A novel approach to the quantification of aortic root in vivo structural mechanics

Numerical simulation of the distal stent graft-induced new entry after TEVAR

The study aimed to investigate the mechanical factors for distal stent graft-induced new entry (dSINE) in aortic dissection patients and discussed these factors in conjunction with aortic morphology. Two patients (one dSINE and one non-dSINE), with the same age, gender, and type of implanted stent, were selected, then aortic morphological parameters were calculated. In addition, the stent material parameters used by the patients were also fitted. Simulations were performed based on the patient's aortic model and the stent graft used. The true lumen segment at the distal stent graft was designated as the "dSINE risk zone," and mechanical parameters (maximum principal strain, maximum principal stress) were computed. When approaching the area with higher mechanical parameters in the dSINE risk zone, dSINE patient exhibited higher values and growth rates in mechanical parameters compared to non-dSINE patient. Furthermore, dSINE patient also presented larger aortic taper ratio, stent oversizing ratio, and expansion mismatch ratio of the distal true lumen (EMRDTR). The larger mechanical parameters and growth rates in dSINE patient corresponded to a greater aortic taper ratio, stent oversizing ratio, and EMRDTR. The failure of dSINE prediction by the stent tortuosity index indicated that mechanical parameters were the fundamental reasons for dSINE development.

Fluid-structure interactions of peripheral arteries using a coupled in silico and in vitro approach

Vascular compliance is considered both a cause and a consequence of cardiovascular disease and a significant factor in the mid- and long-term patency of vascular grafts. However, the biomechanical effects of localised changes in compliance cannot be satisfactorily studied with the available medical imaging technologies or surgical simulation materials. To address this unmet need, we developed a coupled silico-vitro platform which allows for the validation of numerical fluid-structure interaction results as a numerical model and physical prototype. This numerical one-way and two-way fluid-structure interaction study is based on a three-dimensional computer model of an idealised femoral artery which is validated against patient measurements derived from the literature. The numerical results are then compared with experimental values collected from compliant arterial phantoms via direct pressurisation and ring tensile testing. Phantoms within a compliance range of 1.4-68.0%/100 mmHg were fabricated via additive manufacturing and silicone casting, then mechanically characterised via ring tensile testing and optical analysis under direct pressurisation with moderately statistically significant differences in measured compliance ranging between 10 and 20% for the two methods. One-way fluid-structure interaction coupling underestimated arterial wall compliance by up to 14.7% compared with two-way coupled models. Overall, Solaris™ (Smooth-On) matched the compliance range of the numerical and in vivo patient models most closely out of the tested silicone materials. Our approach is promising for vascular applications where mechanical compliance is especially important, such as the study of diseases which commonly affect arterial wall stiffness, such as atherosclerosis, and the model-based design, surgical training, and optimisation of vascular prostheses.

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.

Fluid-Structure Interaction Simulations of Repaired Type A Aortic Dissection: a Comprehensive Comparison With Rigid Wall Models

This study aimed to evaluate the effect of aortic wall compliance on intraluminal hemodynamics within surgically repaired type A aortic dissection (TAAD). Fully coupled two-way fluid-structure interaction (FSI) simulations were performed on two patient-specific post-surgery TAAD models reconstructed from computed tomography angiography images. Our FSI model incorporated prestress and different material properties for the aorta and graft. Computational results, including velocity, wall shear stress (WSS) and pressure difference between the true and false lumen, were compared between the FSI and rigid wall simulations. It was found that the FSI model predicted lower blood velocities and WSS along the dissected aorta. In particular, the area exposed to low time-averaged WSS (≤0.2 Pa) was increased from 21 cm² (rigid) to 38 cm² (FSI) in patient 1 and from 35 cm² (rigid) to 144 cm² (FSI) in patient 2. FSI models also produced more disturbed flow where much larger regions presented with higher turbulence intensity as compared to the rigid wall models. The effect of wall compliance on pressure difference between the true and false lumen was insignificant, with the maximum difference between FSI and rigid models being less than 0.25 mmHg for the two patient-specific models. Comparisons of simulation results for models with different Young’s moduli revealed that a more compliant wall resulted in further reduction in velocity and WSS magnitudes because of increased displacements. This study demonstrated the importance of FSI simulation for accurate prediction of low WSS regions in surgically repaired TAAD, but a rigid wall computational fluid dynamics simulation would be sufficient for prediction of luminal pressure difference.

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.

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.

Subject-specific multiscale modeling of aortic valve biomechanics

A Finite Element workflow for the multiscale analysis of the aortic valve biomechanics was developed and applied to three physiological anatomies with the aim of describing the aortic valve interstitial cells biomechanical milieu in physiological conditions, capturing the effect of subject-specific and leaflet-specific anatomical features from the organ down to the cell scale. A mixed approach was used to transfer organ-scale information down to the cell-scale. Displacement data from the organ model were used to impose kinematic boundary conditions to the tissue model, while stress data from the latter were used to impose loading boundary conditions to the cell level. Peak of radial leaflet strains was correlated with leaflet extent variability at the organ scale, while circumferential leaflet strains varied over a narrow range of values regardless of leaflet extent. The dependency of leaflet biomechanics on the leaflet-specific anatomy observed at the organ length-scale is reflected, and to some extent emphasized, into the results obtained at the lower length-scales. At the tissue length-scale, the peak diastolic circumferential and radial stresses computed in the fibrosa correlated with the leaflet surface area. At the cell length-scale, the difference between the strains in two main directions, and between the respective relationships with the specific leaflet anatomy, was even more evident; cell strains in the radial direction varied over a relatively wide range (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.36-0.87$$\end{document}0.36-0.87) with a strong correlation with the organ length-scale radial strain (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^{2}= 0.95$$\end{document}R2=0.95); conversely, circumferential cell strains spanned a very narrow range (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.75-0.88$$\end{document}0.75-0.88) showing no correlation with the circumferential strain at the organ level (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^{2}= 0.02$$\end{document}R2=0.02). Within the proposed simulation framework, being able to account for the actual anatomical features of the aortic valve leaflets allowed to gain insight into their effect on the structural mechanics of the leaflets at all length-scales, down to the cell scale.

Patient-Specific Bicuspid Aortic Valve Biomechanics: A Magnetic Resonance Imaging Integrated Fluid-Structure Interaction Approach

Congenital bicuspid aortic valve (BAV) consists of two fused cusps and represents a major risk factor for calcific valvular stenosis. Herein, a fully coupled fluid-structure interaction (FSI) BAV model was developed from patient-specific magnetic resonance imaging (MRI) and compared against in vivo 4-dimensional flow MRI (4D Flow). FSI simulation compared well with 4D Flow, confirming direction and magnitude of the flow jet impinging onto the aortic wall as well as location and extension of secondary flows and vortices developing at systole: the systolic flow jet originating from an elliptical 1.6 cm² orifice reached a peak velocity of 252.2 cm/s, 0.6% lower than 4D Flow, progressively impinging on the ascending aorta convexity. The FSI model predicted a peak flow rate of 22.4 L/min, 6.7% higher than 4D Flow, and provided BAV leaflets mechanical and flow-induced shear stresses, not directly attainable from MRI. At systole, the ventricular side of the non-fused leaflet revealed the highest wall shear stress (WSS) average magnitude, up to 14.6 Pa along the free margin, with WSS progressively decreasing towards the belly. During diastole, the aortic side of the fused leaflet exhibited the highest diastolic maximum principal stress, up to 322 kPa within the attachment region. Systematic comparison with ground-truth non-invasive MRI can improve the computational model ability to reproduce native BAV hemodynamics and biomechanical response more realistically, and shed light on their role in BAV patients' risk for developing complications; this approach may further contribute to the validation of advanced FSI simulations designed to assess BAV biomechanics.

The impact of balloon-expandable transcatheter aortic valve replacement on concomitant mitral regurgitation: a comprehensive computational analysis

The aortic and mitral valves function in a reciprocal interdependent fashion. However, the impact of transcatheter aortic valve replacement (TAVR) on the aortic-mitral continuity and severity of mitral regurgitation (MR) are poorly understood. In this study, a comprehensive engineering analysis was performed to investigate the impact of TAVR on MR severity and left heart dynamics in a retrospective patient case who harbours bicuspid aortic valve stenosis and concomitant functional MR. The TAVR procedure was computer simulated using a balloon-expandable valve, and the impact of three implantation heights on aortic-mitral coupling, MR severity and device performance were analysed. The accuracy and predictability of the computer modelling framework were validated with pre- and post-operative echo data. The highest deployment model resulted in higher stresses in the native leaflets, contact radial force and stent recoil, while the midway implantation model gave better haemodynamic performance and MR reduction in this patient case. Although the regurgitant volume decreased (less than 10%) for the three deployment configurations, no significant differences in MR severity improvement and mitral leaflet tethering were found. Acute improvement in MR was (i) due to the mechanical compression of the stent against the aortic-mitral curtain, (ii) due to an immediate drop in the ventricular pressure and transmitral pressure gradient. Albeit a single real clinical case, it is our hope that such detailed engineering computational analysis could shed light on the underlying biomechanical mechanisms of TAVR impact on MR.

New imaging techniques project the cellular and molecular alterations underlying bicuspid aortic valve development

Bicuspid aortic valve (BAV) disease is the most common congenital cardiac malformation associated with an increased lifetime risk and a high rate of surgically-relevant valve deterioration and aortic dilatation. Genomic data revealed that different genes are associated with BAV. A dominant genetic factor for the recent past was the basis to the recommendation for a more extensive aortic intervention. However very recent evidence that hemodynamic stressors and alterations of wall shear stress play an important role independent from the genetic trait led to more conservative treatment recommendations. Therefore, there is a current need to improve the ability to risk stratify BAV patients in order to obtain an early detection of valvulopathy and aortopathy while also to predict valve dysfunction and/or aortic disease development. Imaging studies based on new cutting-edge technologies, such us 4-dimensional (4D) flow magnetic resonance imaging (MRI), two-dimensional (2D) or three-dimensional (3D) speckle-tracking imaging (STI) and computation fluid dynamics, combined with studies demonstrating new gene mutations, specific signal pathways alterations, hemodynamic influences, circulating biomarkers modifications, endothelial progenitor cell impairment and immune/inflammatory response, all detected BAV valvulopathy progression and aortic wall abnormality. Overall, the main purpose of this review article is to merge the evidences of imaging and basic science studies in a coherent hypothesis that underlies and thus projects the development of both BAV during embryogenesis and BAV-associated aortopathy and its complications in the adult life, with the final goal to identifying aneurysm formation/rupture susceptibility to improve diagnosis and management of patients with BAV-related aortopathy.

A machine learning approach as a surrogate of finite element analysis-based inverse method to estimate the zero-pressure geometry of human thoracic aorta

Advances in structural finite element analysis (FEA) and medical imaging have made it possible to investigate the in vivo biomechanics of human organs such as blood vessels, for which organ geometries at the zero-pressure level need to be recovered. Although FEA-based inverse methods are available for zero-pressure geometry estimation, these methods typically require iterative computation, which are time-consuming and may be not suitable for time-sensitive clinical applications. In this study, by using machine learning (ML) techniques, we developed an ML model to estimate the zero-pressure geometry of human thoracic aorta given 2 pressurized geometries of the same patient at 2 different blood pressure levels. For the ML model development, a FEA-based method was used to generate a dataset of aorta geometries of 3125 virtual patients. The ML model, which was trained and tested on the dataset, is capable of recovering zero-pressure geometries consistent with those generated by the FEA-based method. Thus, this study demonstrates the feasibility and great potential of using ML techniques as a fast surrogate of FEA-based inverse methods to recover zero-pressure geometries of human organs.