Modeling risk of coronary obstruction during transcatheter aortic valve replacement

Sensitivity of Left Atrial Flow Dynamics to Echocardiographic and Computed Tomography Data

Computational simulations are a powerful tool in the understanding, diagnosing, and treatment of cardiovascular diseases. Incomplete clinical data often limits computational assessment, which may lead to inaccuracies. This study aims to assess the sensitivity of left atrial flow dynamics to echocardiographic and computed tomography data. Models of the LA were reconstructed at the E-wave(Geometry 1)and end-diastolic(Geometry 2)phases from CT scans. CFD simulations were carried out using 3 different sets of BCs. BC2 and BC3 presented similar results that were significantly different from BC1. The effect from the choice of geometry was significant with BC2 and BC3 but minor with BC1. Differences in parameters across the simulated cases highlight the importance of using consistent BCs and geometries for CFD studies. Acquiring the pressure in the LA does not seem to be necessary for the accuracy of CFD simulations. Validation of all simulations indicates reliable patient-specific results.

Beyond Static Planning: Computational Predictive Modeling to Avoid Coronary Artery Occlusion in TAVR

BACKGROUND

Coronary artery occlusion (CO) during transcatheter aortic valve replacement (TAVR) is a devastating complication. The objective of this study was to assess the clinical impact of a computational predictive modeling algorithm for CO during TAVR planning.

METHODS

From January 2020 to December 2022, 116 patients (7.6%) who underwent TAVR evaluation were deemed to be at increased risk of CO on the basis of traditional criteria. Patients underwent prospective computational modeling (DASI Simulations) to assess their risk of CO during TAVR; procedural modifications and clinical results were reviewed retrospectively.

RESULTS

Of the 116 patients at risk for CO by traditional methodology, 53 had native aortic valve stenosis (45.7%), 47 had undergone previous surgical AVR (40.5%), and 16 had undergone previous TAVR (13.8%). Transcatheter valve choice, size, or implantation depth was modeled for all patients. Computational modeling predicted an increased risk of CO in 39 of 116 (31.9%) patients. Within this subcohort, 29 patients proceeded with TAVR. Procedural modifications to augment the risk of CO included bioprosthetic or native aortic scallop intentional laceration to prevent iatrogenic coronary artery obstruction during TAVR (n = 10), chimney coronary stents (n = 8), and coronary access without stents (n = 3). There were no episodes of coronary artery compromise among patients after TAVR, either for those predicted to be at high risk of CO (with procedural modifications) or those predicted to be at low risk (standard TAVR).

CONCLUSIONS

The use of preoperative simulations for TAVR in patient-specific geometry through computational predictive modeling of CO is an effective enhancement to procedure planning.

The Current Landscape of Artificial Intelligence in Imaging for Transcatheter Aortic Valve Replacement

Purpose

This review explores the current landscape of AI applications in imaging for TAVR, emphasizing the potential and limitations of these tools for (1) automating the image analysis and reporting process, (2) improving procedural planning, and (3) offering additional insight into post-TAVR outcomes. Finally, the direction of future research necessary to bridge these tools towards clinical integration is discussed.

Recent Findings

Transcatheter aortic valve replacement (TAVR) has become a pivotal treatment option for select patients with severe aortic stenosis, and its indication for use continues to broaden. Noninvasive imaging techniques such as CTA and MRA have become routine for patient selection, preprocedural planning, and predicting the risk of complications. As the current methods for pre-TAVR image analysis are labor-intensive and have significant inter-operator variability, experts are looking towards artificial intelligence (AI) as a potential solution.

Summary

AI has the potential to significantly enhance the planning, execution, and post-procedural follow up of TAVR. While AI tools are promising, the irreplaceable value of nuanced clinical judgment by skilled physician teams must not be overlooked. With continued research, collaboration, and careful implementation, AI can become an integral part in imaging for TAVR, ultimately improving patient care and outcomes.

Evolving capabilities of computed tomography imaging for transcatheter valvular heart interventions - new opportunities for precision medicine

The last decade has witnessed a substantial growth in percutaneous treatment options for heart valve disease. The development in these innovative therapies has been mirrored by advances in multi-detector computed tomography (MDCT). MDCT plays a central role in obtaining detailed pre-procedural anatomical information, helping to inform clinical decisions surrounding procedural planning, improve clinical outcomes and prevent potential complications. Improvements in MDCT image acquisition and processing techniques have led to increased application of advanced analytics in routine clinical care. Workflow implementation of patient-specific computational modeling, fluid dynamics, 3D printing, extended reality, extracellular volume mapping and artificial intelligence are shaping the landscape for delivering patient-specific care. This review will provide an insight of key innovations in the field of MDCT for planning transcatheter heart valve interventions.

Cardiac computed tomography post-transcatheter aortic valve replacement

Transcatheter aortic valve replacement (TAVR) is performed to treat aortic stenosis and is increasingly being utilised in the low-to-intermediate-risk population. Currently, attention has shifted towards long-term outcomes, complications and lifelong maintenance of the bioprosthesis. Some patients with TAVR in-situ may develop significant coronary artery disease over time requiring invasive coronary angiography, which may be problematic with the TAVR bioprosthesis in close proximity to the coronary ostia. In addition, younger patients may require a second transcatheter heart valve (THV) to 'replace' their in-situ THV because of gradual structural valve degeneration. Implantation of a second THV carries a risk of coronary obstruction, thereby requiring comprehensive pre-procedural planning. Unlike in the pre-TAVR period, cardiac CT angiography in the post-TAVR period is not well established. However, post-TAVR cardiac CT is being increasingly utilised to evaluate mechanisms for structural valve degeneration and complications, including leaflet thrombosis. Post-TAVR CT is also expected to have a significant role in risk-stratifying and planning future invasive procedures including coronary angiography and valve-in-valve interventions. Overall, there is emerging evidence for post-TAVR CT to be eventually incorporated into long-term TAVR monitoring and lifelong planning.

Modeling of valve-in-valve transcatheter aortic valve implantation after aortic root replacement using a 3-dimensional artificial intelligence algorithm

OBJECTIVE

Aortic root replacement requires construction of a composite valve-graft and reimplantation of coronary arteries. This study assessed the feasibility of valve-in-valve transcatheter aortic valve implantation after aortic root replacement.

METHODS

A retrospective review was conducted on 74 consecutive patients who received a composite valve-graft at a single institution from 2019 to 2021. Forty patients had bioprosthetic valves with adequate postoperative gated computed tomographic angiography scans. Computational simulations of balloon and self-expanding transcatheter valve deployments were performed. The modeled coronary distances were compared with traditional, manually measured valve-to-coronary distances.

RESULTS

There was a statistically significant difference in the modeled versus manual measurements of valve to coronary distances for all patients regardless of valve type or coronary artery analyzed (P < .05). Most patients are low risk for coronary obstruction per 3-dimensional modeling, including those with a valve-to-coronary distance <4 mm. Only 1 patient (2.5%) was at risk for coronary obstruction for the left coronary artery using a balloon valve. No other valve combination was considered high risk of coronary obstruction. Five patients (12.5%) were at risk for possible valve stent deformation at the outflow, due to angulation at the graft anastomosis.

CONCLUSIONS

Following aortic root replacement, all patients were candidates for valve-in-valve procedure using 1 or both types of transcatheter heart valves. Self-expanding valves may be at higher risk for stent frame deformation at graft anastomotic lines and balloon-expandable valves may be at higher risk of coronary obstruction.

Computational fluid dynamics in cardiac surgery and perfusion: A review

Cardiovascular diseases persist as a leading cause of mortality and morbidity, despite significant advances in diagnostic and surgical approaches. Computational Fluid Dynamics (CFD) represents a branch of fluid mechanics widely used in industrial engineering but is increasingly applied to the cardiovascular system. This review delves into the transformative potential for simulating cardiac surgery procedures and perfusion systems, providing an in-depth examination of the state-of-the-art in cardiovascular CFD modeling. The study first describes the rationale for CFD modeling and later focuses on the latest advances in heart valve surgery, transcatheter heart valve replacement, aortic aneurysms, and extracorporeal membrane oxygenation. The review underscores the role of CFD in better understanding physiopathology and its clinical relevance, as well as the profound impact of hemodynamic stimuli on patient outcomes. By integrating computational methods with advanced imaging techniques, CFD establishes a quantitative framework for understanding the intricacies of the cardiac field, providing valuable insights into disease progression and treatment strategies. As technology advances, the evolving synergy between computational simulations and clinical interventions is poised to revolutionize cardiovascular care. This collaboration sets the stage for more personalized and effective therapeutic strategies. With its potential to enhance our understanding of cardiac pathologies, CFD stands as a promising tool for improving patient outcomes in the dynamic landscape of cardiovascular medicine.

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.

Effect of TAVR commissural alignment on coronary flow: A fluid-structure interaction analysis

BACKGROUND AND OBJECTIVES

Coronary obstruction is a complication that may affect patients receiving Transcatheter Aortic Valve Replacement (TAVR), with catastrophic consequences and long-term negative effects. To enable healthy coronary perfusion, it is fundamental to appropriately position the device with respect to the coronary ostia. Nonetheless, most TAVR delivery systems do not control commissural alignment to do so. Moreover, no in silico study has directly assessed the effect of commissural alignment on coronary perfusion. This work aims to evaluate the effect of TAVR commissural alignment on coronary perfusion and device performance.

METHODS

A two-way computational fluid-structure interaction model is used to predict coronary perfusion at different commissural alignments. Moreover, in each scenario, hemodynamic biomarkers are evaluated to assess device performance.

RESULTS

Commissural misalignment is shown to reduce the total coronary perfusion by -3.2% and the flow rate to a single coronary branch by -6.8%. It is also observed to impair valvular function by reducing the systolic geometric orifice area by -2.5% and increasing the systolic transvalvular pressure gradients by +5.3% and the diastolic leaflet stresses by +16.0%.

CONCLUSIONS

The present TAVR patient model indicates that coronary perfusion, hemodynamic and structural performance are minimized when the prosthesis commissures are fully misaligned with the native ones. These results support the importance of enabling axial control in new TAVR delivery catheter systems and defining recommended values of commissural alignment in upcoming clinical treatment guidelines.

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.

Computed tomography to guide transcatheter aortic valve implantation

Since its introduction in 2022, transcatheter aortic valve implantation (TAVI) has revolutionized the treatment and prognosis of patients with aortic stenosis. Robust clinical trial data and a wealth of scientific evidence support its efficacy and safety. One of the key factors for success of the TAVI procedure is careful preprocedural planning using imaging. Computed tomography (CT) has developed into the standard imaging method for comprehensive patient assessment in this context. Suitability of the femoral and iliac arteries for transfemoral access, exact measurement of aortic annulus size and geometry as the basis for prosthesis selection, quantification of the spatial relationship of the coronary ostia to the aortic annular plane, and identification of optimal fluoroscopic projection angles for the implantation procedure are among the most important information that can be gained from preprocedural CT. Further research is aimed at improving risk stratification, for example, with respect to annular perforation, periprosthetic aortic regurgitation, and need for postprocedural implantation of a permanent pacemaker.

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.

Redo-Transcatheter Aortic Valve Implantation Using the SAPIEN 3/Ultra Transcatheter Heart Valves-Expert Consensus on Procedural Planning and Techniques

Recent guidelines on valvular heart disease in Europe and the United States have expanded the indications for transcatheter aortic valve implantation (TAVI) to younger patients and those at lower surgical risk with severe symptomatic aortic stenosis. Consequently, the number of TAVI procedures will significantly increase worldwide. Patients with longer life expectancies will outlive their transcatheter heart valves (THVs) and require established treatment strategies for re-intervention. Current data have shown encouraging outcomes, including low mortality, with redo-TAVI; in contrast, surgical explantation of THVs is associated with high mortality. Redo-TAVI, therefore, is likely to be the treatment of choice for THV failure. The expected increase in the number of redo-TAVIs stands in contrast to the current lack of evidence on how this procedure should be planned and performed, including the risks and pitfalls operators need to consider. Preliminary reports stress the importance of preprocedural planning, understanding of THV skirt and leaflet characteristics, and implantation guidelines specific to different THVs. Currently, SAPIEN 3/Ultra is the only THV approved in Europe and the United States for redo-TAVI. Therefore, we gathered a panel of experts in TAVI procedures with the aim of providing operative guidance on redo-TAVI, using the SAPIEN 3/Ultra THV. This consensus article presents a step-by-step approach encompassing clinical, anatomical, and technical aspects in preprocedural planning, procedural techniques, and postprocedural care. In conclusion, the recommendations aim to improve the feasibility, safety, and long-term outcomes of redo-TAVI, including the durability of implanted THVs.

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.

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

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

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.

A Preliminary Study on the Usage of a Data-Driven Probabilistic Approach to Predict Valve Performance Under Different Physiological Conditions

Predicting potential complications after aortic valve replacement (AVR) is a crucial task that would help pre-planning procedures. The goal of this work is to generate data-driven models based on logistic regression, where the probability of developing transvalvular pressure gradient (DP) that exceeds 20 mmHg under different physiological conditions can be estimated without running extensive experimental or computational methods. The hemodynamic assessment of a 26 mm SAPIEN 3 transcatheter aortic valve and a 25 mm Magna Ease surgical aortic valve was performed under pulsatile conditions of a large range of systolic blood pressures (SBP; 100-180 mmHg), diastolic blood pressures (DBP; 40-100 mmHg), and heart rates of 60, 90 and 120 bpm. Logistic regression modeling was used to generate a predictive model for the probability of having a DP > 20 mmHg for both valves under different conditions. Experiments on different pressure conditions were conducted to compare the probabilities of the generated model and those obtained experimentally. To test the accuracy of the predictive model, the receiver operation characteristics curves were generated, and the areas under the curve (AUC) were calculated. The probabilistic predictive model of DP > 20 mmHg was generated with parameters specific to each valve. The AUC obtained for the SAPIEN 3 DP model was 0.9465 and that for Magna Ease was 0.9054 indicating a high model accuracy. Agreement between the DP probabilities obtained between experiments and predictive model was found. This model is a first step towards developing a larger statistical and data-driven model that can inform on certain valves reliability during AVR pre-procedural planning.

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.

Impact of blood pressure on coronary perfusion and valvular hemodynamics after aortic valve replacement

OBJECTIVE

Our objective was to evaluate the impact of various blood pressures (BPs) on coronary perfusion and valvular hemodynamics following aortic valve replacement (AVR).

BACKGROUND

Lower systolic and diastolic (SBP/DBP) pressures from the recommended optimal target range of SBP < 120-130 mmHg and DBP < 80 mmHg after AVR have been independently associated with increased cardiovascular and all-cause mortality.

METHODS

The hemodynamic assessment of a 26 mm SAPIEN 3 transcatheter aortic valve (TAV), 29 mm Evolut R TAV, and 25 mm Magna Ease surgical aortic valve (SAV) was performed in a pulsed left heart simulator with varying SBP, DBP, and heart rate (HR) conditions (60 and 120 bpm) at 5 L/min cardiac output (CO). Average coronary flow (CF), effective orifice areas (EOAs), and valvulo-arterial impedance (Zva) were calculated.

RESULTS

At HR of 60 bpm, at SBP < 120 mmHg and DBP < 60 mmHg, CF decreased below the physiological lower limit with several different valves. Zva and EOA were found to increase and decrease respectively with increasing SBP and DBP. The same results were found with an HR of 120 bpm. The trends of CF variation with BP were similar in all valves however the drop below the lower physiological CF limit was valve dependent.

CONCLUSION

In a controlled in vitro system, with different aortic valve prostheses in place, CF decreased below the physiologic minimum when SBP and DBP were in the range targeted by blood pressure guidelines. Combined with recent observations from patients treated with AVR, these findings underscore the need for additional studies to identify the optimal BP in patients treated with AVR for AS.

Transcatheter Aortic Valve Implantation in Sievers Type 0 vs. Type 1 Bicuspid Aortic Valve Morphology: Systematic Review and Meta-Analysis

Background: Transcatheter aortic valve implantation (TAVI) has achieved satisfactory outcomes in the selected patients with bicuspid aortic valve (BAV), predominately type 1 BAV (~90%). However, there are few reports about the safety and efficacy of TAVI in type 0 BAV. Therefore, in the current study, we aimed to compare procedural and 30-day outcomes after TAVI between type 0 and type 1 BAV.

Methods: Studies comparing the outcomes of TAVI in Sievers type 0 vs. type 1 BAV were retrieved from PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2021. The data were extracted regarding the study characteristics and outcomes. The odds ratios (ORs) with 95% CIs were pooled for procedural and 30-day outcomes.

Results: Six observational studies were included with determined type 0 BAV in 226 patients and type 1 BAV in 902 patients. The patients with type 0 BAV were slightly younger, had larger supra-annular structure, and more frequently implanted self-expanding prosthesis compared with type 1 BAV. In the pooled analyses, the patients with type 0 BAV had a similar incidence of procedural death (OR = 2.6, 95% CI 0.7–10.3), device success (OR = 0.6; 95% CI 0.3–1.3), and ≥ mild (OR = 0.8; 95% CI 0.4–1.6) or moderate (OR = 0.9, 95% CI 0.4–1.8) paravalvular leak, whereas significantly higher mean aortic gradient (mean difference = 1.4 mmHg, 95% CI 0.03–2.7) and increased coronary compromise risk (OR = 7.2; 95% CI 1.5–34.9), compared with type 1 BAV. Meanwhile, the incidence of death (OR = 1.2; 95% CI 0.5–3.1), stroke (OR = 0.5; 95% CI 0.1–2.4), and new pacemaker (OR = 0.6; 95% CI 0.2–2.2) at 30 days were not significantly different between the BAV morphologies (p > 0.05). The treatment effect heterogeneity across the studies for the above outcomes were low.

Conclusions: The patients with type 0 BAV appear to have similar short-term outcomes after TAVI compared with type 1 BAV. Whereas, TAVI for type 0 BAV aortic stenosis might lead to an elevated coronary obstruction risk and suboptimal aortic valvular hemodynamics.

Simple 2-dimensional anatomic model to predict the risk of coronary obstruction during transcatheter aortic valve replacement

OBJECTIVE

In this study, a 2-dimensional (2D) index relying on preprocedural computed tomography (CT) data was developed to evaluate the risk of coronary obstruction during transcatheter aortic valve replacement (TAVR) procedures.

METHODS

Anatomic measurements from pre-TAVR CT scans were collected in 28 patients among 600 who were flagged as high risk (defined as meeting coronary artery height, h, <14 mm and/or sinus of Valsalva diameter, SOVd, <30 mm) for coronary obstruction. A geometric model derived from these anatomic measurements was used to predict the post-TAVR native cusp apposition relative to the coronary ostium. The distance from the cusp to the coronary ostium, DLC2D, was measured from the geometric model and indexed with the coronary artery diameter, d, to yield a fractional obstruction measure, DLC2D/d.

RESULTS

Twenty-three of 28 high-risk patients successfully underwent TAVR without coronary obstruction, of whom 1 had coronary obstruction and 4 were deemed non-TAVR candidates. DLC2D/d differed significantly between the 2 groups (P < .0018), but neither h nor SOVd did (P > .32). The optimal sensitivity and specificity for DLC2D/d were 85% and occurred at a cutoff of 0.45. The optimal sensitivity and specificity of h and SOVd in this high-risk group were only 60% and 40%, respectively, for cutoffs of h = 10 mm and SOVd = 30.5 mm.

CONCLUSIONS

The 2D geometric model derived in this study shows promise for identifying patients with low-lying coronary ostium and/or small SOVd that may be safely treated with TAVR. DLC2D/d is more predictive of obstruction or poor TAVR candidacy compared with h and SOVd.

Transcatheter Heart Valves: A Biomaterials Perspective

Heart valve disease is prevalent throughout the world, and the number of heart valve replacements is expected to increase rapidly in the coming years. Transcatheter heart valve replacement (THVR) provides a safe and minimally invasive means for heart valve replacement in high-risk patients. The latest clinical data demonstrates that THVR is a practical solution for low-risk patients. Despite these promising results, there is no long-term (>20 years) durability data on transcatheter heart valves (THVs), raising concerns about material degeneration and long-term performance. This review presents a detailed account of the materials development for THVRs. It provides a brief overview of THVR, the native valve properties, the criteria for an ideal THV, and how these devices are tested. A comprehensive review of materials and their applications in THVR, including how these materials are fabricated, prepared, and assembled into THVs is presented, followed by a discussion of current and future THVR biomaterial trends. The field of THVR is proliferating, and this review serves as a guide for understanding the development of THVs from a materials science and engineering perspective.

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.

New Insights into Valve Hemodynamics

Heart valve diseases are common disorders with five million annual diagnoses being made in the United States alone. All heart valve disorders alter cardiac hemodynamic performance; therefore, treatments aim to restore normal flow. This paper reviews the state-of-the-art clinical and engineering advancements in heart valve treatments with a focus on hemodynamics. We review engineering studies and clinical literature on the experience with devices for aortic valve treatment, as well as the latest advancements in mitral valve treatments and the pulmonic and tricuspid valves on the right side of the heart. Upcoming innovations will potentially revolutionize treatment of heart valve disorders. These advancements, and more gradual enhancements in the procedural techniques and imaging modalities, could improve the quality of life of patients suffering from valvular disease who currently cannot be treated.