Patient-specific simulation of endovascular repair surgery with tortuous aneurysms requiring flexible stent-grafts

Computational prediction of proximal sealing in endovascular abdominal aortic aneurysm repair with unfavorable necks

BACKGROUND AND OBJECTIVE

Endovascular aortic aneurysm repair (EVAR) has become the standard treatment for abdominal aortic aneurysms in most centers. However, proximal sealing complications leading to endoleaks and migrations sometimes occur, particularly in unfavorable aortic anatomies and are strongly dependent on biomechanical interactions between the aortic wall and the endograft. The objective of the present work is to develop and validate a computational patient-specific model that can accurately predict these complications.

METHODS

Based on pre-operative CT-scans, we developed finite element models of the aorta of 10 patients who underwent endovascular aortic aneurysm repair, 7 with standard morphologies and 3 with unfavorable anatomies. We simulated the deployment of stent grafts in each aorta by solving mechanical equilibrium with a virtual shell method. Eventually we compared the actual stent ring positions from post-operative computed-tomography-scans with the predicted simulated positions.

RESULTS

A successful deployment simulation could be performed for each patient. Relative radial, transverse and longitudinal deviations were 6.3 ± 4.4%, 2.5 ± 0.9 mm and 1.4 ± 1.1 mm, respectively.

CONCLUSIONS

The numerical model predicted accurately stent-graft positions in the aortic neck of 10 patients, even in complex anatomies. This shows the potential of computer simulation to anticipate possible proximal endoleak complications before EVAR interventions.

Prediction of bird-beak configuration in thoracic endovascular aortic repair preoperatively using patient-specific finite element simulations

Objectives

Formation of bird-beak configuration in thoracic endovascular aortic repair (TEVAR) has been shown to be correlated with the risk of complications such as type Ia endoleaks, stent graft migration, and collapse. The aim of this study was to use patient-specific computational simulations of TEVAR to predict the formation of bird-beak configuration preoperatively.

Methods

Patient-specific TEVAR computational simulations are developed using a retrospective cohort of patients treated for thoracic aortic aneurysm. The preoperative computed tomography images were segmented to develop three-dimensional geometry of the thoracic aorta. These geometries were used in finite element simulations of stent graft deployment during TEVAR. Simulated results were compared against the postoperative computed tomography images to assess the accuracy of simulations in predicting the proximal position of a deployed stent graft and presence of bird-beak. In cases with a bird-beak configuration, the length and angle of the bird-beak were measured and compared between the simulated and postoperative results.

Results

Twelve TEVAR patient cases were simulated. Computational simulations were able to accurately predict whether the proximal stent graft was fully apposed, proximal bare stents were protruded, or bird-beak configuration was present. In three cases with bird-beak configuration, simulations predicted the length and angle of the bird-beak with less than 10% and 24% error, respectively. Other factors such as a small aortic arch angle, small oversizing value, and landing zones close to the arch apex may have played a role in formation of bird-beak in these patients.

Conclusions

Computational simulations of TEVAR accurately predicted the proximal position of a deployed stent graft and the presence of bird-beak preoperatively. The computational models were able to predict the length and angle of bird-beak configurations with good accuracy. These simulations can provide insight into the surgical planning process with the goal of minimizing bird-beak occurrence.

A modeling framework for computational simulations of thoracic endovascular aortic repair

Thoracic endovascular aortic repair (TEVAR) is a minimally invasive treatment for thoracic aortic conditions including aneurysms and is associated with a number of postoperative stent graft related complications. Computational simulations of TEVAR have the potential to predict surgical outcomes and complications preoperatively. When using simulations for stent graft design and prediction of complications in a population, it is difficult to generalize patient-specific TEVAR computational models due to patient variability. This study proposes a novel modeling framework for creating realistic population-based computational models of TEVAR focused on aneurysms that allow for developing various clinically relevant geometric configurations and scenarios that are not easily attainable with limited patient data. The framework includes a methodology for developing population-based thoracic aortic geometries and defining age-dependent aortic tissue material models, as well as detailed steps and boundary conditions for finite element modeling of stent graft deployment during TEVAR. The simulation framework is illustrated for predicting the formation of a bird-beak configuration, a wedge-shaped gap at the proximal end of the deployed stent graft in TEVAR that leads to incomplete seal. A baseline TEVAR simulation model was developed along with three simulations in which the value of aortic curvature, aortic arch angle, or aortic tissue properties varied from the baseline model. Analyzing the length and angle of the bird-beak configuration in each case shows that the bird-beak size is sensitive to different values of the aortic geometry highlighting the importance of using realistic parameter values.

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

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

Evaluation and Verification of Fast Computational Simulations of Stent-Graft Deployment in Endovascular Aneurysmal Repair

Fenestrated Endovascular Aortic Repair, also known as FEVAR, is a minimally invasive procedure that allows surgeons to repair the aorta while still preserving blood flow to kidneys and other critical organs. Given the high complexity of FEVAR, there is a pressing need to develop numerical tools that can assist practitioners at the preoperative planning stage and during the intervention. The aim of the present study is to introduce and to assess an assistance solution named Fast Method for Virtual Stent-graft Deployment for computer assisted FEVAR. This solution, which relies on virtual reality, is based on a single intraoperative X-ray image. It is a hybrid method that includes the use of intraoperative images and a simplified mechanical model based on corotational beam elements. The method was verified on a phantom and validated on three clinical cases, including a case with fenestrations. More specifically, we quantified the errors induced by the different simplifications of the mechanical model, related to fabric simulation and aortic wall mechanical properties. Overall, all errors for both stent and fenestration positioning were less than 5 mm, making this method compatible with clinical expectations. More specifically, the errors related to fenestration positioning were less than 3 mm. Although requiring further validation with a higher number of test cases, our method could achieve an accuracy compatible with clinical specifications within limited calculation time, which is promising for future implementation in a clinical context.

Validation and Verification of High-Fidelity Simulations of Thoracic Stent-Graft Implantation

Thoracic Endovascular Aortic Repair (TEVAR) is the preferred treatment option for thoracic aortic pathologies and consists of inserting a self-expandable stent-graft into the pathological region to restore the lumen. Computational models play a significant role in procedural planning and must be reliable. For this reason, in this work, high-fidelity Finite Element (FE) simulations are developed to model thoracic stent-grafts. Experimental crimp/release tests are performed to calibrate stent-grafts material parameters. Stent pre-stress is included in the stent-graft model. A new methodology for replicating device insertion and deployment with explicit FE simulations is proposed. To validate this simulation, the stent-graft is experimentally released into a 3D rigid aortic phantom with physiological anatomy and inspected in a computed tomography (CT) scan at different time points during deployment with an ad-hoc set-up. A verification analysis of the adopted modeling features compared to the literature is performed. With the proposed methodology the error with respect to the CT is on average 0.92 ± 0.64%, while it is higher when literature models are adopted (on average 4.77 ± 1.83%). The presented FE tool is versatile and customizable for different commercial devices and applicable to patient-specific analyses.

Patient-specific computational modeling of endovascular aneurysm repair: State of the art and future directions

Endovascular aortic repair (EVAR) has become the preferred intervention option for aortic aneurysms and dissections. This is because EVAR is much less invasive than the alternative open surgery repair. While in-hospital mortality rates are smaller for EVAR than open repair (1%-2% vs. 3%-5%), the early benefits of EVAR are lost after 3 years due to larger rates of complications in the EVAR group. Clinicians follow instructions for use (IFU) when possible, but are left with personal experience on how to best proceed and what choices to make with respect to stent-graft (SG) model choice, sizing, procedural options, and their implications on long-term outcomes. Computational modeling of SG deployment in EVAR and tissue remodeling after intervention offers an alternative way of testing SG designs in silico, in a personalized way before intervention, to ultimately select the strategies leading to better outcomes. Further, computational modeling can be used in the optimal design of SGs in cases of complex geometries. In this review, we address some of the difficulties and successes associated with computational modeling of EVAR procedures. There is still work to be done in all areas of EVAR in silico modeling, including model validation, before models can be applied in the clinic, but much progress has already been made. Critical to clinical implementation are current efforts focusing on developing fast algorithms that can achieve (near) real-time solutions, as well as ways of dealing with inherent uncertainties related to patient aortic wall degradation on an individualized basis. We are optimistic that EVAR modeling in the clinic will soon become a reality to help clinicians optimize EVAR interventions and ultimately reduce EVAR-associated complications.

Patient-specific simulation of stent-graft deployment in type B aortic dissection: model development and validation

Thoracic endovascular aortic repair (TEVAR) has been accepted as the mainstream treatment for type B aortic dissection, but post-TEVAR biomechanical-related complications are still a major drawback. Unfortunately, the stent-graft (SG) configuration after implantation and biomechanical interactions between the SG and local aorta are usually unknown prior to a TEVAR procedure. The ability to obtain such information via personalised computational simulation would greatly assist clinicians in pre-surgical planning. In this study, a virtual SG deployment simulation framework was developed for the treatment for a complicated aortic dissection case. It incorporates patient-specific anatomical information based on pre-TEVAR CT angiographic images, details of the SG design and the mechanical properties of the stent wire, graft and dissected aorta. Hyperelastic material parameters for the aortic wall were determined based on uniaxial tensile testing performed on aortic tissue samples taken from type B aortic dissection patients. Pre-stress conditions of the aortic wall and the action of blood pressure were also accounted for. The simulated post-TEVAR configuration was compared with follow-up CT scans, demonstrating good agreement with mean deviations of 5.8% in local open area and 4.6 mm in stent strut position. Deployment of the SG increased the maximum principal stress by 24.30 kPa in the narrowed true lumen but reduced the stress by 31.38 kPa in the entry tear region where there was an aneurysmal expansion. Comparisons of simulation results with different levels of model complexity suggested that pre-stress of the aortic wall and blood pressure inside the SG should be included in order to accurately predict the deformation of the deployed SG.

Assessment of fenestrated Anaconda stent graft design by numerical simulation: Results of a European prospective multicenter study

OBJECTIVE

A crucial step in designing fenestrated stent grafts for treatment of complex aortic abdominal aneurysms is the accurate positioning of the fenestrations. The deployment of a fenestrated stent graft prototype in a patient-specific rigid aortic model can be used for design verification in vitro, but is time and human resources consuming. Numerical simulation (NS) of fenestrated stent graft deployment using the finite element analysis has recently been developed; the aim of this study was to compare the accuracy of fenestration positioning by NS and in vitro.

METHODS

All consecutive cases of complex aortic abdominal aneurysm treated with the Fenestrated Anaconda (Terumo Aortic) in six European centers were included in a prospective, observational study. To compare fenestration positioning, the distance from the center of the fenestration to the proximal end of the stent graft (L) and the angular distance from the 0° position (C) were measured and compared between in vitro testing (L1, C1) and NS (L2, C2). The primary hypothesis was that ΔL (|L2 - L1|) and ΔC (|C2 - C1|) would be 2.5 or less mm in more than 80% of the cases. The duration of both processes was also compared.

RESULTS

Between May 2018 and January 2019, 50 patients with complex aortic abdominal aneurysms received a fenestrated stent graft with a total of 176 fenestrations. The ΔL and ΔC was 2.5 mm or less for 173 (98%) and 174 (99%) fenestrations, respectively. The NS process duration was significantly shorter than the in vitro (2.1 days [range, 1.0-5.2 days] vs 20.6 days [range, 9-82 days]; P < .001).

CONCLUSIONS

Positioning of fenestrations using NS is as accurate as in vitro and could significantly decrease delivery time of fenestrated stent grafts.

Patient-Specific Virtual Stent-Graft Deployment for Type B Aortic Dissection: A Pilot Study of the Impact of Stent-Graft Length

Thoracic endovascular aortic repair (TEVAR) has been accepted as a standard treatment option for complicated type B aortic dissection. Distal stent-graft-induced new entry (SINE) is recognised as one of the main post-TEVAR complications, which can lead to fatal prognosis. Previous retrospective cohort studies suggested that short stent-graft (SG) length (<165 mm) might correlate with increased risk of distal SINE. However, the influence of SG length on changes in local biomechanical conditions before and after TEVAR is unknown. In this paper, we aim to address this issue using a virtual SG deployment simulation model developed for application in type B aortic dissection. Our model incorporates detailed SG design and hyperelastic behaviour of the aortic wall. By making use of patient-specific geometry reconstructed from pre-TEVAR computed tomography angiography (CTA) scan, our model can predict post-TEVAR SG configuration and wall stress. Virtual SG deployment simulations were performed on a patient who underwent TEVAR with a short SG (158 mm in length), mimicking the actual clinical procedure. Further simulations were carried out on the same patient geometry but with different SG lengths (183 mm and 208 mm) in order to evaluate the effect of SG length on changes in local stress in the treated aorta. Comparisons of simulation results for different SG lengths showed the location of maximum stress varied with the SG length. With the short SG (deployed in the patient), the maximum von Mises stress of 238.9 kPa was found on the intimal flap at the distal landing zone where SINE was identified at 3-month follow-up. Increasing the SG length caused the maximum von Mises stress to move away from the distal landing zone where stress values were reduced by approximately 17% with the medium-length SG and by 60% with the long SG. This pilot study demonstrates the potential of using the virtual SG deployment model as a pre-surgical planning tool to help select the most appropriate SG length for individual patients.

Blood Flow Quantification in Peripheral Arterial Disease: Emerging Diagnostic Techniques in Vascular Surgery

The assessment of local blood flow patterns in patients with peripheral arterial disease is clinically relevant, since these patterns are related to atherosclerotic disease progression and loss of patency in stents placed in peripheral arteries, through mechanisms such as recirculating flow and low wall shear stress (WSS). However, imaging of vascular flow in these patients is technically challenging due to the often complex flow patterns that occur near atherosclerotic lesions. While several flow quantification techniques have been developed that could improve the outcomes of vascular interventions, accurate 2D or 3D blood flow quantification is not yet used in clinical practice. This article provides an overview of several important topics that concern the quantification of blood flow in patients with peripheral arterial disease. The hemodynamic mechanisms involved in the development of atherosclerosis and the current clinical practice in the diagnosis of this disease are discussed, showing the unmet need for improved and validated flow quantification techniques in daily clinical practice. This discussion is followed by a showcase of state-of-the-art blood flow quantification techniques and how these could be used before, during and after treatment of stenotic lesions to improve clinical outcomes. These techniques include novel ultrasound-based methods, Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD). The last section discusses future perspectives, with advanced (hybrid) imaging techniques and artificial intelligence, including the implementation of these techniques in clinical practice.

Blood Flow Quantification in Peripheral Arterial Disease: Emerging Diagnostic Techniques in Vascular Surgery

The assessment of local blood flow patterns in patients with peripheral arterial disease is clinically relevant, since these patterns are related to atherosclerotic disease progression and loss of patency in stents placed in peripheral arteries, through mechanisms such as recirculating flow and low wall shear stress (WSS). However, imaging of vascular flow in these patients is technically challenging due to the often complex flow patterns that occur near atherosclerotic lesions. While several flow quantification techniques have been developed that could improve the outcomes of vascular interventions, accurate 2D or 3D blood flow quantification is not yet used in clinical practice. This article provides an overview of several important topics that concern the quantification of blood flow in patients with peripheral arterial disease. The hemodynamic mechanisms involved in the development of atherosclerosis and the current clinical practice in the diagnosis of this disease are discussed, showing the unmet need for improved and validated flow quantification techniques in daily clinical practice. This discussion is followed by a showcase of state-of-the-art blood flow quantification techniques and how these could be used before, during and after treatment of stenotic lesions to improve clinical outcomes. These techniques include novel ultrasound-based methods, Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD). The last section discusses future perspectives, with advanced (hybrid) imaging techniques and artificial intelligence, including the implementation of these techniques in clinical practice.

Numerical simulation of fenestrated graft deployment: Anticipation of stent graft and vascular structure adequacy

Fenestrated endovascular aneurism repair (FEVAR) is a minimally invasive technique, and its success depends on the adequacy of the correspondence between the visceral arteries ostia and position of the fenestrations of the stent graft (SG) during its deployment in juxtarenal aneurisms. However, the fenestration position is generally determined from a preoperative computerised tomography (CT) scan, without considering the vascular deformation induced by the insertion of the endovascular tools. Catheterisation difficulties may occur during clinical procedures. Accordingly, the objective of this work is to present an initial proof of concept aimed at anticipating and optimising the position of the fenestrations, while considering the vascular deformation induced by the insertion of the endovascular tools. The proposed method relies on the finite element method to simulate the SG deployment in a vascular structure (VS), and considers the vascular deformation induced by the tools. After determining the optimal simulation parameters for a patient-specific case, the robustness of the method is demonstrated on six other representative anatomies. The simulated SG is also compared with post-deployment CT observations, and demonstrates good adequacy. The results show that the numerically corrected fenestration positions, as determined from the simulated results following the insertion of the endovascular tools, deviate from those of the standard plan (as determined from the preoperative CT scan). This indicates that the SG-VS adequacy could be improved via simulation-based planning, to anticipate potential catheterisation difficulties.

Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses

Numerical models of endografts for the simulation of endovascular aneurysm repair are increasingly important in the improvement of device designs and patient outcomes. Nevertheless, current finite element analysis (FEA) models of complete endograft devices come at a high computational cost, requiring days of runtime, therefore restricting their applicability. In the current study, an efficient FEA model of the Anaconda™ endograft (Terumo Aortic, UK) was developed, able to yield results in just over 4 h, an order of magnitude less than similar models found in the literature. The model was used to replicate a physical device that was deployed in a 3D printed aorta and comparison of the two shapes illustrated a less than 5 mm placement error of the model in the regions of interest, consistent with other more computationally intensive models in the literature. Furthermore, the final goal of the study was to utilize the deployed fabric model in a hemodynamic analysis that would incorporate realistic fabric folds, a feature that is almost always omitted in similar simulations. By successfully exporting the deployed graft geometry into a flow analysis, it was illustrated that the inclusion of fabric wrinkles enabled clinically significant flow patterns such as flow stagnation and recirculation to be detected, paving the way for this modelling methodology to be used in future for stent design optimisation.

Method to simulate distal flow resistance in coronary arteries in 3D printed patient specific coronary models

BACKGROUND

Three-dimensional printing (3DP) offers a unique opportunity to build flexible vascular patient-specific coronary models for device testing, treatment planning, and physiological simulations. By optimizing the 3DP design to replicate the geometrical and mechanical properties of healthy and diseased arteries, we may improve the relevance of using such models to simulate the hemodynamics of coronary disease. We developed a method to build 3DP patient specific coronary phantoms, which maintain a significant part of the coronary tree, while preserving geometrical accuracy of the atherosclerotic plaques and allows for an adjustable hydraulic resistance.

METHODS

Coronary computed tomography angiography (CCTA) data was used within Vitrea (Vital Images, Minnetonka, MN) cardiac analysis application for automatic segmentation of the aortic root, Left Anterior Descending (LAD), Left Circumflex (LCX), Right Coronary Artery (RCA), and calcifications. Stereolithographic (STL) files of the vasculature and calcium were imported into Autodesk Meshmixer for 3D model optimization. A base with three chambers was built and interfaced with the phantom to allow fluid collection and independent distal resistance adjustment of the RCA, LAD and LCX and branching arteries. For the 3DP we used Agilus for the arterial wall, VeroClear for the base and a Vero blend for the calcifications, respectively. Each chamber outlet allowed interface with catheters of varying lengths and diameters for simulation of hydraulic resistance of both normal and hyperemic coronary flow conditions. To demonstrate the manufacturing approach appropriateness, models were tested in flow experiments.

RESULTS

Models were used successfully in flow experiments to simulate normal and hyperemic flow conditions. The inherent mean resistance of the chamber for the LAD, LCX, and RCA, were 1671, 1820, and 591 (dynes ∙ sec/ cm5), respectively. This was negligible when compared with estimates in humans, with the chamber resistance equating to 0.65-5.86%, 1.23-6.86%, and 0.05-1.67% of the coronary resistance for the LAD, LCX, and RCA, respectively at varying flow rates and activity states. Therefore, the chamber served as a means to simulate the compliance of the distal coronary trees and to allow facile coupling with a set of known resistance catheters to simulate various physical activity levels.

CONCLUSIONS

We have developed a method to create complex 3D printed patient specific coronary models derived from CCTA, which allow adjustable distal capillary bed resistances. This manufacturing approach permits comprehensive coronary model development which may be used for physiologically relevant flow simulations.

Numerical modeling and simulations of type B aortic dissection treated by stent-grafts with different oversizing ratios

Retrograde type A dissection after thoracic endovascular aortic repair has been a major drawback of endovascular treatment. This study investigated the biomechanical mechanism of stent-graft-induced new lesions after implantation and analyzed the relationship between radial force and spring-back force of the stent-graft when it was implanted virtually under different oversizing ratios. Based on the computed tomography angiography images, a three-dimensional geometric model of a patient-specific aortic dissection was established. The stent was designed in CAD software and the stent-graft implantation procedure under different oversizing ratios was simulated in the finite element analysis software. Implantation simulations were performed six times for each stent-graft model under 0%, 3%, 6%, 9%, 12%, and 15% oversizing ratios and the peak stress of the aorta was compared among groups. It was observed that the peak stress of the aorta was located where the proximal bare stent interacted with aortic wall and its value was increased by 62.2% from 0% to 15% oversizing ratio. The conclusions are reached that the long-term higher stress in the aortic wall may lead to the emergence of new lesions in these areas, and the radial force plays a key role in the formation of a new entry in the real aorta model.

Numerical study on the effect of stent shape on suture forces in stent-grafts

Second-generation stent-grafts (SGs) have addressed many of the mechanical problems reported for first-generation endoprostheses, such as graft tear and stent rupture; however, suture wear and detachment due to pulsatile fatigue remains an issue. Numerical studies on the mechanical behavior of these endoprostheses usually model the attachment between stents and graft as a continuous ''tie'' constraint, which does not provide information on the mechanical loads acting on individual sutures. This paper presents a suitable approach for Finite Element (FE) simulations of SGs which allows for a qualitative evaluation of the loads acting on sutures. Attachment between stents and graft is modeled as rigid beams at discrete locations of the endoprostheses, and the reaction forces on the beams are analyzed. This modeling strategy is employed for four different SG models (two Z-stented commercial models and two circular-stented models) subjected to a severe 180° U-bend, followed by intraluminal pressurization. Results show that, for all models, the majority of sutures is experiencing fluctuating forces within a cardiac cycle (between 80 and 120 mmHg), which points to pulsatile fatigue as potential failure mode. In addition, the highest loads are concentrated in kinks and, for Z-stented models, at the apexes of stents. Moreover, suture loads for circular-stented models are lower than for Z-stented models, indicating better resistance to suture detachment. All these observations are in line with experimental results published in the literature, and, therefore, the procedure herein proposed may serve as a valuable tool in the development of new SG models with better suture resistance to pulsatile wear and fatigue.

Computational analysis of Nitinol stent-graft for endovascular aortic repair (EVAR) of abdominal aortic aneurysm (AAA): Crimping, sealing and fluid-structure interaction (FSI)

OBJECTIVES

We evaluate the crimping strain, sealing stress and contact forces on a Nitinol stent deployed in the aorta during endovascular aortic (or aneurysm) repair (EVAR) procedures. Nitinol shape memory effect (SME) is used. We also study the fluid-structure interaction (FSI) of the blood flow on the stented aorta.

METHODS

We employ Solidworks to generate a closed-cell honeycomb stent structure used to treat abdominal aortic aneurysm (AAA). We use the commercial Abaqus/Simulia finite element (FEM) simulation package to study the displacements and stresses experienced by the stent during the crimping phase and deployment into the aortic segment. The Nitinol stent is covered with Dacron, a popular graft material. We implement our own user-material (UMAT) subroutines to model the shape memory effect (SME) of Nitinol. The effect of the stent geometry is analyzed. We use the FSI analysis in Abaqus/Simulia to understand the effect of hemodynamic loading on the stent.

RESULTS

Results indicate that the crimping strain increases as the stent strut spacing increases. This is also the case for the radius of curvature. Maximum strains developed on the stent during crimping are in the order of 10%. Stresses exerted by the stent needed to completely seal the aorta are found to be below the yield stress values of Nitinol (700 MPa). Wall shear stresses (WSS) on the stented aorta are close to WSS obtained on the aorta alone.

CONCLUSION

Using Nitinol's thermo-reactivity property as opposed to its superelasticity causes the stent-graft to deploy more gently.

Customized stent-grafts for endovascular aneurysm repair with challenging necks: A numerical proof of concept

Endovascular aortic repair (EVAR) is a challenging intervention whose long-term success strongly depends on the appropriate stent-graft (SG) selection and sizing. Most off-the-shelf SGs are straight and cylindrical. Especially in challenging vessel morphologies, the morphology of off-the-shelf SGs is not able to meet the patient-specific demands. Advanced manufacturing technologies facilitate the development of highly customized SGs. Customized SGs that have the same morphology as the luminal vessel surface could considerably improve the quality of the EVAR outcome with reduced likelihoods of EVAR related complications such as endoleaks type I and SG migration. In this contribution, we use an in silico EVAR methodology that approximates the deployed state of the elastically deformable SG in a hyperelastic, anisotropic vessel. The in silico EVAR results of off-the-shelf SGs and customized SGs are compared qualitatively and quantitatively in terms of mechanical and geometrical parameters such as stent stresses, contact tractions, SG fixation forces and the SG-vessel attachment. In a numerical proof of concept, eight different vessel morphologies, such as a conical vessel, a barrel shaped vessel and a curved vessel, are used to demonstrate the added value of customized SGs compared to off-the-shelf SGs. The numerical investigation has shown large benefits of the highly customized SGs compared to off-the-shelf SGs with respect to a better SG-vessel attachment and a considerable increase in SG fixation forces of up to 50% which indicate decreased likelihoods of EVAR related complications. Hence, this numerical proof of concept motivates further research and development of highly customized SGs for the use in challenging vessel morphologies.

Artificial intelligence in abdominal aortic aneurysm

OBJECTIVE

Abdominal aortic aneurysm (AAA) is a life-threatening disease, and the only curative treatment relies on open or endovascular repair. The decision to treat relies on the evaluation of the risk of AAA growth and rupture, which can be difficult to assess in practice. Artificial intelligence (AI) has revealed new insights into the management of cardiovascular diseases, but its application in AAA has so far been poorly described. The aim of this review was to summarize the current knowledge on the potential applications of AI in patients with AAA.

METHODS

A comprehensive literature review was performed. The MEDLINE database was searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search strategy used a combination of keywords and included studies using AI in patients with AAA published between May 2019 and January 2000. Two authors independently screened titles and abstracts and performed data extraction. The search of published literature identified 34 studies with distinct methodologies, aims, and study designs.

RESULTS

AI was used in patients with AAA to improve image segmentation and for quantitative analysis and characterization of AAA morphology, geometry, and fluid dynamics. AI allowed computation of large data sets to identify patterns that may be predictive of AAA growth and rupture. Several predictive and prognostic programs were also developed to assess patients' postoperative outcomes, including mortality and complications after endovascular aneurysm repair.

CONCLUSIONS

AI represents a useful tool in the interpretation and analysis of AAA imaging by enabling automatic quantitative measurements and morphologic characterization. It could be used to help surgeons in preoperative planning. AI-driven data management may lead to the development of computational programs for the prediction of AAA evolution and risk of rupture as well as postoperative outcomes. AI could also be used to better evaluate the indications and types of surgical treatment and to plan the postoperative follow-up. AI represents an attractive tool for decision-making and may facilitate development of personalized therapeutic approaches for patients with AAA.

Patient Specific Computer Modelling for Automated Sizing of Fenestrated Stent Grafts

OBJECTIVE

The aim was to validate a computational patient specific model of Zenith® fenestrated device deployment in abdominal aortic aneurysms to predict fenestration positions.

METHODS

This was a retrospective analysis of the accuracy of numerical simulation for fenestrated stent graft sizing. Finite element computational simulation was performed in 51 consecutive patients that underwent successful endovascular repair with Zenith® fenestrated stent grafts in two vascular surgery units with a high volume of aortic procedures. Longitudinal and rotational clock positions of fenestrations were measured on the simulated models. These measurements were compared with those obtained by (i) an independent observer on the post-operative computed tomography (CT) scan and (ii) by the stent graft manufacturer planning team on the pre-operative CT scan. (iii) Pre- and post-operative positions were also compared. Longitudinal distance and clock face discrepancies >3 mm and 15°, respectively, were considered significant. Reproducibility was assessed using Bland-Altman and linear regression analysis.

RESULTS

A total of 195 target arteries were analysed. Both Bland-Altman and linear regression showed good reproducibility between the three measurement techniques performed. The median absolute difference between the simulation and post-operative CT scan was 1.0 ± 1.1 mm for longitudinal distance measurements and 6.9 ± 6.1° for clock positions. The median absolute difference between the planning centre and post-operative CT scan was 0.8 ± 0.8 mm for longitudinal distance measurements and 5.1 ± 5.0° for clock positions. Finally, the median absolute difference between the simulation and the planning centre was 0.96 ± 0.97 mm for longitudinal distance measurements and 4.8 ± 3.6° for clock positions.

CONCLUSION

The numerical model of deployed fenestrated stent grafts is accurate for planning position of fenestrations. It has been validated in 51 patients, for whom fenestration locations were similar to the sizing performed by physicians and the planning centre.

Use of Numerical Simulation to Predict Iliac Complications During Placement of An Aortic Stent Graft

BACKGROUND

During endovascular aneurysm repair (EVAR), complex iliac anatomy is a source of complications such as unintentional coverage of the hypogastric artery. The aim of our study was to evaluate ability to predict coverage of the hypogastric artery using a biomechanical model simulating arterial deformations caused by the delivery system.

METHODS

The biomechanical model of deformation has been validated by many publications. The simulations were performed on 38 patients included retrospectively, for a total of 75 iliac arteries used for the study. On the basis of objective measurements, two groups were formed: one with "complex" iliac anatomy (n = 38 iliac arteries) and the other with "simple" iliac anatomy (n = 37 iliac arteries). The simulation enabled measurement of the lengths of the aorta and the iliac arteries once deformed by the device. Coverage of the hypogastric artery was predicted if the deformed renal/iliac bifurcation length (L_pre) was less than the length of the implanted device (L_stent-measured on the postoperative computed tomography [CT]) and nondeformed L_pre was greater than L_stent.

RESULTS

Nine (12%) internal iliac arteries were covered unintentionally. Of the coverage attributed to perioperative deformations, 1 case (1.3%) occurred with simple anatomy and 6 (8.0%) with complex anatomy (P = 0.25). All cases of unintentional coverage were predicted by the simulation. The simulation predicted hypogastric coverage in 35 cases (46.7%). There were therefore 26 (34.6%) false positives. The simulation had a sensitivity of 100% and a specificity of 60.6%. On multivariate analysis, the factors significantly predictive of coverage were the iliac tortuosity index (P = 0.02) and the predicted margin between the termination of the graft limb and the origin of the hypogastric artery in nondeformed (P = 0.009) and deformed (P = 0.001) anatomy.

CONCLUSIONS

Numerical simulation is a sensitive tool for predicting the risk of hypogastric coverage during EVAR and allows more precise preoperative sizing. Its specificity is liable to be improved by using a larger cohort.

Evaluation of a New Approach for Modeling Full Ring Stent Bundles with the Inclusion of Manufacturing Strains

Ring stent bundles have been used in several biomedical stent-graft devices for decades, yet in the published literature, the numerical models of these structures always present significant simplifications. In this paper, a finite element (FE) ring stent bundle has been developed and evaluated with a combination of beam and surface elements. With this approach, the shape, the global stiffness and the strains of the structure can all be well predicted at a low computational cost while the approach is suitable for application to non-symmetrical, patient-specific implant simulations. The model has been validated against analytical and experimental data showing that the manufacturing strains can be predicted to a 0.1% accuracy and the structural stiffness with 0–7% precision. The model has also been compared with a more computationally expensive FE model of higher fidelity, revealing a discrepancy of 0–5% of the strain value. Finally, it has been shown that the exclusion of the manufacturing process from the simulation, a technique used in the literature, quadruples the analysis error. This is the first model that can capture the mechanical state of a full ring stent bundle, suitable for complex implant geometry simulations, with such accuracy.

Co-localization of microstructural damage and excessive mechanical strain at aortic branches in angiotensin-II-infused mice

Animal models of aortic aneurysm and dissection can enhance our limited understanding of the etiology of these lethal conditions particularly because early-stage longitudinal data are scant in humans. Yet, the pathogenesis of often-studied mouse models and the potential contribution of aortic biomechanics therein remain elusive. In this work, we combined micro-CT and synchrotron-based imaging with computational biomechanics to estimate in vivo aortic strains in the abdominal aorta of angiotensin-II-infused ApoE-deficient mice, which were compared with mouse-specific aortic microstructural damage inferred from histopathology. Targeted histology showed that the 3D distribution of micro-CT contrast agent that had been injected in vivo co-localized with precursor vascular damage in the aortic wall at 3 days of hypertension, with damage predominantly near the ostia of the celiac and superior mesenteric arteries. Computations similarly revealed higher mechanical strain in branching relative to non-branching regions, thus resulting in a positive correlation between high strain and vascular damage in branching segments that included the celiac, superior mesenteric, and right renal arteries. These results suggest a mechanically driven initiation of damage at these locations, which was supported by 3D synchrotron imaging of load-induced ex vivo delaminations of angiotensin-II-infused suprarenal abdominal aortas. That is, the major intramural delamination plane in the ex vivo tested aortas was also near side branches and specifically around the celiac artery. Our findings thus support the hypothesis of an early mechanically mediated formation of microstructural defects at aortic branching sites that subsequently propagate into a macroscopic medial tear, giving rise to aortic dissection in angiotensin-II-infused mice.

Patient-specific in silico endovascular repair of abdominal aortic aneurysms: application and validation

Non-negligible postinterventional complication rates after endovascular aneurysm repair (EVAR) leave room for further improvements. Since the potential success of EVAR depends on various patient-specific factors, such as the complexity of the vessel geometry and the physiological state of the vessel, in silico models can be a valuable tool in the preinterventional planning phase. A suitable in silico EVAR methodology applied to patient-specific cases can be used to predict stent-graft (SG)-related complications, such as SG migration, endoleaks or tissue remodeling-induced aortic neck dilatation and to improve the selection and sizing process of SGs. In this contribution, we apply an in silico EVAR methodology that predicts the final state of the deployed SG after intervention to three clinical cases. A novel qualitative and quantitative validation methodology, that is based on a comparison between in silico results and postinterventional CT data, is presented. The validation methodology compares average stent diameters pseudo-continuously along the total length of the deployed SG. The validation of the in silico results shows very good agreement proving the potential of using in silico approaches in the preinterventional planning of EVAR. We consider models of bifurcated, marketed SGs as well as sophisticated models of patient-specific vessels that include intraluminal thrombus, calcifications and an anisotropic model for the vessel wall. We exemplarily show the additional benefit and applicability of in silico EVAR approaches to clinical cases by evaluating mechanical quantities with the potential to assess the quality of SG fixation and sealing such as contact tractions between SG and vessel as well as SG-induced tissue overstresses.

Predictive Numerical Simulations of Double Branch Stent-Graft Deployment in an Aortic Arch Aneurysm

Total endovascular repair of the aortic arch represents a promising option for patients ineligible to open surgery. Custom-made design of stent-grafts (SG), such as the Terumo Aortic^® RelayBranch device (DB), requires complex preoperative measures. Accurate SG deployment is required to avoid intraoperative or postoperative complications, which is extremely challenging in the aortic arch. In that context, our aim is to develop a computational tool able to predict SG deployment in such highly complex situations. A patient-specific case is performed with complete deployment of the DB and its bridging stents in an aneurysmal aortic arch. Deviations of our simulation predictions from actual stent positions are estimated based on post-operative scan and a sensitivity analysis is performed to assess the effects of material parameters. Results show a very good agreement between simulations and post-operative scan, with especially a torsion effect, which is successfully reproduced by our simulation. Relative diameter, transverse and longitudinal deviations are of 3.2 ± 4.0%, 2.6 ± 2.9 mm and 5.2 ± 3.5 mm respectively. Our numerical simulations show their ability to successfully predict the DB deployment in complex anatomy. The results emphasize the potential of computational simulations to assist practitioners in planning and performing complex and secure interventions.

Predicting Rotation in Fenestrated Endovascular Aneurysm Repair Using Finite Element Analysis

Fenestrated endovascular aneurysm repair (FEVAR) is a minimally invasive method of abdominal aortic aneurysm (AAA) repair utilized in patients with complex vessel anatomies. Stent grafts (SG) used in this process contain fenestrations within the device that need to be aligned with the visceral arteries upon successful SG deployment. Proper alignment is crucial to maintain blood flow to these arteries and avoid surgical complications. During fenestrated SG deployment, rotation of the SG can occur during the unsheathing process. This leads to misalignment of the vessels, and the fenestrations and is associated with poor clinical outcomes. The aim of this study was to develop a computational model of the FEVAR process to predict SG rotation. Six patient-specific cases are presented and compared with surgical case data. Realistic material properties, frictional effects, deployment methods, and boundary conditions are included in the model. A mean simulation error of 2 deg (range 1–4 deg) was observed. This model was then used to conduct a parameter study of frictional properties to see if rotation could be minimized. This study showed that increasing or decreasing the coefficients of friction (COF) between the sheath and the vessel walls would decrease the amount of rotation observed. Our model accurately predicts the amount of SG rotation observed during FEVAR and can be used as a preoperative planning tool within the surgical workflow.

A methodology for in silico endovascular repair of abdominal aortic aneurysms

Endovascular aneurysm repair (EVAR) can involve some unfavorable complications such as endoleaks or stent-graft (SG) migration. Such complications, resulting from the complex mechanical interaction of vascular tissue, SG and blood flow or incompatibility of SG design and vessel geometry, are difficult to predict. Computational vascular mechanics models can be a predictive tool for the selection, sizing and placement process of SGs depending on the patient-specific vessel geometry and hence reduce the risk of potential complications after EVAR. In this contribution, we present a new in silico EVAR methodology to predict the final state of the deployed SG after intervention and evaluate the mechanical state of vessel and SG, such as contact forces and wall stresses. A novel method to account for residual strains and stresses in SGs, resulting from the precompression of stents during the assembly process of SGs, is presented. We suggest a parameter continuation approach to model various different sizes of SGs within one in silico EVAR simulation which can be a valuable tool when investigating the issue of SG oversizing. The applicability and robustness of the proposed methods are demonstrated on the example of a synthetic abdominal aortic aneurysm geometry.

Patient-specific 3D printing simulation to guide complex coronary intervention

The field of three-dimensional printing applied to patient-specific simulation is evolving as a tool to enhance intervention results. We report the first case of a fully simulated percutaneous coronary intervention in a three-dimensional patient-specific model to guide treatment. An 85-year-old female presented with symptomatic in-stent restenosis in the ostial circumflex and was scheduled for percutaneous coronary intervention. Considering the complexity of the anatomy, patient setting and intervention technique, we elected to replicate the coronary anatomy using a three-dimensional model. In this way, we simulated the intervention procedure beforehand in the catheterization laboratory using standard materials. The procedure was guided by optical coherence tomography, with pre-dilatation of the lesion, implantation of a single drug-eluting stent in the ostial circumflex and kissing balloon inflation to the left anterior descending artery and circumflex. Procedural steps were replicated in the real patient's treatment, with remarkable parallelism in angiographic outcome and luminal gain at intracoronary imaging. In this proof-of-concept report, we show that patient-specific simulation is feasible to guide the treatment strategy of complex coronary artery disease. It enables the surgical team to plan and practice the procedure beforehand, and possibly predict complications and gain confidence.

3D Printed Abdominal Aortic Aneurysm Phantom for Image Guided Surgical Planning with a Patient Specific Fenestrated Endovascular Graft System

Following new trends in precision medicine, Juxatarenal Abdominal Aortic Aneurysm (JAAA) treatment has been enabled by using patient-specific fenestrated endovascular grafts. The X-ray guided procedure requires precise orientation of multiple modular endografts within the arteries confirmed via radiopaque markers. Patient-specific 3D printed phantoms could familiarize physicians with complex procedures and new devices in a risk-free simulation environment to avoid periprocedural complications and improve training. Using the Vascular Modeling Toolkit (VMTK), 3D Data from a CTA imaging of a patient scheduled for Fenestrated EndoVascular Aortic Repair (FEVAR) was segmented to isolate the aortic lumen, thrombus, and calcifications. A stereolithographic mesh (STL) was generated and then modified in Autodesk MeshMixer for fabrication via a Stratasys Eden 260 printer in a flexible photopolymer to simulate arterial compliance. Fluoroscopic guided simulation of the patient-specific FEVAR procedure was performed by interventionists using all demonstration endografts and accessory devices. Analysis compared treatment strategy between the planned procedure, the simulation procedure, and the patient procedure using a derived scoring scheme.

RESULTS

With training on the patient-specific 3D printed AAA phantom, the clinical team optimized their procedural strategy. Anatomical landmarks and all devices were visible under x-ray during the simulation mimicking the clinical environment. The actual patient procedure went without complications.

CONCLUSIONS

With advances in 3D printing, fabrication of patient specific AAA phantoms is possible. Simulation with 3D printed phantoms shows potential to inform clinical interventional procedures in addition to CTA diagnostic imaging.