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

Aortic arch anatomical differences in male type B aortic dissection patients vs. healthy male individuals

BACKGROUND

Understanding the distinct anatomical differences between patients with type B aortic dissection (TBAD) and control patients (CPs) can enhance our knowledge of normal and pathological aortic dimensions. This study aimed to deepen our knowledge of these dimensions by measuring and comparing the anatomical indices of the aortic arch in male patients with TBAD and non-TBAD male patients.

METHODS

In this cross-sectional observational study, 62 TBAD patients (TBADPs) and 43 CPs were assessed. Using a fit centerline approach, we identified three pivotal anatomical landmarks: Point A, Point B, and Point C. These landmarks represented intersections of the aortic arch with the brachiocephalic trunk, left common carotid artery, and left subclavian artery, respectively. These points defined Zones 1, 2, and 3, which collectively span the entire proximal aorta from the proximal end of the aortic valve to Point C. Our analyses compared key anatomical indices such as diameter of the circumscribed circle (Dcirc), ellipticity, curvature, tortuosity between TBADP and CP at critical points and regions.

RESULTS

TBADPs showed a more circular cross-sectional shape at Points A, B and C, as indicated by reduced values of Dcirc_A (P = 0.031), ellipticity_A (P = 0.034) and ellipticity_B (P = 0.048), together with a significant decrease in Dcirc_C (P = 0.015) and ellipticity_C (P = 0.007). The aortic arch in TBADPs showed enhanced tortuosity in Zone 1 (p = 0.002) and extended elongation in Zone 3 (p = 0.001).

CONCLUSIONS

The study found that the aortic arch in male TBAD patients is more circular near its primary branches, has greater tortuosity in Zone 1, and is longer in Zone 3 compared to male control patients.

Stent Graft-Induced High Wall Stress Promoted Aortic Wall Failure and Aortic Wall Injurious Complications After TEVAR: A Study of Numerical Simulation and Bioinformatics Analysis Based on Pig Models

OBJECTIVES

Stent graft-related aortic injury is a major complication after thoracic endovascular aortic repair (TEVAR) and seriously affects patient prognosis. However, the distribution characteristics of aortic wall stress under the action of stent grafts and the mechanism of abnormal wall stress leading to aortic wall injury and adverse remodeling were unclear. The aim of this study was to explore the potential mechanisms of high wall stress on the structural and functional alterations of the aortic wall by combining animal experiments, numerical simulations, and bioinformatics.

METHODS

We observed stent graft-induced aortic injury by performing fenestrated TEVAR in 6 pigs, and quantitatively analyzed and visualized the stress distribution of the aortic wall under the stent graft through numerical simulation. Hematoxylin and eosin (HE) staining, Masson's trichrome staining, Verhoeff's Van Gieson (EVG) staining, and immunostaining were used to evaluate pathological changes in the aorta. Based on the numerical simulation results, the corresponding high-stress and low-stress regions of the aortic wall were subjected to bulk-RNA sequencing, and hub genes were identified by bioinformatics analysis.

RESULTS

Stent grafts were successfully implanted in 5 pigs. In all computational models, we found that obvious deformation and characteristic maximum stress concentration occurred on the side of the greater curve of the aortic arch in contact with the stent graft tip, and the high wall stress concentration areas were highly consistent with the obvious pathological injury area. Subsequent pathological analysis revealed that high wall stress-induced confusion and fragmentation of elastic fibers, collagen deposition, loss and phenotypic switching of vascular smooth muscle cells, and increased inflammatory responses. Gene expression profiles of the aortic wall under different wall stress conditions were described for the first time, and the hub genes (TGFB1, CDH5, DCN, ITGA5, ITGB3, and WT1) that may be involved in regulating the aortic injury and remodeling process in response to high wall stress stimulation were identified.

CONCLUSIONS

This study revealed a panoramic view of stent graft-associated high wall stress-induced aortic wall injury through technical approaches of multiple dimensions. Understanding these biomechanical features and hub genes is pivotal for advancing our comprehension of the complications associated with aortic injury after TEVAR and facilitating the development of future therapeutic interventions.

CLINICAL IMPACT

This study revealed a panoramic view of stent graft-associated high wall stress-induced aortic wall injury through technical approaches of multiple dimensions. The biomechanical distribution characteristics of the aortic wall, the secondary pathological injury and the alteration of gene expression profile under the action of stent graft were comprehensively revealed by animal experiments for the first time. This will advance clinicians' comprehension of complications associated with aortic injury after TEVAR, provide a new biomechanical perspective for the rational preoperative planning of TEVAR and the management of postoperative complications, and facilitate the development of future therapeutic interventions and stent graft device designs.

Discussing on the Aortic Coverage in Type B Aortic Dissection Treatment: A Comprehensive Scoping Review

OBJECTIVE

The objective of this study is to investigate and address the question surrounding the determination of the optimal endograft length of coverage during TEVAR for type B aortic dissection (TBAD), with a particular emphasis on the distal landing zone (DLZ).

DATA SOURCES

MEDLINE, Scopus, and Web of Science databases were used.

METHODS

The PRISMA-ScR statement was followed.

RESULTS

Several variables can contribute to the length of coverage during TEVAR in TBAD patient. Baseline patient's characteristics, TBAD-related features, the type of endoprosthesis, and postoperative graft behaviour may contribute to the choice of coverage.

CONCLUSIONS

No robust data have been published regarding the optimal length of TEVAR. Therefore, reporting the percentage of covered aorta and improving computational studies should be valorised to improve postoperative outcomes.

On the necessity to include arterial pre-stress in patient-specific simulations of minimally invasive procedures

Transcatheter aortic valve implantation (TAVI) and thoracic endovascular aortic repair (TEVAR) are minimally invasive procedures for treating aortic valves and diseases. Finite element simulations have proven to be valuable tools in predicting device-related complications. In the literature, the inclusion of aortic pre-stress has not been widely investigated. It plays a crucial role in determining the biomechanical response of the vessel and the device-tissue interaction. This study aims at demonstrating how and when to include the aortic pre-stress in patient-specific TAVI and TEVAR simulations. A percutaneous aortic valve and a stent-graft were implanted in aortic models reconstructed from patient-specific CT scans. Two scenarios for each patient were compared, i.e., including and neglecting the wall pre-stress. The neglection of pre-stress underestimates the contact pressure of 48% and 55%, the aorta stresses of 162% and 157%, the aorta strains of 77% and 21% for TAVI and TEVAR models, respectively. The stent stresses are higher than 48% with the pre-stressed aorta in TAVI simulations; while, similar results are obtained in TEVAR cases. The distance between the device and the aorta is similar with and without pre-stress. The inclusion of the aortic wall pre-stress has the capability to give a better representation of the biomechanical behavior of the arterial tissues and the implanted device. It is suggested to include this effect in patient-specific simulations replicating the procedures.

Investigating the Role of Thrombosis, Fenestration, and False Lumen Orbital Orientation in the Hemodynamics of Type B Aortic Dissection

While much about the fundamental mechanisms behind the initiation and progression of Type B aortic dissection (TBAD) is still unknown, predictive models based on patient-specific computational fluid dynamics (CFD) can help in risk stratification and optimal clinical decision-making. Aiming at the development of personalized treatment, CFD simulations can be leveraged to investigate the interplay between complex aortic flow patterns and anatomical features. In this study, the hemodynamics of false lumen thrombosis, a large fenestration, and the orbital orientation of the false lumen is studied through image-based CFD simulations on three TBAD patient-specific geometries. A new pipeline was developed leveraging the open-source software SimVascular and Paraview to analyze multiple patients simultaneously and to achieve large-scale parallelization in CFD results based on patients' computed tomography (CT) images. The results of this study suggest that the internal orbital orientation of the false lumen contributes to maintaining a positive luminal pressure difference Δ P T L - F L = P T L - P F L between the true lumen (TL) and the false lumen (FL), despite an impingement area in the false lumen near the entry tear. A positive and high luminal pressure difference is thought to promote TL expansion and FL compression. Moreover, it was also found that both FL thrombosis at the entry tear region, and the presence of a large fenestration in the descending thoracic aorta reduce the magnitude of the negative luminal pressure difference, which in turn may reduce FL expansion and the risk of unstable aortic growth.

Towards biomechanics-based pre-procedural planning for thoracic endovascular aortic repair of aortic dissection

BACKGROUND AND OBJECTIVE

Although thoracic aortic endovascular repair (TEVAR) has shown promising outcomes in the treatment of patients with complicated type B aortic dissection, complications still occur after TEVAR that can lead to catastrophic events. Biomechanical interactions between the stent-graft (SG) and the local aortic tissue play a critical role in determining the outcome of TEVAR. Different SG design may cause different biomechanical responses in the treated aorta, but such information is not known at the time of pre-procedural planning. By developing patient-specific virtual stent-graft deployment tools, it is possible to analyse and compare the biomechanical impact of different SGs on the local aorta for individual patients.

METHODS

A finite element based virtual SG deployment model was employed in this study. Computational simulations were performed on a patient-specific model of type B aortic dissection, accounting for details of the SG design and the hyperelastic behaviour of the aortic wall. Based on the geometry reconstructed from the pre-TEVAR CTA scan, the patient-specific aortic dissection model was created and pre-stressed. Parametric models of three different SG products (SG1, SG2 and SG3) were built with two different lengths for each design. The SG models incorporated different stent and graft materials, stent strut patterns, and assembly approaches. Using our validated SG deployment simulation framework, virtual trials were performed on the patient-specific aortic dissection model using different SG products and varying SG lengths.

CONCLUSION

Simulation results for different SG products suggest that SG3 with a longer length (SG3-long) would be the most appropriate device for the individual patient. Compared to SG1-short (the SG deployed in the patient), SG3-long followed the true lumen tortuosity closely, resulted in a more uniform true lumen expansion and a significant reduction in peak stress in the distal landing zone. These simulation results are promising and demonstrate the feasibility of using the virtual SG deployment model to assist clinicians in pre-procedural planning.

Irregular anatomical features can alter hemodynamics in Takayasu arteritis

Objective

Takayasu arteritis (TA) is a difficult disease to deal with because there are neither reliable clinical signs, laboratory biomarkers, nor a single noninvasive imaging technique that can be used for early diagnosis and disease activity monitoring. Knowledge of aortic hemodynamics in TA is lacking. This study aimed to fill this gap by assessing hemodynamics in patients with TA using image-based computational fluid dynamics (CFD) simulations.

Methods

Eleven patients with TA were included in the present study. Patient-specific geometries were reconstructed from either clinical aortic computed tomography angiography or magnetic resonance angiography studies and coupled with physiological boundary conditions for CFD simulations. Key anatomical and hemodynamic parameters were compared with a control group consisting of 18 age- and sex-matched adults without TA who had healthy aortas.

Results

Compared with controls, patients with TA had significantly higher aortic velocities (0.9 m/s [0.7, 1.1 m/s] vs 0.6 m/s [0.5, 0.7 m/s]; P = .002), maximum time-averaged wall shear stress (14.2 Pa [9.8, 20.9 Pa] vs 8.0 Pa [6.2, 10.3 Pa]; P = .004), and maximum pressure drops between the ascending and descending aorta (36.9 mm Hg [29.0, 49.3 mm Hg] vs 28.5 mm Hg [25.8, 31.5 mm Hg]; P = .004). These significant hemodynamic alterations in patients with TA might result from abnormal anatomical features including smaller arch diameter (20.0 mm [13.8, 23.3 mm] vs 25.2 mm [23.3, 26.8 mm]; P = .003), supra-aortic branch diameters (21.9 mm [18.5, 24.6 mm] vs 25.7 mm [24.3, 28.3 mm]; P = .003) and descending aorta diameter (14.7 mm [12.2, 16.8 mm] vs 22.5 mm [19.8, 24.0 mm]; P < .001).

Conclusions

CFD analysis reveals hemodynamic changes in the aorta of patients with TA. The applicability of CFD technique coupled with standard imaging assessments in predicting disease progression of such patients will be explored in future studies. Future large cohort study with outcome correlation is also warranted.

Clinical Relevance

Based on patient-specific computational fluid dynamics simulations, the present retrospective study revealed significant difference in aortic hemodynamics between the patients with and without Takayasu arteritis (TA). To the best of our knowledge, this study is the first to evaluate hemodynamic conditions within TA, demonstrating the potential of computational flow modeling in capturing abnormal hemodynamic forces, such as high wall shear stress, resulted from irregular morphological changes. In the future, assessing the hemodynamic parameters within patients with TA during the prestenotic period, together with longitudinal computational fluid dynamics studies may allow better monitoring and management of TA.

Hemodynamic parameters impact the stability of distal stent graft-induced new entry

Stent graft-induced new entry tear (SINE) is a serious complication in aortic dissection patients caused by the stent-graft itself after thoracic endovascular aortic repair (TEVAR). The stability of SINE is a key indicator for the need and timing of reinterventions. This study aimed to understand the role of hemodynamics in SINE stability by means of computational fluid dynamics (CFD) analysis based on patient-specific anatomical information. Four patients treated with TEVAR who developed a distal SINE (dSINE) were included; two patients had a stable dSINE and two patients experienced expansion of the dSINE upon follow-up examinations. CFD simulations were performed on geometries reconstructed from computed tomography scans acquired upon early detection of dSINE in these patients. Computational results showed that stable dSINEs presented larger regions with low time-averaged wall shear stress (TAWSS) and high relative residence time (RRT), and partial thrombosis was observed at subsequent follow-ups. Furthermore, significant systolic antegrade flow was observed in the unstable dSINE which also had a larger retrograde flow fraction (RFF) on the SINE plane. In conclusion, this pilot study suggested that high RRT and low TAWSS may indicate stable dSINE by promoting thrombosis, whereas larger RFF and antegrade flows inside dSINE might be associated with its expansion.

Aortic haemodynamics and wall stress analysis following arch aneurysm repair using a single-branched endograft

Introduction

Thoracic endovascular aortic repair (TEVAR) of the arch is challenging given its complex geometry and the involvement of supra-aortic arteries. Different branched endografts have been designed for use in this region, but their haemodynamic performance and the risk for post-intervention complications are not yet clear. This study aims to examine aortic haemodynamics and biomechanical conditions following TVAR treatment of an aortic arch aneurysm with a two-component single-branched endograft.

Methods

Computational fluid dynamics and finite element analysis were applied to a patient-specific case at different stages: pre-intervention, post-intervention and follow-up. Physiologically accurate boundary conditions were used based on available clinical information.

Results

Computational results obtained from the post-intervention model confirmed technical success of the procedure in restoring normal flow to the arch. Simulations of the follow-up model, where boundary conditions were modified to reflect change in supra-aortic vessel perfusion observed on the follow-up scan, predicted normal flow patterns but high levels of wall stress (up to 1.3M MPa) and increased displacement forces in regions at risk of compromising device stability. This might have contributed to the suspected endoleaks or device migration identified at the final follow up.

Discussion

Our study demonstrated that detailed haemodynamic and biomechanical analysis can help identify possible causes for post-TEVAR complications in a patient-specific setting. Further refinement and validation of the computational workflow will allow personalised assessment to aid in surgical planning and clinical decision making.

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.

Advanced risk prediction for aortic dissection patients using imaging-based computational flow analysis

Patients with either a repaired or medically managed aortic dissection have varying degrees of risk of developing late complications. High-risk patients would benefit from earlier intervention to improve their long-term survival. Currently serial imaging is used for risk stratification, which is not always reliable. On the other hand, understanding aortic haemodynamics within a dissection is essential to fully evaluate the disease and predict how it may progress. In recent decades, computational fluid dynamics (CFD) has been extensively applied to simulate complex haemodynamics within aortic diseases, and more recently, four-dimensional (4D)-flow magnetic resonance imaging (MRI) techniques have been developed for in vivo haemodynamic measurement. This paper presents a comprehensive review on the application of image-based CFD simulations and 4D-flow MRI analysis for risk prediction in aortic dissection. The key steps involved in patient-specific CFD analyses are demonstrated. Finally, we propose a workflow incorporating computational modelling for personalised assessment to aid in risk stratification and treatment decision-making.

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.

Applicability assessment for in-silico patient-specific TEVAR procedures

Thoracic Endovascular Aortic Repair (TEVAR) is a minimally invasive technique to treat thoracic aorta pathologies and consists of placing a self-expandable stent-graft into the pathological region to restore the vessel lumen and recreate a more physiological condition. Exhaustive computational models, namely the finite element analysis, can be implemented to reproduce the clinical procedure. In this context, numerical models, if used for clinical applications, must be reliable and the simulation credibility should be proved to predict clinical procedure outcomes or to build in-silico clinical trials. This work aims first at applying a previously validated TEVAR methodology to a patient-specific case. Then, defining the TEVAR procedure performed on a patient population as the context of use, the overall applicability of the TEVAR modeling is assessed to demonstrate the reliability of the model itself following a step-by-step method based on the ASME V&V40 protocol. Validation evidence sources are identified for the specific context of use and adopted to demonstrate the applicability of the numerical procedure, thereby answering a question of interest that evaluates the deployed stent-graft configuration in the vessel.

Longitudinal morphological changes of the aorta and the endograft position before and after distal stent graft-induced new entry in aortic dissections

OBJECTIVES

The aim of this study was to assess the endograft position and aortic geometry changes after thoracic endovascular aortic repair (TEVAR) and frozen elephant trunk (FET) in distal stent-induced new entry (dSINE) patients.

METHODS

In this retrospective cohort study, the baseline demographic and the follow-up data were extracted from the hospital records, and computed tomography scans of dSINE patients after TEVAR or FET between 2011 and 2021 were analysed regarding endograft oversizing, length and migration, taper ratio, aortic diameter at the endograft end, aortic elongation (thoracic inner and outer curvature), wedge apposition angle and tortuosity angle in the distal landing zone.

RESULTS

dSINE was found in 22/213 (10%) of TEVAR and 10/31 (32%) of FET patients. The total follow-up time was 45 (27; 59) months. TEVAR was mainly performed with Relay NBS endograft (77%) and FET with Evita open prosthesis (80%). Paraplegia and stroke rates were 3%. dSINE occurred 17 (7; 35) months post-TEVAR and was instantly treated in 18 patients (56%) or followed up for 21 (11; 34) months (n = 14). Migration [+5 mm (1; 11; P < 0.001)], birdbeak angle [+9° (0; 27; P = 0.039)] and aortic diameter +5 mm (1; 11; P < 0.001) increased after dSINE, whereas aortic elongation increased already before [+12 mm (0; 27; P = 0.015)] and peaked after dSINE [+30 mm (9; 38; P < 0.001)]. The aortic elongation was more pronounced in the outer aortic curvature before and after dSINE (before: P = 0.039, after: P = 0.024). Postoperative wedge apposition [17° (12; 20)] increased before dSINE [21° (16; 35; P < 0.001)] and peaked thereafter [31° (21; 40; P < 0.001)].

CONCLUSIONS

Aortic elongation may influence the endograft position and provoke TEVAR failure in the distal and proximal landing zones.

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.