Patient-specific computational models to support interventional procedures: a case study of complex aortic re-coarctation

Applications of computational fluid dynamics to congenital heart diseases: a practical review for cardiovascular professionals

INTRODUCTION

The increased survival rate of patients with congenital heart disease (CHD) has made it likely that 70%-95% of infants with CHDs surviving into adulthood often require careful follow-up and (repeat) interventions. Patients with CHDs often have abnormal blood flow patterns, due to both primary cardiac defect and the consequent surgical or endovascular repair.

AREA COVERED

Computational fluid dynamics (CFD) alone or coupled with advanced imaging tools can assess blood flow patterns of CHDs to both understand their pathophysiology and anticipate the results of surgical or interventional repair.

EXPERT OPINION

CFD is a mathematical technique that quantifies and describes the characteristics of fluid flow using the laws of physics. Through dedicated software based on virtual reconstruction and simulation and patients' real data coming from computed tomography, magnetic resonance imaging, and 3/4 D-ultrasound, reconstruction of models of circulation of most CHD can be accomplished. CFD can provide insights about the pathophysiology of coronary artery anomalies, interatrial shunts, coarctation of the aorta and aortic bicuspid valve, tetralogy of Fallot and univentricular heart, with the capability in some cases of simulating different types of surgical or interventional repair and tailoring the treatment on the basis of these findings.

A validated computational framework to predict outcomes in TAVI

Transcatheter aortic valve implantation (TAVI) still presents complications: paravalvular leakage (PVL) and onset of conduction abnormalities leading to permanent pacemaker implantation. Our aim was testing a validated patient-specific computational framework for prediction of TAVI outcomes and possible complications. Twenty-eight TAVI patients (14 SapienXT and 14 CoreValve) were retrospectively selected. Pre-procedural CT images were post-processed to create 3D patient-specific implantation sites. The procedures were simulated with finite element analysis. Simulations' results were compared against post-procedural clinical fluoroscopy and echocardiography images. The computational model was in good agreement with clinical findings: the overall stent diameter difference was 2.6% and PVL was correctly identified with a post-processing algorithm in 83% of cases. Strains in the implantation site were studied to assess the risk of conduction system disturbance and were found highest in the patient who required pacemaker implantation. This study suggests that computational tool could support safe planning and broadening of TAVI.

A Patient-Specific CFD Pipeline Using Doppler Echocardiography for Application in Coarctation of the Aorta in a Limited Resource Clinical Context

Congenital heart disease (CHD) is the most common birth defect globally and coarctation of the aorta (CoA) is one of the commoner CHD conditions, affecting around 1/1800 live births. CoA is considered a CHD of critical severity. Unfortunately, the prognosis for a child born in a low and lower-middle income country (LLMICs) with CoA is far worse than in a high-income country. Reduced diagnostic and interventional capacities of specialists in these regions lead to delayed diagnosis and treatment, which in turn lead to more cases presenting at an advanced stage. Computational fluid dynamics (CFD) is an important tool in this context since it can provide additional diagnostic data in the form of hemodynamic parameters. It also provides an in silico framework, both to test potential procedures and to assess the risk of further complications arising post-repair. Although this concept is already in practice in high income countries, the clinical infrastructure in LLMICs can be sparse, and access to advanced imaging modalities such as phase contrast magnetic resonance imaging (PC-MRI) is limited, if not impossible. In this study, a pipeline was developed in conjunction with clinicians at the Red Cross War Memorial Children’s Hospital, Cape Town and was applied to perform a patient-specific CFD study of CoA. The pipeline uses data acquired from CT angiography and Doppler transthoracic echocardiography (both much more clinically available than MRI in LLMICs), while segmentation is conducted via SimVascular and simulation is realized using OpenFOAM. The reduction in cost through use of open-source software and the use of broadly available imaging modalities makes the methodology clinically feasible and repeatable within resource-constrained environments. The project identifies the key role of Doppler echocardiography, despite its disadvantages, as an intrinsic component of the pipeline if it is to be used routinely in LLMICs.

Prediction of post-stenting biomechanics in coarcted aortas: A pilot finite element study

Endovascular stenting has recently become a standard treatment for native coarctation of the aorta (CoA) in children and young adults, given the efficacy in relieving vessel obstruction with a low incidence of adverse events. Yet, despite the short-term success of the technique, late hypertension remains an endemic risk. To assess the impact of the percutaneous procedure on the aortic wall biomechanics, we designed a novel finite element (FE) protocol for the simulation of endovascular stenting in three patient-specific CoA anatomies, developing a remeshing procedure that allows for coping with different CoA severities. Our FE protocol was able to yield numerical results on stent distortions and stresses, as well as on changes in aortic wall stresses and distensibility. These results were consistent with intraprocedural in-vivo evidences and with previous findings from the literature, and they suggest that our numerical approach could be used to understand the role of patient specific anatomical features (CoA severity and arch type) on the post-stenting aortic biomechanics. If soundly validated on a vast cohort of patients, our approach could support patient selection for the procedure.

Subject-specific simulation for non-invasive assessment of aortic coarctation: Towards a translational approach

We present a multi-scale CFD-based study conducted in a cohort of 11 patients with coarctation of the aorta (CoA). The study explores the potential for implementation of a workflow using non-invasive routinely collected medical imaging data and clinical measurements to provide a more detailed insight into local aortic haemodynamics in order to support clinical decision making. Our approach is multi-scale, using a reduced-order model (1D/0D) and an optimization process for the personalization of patient-specific boundary conditions and aortic vessel wall parameters from non-invasive measurements, to inform a more complex model (3D/0D) representing 3D aortic patient-specific anatomy. The reliability of the modelling approach is investigated by comparing 3D/0D model pressure drop estimation with measured peak gradients recorded during diagnostic cardiac catheterization and 2D PC-MRI flow rate measurements in the descending aorta. The current study demonstrated that the proposed approach requires low levels of user interaction, making it suitable for the clinical setting. The agreement between computed blood pressure drop and catheter measurements is 10  ±  8 mmHg at the coarctation site. The comparison between CFD derived and catheter measured pressure gradients indicated that the model has to be improved, suggesting the use of time varying pressure waveforms to further optimize the tuning process and modelling assumptions.

Evaluation of a modified Cheatham-Platinum stent for the treatment of aortic coarctation by finite element modelling

Objectives

Stent implantation for the treatment of aortic coarctation has become a standard approach for the management of older children and adults. Criteria for optimal stent design and construction remain undefined. This study used computational modelling to compare the performance of two generations of the Cheatham-Platinum stent (NuMED, Hopkinton, NY, USA) deployed in aortic coarctation using finite element analysis.

Design

Three-dimensional models of both stents, reverse engineered from microCT scans, were implanted in the aortic model of one representative patient. They were virtually expanded in the vessel with a 16 mm balloon and a pressure of 2 atm.

Results

The conventional stent foreshortened to 96.5% of its initial length, whereas the new stent to 99.2% of its initial length. Diameters in 15 slices across the conventional stent were 11.6–15 mm (median 14.2 mm) and slightly higher across the new stent: 10.7–15.3 mm (median 14.5 mm) (p= 0.021). Apposition to the vessel wall was similar: conventional stent 31.1% and new stent 28.6% of total stent area.

Conclusions

The new design Cheatham-Platinum stent showed similar deployment results compared to the conventional design. The new stent design showed slightly higher expansion, using the same delivery balloon. Patient-specific computational models can be used for virtual implantation of new aortic stents and promise to inform subsequent in vivo trials.

Population-specific material properties of the implantation site for transcatheter aortic valve replacement finite element simulations

Patient-specific computational models are an established tool to support device development and test under clinically relevant boundary conditions. Potentially, such models could be used to aid the clinical decision-making process for percutaneous valve selection; however, their adoption in clinical practice is still limited to individual cases. To be fully informative, they should include patient-specific data on both anatomy and mechanics of the implantation site. In this work, fourteen patient-specific computational models for transcatheter aortic valve replacement (TAVR) with balloon-expandable Sapien XT devices were retrospectively developed to tune the material parameters of the implantation site mechanical model for the average TAVR population. Pre-procedural computed tomography (CT) images were post-processed to create the 3D patient-specific anatomy of the implantation site. Balloon valvuloplasty and device deployment were simulated with finite element (FE) analysis. Valve leaflets and aortic root were modelled as linear elastic materials, while calcification as elastoplastic. Material properties were initially selected from literature; then, a statistical analysis was designed to investigate the effect of each implantation site material parameter on the implanted stent diameter and thus identify the combination of material parameters for TAVR patients. These numerical models were validated against clinical data. The comparison between stent diameters measured from post-procedural fluoroscopy images and final computational results showed a mean difference of 2.5 ± 3.9%. Moreover, the numerical model detected the presence of paravalvular leakage (PVL) in 79% of cases, as assessed by post-TAVR echocardiographic examination. The final aim was to increase accuracy and reliability of such computational tools for prospective clinical applications.

Patient-specific simulations for planning treatment in congenital heart disease

Patient-specific computational models have been extensively developed over the last decades and applied to investigate a wide range of cardiovascular problems. However, translation of these technologies into clinical applications, such as planning of medical procedures, has been limited to a few single case reports. Hence, the use of patient-specific models is still far from becoming a standard of care in clinical practice. The aim of this study is to describe our experience with a modelling framework that allows patient-specific simulations to be used for prediction of clinical outcomes. A cohort of 12 patients with congenital heart disease who were referred for percutaneous pulmonary valve implantation, stenting of aortic coarctation and surgical repair of double-outlet right ventricle was included in this study. Image data routinely acquired for clinical assessment were post-processed to set up patient-specific models and test device implantation and surgery. Finite-element and computational fluid dynamics analyses were run to assess feasibility of each intervention and provide some guidance. Results showed good agreement between simulations and clinical decision including feasibility, device choice and fluid-dynamic parameters. The promising results of this pilot study support translation of computer simulations as tools for personalization of cardiovascular treatments.

Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease

Noninvasive engineering models are now being used for diagnosing and planning the treatment of cardiovascular disease. Techniques in computational modeling and additive manufacturing have matured concurrently, and results from simulations can inform and enable the design and optimization of therapeutic devices and treatment strategies. The emerging synergy between large-scale simulations and 3D printing is having a two-fold benefit: first, 3D printing can be used to validate the complex simulations, and second, the flow models can be used to improve treatment planning for cardiovascular disease. In this review, we summarize and discuss recent methods and findings for leveraging advances in both additive manufacturing and patient-specific computational modeling, with an emphasis on new directions in these fields and remaining open questions.

Role of Computational Modelling in Planning and Executing Interventional Procedures for Congenital Heart Disease

Increasingly, computational modelling and numerical simulations are used to help plan complex surgical and interventional cardiovascular procedures in children and young adults with congenital heart disease. From its origins more than 30 years ago, surgical planning with analysis of flow hemodynamics and energy loss/efficiency has helped design and implement many modifications to existing techniques. On the basis of patient-specific medical imaging, surgical planning allows accurate model production that can then be manipulated in a virtual surgical environment, with the proposed solutions finally tested with advanced computational fluid dynamics to evaluate the results. Applications include a broad range of congenital heart disease, including patients with single-ventricle anatomy undergoing staged palliation, those with arch obstruction, with double outlet right ventricle, or with tetralogy of Fallot. In the present work, we focus on clinical applications of this exciting field. We describe the framework for these techniques, including brief descriptions of the engineering principles applied and the interaction between "benchtop" data with medical decision-making. We highlight some early insights learned from pioneers over the past few decades, including refinements in Fontan baffle geometries and configurations. Finally, we offer a glimpse into exciting advances that are presently being explored, including use of modelling for transcatheter interventions. In this era of personalized medicine, computational modelling and surgical planning allows patient-specific tailoring of interventions to optimize clinical outcomes.

Computational modelling for congenital heart disease: how far are we from clinical translation?

Computational models of congenital heart disease (CHD) have become increasingly sophisticated over the last 20 years. They can provide an insight into complex flow phenomena, allow for testing devices into patient-specific anatomies (pre-CHD or post-CHD repair) and generate predictive data. This has been applied to different CHD scenarios, including patients with single ventricle, tetralogy of Fallot, aortic coarctation and transposition of the great arteries. Patient-specific simulations have been shown to be informative for preprocedural planning in complex cases, allowing for virtual stent deployment. Novel techniques such as statistical shape modelling can further aid in the morphological assessment of CHD, risk stratification of patients and possible identification of new ‘shape biomarkers’. Cardiovascular statistical shape models can provide valuable insights into phenomena such as ventricular growth in tetralogy of Fallot, or morphological aortic arch differences in repaired coarctation. In a constant move towards more realistic simulations, models can also account for multiscale phenomena (eg, thrombus formation) and importantly include measures of uncertainty (ie, CIs around simulation results). While their potential to aid understanding of CHD, surgical/procedural decision-making and personalisation of treatments is undeniable, important elements are still lacking prior to clinical translation of computational models in the field of CHD, that is, large validation studies, cost-effectiveness evaluation and establishing possible improvements in patient outcomes.

The Impact of Cardiac Motion on Aortic Valve Flow Used in Computational Simulations of the Thoracic Aorta

Advancements in image-based computational modeling are producing increasingly more realistic representations of vasculature and hemodynamics, but so far have not compensated for cardiac motion when imposing inflow boundary conditions. The effect of cardiac motion on aortic flow is important when assessing sequelae in this region including coarctation of the aorta (CoA) or regurgitant fraction. The objective of this investigation was to develop a method to assess and correct for the influence of cardiac motion on blood flow measurements through the aortic valve (AoV) and to determine its impact on patient-specific local hemodynamics quantified by computational fluid dynamics (CFD). A motion-compensated inflow waveform was imposed into the CFD model of a patient with repaired CoA that accounted for the distance traveled by the basal plane during the cardiac cycle. Time-averaged wall shear stress (TAWSS) and turbulent kinetic energy (TKE) values were compared with CFD results of the same patient using the original waveform. Cardiac motion resulted in underestimation of flow during systole and overestimation during diastole. Influences of inflow waveforms on TAWSS were greatest along the outer wall of the ascending aorta (AscAo) (∼30 dyn/cm2). Differences in TAWSS were more pronounced than those from the model creation or mesh dependence aspects of CFD. TKE was slightly higher for the motion-compensated waveform throughout the aortic arch. These results suggest that accounting for cardiac motion when quantifying blood flow through the AoV can lead to different conclusions for hemodynamic indices, which may be important if these results are ultimately used to predict patient outcomes.

Impact of different aortic valve calcification patterns on the outcome of transcatheter aortic valve implantation: A finite element study

Transcatheter aortic valve implantation (TAVI) can treat symptomatic patients with calcific aortic stenosis. However, the severity and distribution of the calcification of valve leaflets can impair the TAVI efficacy. Here we tackle this issue from a biomechanical standpoint, by finite element simulation of a widely adopted balloon-expandable TAVI in three models representing the aortic root with different scenarios of calcific aortic stenosis. We developed a modeling approach realistically accounting for aortic root pressurization and complex anatomy, detailed calcification patterns, and for the actual stent deployment through balloon-expansion. Numerical results highlighted the dependency on the specific calcification pattern of the "dog-boning" of the stent. Also, local stent distortions were associated with leaflet calcifications, and led to localized gaps between the TAVI stent and the aortic tissues, with potential implications in terms of paravalvular leakage. High stresses were found on calcium deposits, which may be a risk factor for stroke; their magnitude and the extent of the affected regions substantially increased for the case of an "arc-shaped" calcification, running from commissure to commissure. Moreover, high stresses due to the interaction between the aortic wall and the leaflet calcifications were computed in the annular region, suggesting an increased risk for annular damage. Our analyses suggest a relation between the alteration of the stresses in the native anatomical components and prosthetic implant with the presence and distribution of relevant calcifications. This alteration is dependent on the patient-specific features of the calcific aortic stenosis and may be a relevant indicator of suboptimal TAVI results.