Quantitative Prediction of Paravalvular Leak in Transcatheter Aortic Valve Replacement Based on Tissue-Mimicking 3D Printing

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.

Rapid segmentation of computed tomography angiography images of the aortic valve: the efficacy and clinical value of a deep learning algorithm

Objectives

The goal of this study was to explore the reliability and clinical value of fast, accurate automatic segmentation of the aortic root based on a deep learning tool compared with computed tomography angiography.

Methods

A deep learning tool for automatic 3-dimensional aortic root reconstruction, the CVPILOT system (TAVIMercy Data Technology Ltd., Nanjing, China), was trained and tested using computed tomography angiography scans collected from 183 patients undergoing transcatheter aortic valve replacement from January 2021 to December 2022. The quality of the reconstructed models was assessed using validation data sets and evaluated clinically by experts.

Results

The segmentation of the ascending aorta and the left ventricle attained Dice similarity coefficients (DSC) of 0.9806/0.9711 and 0.9603/0.9643 for the training and validation sets, respectively. The leaflets had a DSC of 0.8049/0.7931, and the calcification had a DSC of 0.8814/0.8630. After 6 months of application, the system modeling time was reduced to 19.83 s.

Conclusion

For patients undergoing transcatheter aortic valve replacement, the CVPILOT system facilitates clinical workflow. The reliable evaluation quality of the platform indicates broad clinical application prospects in the future.

Development and validation of 3-dimensional simulators for penile prosthesis surgery

BACKGROUND

The acquisition of skills in penile prosthesis surgery has many limitations mainly due to the absence of simulators and models for training. Three-dimensional (3D) printed models can be utilized for surgical simulations, as they provide an opportunity to practice before entering the operating room and provide better understanding of the surgical approach.

AIM

This study aimed to evaluate and validate a 3D model of human male genitalia for penile prosthesis surgery.

METHODS

This study included 3 evaluation and validation stages. The first stage involved verification of the 3D prototype model for anatomic landmarks compared with a cadaveric pelvis. The second stage involved validation of the improved model for anatomic accuracy and teaching purposes with the Rochester evaluation score. The third stage comprised validation of the suitability of the 3D prototype model as a surgical simulator and for skill acquisition. The third stage was performed at 3 centers using a modified version of a pre-existing, validated questionnaire and correlated with the Rochester evaluation score.

OUTCOME

We sought to determine the suitability of 3D model for training in penile prosthesis surgery in comparison with the available cadaveric model.

RESULTS

The evaluation revealed a high Pearson correlation coefficient (0.86) between questions of the Rochester evaluation score and modified validated questionnaire. The 3D model scored 4.33 ± 0.57 (on a Likert scale from 1 to 5) regarding replication of the relevant human anatomy for the penile prosthesis surgery procedure. The 3D model scored 4.33 ± 0.57 (on a Likert scale from 1 to 5) regarding its ability to improve technical skills, teach and practice the procedure, and assess a surgeon's ability. Furthermore, the experts stated that compared with the cadaver, the 3D model presented greater ethical suitability, reduced costs, and easier accessibility.

CLINICAL IMPLICATIONS

A validated 3D model is a suitable alternative for penile prosthesis surgery training.

STRENGTHS AND LIMITATIONS

This is the first validated 3D hydrogel model for penile prosthesis surgery teaching and training that experts consider suitable for skill acquisition. Because specific validated guidelines and questionnaires for the validation and verifications of 3D simulators for penile surgery are not available, a modified questionnaire was used.

CONCLUSION

The current 3D model for penile prosthesis surgery shows promising results regarding anatomic properties and suitability to train surgeons to perform penile implant surgery. The possibility of having an ethical, easy-to-use model with lower costs and limited consequences for the environment is encouraging for further development of the models.

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.

Preprocedural Planning of Left Atrial Appendage Occlusion: A Review of the Use of Additive Manufacturing

Stroke is a significant public health problem, with non-valvular atrial fibrillation (NVAF) being one of its main causes. This cardiovascular arrhythmia predisposes to the production of intracardiac thrombi, mostly formed in the left atrial appendage (LAA). When there are contraindications to treatment with oral anticoagulants, another therapeutic option to reduce the possibility of thrombus formation in the LAA is the implantation of an occlusion device by cardiac catheterization. The effectiveness of LAA occlusion is dependent on accurate preprocedural device sizing and proper device positioning at the LAA ostium, to ensure sufficient device anchoring and avoid peri-device leaks. Additive manufacturing, commonly known as three-dimensional printing (3DP), of LAA models is beginning to emerge in the scientific literature to address these challenges through procedural simulation. This review aims at clarifying the impact of 3DP on preprocedural planning of LAA occlusion, specifically in the training of cardiac surgeons and in the assessment of the perfect adjustment between the LAA and the biomedical implant.

PyTorch-FEA: Autograd-enabled finite element analysis methods with applications for biomechanical analysis of human aorta

BACKGROUND AND OBJECTIVES

Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed.

METHODS

In this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance.

RESULTS

We applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.

CONCLUSIONS

We have presented PyTorch-FEA, a new library of FEA code and methods, representing a new approach to develop FEA methods to forward and inverse problems in solid mechanics. PyTorch-FEA eases the development of new inverse methods and enables a natural integration of FEA and DNNs, which will have numerous potential applications.

A benchmark study of convolutional neural networks in fully automatic segmentation of aortic root

Recent clinical studies have suggested that introducing 3D patient-specific aortic root models into the pre-operative assessment procedure of transcatheter aortic valve replacement (TAVR) would reduce the incident rate of peri-operative complications. Tradition manual segmentation is labor-intensive and low-efficient, which cannot meet the clinical demands of processing large data volumes. Recent developments in machine learning provided a viable way for accurate and efficient medical image segmentation for 3D patient-specific models automatically. This study quantitively evaluated the auto segmentation quality and efficiency of the four popular segmentation-dedicated three-dimensional (3D) convolutional neural network (CNN) architectures, including 3D UNet, VNet, 3D Res-UNet and SegResNet. All the CNNs were implemented in PyTorch platform, and low-dose CTA image sets of 98 anonymized patients were retrospectively selected from the database for training and testing of the CNNs. The results showed that despite all four 3D CNNs having similar recall, Dice similarity coefficient (DSC), and Jaccard index on the segmentation of the aortic root, the Hausdorff distance (HD) of the segmentation results from 3D Res-UNet is 8.56 ± 2.28, which is only 9.8% higher than that of VNet, but 25.5% and 86.4% lower than that of 3D UNet and SegResNet, respectively. In addition, 3D Res-UNet and VNet also performed better in the 3D deviation location of interest analysis focusing on the aortic valve and the bottom of the aortic root. Although 3D Res-UNet and VNet are evenly matched in the aspect of classical segmentation quality evaluation metrics and 3D deviation location of interest analysis, 3D Res-UNet is the most efficient CNN architecture with an average segmentation time of 0.10 ± 0.04 s, which is 91.2%, 95.3% and 64.3% faster than 3D UNet, VNet and SegResNet, respectively. The results from this study suggested that 3D Res-UNet is a suitable candidate for accurate and fast automatic aortic root segmentation for pre-operative assessment of TAVR.

Advances in Imaging for Tricuspid Transcatheter Edge-to-Edge Repair: Lessons Learned and Future Perspectives

Severe tricuspid valve (TV) regurgitation (TR) has been associated with adverse long-term outcomes in several natural history studies, but isolated TV surgery presents high mortality and morbidity rates. Transcatheter tricuspid valve interventions (TTVI) therefore represent a promising field and may currently be considered in patients with severe secondary TR that have a prohibitive surgical risk. Tricuspid transcatheter edge-to-edge repair (T-TEER) represents one of the most frequently used TTVI options. Accurate imaging of the tricuspid valve (TV) apparatus is crucial for T-TEER preprocedural planning, in order to select the right candidates, and is also fundamental for intraprocedural guidance and post-procedural follow-up. Although transesophageal echocardiography represents the main imaging modality, we describe the utility and additional value of other imaging modalities such as cardiac CT and MRI, intracardiac echocardiography, fluoroscopy, and fusion imaging to assist T-TEER. Developments in the field of 3D printing, computational models, and artificial intelligence hold great promise in improving the assessment and management of patients with valvular heart disease.

PyTorch-FEA: Autograd-enabled Finite Element Analysis Methods with Applications for Biomechanical Analysis of Human Aorta

Motivation

Finite-element analysis (FEA) is widely used as a standard tool for stress and deformation analysis of solid structures, including human tissues and organs. For instance, FEA can be applied at a patient-specific level to assist in medical diagnosis and treatment planning, such as risk assessment of thoracic aortic aneurysm rupture/dissection. These FEA-based biomechanical assessments often involve both forward and inverse mechanics problems. Current commercial FEA software packages (e.g., Abaqus) and inverse methods exhibit performance issues in either accuracy or speed.

Methods

In this study, we propose and develop a new library of FEA code and methods, named PyTorch-FEA, by taking advantage of autograd, an automatic differentiation mechanism in PyTorch. We develop a class of PyTorch-FEA functionalities to solve forward and inverse problems with improved loss functions, and we demonstrate the capability of PyTorch-FEA in a series of applications related to human aorta biomechanics. In one of the inverse methods, we combine PyTorch-FEA with deep neural networks (DNNs) to further improve performance.

Results

We applied PyTorch-FEA in four fundamental applications for biomechanical analysis of human aorta. In the forward analysis, PyTorch-FEA achieved a significant reduction in computational time without compromising accuracy compared with Abaqus, a commercial FEA package. Compared to other inverse methods, inverse analysis with PyTorch-FEA achieves better performance in either accuracy or speed, or both if combined with DNNs.

Comparison of patients with bicuspid and tricuspid aortic valve in transcatheter aortic valve implantation

BACKGROUND

Transcatheter aortic valve implantation (TAVI) has emerged as a safe and effective alternative to surgery for aortic stenosis (AS). However, there are still differences in the procedural process and outcome of bicuspid aortic valve (BAV) treated with TAVI compared with tricuspid aortic valve.

AREAS COVERED

This review paper aims to summarize the main characteristics and clinical evidence of TAVI in patients with bicuspid and tricuspid aortic valves and compare the outcomes of TAVI procedure.

EXPERT OPINION

The use of TAVI in patients with BAV has shown similar clinical outcomes compared with tricuspid aortic valve. The efficacy of TAVI for challenging BAV anatomies remains a concern due to the lack of randomized trials. Detailed preprocedural planning is of great importance in low-surgical-risk BAV patients. A better understanding of which subtypes of BAV anatomy are at greater risk for adverse outcomes can potentially benefit the selection of TAVI or open-heart surgery in low surgical risk AS patients.

HEARTBEAT4D: An Open-source Toolbox for Turning 4D Cardiac CT into VR/AR

Four-dimensional data sets are increasingly common in MRI and CT. While clinical visualization often focuses on individual temporal phases capturing the tissue(s) of interest, it may be possible to gain additional insight through exploring animated 3D reconstructions of physiological motion made possible by augmented or virtual reality representations of 4D patient imaging. Cardiac CT acquisitions can provide sufficient spatial resolution and temporal data to support advanced visualization, however, there are no open-source tools readily available to facilitate the transformation from raw medical images to dynamic and interactive augmented or virtual reality representations. To address this gap, we developed a workflow using free and open-source tools to process 4D cardiac CT imaging starting from raw DICOM data and ending with dynamic AR representations viewable on a phone, tablet, or computer. In addition to assembling the workflow using existing platforms (3D Slicer and Unity), we also contribute two new features: 1. custom software which can propagate a segmentation created for one cardiac phase to all others and export to surface files in a fully automated fashion, and 2. a user interface and linked code for the animation and interactive review of the surfaces in augmented reality. Validation of the surface-based areas demonstrated excellent correlation with radiologists' image-based areas (R > 0.99). While our tools were developed specifically for 4D cardiac CT, the open framework will allow it to serve as a blueprint for similar applications applied to 4D imaging of other tissues and using other modalities. We anticipate this and related workflows will be useful both clinically and for educational purposes.

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.

The application of 3D printing in preoperative planning for transcatheter aortic valve replacement: a systematic review

BACKGROUND

Recently, transcatheter aortic valve replacement (TAVR) has been suggested as a less invasive treatment compared to surgical aortic valve replacement, for patients with severe aortic stenosis. Despite the attention, persisting evidence suggests that several procedural complications are more prevalent with the transcatheter approach. Consequently, a systematic review was undertaken to evaluate the application of three-dimensional (3D) printing in preoperative planning for TAVR, as a means of predicting and subsequently, reducing the incidence of adverse events.

METHODS

MEDLINE, Web of Science and Embase were searched to identify studies that utilised patient-specific 3D printed models to predict or mitigate the risk of procedural complications.

RESULTS

13 of 219 papers met the inclusion criteria of this review. The eligible studies have shown that 3D printing has most commonly been used to predict the occurrence and severity of paravalvular regurgitation, with relatively high accuracy. Studies have also explored the usefulness of 3D printed anatomical models in reducing the incidence of coronary artery obstruction, new-onset conduction disturbance and aortic annular rapture.

CONCLUSION

Patient-specific 3D models can be used in pre-procedural planning for challenging cases, to help deliver personalised treatment. However, the application of 3D printing is not recommended for routine clinical practice, due to practicality issues.

Left Atrial Appendage Occlusion: Current Stroke Prevention Strategies and a Shift Toward Data-Driven, Patient-Specific Approaches

The left atrial appendage (LAA) is a complex structure with unknown physiologic function protruding from the main body of the left atrium. In patients with atrial fibrillation, the left atrium does not contract effectively. Insufficient atrial and LAA contractility predisposes the LAA morphology to hemostasis and thrombus formation, leading to an increased risk of cardioembolic events. Oral anticoagulation therapies are the mainstay of stroke prevention options for patients; however, not all patients are candidates for long-term oral anticoagulation. Percutaneous occlusion devices are an attractive alternative to long-term anticoagulation therapy, although they are not without limitations, such as peri-implant leakage and device-related thrombosis. Although efforts have been made to reduce these risks, significant interpatient heterogeneity inevitably yields some degree of device-anatomy mismatch that is difficult to resolve using current devices and can ultimately lead to insufficient occlusion and poor patient outcomes. In this state-of-the-art review, we evaluated the anatomy of the LAA as well as the current pathophysiologic understanding and stroke prevention strategies used in the management of the risk of stroke associated with atrial fibrillation. We highlighted recent advances in computed tomography imaging, preprocedural planning, computational modeling, and novel additive manufacturing techniques, which represent the tools needed for a paradigm shift toward patient-centric LAA occlusion. Together, we envisage that these techniques will facilitate a pipeline from the imaging of patient anatomy to patient-specific computational and bench-top models that enable customized, data-driven approaches for LAA occlusion that are engineered specifically to meet each patient's unique needs.

3D-Printing to Plan Complex Transcatheter Paravalvular Leaks Closure

Background: Percutaneous closure of paravalvular leak (PVL) has emerged as an alternative to surgical management in selected cases. Achieving complete PVL occlusion, while respecting prosthesis function remains challenging. A multimodal imaging analysis of PVL morphology before and during the procedure is mandatory to select an appropriate device. We aim to explore the additional value of 3D printing in predicting device related adverse events including mechanical valve leaflet blockade, risk of device embolization and residual shunting. Methods: From the FFPP registries (NCT05089136 and NCT05117359), we included 11 transcatheter PVL closure procedures from three centers for which 3D printed models were produced. Cardiac CT was used for segmentation for 3D printed models (3D-heartmodeling, Caissargues, France). Technology used a laser to fuse very fine powders (TPU Thermoplastic polyurethane) into a final part-laser sintering technology (SLS) with an adapted elasticity. A simulation on 3D printed model was performed using a set of occluders. Results: PVLs were located around aortic prostheses in six cases, mitral prostheses in four cases and tricuspid ring in one case. The device chosen during the simulation on the 3D printed model matched the one implanted in eight cases. In the three other cases, a similar device type was chosen during the procedures but with a different size. A risk of prosthesis leaflet blockade was identified on 3D printed models in four cases. During the procedure, the occluder was removed before release in one case. In another case the device was successfully repositioned and released. In two patients, leaflet impingement was observed post-operatively and surgical device removal had to be performed. Conclusion: In a case-series of complex transcatheter PVL closure procedures, hands-on simulation testing on 3D printed models proved its usefulness to plan and facilitate these challenging procedures.

Imaging-Based, Patient-Specific Three-Dimensional Printing to Plan, Train, and Guide Cardiovascular Interventions: A Systematic Review and Meta-Analysis

BACKGROUND

To tailor cardiovascular interventions, the use of three-dimensional (3D), patient-specific phantoms (3DPSP) encompasses patient education, training, simulation, procedure planning, and outcome-prediction.

AIM

This systematic review and meta-analysis aims to investigate the current and future perspective of 3D printing for cardiovascular interventions.

METHODS

We systematically screened articles on Medline and EMBASE reporting the prospective use of 3DPSP in cardiovascular interventions by using combined search terms. Studies that compared intervention time depending on 3DPSP utilisation were included into a meta-analysis.

RESULTS

We identified 107 studies that prospectively investigated a total of 814 3DPSP in cardiovascular interventions. Most common settings were congenital heart disease (CHD) (38 articles, 6 comparative studies), left atrial appendage (LAA) occlusion (11 articles, 5 comparative, 1 randomised controlled trial [RCT]), and aortic disease (10 articles). All authors described 3DPSP as helpful in assessing complex anatomic conditions, whereas poor tissue mimicry and the non-consideration of physiological properties were cited as limitations. Compared to controls, meta-analysis of six studies showed a significant reduction of intervention time in LAA occlusion (n=3 studies), and surgery due to CHD (n=3) if 3DPSPs were used (Cohen's d=0.54; 95% confidence interval, 0.13 to 0.95; p=0.001), however heterogeneity across studies should be taken into account.

CONCLUSIONS

3DPSP are helpful to plan, train, and guide interventions in patients with complex cardiovascular anatomy. Benefits for patients include reduced intervention time with the potential for lower radiation exposure and shorter mechanical ventilation times. More evidence and RCTs including clinical endpoints are needed to warrant adoption of 3DPSP into routine clinical practice.

Prodigiosin: a promising biomolecule with many potential biomedical applications

Pigments are among the most fascinating molecules found in nature and used by human civilizations since the prehistoric ages. Although most of the bio-dyes reported in the literature were discovered around the eighties, the necessity to explore novel compounds for new biological applications has made them resurface as potential alternatives. Prodigiosin (PG) is an alkaloid red bio-dye produced by diverse microorganisms and composed of a linear tripyrrole chemical structure. PG emerges as a really interesting tool since it shows a wide spectrum of biological activities, such as antibacterial, antifungal, algicidal, anti-Chagas, anti-amoebic, antimalarial, anticancer, antiparasitic, antiviral, and/or immunosuppressive. However, PG vehiculation into different delivery systems has been proposed since possesses low bioavailability because of its high hydrophobic character (XLogP3-AA = 4.5). In the present review, the general aspects of the PG correlated with synthesis, production process, and biological activities are reported. Besides, some of the most relevant PG delivery systems described in the literature, as well as novel unexplored applications to potentiate its biological activity in biomedical applications, are proposed.

Mitral Valve-in-Valve Implant of a Balloon-Expandable Valve Guided by 3-Dimensional Printing

Background

Our goal was to explore the role of 3-dimensional (3D) printing in facilitating the outcome of a mitral valve-in-valve (V-in-V) implant of a balloon-expandable valve.

Methods

From November 2020 to April 2021, 6 patients with degenerated mitral valves were treated by a transcatheter mitral V-in-V implant of a balloon-expandable valve. 3D printed mitral valve pre- and post-procedure models were prepared to facilitate the process by making individualized plans and evaluating the outcomes.

Results

Each of the 6 patients was successfully implanted with a balloon-expandable valve. From post-procedural images and the 3D printed models, we could clearly observe the valve at the ideal position, with the proper shape and no regurgitation. 3D printed mitral valve models contributed to precise decisions, the avoidance of complications, and the valuation of outcomes.

Conclusions

3D printing plays an important role in guiding the transcatheter mitral V-in-V implant of a balloon-expandable valve.

Clinical Trial Registration

ClinicalTrials.gov Protocol Registration System (NCT02917980).

Comparison of Balloon-Expandable Valve and Self-Expandable Valve in Transcatheter Aortic Valve Replacement: A Patient-Specific Numerical Study

Transcatheter aortic valve replacement (TAVR) is a minimally invasive strategy for the treatment of aortic stenosis. The complex post-operative complications of TAVR were related to the type of implanted prosthetic valve, and the deep mechanism of this relationship may guide the clinical pre-operative planning. The purpose of this study was to develop a numerical method of TAVR to compare the outcome difference between balloon-expandable valve and self-expandable valve and predict the post-operative results. A complete patient-specific aortic model was reconstructed. Two prosthetic valves (balloon-expandable valve and self-expandable valve) were introduced to simulate the implantation procedure, and post-procedural function was studied with fluid-structure interaction method, respectively. Results showed similar stress distribution for two valves, but higher peak stress for balloon-expandable valve model. Compared with the self-expandable valve, the balloon-expandable valve was associated with a better circular cross-section and smaller paravalvular gaps area. Hemodynamic parameters like cardiac output, mean transvalvular pressure difference and effective orifice area (EOA) of the balloon-expandable valve model were better than those of the self-expandable valve model. Significant outcome difference was found for two prosthetic valves. Balloon-expandable valve may effectively decrease the risk and degree of post-operative paravalvular leak, while self-expandable valve was conducive to lower stroke risk due to lower aortic stress. The numerical TAVR simulation process may become an assistant tool for prosthesis selection in pre-operative planning and post-operative prediction.

The Role of 3D Printing in Planning Complex Medical Procedures and Training of Medical Professionals-Cross-Sectional Multispecialty Review

Medicine is a rapidly-evolving discipline, with progress picking up pace with each passing decade. This constant evolution results in the introduction of new tools and methods, which in turn occasionally leads to paradigm shifts across the affected medical fields. The following review attempts to showcase how 3D printing has begun to reshape and improve processes across various medical specialties and where it has the potential to make a significant impact. The current state-of-the-art, as well as real-life clinical applications of 3D printing, are reflected in the perspectives of specialists practicing in the selected disciplines, with a focus on pre-procedural planning, simulation (rehearsal) of non-routine procedures, and on medical education and training. A review of the latest multidisciplinary literature on the subject offers a general summary of the advances enabled by 3D printing. Numerous advantages and applications were found, such as gaining better insight into patient-specific anatomy, better pre-operative planning, mock simulated surgeries, simulation-based training and education, development of surgical guides and other tools, patient-specific implants, bioprinted organs or structures, and counseling of patients. It was evident that pre-procedural planning and rehearsing of unusual or difficult procedures and training of medical professionals in these procedures are extremely useful and transformative.

Treatment of Bicuspid Aortic Valve Stenosis with TAVR: Filling Knowledge Gaps Towards Reducing Complications

PURPOSE OF REVIEW

Bicuspid aortic valve (BAV) disease is the most common congenital heart defect worldwide. When severe, symptomatic aortic stenosis ensues, the treatment has increasingly become transcatheter aortic valve replacement (TAVR). The purpose of this review is to identify BAV classification and imaging methods, outline TAVR outcomes in BAV anatomy, and discuss how computational modeling can enhance TAVR treatment in BAV patients.

RECENT FINDINGS

TAVR use in BAV patients, when compared to use in tricuspid aortic valves, showed lower device success rate, and there remains no long-term randomized trial data. It has been reported that BAV patients with severe calcification increase the rate of complications. Additionally, the asymmetrical morphology of BAVs often results in asymmetric stent geometries which have implications for increased thrombosis risk and decreased durability. These adverse outcomes are currently very difficult to predict from routine pre-procedural imaging alone. Recently developed patient specific experimental and computational techniques have the potential to assist in filling knowledge gaps in the mechanisms of these complications and provide more information during preclinical planning for better TAVR selection in low surgical risk BAV patients. Efficacy of TAVR for irregular BAV anatomies remains concerning due to the lack of a long-term randomized trial data, their increased rate of short-term complications, and signs that long-term durability could be an issue. More knowledge on identifying which BAV anatomies are at greater risk for these adverse outcomes can potentially improve patient selection for TAVR versus SAVR in low surgical risk BAV patients.

Successful Closure of Paravalvular Leak Using Computed Tomography Image Fusion and Planning With 3-Dimensional Printing

The presence of moderate to severe paravalvular leak increases mortality. We present a case of giant paravalvular leak closure using the 3-dimensional printing model to assess the success of the device to be used for its closure, computed tomography was performed for planning and guiding the procedure by image fusion. (Level of Difficulty: Advanced.).

Development of a Multi-Material 3D Printer for Functional Anatomic Models

Anatomic models are important in medical education and pre-operative planning as they help students or doctors prepare for real scenarios in a risk-free way. Several experimental anatomic models were made with additive manufacturing techniques to improve geometric, radiological, or mechanical realism. However, reproducing the mechanical behavior of soft tissues remains a challenge. To solve this problem, multi-material structuring of soft and hard materials was proposed in this study, and a three-dimensional (3D) printer was built to make such structuring possible. The printer relies on extrusion to deposit certain thermoplastic and silicone rubber materials. Various objects were successfully printed for testing the feasibility of geometric features such as thin walls, infill structuring, overhangs, and multi-material interfaces. Finally, a small medical image-based ribcage model was printed as a proof of concept for anatomic model printing. The features enabled by this printer offer a promising outlook on mimicking the mechanical properties of various soft tissues.

Mechanical properties of tissue-mimicking composites formed by material jetting additive manufacturing

Capitalizing on features including high resolution, smooth surface finish, large build volume, and simultaneous multi-color/multi-material printing, material jetting additive manufacturing enables the fabrication of full-scale anatomic models. The ability to print materials that resemble relevant, compliant tissues has especially motivated implementation of material jetting for patient-specific surgical planning or training models. In an effort to broaden the material selection for the material jetting process, and to provide materials that more closely mimic the functional needs for a wider variety of tissues, a composite material system is explored that uses non-curing fluid dispersed into a photo-curable medium. The material properties of the composites are examined through both thermal and mechanical analysis (dynamic mechanical analysis, Shore hardness testing, puncture testing, and tensile testing). Higher contributions of non-curing fluid generally reduce part strength and stiffness, and exponential and second-order polynomial expressions are appropriate fits for many of the mechanical properties as functions of non-curing fluid concentration. Through the fundamental exploration of the impact of an added diluent on material properties, the study advances knowledge on the process-property relationship for multi-material jetting. Additionally, better understanding of the mechanical property space offered by these materials will expand the capabilities of material jetting in the context of biomedical applications. The collection of mechanical properties serve as reference data sets to facilitate quicker screening for tissue-mimicking, medical models.

Active Image Synthesis for Efficient Labeling

The great success achieved by deep neural networks attracts increasing attention from the manufacturing and healthcare communities. However, the limited availability of data and high costs of data collection are the major challenges for the applications in those fields. We propose in this work AISEL, an active image synthesis method for efficient labeling, to improve the performance of the small-data learning tasks. Specifically, a complementary AISEL dataset is generated, with labels actively acquired via a physics-based method to incorporate underlining physical knowledge at hand. An important component of our AISEL method is the bidirectional generative invertible network (GIN), which can extract interpretable features from the training images and generate physically meaningful virtual images. Our AISEL method then efficiently samples virtual images not only further exploits the uncertain regions but also explores the entire image space. We then discuss the interpretability of GIN both theoretically and experimentally, demonstrating clear visual improvements over the benchmarks. Finally, we demonstrate the effectiveness of our AISEL framework on aortic stenosis application, in which our method lowers the labeling cost by 90 percent while achieving a 15 percent improvement in prediction accuracy.

3D Printing-A Cutting Edge Technology for Treating Post-Infarction Patients

The increasing complexity of cardiovascular interventions requires advanced peri-procedural imaging and tailored treatment. Three-dimensional printing technology represents one of the most significant advances in the field of cardiac imaging, interventional cardiology or cardiovascular surgery. Patient-specific models may provide substantial information on intervention planning in complex cardiovascular diseases, and volumetric medical imaging from CT or MRI can be translated into patient-specific 3D models using advanced post-processing applications. 3D printing and additive manufacturing have a great variety of clinical applications targeting anatomy, implants and devices, assisting optimal interventional treatment and post-interventional evaluation. Although the 3D printing technology still lacks scientific evidence, its benefits have been shown in structural heart diseases as well as for treatment of complex arrhythmias and corrective surgery interventions. Recent development has enabled transformation of conventional 3D printing into complex 3D functional living tissues contributing to regenerative medicine through engineered bionic materials such hydrogels, cell suspensions or matrix components. This review aims to present the most recent clinical applications of 3D printing in cardiovascular medicine, highlighting also the potential for future development of this revolutionary technology in the medical field.

3D Printing in Modern Cardiology

BACKGROUND

3D printing represents an emerging technology in the field of cardiovascular medicine. 3D printing can help to perform a better analysis of complex anatomies to optimize intervention planning.

METHODS

A systematic review was performed to illustrate the 3D printing technology and to describe the workflow to obtain 3D printed models from patient-specific images. Examples from our laboratory of the benefit of 3D printing in planning interventions were also reported.

RESULTS

3D printing technique is reliable when applied to high-quality 3D image data (CTA, CMR, 3D echography), but it still needs the involvement of expert operators for image segmentation and mesh refinement. 3D printed models could be useful in interventional planning, although prospective studies with comprehensive and clinically meaningful endpoints are required to demonstrate the clinical utility.

CONCLUSION

3D printing can be used to improve anatomy understanding and surgical planning.

Three-dimensional virtual and printed models for planning adult cardiovascular surgery

BACKGROUND

The objective of this study was to explore the usefulness of virtual models and three-dimensional (3D) printing technologies for planning complex non-congenital cardiovascular surgery.

METHODS

Between July 2018 and December 2019, adult patients with different cardiovascular structural diseases were included in a clinical protocol to explore the usefulness of Standard Tessellation Language (STL)-based virtual models and 3D printing for prospectively planning surgery. A qualitative descriptive analysis from the surgeon's viewpoint was done based on the characteristics, advantages and usefulness of 3D models for guiding, planning and simulating the surgical procedures.

RESULTS

A total of 14 custom 3D-printed heart and great vessel replicas with their corresponding 3D virtual models were created for preoperative surgical planning. Six of 14 models helped to redefine the surgical approach, 3 were useful to verify device delivery, while the rest did not change the surgical decision. In all open surgery cases, cardiac and vascular anatomy accuracy of virtual and physical 3D replicas was validated by direct visualisation of the organs during surgery. Printing was achieved through an external provider associated with the Hospital, who printed the final prototype in 5-7 days. Printed production cost was between 100 and 500 USD per model.

CONCLUSIONS

In the current study, the selected 3D printed models presented different advantages (visual, tactile, and instrumental) over the traditional flat anatomical images when simulating and planning some complex types of surgery. Notwithstanding 3D printing advantages, STL-based virtual models were pre-printing useful tools when instrumentation on a physical replica was not required.

3D Printing for Cardiovascular Applications: From End-to-End Processes to Emerging Developments

3D printing as a means of fabrication has seen increasing applications in medicine in the last decade, becoming invaluable for cardiovascular applications. This rapidly developing technology has had a significant impact on cardiovascular research, its clinical translation and education. It has expanded our understanding of the cardiovascular system resulting in better devices, tools and consequently improved patient outcomes. This review discusses the latest developments and future directions of generating medical replicas ('phantoms') for use in the cardiovascular field, detailing the end-to-end process from medical imaging to capture structures of interest, to production and use of 3D printed models. We provide comparisons of available imaging modalities and overview of segmentation and post-processing techniques to process images for printing, detailed exploration of latest 3D printing methods and materials, and a comprehensive, up-to-date review of milestone applications and their impact within the cardiovascular domain across research, clinical use and education. We then provide an in-depth exploration of future technologies and innovations around these methods, capturing opportunities and emerging directions across increasingly realistic representations, bioprinting and tissue engineering, and complementary virtual and mixed reality solutions. The next generation of 3D printing techniques allow patient-specific models that are increasingly realistic, replicating properties, anatomy and function.

[Comprehensive review of 3D printing use in medicine: Comparison with practical applications in urology]

INTRODUCTION

Over the past few years, 3D printing has evolved rapidly. This has resulted in an increasing number of scientific publications reporting on the medical use of 3D printing. These applications can range from patient information, preoperative planning, education, or 3D printing of patient-specific surgical implants. The objective of this review was to give an overview of the different applications in urology and other disciplines based on a selection of publications.

METHODS

In the current narrative review the Medline database was searched to identify all the related reports discussing the use of 3D printing in the medical field and more specifically in Urology. 3D printing applications were categorized so they could be searched more thoroughly within the Medline database.

RESULTS

Three-dimensional printing can help improve pre-operative patient information, anatomy and medical trainee education. The 3D printed models may assist the surgeon in preoperative planning or become patient-specific surgical simulation models. In urology, kidney cancer surgery is the most concerned by 3D printing-related publications, for preoperative planning, but also for surgical simulation and surgical training.

CONCLUSION

3D printing has already proven useful in many medical applications, including urology, for patient information, education, pre-operative planning and surgical simulation. All areas of urology are involved and represented in the literature. Larger randomized controlled studies will certainly allow 3D printing to benefit patients in routine clinical practice.

Three-dimensional printing for heart diseases: clinical application review

Heart diseases remain the top threat to human health, and the treatment of heart diseases changes with each passing day. Convincing evidence shows that three-dimensional (3D) printing allows for a more precise understanding of the complex anatomy associated with various heart diseases. In addition, 3D-printed models of cardiac diseases may serve as effective educational tools and for hands-on simulation of surgical interventions. We introduce examples of the clinical applications of different types of 3D printing based on specific cases and clinical application scenarios of 3D printing in treating heart diseases. We also discuss the limitations and clinically unmet needs of 3D printing in this context.

Paravalvular leak prediction after transcatheter aortic valve replacement with self-expandable prosthesis based on quantitative aortic calcification analysis

Background

Paravalvular leak (PVL) is one of the most common complications of transcatheter aortic valve replacement (TAVR) and affects short- and long-term outcomes. The aim of this study was to identify the computed tomography (CT) imaging biomarkers that allow PVL after TAVR to be predicted.

Methods

Patients were included who had severe aortic valve stenosis, had undergone TAVR with a self-expanding valve, and had undergone a pre-procedural CT scan. Data on baseline characteristics, procedural and long-term outcomes were collected retrospectively. We used MATLAB software with a self-developed algorithm for CT scan analysis and found parameters that quantified aortic valve calcifications (AVC) in detail.

Results

Fifty patients were included. The identified CT-derived parameters included AVC size, volume, thickness and density, as well as calcium radial distribution. The volume of the largest calcium block, calcium perimeter and calcium size (assessed by Feret's diameter) showed a strong association with PVL occurrence after TAVR (P=0.012, P=0.001 and P=0.045, respectively). The prognostic model showed that a 10 mm² increase in the local AVC amount in each valve section was associated with a 9.8% (95% CI: 2-18%; P=0.019) increase in the risk of PVL occurrence in the corresponding area after TAVR. ROC analysis revealed that the cut-off point of the AVC area was 96.5 mm² in the polar coordinate system presentation. Kaplan-Meier curves showed worse PVL-free survival in patients with more than 96.5 mm² of calcium area (P=0.013; log-rank).

Conclusions

Quantitative AVC assessment for PVL prediction may play an important role in screening before TAVR. In future, the use of quantitative AVC assessment as an imaging biomarker in TAVR candidates and the creation and extension of an online database containing quantitative AVC parameters may help to identify high PVL risk patients.

Patient-specific in vitro testing for evaluating TAVR clinical performance-A complementary approach to current ISO standard testing

Following in vitro tests established for surgical prosthetic heart valves, transcatheter aortic valves (TAV) are similarly tested in idealized geometries-excluding effects that may hamper TAVR performance in situ. Testing in vitro in pulse duplicator systems that incorporated patient-specific replicas would enhance the testing veracity by bringing it closer to the clinical scenario. To that end we compare TAV hemodynamic performance tested in idealized geometries according to the ISO standard (baseline performance) to that obtained by testing the TAVs following deployment in patient-specific replicas. Balloon-expandable (n = 2) and self-expandable (n = 3) TAVs were tested in an idealized geometry in mock-circulation system (following ISO 5840-3 guidelines) and compared to the measurements in a dedicated mock-circulation system adapted for the five patient-specific replicas. Patient-specific deployments resulted in a decline in performance as compared to the baseline idealized testing, as well as a variation in performance that depended on the design features of each device that was further correlated with the radial expansion and eccentricity of the deployed TAV stent (obtained with CT-scans of the deployed valves). By excluding the deployment effects in irregular geometries, the current idealized ISO testing is limited to characterize the baseline device performance. Utilizing patient-specific anatomic contours provides performance indicators under more stringent conditions likely encountered in vivo. It has the potential to enhance testing and development complementary to the ISO standard, for improved TAV safety and effectiveness.

Modelling and manufacturing of 3D-printed, patient-specific, and anthropomorphic gastric phantoms: a pilot study

Interventional devices including intragastric balloons are widely used to treat obesity. This study aims to develop 3D-printed, patient-specific, and anthropomorphic gastric phantoms with mechanical properties similar to those of human stomach. Using computed tomography gastrography (CTG) images of three patients, gastric phantoms were modelled through shape registration to align the stomach shapes of three different phases. Shape accuracies of the original gastric models versus the 3D-printed phantoms were compared using landmark distances. The mechanical properties (elongation and tensile strength), number of silicone coatings (0, 2, and 8 times), and specimen hardness (50, 60, and 70 Shore A) of three materials (Agilus, Elastic, and Flexa) were evaluated. Registration accuracy was significantly lower between the arterial and portal phases (3.16 ± 0.80 mm) than that between the portal and delayed phases (8.92 ± 0.96 mm). The mean shape accuracy difference was less than 10 mm. The mean elongations and tensile strengths of the Agilus, Elastic, and Flexa were 264%, 145%, and 146% and 1.14, 1.59, and 2.15 MPa, respectively, and their mechanical properties differed significantly (all p < 0.05). Elongation and tensile strength assessments, CTG image registration and 3D printing resulted in highly realistic and patient-specific gastric phantoms with reasonable shape accuracies.

3D Printing, Computational Modeling, and Artificial Intelligence for Structural Heart Disease

Structural heart disease (SHD) is a new field within cardiovascular medicine. Traditional imaging modalities fall short in supporting the needs of SHD interventions, as they have been constructed around the concept of disease diagnosis. SHD interventions disrupt traditional concepts of imaging in requiring imaging to plan, simulate, and predict intraprocedural outcomes. In transcatheter SHD interventions, the absence of a gold-standard open cavity surgical field deprives physicians of the opportunity for tactile feedback and visual confirmation of cardiac anatomy. Hence, dependency on imaging in periprocedural guidance has led to evolution of a new generation of procedural skillsets, concept of a visual field, and technologies in the periprocedural planning period to accelerate preclinical device development, physician, and patient education. Adaptation of 3-dimensional (3D) printing in clinical care and procedural planning has demonstrated a reduction in early-operator learning curve for transcatheter interventions. Integration of computation modeling to 3D printing has accelerated research and development understanding of fluid mechanics within device testing. Application of 3D printing, computational modeling, and ultimately incorporation of artificial intelligence is changing the landscape of physician training and delivery of patient-centric care. Transcatheter structural heart interventions are requiring in-depth periprocedural understanding of cardiac pathophysiology and device interactions not afforded by traditional imaging metrics.

Utility of Three-Dimensional (3D) Modeling for Planning Structural Heart Interventions (with an Emphasis on Valvular Heart Disease)

PURPOSE OF REVIEW

Advanced imaging has played a vital role in the contemporary, rapid rise of structural heart interventions. 3D modeling and printing has emerged as one of the most recent imaging tools and the implementation of 3D modeling is expected to increase with further advances in imaging, print hardware, and materials.

RECENT FINDINGS

3D modeling can be used to educate patients and clinical teams, provide ex vivo procedural simulation, and improve outcomes. Intra-procedural success rates may be improved, and post-procedural complications can be predicted more robustly with appropriate application of 3D modeling. Recent advances in technology have increased the availability of this tool, such that there can be more ready adoption into a routine clinical workflow. Familiarity with 3D modeling and its current utilization and role in structural interventions will help inform how to approach and adapt this exciting new technology.

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.

3D printing tissue-mimicking materials for realistic transseptal puncture models

Applications of additive manufacturing (commonly referred to as 3D printing) in direct fabrication of models for pre-surgical planning, functional testing, and medical training are on the rise. However, one current limitation to the accuracy of models for cardiovascular procedural training is a lack of printable materials that accurately mimic human tissue. Most of the available elastomeric materials lack mechanical properties representative of human tissues. To address the gap, the authors explore the multi-material capability of material jetting additive manufacturing to combine non-curing and photo-curing inks to achieve material properties that more closely replicate human tissues. The authors explore the impact of relative material concentration on tissue-relevant properties from puncture and tensile testing under submerged conditions. Further, the authors demonstrate the ability to mimic the mechanical properties of the fossa ovalis, which proves beneficial for accurately simulating transseptal punctures. A fossa ovalis mimic was printed and assembled within a full patient-specific heart model for validation, where it exhibited accuracy in both mechanical properties and geometry. The explored material combination provides the opportunity to fabricate future medical models that are more realistic and better suited for pre-surgical planning and medical student training. This will ultimately guide safer, more efficient practices.

Accuracy of cardiac magnetic resonance generated 3D models of the aortic annulus compared to cardiovascular computed tomography generated 3D models

To evaluate the accuracy of 3D models of the aortic-root generated from non-contrast cardiac magnetic resonance (CMR). Data were retrospectively collected from 30 consecutive patients who underwent surgical aortic valve replacement and had available records of both intra-operative assessment and pre-surgery annulus assessment by cardiovascular computed tomography (CCT) and CMR. The 3D models were independently segmented, modelled and printed by two blinded "manufacturers". The measurements on the models were carried out by two cardiac surgeons with Hegar dilator. Data were analyzed with non-parametric tests. There was no significant intra- or inter-observer variability (p ≥ 0.13). The agreement between the diameter of the 3D model derived from CMR images and either the anatomical reference of the intraoperative measurement (p = 0.10, r = 0.97) or the radiological reference of the 3D model generated from CCT (p = 0.71, r = 0.92) was very good. The process of segmentation plus the post-processing was about 17 ± 2 min for a model created by CMR, significantly higher than a model created from CCT (7 ± 2 min; p < 0.001). The printing time for a single model did not differ between the two modalities (p = 0.61) and was less than 60 min. The cost for a single model was approximately 0.5 €. 3D models generated from non-contrast CMR performed well when compared to the anatomical reference standard and are comparable to the pair CCT derived models.

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.

3-Dimensional printing to predict paravalvular regurgitation after transcatheter aortic valve replacement

BACKGROUND

There is no effective method to predict paravalvular regurgitation prior to transcatheter aortic valve replacement (TAVR).

METHODS

We retrospectively analyzed pre-TAVR computed tomography (CT) scans of 20 patients who underwent TAVR for severe, calcific aortic stenosis and subsequently printed 3-dimensional (3D) aortic root models of each patient. Models were printed using Ninjaflex thermoplastic polyurethane (TPU) (Ninjatek Manheim, PA) and TPU 95A (Ultimaker, Netherlands) on Ultimaker 3 Extended 3D printer (Ultimaker, Netherlands). The models were implanted at nominal pressure with same sized Sapien balloon-expandable frames (Edwards Lifesciences, CA) as received in-vivo. Ex-vivo implanted TAVR models (eTAVR) were scanned using Siemens SOMATOM flash dual source CT (Siemens, Malvern, PA) and then analyzed with Mimics software (Materialize NV, Leuven, Belgium) to evaluate relative stent appositions. eTAVR were then compared to post-TAVR echocardiograms for each patient to assess for correlations of identified and predicted paravalvular leak (PVL) locations.

RESULTS

A total of 20 patients (70% male) were included in this study. The median age was 77.5 (74-83.5) years. Ten patients were characterized to elicit mild (9/10) or moderate (1/10) PVL, and 10 patients presented no PVL. In patients with echocardiographic PVL, eTAVR 3D model analyses correctly identified the site of PVL in 8/10 cases. In patients without echocardiographic PVL, eTAVR 3D model analyses correctly predicted the lack of PVL in 9/10 cases.

CONCLUSION

3D printing may help predict the potential locations of associated PVL post-TAVR, which may have implications for optimizing valve selection and sizing.

3D Printing Applications for Transcatheter Aortic Valve Replacement

PURPOSE OF REVIEW

A combination of evolving 3D printing technologies, new 3D printable materials, and multi-disciplinary collaborations have made 3D printing applications for transcatheter aortic valve replacement (TAVR) a promising tool to promote innovation, increase procedural success, and provide a compelling educational tool. This review synthesizes the knowledge via publications and our group's experience in this area that exemplify uses of 3D printing for TAVR.

RECENT FINDINGS

Patient-specific 3D-printed models have been used for TAVR pre-procedural device sizing, benchtop prediction of procedural complications, planning for valve-in-valve and bicuspid aortic valve procedures, and more. Recent publications also demonstrate how 3D printing can be used to test assumptions about why certain complications occur during THV implantation. Finally, new materials and combinations of existing materials are starting to bridge the large divide between current 3D material and cardiac tissue properties. Several studies have demonstrated the utility of 3D printing in understanding challenges of TAVR. Innovative approaches to benchtop testing and multi-material printing have brought us closer to being able to predict how a THV will interact with a specific patient's aortic anatomy. This work to date is likely to open the door for advancements in other areas of structural heart disease, such as interventions involving the mitral valve, tricuspid valve, and left atrial appendage.

Simulation of semilunar valve function: computer-aided design, 3D printing and flow assessment with MR

BACKGROUND

The structure of the valve leaflets and sinuses are crucial in supporting the proper function of the semilunar valve and ensuring leaflet durability. Therefore, an enhanced understanding of the structural characteristics of the semilunar valves is fundamental to the evaluation and staging of semilunar valve pathology, as well as the development of prosthetic or bioprosthetic valves. This paper illustrates the process of combining computer-aided design (CAD), 3D printing and flow assessment with 4-dimensional flow magnetic resonance imaging (MRI) to provide detailed assessment of the structural and hemodynamic characteristics of the normal semilunar valve.

METHODS

Previously published geometric data on the aortic valve was used to model the 'normal' tricuspid aortic valve with a CAD software package and 3D printed. An MRI compatible flow pump with the capacity to mimic physiological flows was connected to the phantom. A peak flow rate of 100 mL/s and heart rate of 60 beats per minute were used. MRI measurements included cine imaging, 2D and 4D phase-contrast imaging to assess valve motion, flow velocity and complex flow patterns.

RESULTS

Cine MRI data showed normal valve function and competency throughout the cardiac cycle in the 3D-printed phantom. Quantitative analysis of 4D Flow data showed net flow through 2D planes proximal and distal to the valve were very consistent (26.03 mL/s and 26.09 mL/s, respectively). Measurements of net flow value agreed closely with the flow waveform provided to the pump (27.74 mL/s), confirming 4D flow acquisition in relation to the pump output. Peak flow values proximal and distal to the valve were 78.4 mL/s and 63.3 mL/s, respectively. Particle traces of flow from 4D-phase contrast MRI data demonstrated flow through the valve into the ascending aorta and vortices within the aortic sinuses, which are expected during ventricular diastole.

CONCLUSION

In this proof of concept study, we have demonstrated the ability to generate physiological 3D-printed aortic valve phantoms and evaluate their function with cine- and 4D Flow MRI. This technology can work synergistically with promising tissue engineering research to develop optimal aortic valve replacements, which closely reproduces the complex function of the normal aortic valve.