of outcomes of interest in both type 1 and type 0 BAV morphology who underwent TAVR for aortic stenosis were included.

Results

Finally, nine studies were included. Baseline characteristics were generally comparable, but type 1 population was older with a higher surgical risk score compared to type 0 BAV morphology. In the pooled-analysis type 1 BAV had significantly higher risk of post-TAVR new-onset conduction abnormalities (RR = 1.68, 95%CI 1.09–2.60, p = 0.0195) and new PPI (RR = 1.97, 95%CI 1.29–2.99, p = 0.0016) compared to type 0. Random-effects univariate meta-regression indicated that no significant association between baseline characteristics and PPI.

Conclusion

Sievers type 1 BAV morphology was associated with increased risk of post-TAVR PPI and conduction abnormalities compared to type 0. Dedicated cohort is warranted to further validate our hypothesis.

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.

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.

Membranous septum morphology and risk of conduction abnormalities after transcatheter aortic valve implantation

BACKGROUND

There are limited data on the association of membranous septum (MS) morphology and transcatheter heart valve (THV) implantation depth, and the development of new conduction abnormalities (CA) after transcatheter aortic valve implantation (TAVI).

AIMS

The aim of this study was to describe the morphology of the MS and predict the risk of new CA after TAVI based on the MS morphology and THV implantation depth.

METHODS

Based on preprocedural CT scans, the MS depth was measured for every 25% of the entire MS width in 272 TAVI patients without preprocedural bundle branch block (BBB) or pacemaker. Post-procedural CT scans for THV implantation depth assessment were available in 130 of these patients.

RESULTS

The MS depth was a median of 2.5 mm (IQR 1.4-3.8) deeper at the posterior edge when compared to the anterior edge of the MS. New CA developed in 7.1% of patients in whom the THV did not cross the lower MS border at its anterior edge (3.6% with new BBB and high degree CA, respectively), in 18.8% of patients (15.6% with new BBB and 3.1% with new high-degree CA) where the THV overlapped the lower MS border by <2.5 mm and in 47.1% of patients (24.3% with new BBB and 22.9% with new high-degree CA) with THV overlap of the lower MS border by ≥2.5 mm.

CONCLUSIONS

The difference of the MS depth and THV implantation depth measured at the anterior edge of the MS predicted new CA after TAVI.

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.

Patient-specific computer simulation to predict long-term outcomes after transcatheter aortic valve replacement

BACKGROUND

Patient-specific computer simulation may predict the development of paravalvular regurgitation (PVR) after transcatheter aortic valve replacement (TAVR). We hypothesised that patient-specific computer simulation might identify patients at risk for long-term adverse outcomes after TAVR.

METHODS

A multi-centre retrospective study was performed on patients with symptomatic severe aortic stenosis who had undergone TAVR with a self-expanding transcatheter heart valve (THV). Pre-procedural cardiac computed tomography imaging was used to create finite element models of the aortic root. Finite element analysis (FEA) was performed in order to simulate the interaction between the THV and the native anatomy. The blood domain was extracted from the FEA output and computational fluid dynamics (CFD) simulation undertaken. Predicted PVR was recorded in the left ventricular outflow tract. Patients were classified into those where computer simulation predicted no significant PVR (predicted PVR from CFD <16.0 ​mL/s) and those where computer simulation predicted significant PVR (predicted PVR from CFD ≥16.0 ​mL/s).

RESULTS

A total of 203 patients were included in the study. THVs implanted were CoreValve (n ​= ​20), Evolut R (n ​= ​90) and Evolut PRO (n ​= ​93). At 2 years, the Kaplan-Meier estimate of the rate of death from any cause was higher in the group where CFD simulation predicted significant PVR (35.8% vs. 16.3%; hazard ratio, 2.62; 95% confidence interval, 1.29 to 5.30; P ​= ​0.006 by log-rank test).

CONCLUSIONS

Computer simulation may identify patients who are at a higher risk for death after TAVR.

Force distribution within the frame of self-expanding transcatheter aortic valve: Insights from in-vivo finite element analysis

We sought to assess the amount and distribution of force on the valve frame after transcatheter aortic valve replacement (TAVR) via patient-specific computer simulation. Patients successfully treated with the self-expanding Venus A-Valve and multislice computed tomography (MSCT) pre- and post-TAVR were retrospectively included. Patient-specific finite element models of the aortic root and prosthesis were constructed. The force (in Newton) on the valve frame was derived at every 3 mm from the inflow and at every 22.5° on each level. Twenty patients of whom 10 had bicuspid aortic valve (BAV) were analyzed. The total force on the frame was 74.9 N in median (interquartile range 24.0). The maximal force was observed at level 5 that corresponds with the nadir of the bioprosthetic leaflets and was 9.9 (7.1) N in all patients, 10.3 (6.6) N in BAV and 9.7 (9.2) N for patients with tricuspid aortic valve (TAV). The level of maximal force located higher from the native annulus in BAV and TAV patients (8.8 [4.8] vs. 1.8 [7.4] mm). The area of the valve frame at the level of maximal force decreased from 437.4 (239.7) mm² at the annulus to 377.6 (114.3) mm² in BAV, but increased from 397.5 (114.3) mm² at the annulus to 406.7 (108.9) mm² in TAV. The maximum force on the bioprosthetic valve frame is located at the plane of the nadir of the bioprosthetic leaflets. It remains to be elucidated whether this may be associated with bioprosthetic frame and leaflet integrity and/or function.

The incidence and predictors of high-degree atrioventricular block in patients with bicuspid aortic valve receiving self-expandable transcatheter aortic valve implantation

BACKGROUND

The high-degree atrioventricular block (HAVB) in patients with bicuspid aortic valve (BAV) treated with transcatheter aortic valve implantation (TAVI) remains high. The study aims to explore this poorly understood subject of mechanisms and predictors for HAVB in BAV self-expandable TAVI patients.

METHODS

We retrospectively included 181 BAV patients for analysis. Using computed tomography data, the curvature of ascending aorta (AAo) was quantified by the angle (AAo angle) between annulus and the cross-section at 35 mm above annulus (where the stent interacts with AAo the most). The valvular anatomy and leaflet calcification were also characterized.

RESULTS

The 30-day HAVB rate was 16.0% (median time to HAVB was three days). Type-1 morphology was found in 79 patients (43.6%) (left- and right-coronary cusps fusion comprised 79.7%). Besides implantation below membrane septum, large AAo angle [odds ratio (OR) = 1.08, P = 0.016] and type-1 morphology (OR = 4.97, P = 0.001) were found as the independent predictors for HAVB. Together with baseline right bundle branch block, these predictors showed strong predictability for HAVB with area under the cure of 0.84 (sensitivity = 62.1%, specificity = 92.8%). Bent AAo and calcified raphe had a synergistic effect in facilitating high implantation, though the former is associated with at-risk deployment (device implanted above annulus + prothesis pop-out, versus straight AAo: 9.9% vs. 2.2%, P = 0.031).

CONCLUSIONS

AAo curvature and type-1 morphology are novel predictors for HAVB in BAV patients following self-expandable TAVI. For patients with bent AAo or calcified raphe, a progressive approach to implant the device above the lower edge of membrane septum is favored, though should be done cautiously to avoid pop-out.

A computational optimization study of a self-expandable transcatheter aortic valve

Developing an efficient stent frame for transcatheter aortic valves (TAV) needs thorough investigation in different design and functional aspects. In recent years, most TAV studies have focused on their clinical performance, leaflet design, and durability. Although several optimization studies on peripheral stents exist, the TAV stents have different functional requirements and need to be explicitly studied. The aim of this study is to develop a cost-effective optimization framework to find the optimal TAV stent design made of Ni-Ti alloy. The proposed framework focuses on minimizing the maximum strain occurring in the stent during crimping, making use of a simplified model of the stent to reduce computational cost. The effect of the strut cross-section of the stent, i.e., width and thickness, and the number and geometry of the repeating units of the stent (both influencing the cell size) on the maximum strain is investigated. Three-dimensional simulations of the crimping process are used to verify the validity of the simplified representation of the stent, and the radial force has been calculated for further evaluation. The results suggest the key role of the number of cells (repeating units) and strut width on the maximum strain and, consequently, on the stent design. The difference in terms of the maximum strain between the simplified and the 3D model was less than 5%, confirming the validity of the adopted modeling strategy and the robustness of the framework to improve the TAV stent designs through a simple, cost-effective, and reliable procedure.

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.

Transcatheter aortic valve replacement: impact of pre-procedural FEops HEARTguide assessment on device size selection in borderline annulus size cases

OBJECTIVES

The aim of this study is to evaluate device size selection in patients within the borderline annulus size range undergoing transcatheter aortic valve replacement (TAVR) and to assess if pre-procedural patient-specific computer simulation will lead to the selection of a different device size than standard of care.

BACKGROUND

In TAVR, appropriate device sizing is imperative. In borderline annulus size cases no standardised technique for tailored device size selection is currently available. Pre-procedural patient-specific computer simulation can be used, predicting the risk for paravalvular leakage (PVL) and need for permanent pacemaker implantation (PPI).

METHODS

In this multicentre retrospective study, 140 patients in the borderline annulus size range were included. Hereafter, device size selection was left to the discretion of the operator. After TAVR, in 24 of the 140 patients, patient-specific computer simulation calculated the most appropriate device size expected to give the lowest risk for PVL and need for PPI. In these 24 patients, device size selection based on patient-specific computer simulation was compared with standard-of-care device size selection relying on a standardised matrix (Medtronic).

RESULTS

In a significant proportion of the 140 patients (26.4%) a different device size than recommended by the matrix was implanted. In 10 of the 24 patients (41.7%) in whom a computer simulation was performed, a different device size was recommended than by means of the matrix.

CONCLUSIONS

Device size selection in patients within the borderline annulus size range is still ambiguous. In these patients, patient-specific computer simulation is feasible and can contribute to a more tailored device size selection.

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.

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.

Patient-specific Computer Simulation: An Emerging Technology for Guiding the Transcatheter Treatment of Patients with Bicuspid Aortic Valve

Transcatheter aortic valve implantation (TAVI) is increasingly being used to treat younger, lower-risk patients, many of whom have bicuspid aortic valve (BAV). As TAVI begins to enter these younger patient cohorts, it is critical that clinical outcomes from TAVI in BAV are matched to those achieved by surgery. Therefore, the identification of patients who, on an anatomical basis, may not be suitable for TAVI, would be desirable. Furthermore, clinical outcomes of TAVI in BAV might be improved through improved transcatheter heart valve sizing and positioning. One potential solution to these challenges is patient-specific computer simulation. This review presents the methodology and clinical evidence surrounding patient-specific computer simulation of TAVI in BAV.

Predicting TAVI paravalvular regurgitation outcomes based on numerical simulation of the aortic annulus eccentricity and perivalvular areas

Trans-catheter aortic valve implantation (TAVI) is an increasingly adopted technique which provides a minimal invasive solution for patients who suffer from severe aortic stenosis. Some complications of the procedure could be annular rupture or paravalvular leakage, both related with adverse outcome. In TAVI with balloon expandable devices, a mismatch between those two factors leads to a conflict situation, where improving one worsens the other. The presented research proposes a methodology that uses numerical simulation to obtain certain TAVI outcomes related with aortic regurgitation due to paravalvular leakage, such as perivalvular area, aortic eccentricity or annular pressure. The application of the methodology for two patients shows the possibility of predicting those quantities. The highest stress values are distributed along the contact area. Results also show that a great deformation on the aortic annulus does not necessarily imply a higher stress; pressure can either be converted into root reshape or into root stretching. Validation of the results was done using scientific publications, clinical guidelines and clinical reports. Numerical simulation provides a suitable tool that could possibly contribute to optimize the planification procedure adjusting the mismatch between size and pressure.

Impact of Interventricular membranous septum length on pacemaker need with different Transcatheter aortic valve implantation systems

Background The need for new permanent pacemaker implantation (PPI) after Transcatheter Aortic Valve Implantation (TAVI) remains a critical issue. Membranous Septum (MS) length is associated with PPI after TAVI. The aim of this study was to identify different MS thresholds for the contemporary THV-platforms. Methods This retrospective, case-control study enrolled all patients who underwent a successful TAVI procedure with contemporary THV-platforms in the Erasmus University Medical Center between January 2016 and March 2020. The follow-up period for new PPI was 30 days. MS-length was determined by Computed Tomography. Results The study consisted 653 TAVI patients with median age 80.6 years (IQR 74.7-84.8). New PPI occurred in 120 patients (18.4%). Patients with new PPI had a shorter MS-length (2.9 mm (IQR 2.3-4.3) vs. 4.2 mm (IQR 2.9-5.7), p < 0.001). MS-length < 3 mm identified a high-risk phenotype with 30.3% PPI-rate (OR 6.5 [95%CI 2.9-14.9]), MS-length 3-6 mm an intermediate-risk phenotype with 15.4% PPI-rate (OR 2.7 [95%CI 1.2-6.2]) and MS > 6 mm a low-risk phenotype with a 6.3% PPI-rate (reference). For the Lotus valve, there was no significant difference in PPI-rates between the high-risk (45.8%, OR 3.5 [95%CI 0.8-15.1]) and low-risk group (20%). By multivariate analysis MS-length, Agatston-score, use of Lotus valve, and ECG with first-degree AV block, RBBB or bifascular block were independent predictors for new PPI. Conclusion MS-length was an independent predictor for new PPI post-TAVI. Three phenotypes were found based on MS-length. MS < 3 mm was universally associated with a high risk for new PPI (>30%). MS > 6 mm represented a low-risk phenotype with PPI-rate < 10%. PPI-rate varied per THV type in the intermediate phenotype. PPI-rate with Lotus was high regardless of MS-length.

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.

The 'Digital Twin' to enable the vision of precision cardiology

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine.

Value of FEops HEARTguide patient-specific computational simulations in the planning of left atrial appendage closure with the Amplatzer Amulet closure device: rationale and design of the PREDICT-LAA study

BACKGROUND

Optimal preprocedural planning is essential to ensure successful device closure of the left atrial appendage (LAA).

DESIGN

The PREDICT-LAA study is a prospective, international, multicentre, randomised controlled trial (ClinicalTrials.gov NCT04180605). Two hundred patients eligible for LAA closure with an Amplatzer Amulet device (Abbott, USA) will be enrolled in the study. Patients will be allocated to a computational simulation arm (experimental) or standard treatment arm (control) using a 1:1 randomisation. For patients randomised to the computational simulation arm, preprocedural planning will be based on the analysis of cardiac computed tomography (CCT)-based patient-specific computational simulations (FEops HEARTguide, Ghent, Belgium) in order to predict optimal device size and position. For patients in the control arm, preprocedural planning will be based on local practice including CCT analysis. The LAA closure procedure and postprocedural antithrombotic therapy will follow local practice in both arms. The primary endpoint of the study is incomplete LAA closure and device-related thrombus as assessed at 3 months postprocedural CCT. Secondary endpoints encompass procedural efficiency (number of devices used, number of repositioning, procedural time, radiation exposure, contrast dye), procedure-related complications within 7 days postprocedure and a composite of all-cause death and thromboembolic events at 12 months.

CONCLUSION

The objective of the PREDICT-LAA study is to test the hypothesis that a preprocedural planning for LAA closure with the Amplatzer Amulet device based on patient-specific computational simulations can result in a more efficient procedure, optimised procedural outcomes and better clinical outcomes as compared with a standard preprocedural planning.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT04180605).

Transcatheter Restoration of the Left Ventricular Outlet in a Patient With an Implanted Apicoaortic Conduit

We describe the transcatheter management of severe aortic regurgitation in a middle-aged patient with a porcelain aorta who underwent implantation of an apicoaortic valved conduit 12 years ago. Instantaneous relief of heart failure symptoms was achieved by restoring antegrade blood flow to the ascending aorta. (Level of Difficulty: Advanced.)

The history of transcatheter aortic valve implantation: The role and contribution of an early believer and adopter, the Netherlands

This paper describes the history of transcatheter aortic valve implantation (TAVI) from its preclinical phase during which visionary pioneers developed its concept and prototype valves against strong head wind to first application in clinical practice (2002) and the clinical and scientific role of an early believer and adopter, the Netherlands (2005).

3D printed patient-specific aortic root models with internal sensors for minimally invasive applications

Minimally invasive surgeries have numerous advantages, yet complications may arise from limited knowledge about the anatomical site targeted for the delivery of therapy. Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure for treating aortic stenosis. Here, we demonstrate multimaterial three-dimensional printing of patient-specific soft aortic root models with internally integrated electronic sensor arrays that can augment testing for TAVR preprocedural planning. We evaluated the efficacies of the models by comparing their geometric fidelities with postoperative data from patients, as well as their in vitro hemodynamic performances in cases with and without leaflet calcifications. Furthermore, we demonstrated that internal sensor arrays can facilitate the optimization of bioprosthetic valve selections and in vitro placements via mapping of the pressures applied on the critical regions of the aortic anatomies. These models may pave exciting avenues for mitigating the risks of postoperative complications and facilitating the development of next-generation medical devices.