A Systematic Review and Discussion of the Clinical Potential

Funding Information: Funding by Portuguese Foundation for Science and Technology (FCT-MCTES) under the following projects: PTDC/EMD-EMD/1230/2021—Fluid-structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach toward clinical practice ; UNIDEMI UIDB/00667/2020; A. Mourato PhD grant UI/BD/151212/2021; R. Valente PhD grant 2022.12223.BD. Publisher Copyright: © 2022 by the authors.Aortic aneurysm is a cardiovascular disease related to the alteration of the aortic tissue. It is an important cause of death in developed countries, especially for older patients. The diagnosis and treatment of such pathology is performed according to guidelines, which suggest surgical or interventional (stenting) procedures for aneurysms with a maximum diameter above a critical threshold. Although conservative, this clinical approach is also not able to predict the risk of acute complications for every patient. In the last decade, there has been growing interest towards the development of advanced in silico aortic models, which may assist in clinical diagnosis, surgical procedure planning or the design and validation of medical devices. This paper details a comprehensive review of computational modelling and simulations of blood vessel interaction in aortic aneurysms and dissection, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). In particular, the following questions are addressed: “What mathematical models were applied to simulate the biomechanical behaviour of healthy and diseased aortas?” and “Why are these models not clinically implemented?”. Contemporary evidence proves that computational models are able to provide clinicians with additional, otherwise unavailable in vivo data and potentially identify patients who may benefit from earlier treatment. Notwithstanding the above, these tools are still not widely implemented, primarily due to low accuracy, an extensive reporting time and lack of numerical validation.publishersversionpublishe

Modelling blood flow in patients with heart valve disease using deep learning: A computationally efficient method to expand diagnostic capabilities in clinical routine

Introduction: The computational modelling of blood flow is known to provide vital hemodynamic parameters for diagnosis and treatment-support for patients with valvular heart disease. However, most diagnosis/treatment-support solutions based on flow modelling proposed utilize time- and resource-intensive computational fluid dynamics (CFD) and are therefore difficult to implement into clinical practice. In contrast, deep learning (DL) algorithms provide results quickly with little need for computational power. Thus, modelling blood flow with DL instead of CFD may substantially enhances the usability of flow modelling-based diagnosis/treatment support in clinical routine. In this study, we propose a DL-based approach to compute pressure and wall-shear-stress (WSS) in the aorta and aortic valve of patients with aortic stenosis (AS). Methods: A total of 103 individual surface models of the aorta and aortic valve were constructed from computed tomography data of AS patients. Based on these surface models, a total of 267 patient-specific, steady-state CFD simulations of aortic flow under various flow rates were performed. Using this simulation data, an artificial neural network (ANN) was trained to compute spatially resolved pressure and WSS using a centerline-based representation. An unseen test subset of 23 cases was used to compare both methods. Results: ANN and CFD-based computations agreed well with a median relative difference between both methods of 6.0% for pressure and 4.9% for wall-shear-stress. Demonstrating the ability of DL to compute clinically relevant hemodynamic parameters for AS patients, this work presents a possible solution to facilitate the introduction of modelling-based treatment support into clinical practice

Haemodynamic changes in visceral hybrid repairs of type III and type V thoracoabdominal aortic aneurysms

The visceral hybrid procedure combining retrograde visceral bypass grafting and completion endovascular stent grafting is a feasible alternative to conventional open surgical or wholly endovascular repairs of thoracoabdominal aneurysms (TAAA). However, the wide variability in visceral hybrid configurations means that a priori prediction of surgical outcome based on haemodynamic flow profiles such as velocity pattern and wall shear stress post repair remain challenging. We sought to appraise the clinical relevance of computational fluid dynamics (CFD) analyses in the setting of visceral hybrid TAAA repairs. Two patients, one with a type III and the other with a type V TAAA, underwent successful elective and emergency visceral hybrid repairs, respectively. Flow patterns and haemodynamic parameters were analysed using reconstructed pre- and post-operative CT scans. Both type III and type V TAAAs showed highly disturbed flow patterns with varying helicity values preoperatively within their respective aneurysms. Low time-averaged wall shear stress (TAWSS) and high endothelial cell action potential (ECAP) and relative residence time (RRT) associated with thrombogenic susceptibility was observed in the posterior aspect of both TAAAs preoperatively. Despite differing bypass configurations in the elective and emergency repairs, both treatment options appear to improve haemodynamic performance compared to preoperative study. However, we observed reduced TAWSS in the right iliac artery (portending a theoretical risk of future graft and possibly limb thrombosis), after the elective type III visceral hybrid repair, but not the emergency type V repair. We surmise that this difference may be attributed to the higher neo-bifurcation of the aortic stent graft in the type III as compared to the type V repair. Our results demonstrate that CFD can be used in complicated visceral hybrid repair to yield potentially actionable predictive insights with implications on surveillance and enhanced post-operative management, even in patients with complicated geometrical bypass configurations

Computational analysis of blood flow and stress patterns in the aorta of patients with Marfan syndrome

Personalised external aortic root support (PEARS) was designed to prevent progressive aortic dilatation, and the associated risk of aortic dissection, in patients with Marfan syndrome by providing an additional support to the aorta. The objective of this thesis was to understand the biomechanical implications of PEARS surgery as well as to investigate the altered haemodynamics associated with the disease and its treatment. Finite element (FE) models were developed using patient-specific aortic geometries reconstructed from pre and post-PEARS magnetic resonance (MR) images of three Marfan patients. The wall and PEARS materials were assumed to be isotropic, incompressible and linearly elastic. A static load on the inner wall corresponding to the patients’ pulse pressure was applied with a zero-displacement constraint at all boundaries. Results showed that peak aortic stresses and displacements before PEARS were located at the sinuses of Valsalva but following PEARS surgery, they were shifted to the aortic arch, at the intersection between the supported and unsupported aorta. The zero-displacement constraint at the aortic root was subsequently removed and replaced with downward motion measured from in vivo images. This revealed significant increases in the longitudinal wall stress, especially in the pre-PEARS models. Computational fluid dynamics (CFD) models were developed to evaluate flow characteristics. The correlation-based transitional Shear Stress Transport (SST-Tran) model was adopted to simulate potential transitional and turbulence flow during part of the cardiac cycle and flow waveforms derived from phase-contrast MR images were imposed at the inlets. Qualitative patterns of the haemodynamics were similar pre- and post-PEARS with variations in mean helicity flow index (HFI) of -10%, 35% and 20% in the post-PEARS aortas of the three patients. A fluid-structure interaction (FSI) model was developed for one patient, pre- and post-PEARS in order to examine the effect of wall compliance on aortic flow as well as the effect of pulsatile flow on wall stress. This model excluded the sinuses and was based on the laminar flow assumption. The results were similar to those obtained using the rigid wall and static structural models, with minor quantitative differences. Considering the higher computational cost of FSI simulations and the relatively small differences observed in peak wall stress, it is reasonable to suggest that static structural models would be sufficient for wall stress prediction. Additionally, aortic root motion had a more profound effect on wall stress than wall compliance. Further studies are required to assess the statistical significance of the findings outlined in this thesis. Recommendations for future work were also highlighted, with emphasis on model assumptions including material properties, residual stress and boundary conditions.Open Acces

Design of a testing device for an anatomical part of the ascending aorta

Aortic aneurysms are life-threatening pathologies that cause thousands of deaths worldwide. The current main clinical criteria for surgical intervention is aortic diameter, although a large percentage of patients with dissection or rupture has a normal diameter. Computation methods have been adopted to model the biomechanical behaviour of biological tissue in view of adding in the diagnosis of this pathology. Furthermore, experimental testing on aneurismatic aortic tissue has been performed to validate these models. The objective of this study is to integrate com- putational mechanical methods into an innovative experimental test with a specifically designed device where material parameters are obtained by inverse methods assisted by Digital Image Correlation (DIC). Axiomatic Design (AD) is taken into consideration to develop the testing device in a clear, methodical, and efficient way. A case study is analysed, and a patient-specific 3D geometry of an Ascending Thoracic Aortic Aneurysm (ATAA) is obtained by segmenting Computed Tomography Angiography (CTA) images. A methodology is presented by attribut- ing a hyperelastic constitutive model to the geometry and executing Finite Element Analysis (FEA). Future work should rely on real experimental tests where Finite Element Model Up- dating (FEMU) should be adopted to fit the constitutive model more accurately to the actual specimen material.O aneurisma da aorta é uma patologia de risco que provoca milhares de mortes mundialmente. O critério atual para intervenção cirúrgica é o diâmetro da aorta, no entanto, uma grande percentagem de pacientes com dissecção ou rutura da aorta apresenta um diâmetro normal. Métodos computacionais têm sido adotados para modelar o comportamento biomecânico de tecido biológico e auxiliar no diagnóstico desta patologia. Testes experimentais nestes tecidos são executados para validar os modelos. O objetivo deste estudo é um contributo para uma plataforma digital integrando métodos computacionais para o desenvolvimento de um mecan- ismo de ensaio experimental, cuja identificação de parâmetros material deve ser auxiliada pela técnica de correlação digital de imagem 3D. Esta abordagem segue um desenvolvimento de pro- duto orientado por simulação numérica, em que a análise computacional é totalmente integrada como parte do projeto mecânico. Teoria Axiomática de Projeto é tida em consideração para desenvolver o dispositivo de uma forma clara, metódica e eficiente. Um caso de estudo é anal- isado e uma geometria da peça anatómica 3D, específica de um paciente, é obtida através da segmentação de imagens de uma angiotomografia. Uma metodologia é apresentada atribuindo um modelo constitutivo hiperelástico ao material e executando análise de elementos finitos. Como trabalho futuro a identificação dos parametros constitutivos deve ser obtida com recurso a métodos inversos avançados baseados em campos de deformação obtidos por correlação digital de imagem

Novel Applications of Cardiovascular Magnetic Resonance Imaging-Based Computational Fluid Dynamics Modeling in Pediatric Cardiovascular and Congenital Heart Disease

Cardiovascular diseases (CVDs) afflict many people across the world; thus, understanding the pathophysiology of CVD and the biomechanical forces which influence CVD progression is important in the development of optimal strategies to care for these patients. Over the last two decades, cardiac magnetic resonance (CMR) imaging has offered increasingly important insights into CVD. Computational fluid dynamics (CFD) modeling, a method of simulating the characteristics of flowing fluids, can be applied to the study of CVD through the collaboration of engineers and clinicians. This chapter aims to explore the current state of the CMR-derived CFD, as this technique pertains to both acquired CVD (i.e., atherosclerosis) and congenital heart disease (CHD)

Effects of age-associated regional changes in aortic stiffness on human hemodynamics revealed by computational modeling

Although considered by many as the gold standard clinical measure of arterial stiffness, carotid-to-femoral pulse wave velocity (cf-PWV) averages material and geometric properties over a large portion of the central arterial tree. Given that such properties may evolve differentially as a function of region in cases of hypertension and aging, among other conditions, there is a need to evaluate the potential utility of cf-PWV as an early diagnostic of progressive vascular stiffening. In this paper, we introduce a data-driven fluid-solid-interaction computational model of the human aorta to simulate effects of aging-related changes in regional wall properties (e.g., biaxial material stiffness and wall thickness) and conduit geometry (e.g., vessel caliber, length, and tortuosity) on several metrics of arterial stiffness, including distensibility, augmented pulse pressure, and cyclic changes in stored elastic energy. Using the best available biomechanical data, our results for PWV compare well to findings reported for large population studies while rendering a higher resolution description of evolving local and global metrics of aortic stiffening. Our results reveal similar spatio-temporal trends between stiffness and its surrogate metrics, except PWV, thus indicating a complex dependency of the latter on geometry. Lastly, our analysis highlights the importance of the tethering exerted by external tissues, which was iteratively estimated until hemodynamic simulations recovered typical values of tissue properties, pulse pressure, and PWV for each age group

Ascending Aorta Parametric Modeling and Fluid Dynamics Analysis in a Child Patient with Congenital BAV and Ascending Aorta Aneurysm

RÉSUMÉ L’anévrisme de l'aorte ascendante (AAoA) est une déformation qui affecte la partie de l'aorte entre la valve aortique et le tronc brachiocéphalique. L'incidence de cette maladie est plus élevée dans les cas de patients atteints de la pathologie de la Bicuspidie Valvulaire Aortique (BVA). BVA est la malformation cardiaque congénitale la plus commune dans le monde avec une prévalence entre 0.5% et 2%. De nombreux patients atteints de l'AAoA sont des enfants comme cela se produit plus souvent à un plus jeune âge. La chirurgie invasive est actuellement considérée comme l'étalon-or pour le traitement de la déformation de l'aorte. Cette intervention chirurgicale a un taux de mortalité élevé, entre 2.5% et 5% des cas traités, en raison du danger intrinsèque de l'opération qui pourrait prendre plus de 5 heures. L'avènement des techniques chirurgicales à invasion minimale au cours des dernières années a pour but de réduire la nécessité d'une chirurgie invasive en utilisant des dispositifs tels que des stents et des greffes qui sont implantables par cathétérisme. L'utilisation de ces nouvelles techniques d'intervention présente des avantages significatifs par rapport à la chirurgie conventionnelle, comme la diminution du risque de mortalité opératoire et la durée totale de l'intervention et de l'hospitalisation. Cependant, un processus de simulation précisant toutes les conditions possibles dans lesquelles le dispositif implanté pourrait fonctionner est nécessaire. Ce projet de recherche consiste à développer un modèle de l'aorte ascendante par Conception Assistée par Ordinateur (CAO) qui permet de simuler, avec une grande fiabilité, les propriétés mécaniques et morphologiques de cette partie de l'aorte. Ce modèle de l'aorte ascendante peut interagir avec un modèle CAO de tout type de dispositif (par exemple, un stent) pour simuler les effets sur l'aorte. En outre, le modèle peut être utilisé pour des évaluations de Computational Fluid Dynamics (CFD) ainsi que pour mesurer la contrainte de cisaillement à la paroi (WSS) et la vitesse du sang. Dans la littérature, il existe plusieurs exemples de modèles de l'aorte, toutefois, il n'existe aucune preuve actuelle d'une analyse CFD dans laquelle la maladie de BVA est modélisée dans un modèle CAO de l'aorte ascendante dans le cas d'un anévrisme. Pour ce projet de recherche, une base de données de 140 patients a été consultée. Les patients étaient âgés de zéro à dix-huit ans et ont montré plusieurs anomalies tels que le syndrome de Marfan, la BVA, la dilatation de l'aorte et l'anévrisme, etc. Un ensemble d'Images à Résonance Magnétique (IRM) d'un enfant avec un anévrisme de l'aorte ascendante évidente et une BVA a été choisi comme cas spécifique. Le processus de segmentation d'images a été réalisé dans le logiciel Slice-O-Matic afin d'obtenir un nuage de points qui a ensuite été utilisé----------ABSTRACT Ascending Aorta Aneurysm (AAoA) is a deformation which aects the portion of the aorta between the aortic valve and the brachiocephalic trunk. The incidence of this disease is higher in cases of patients with the Bicuspid Aortic Valve (BAV ) pathology. BAV is the most common congenital heart deformation in the world with a prevalence between 0.5% and 2%. Many patients with AAoA are children as it occurs more frequently at a younger age. Invasive surgery is currently considered the gold standard for aortic deformation treatment. This surgical procedure has a high mortality rate, between 2.5% and 5% of the treated cases, because of the intrinsic danger of the operation which could take more than 5 hours. The advent of minimally invasive surgical techniques in recent years aims to reduce the need for invasive surgery using devices such as stents and grafts which are implantable by catheterization. The use of these new interventional techniques has signicant advantages compared to conventional surgery, such as a decreased risk of operative mortality, total time of intervention and hospitalization. However, an accurate simulation process of all the possible conditions in which the implanted device could operate is required. This research project consists of developing a Computer-Aided Design (CAD) model of the ascending aorta which can simulate, with high reliability, the mechanical and morphological properties of the ascending aorta. This model of the ascending aorta can interact with a CAD model of any type of device (eg. stent) to simulate its eects on the aorta. Furthermore, the model can be used for Computational Fluid Dynamics (CFD) evaluations in order to assess Wall Shear Stress (WSS) and blood velocity measurements. In literature, there are several examples of aortic models, however, there is no present evidence of a CFD analysis in which the BAV disease is modeled into a CAD model of the ascending aorta within an aneurysm. For this research project, a database of 140 patients was consulted. Patients were aged between zero and eighteen years old and showed several anomalies, like Marfan syndrome, BAV disease, aortic dilatation and aneurysm, etc. A set of Magnetic Resonance Images (MRIs) of a child patient with an evident ascending aortic aneurysm and BAV disease was chosen as a patient-specic case. The image segmentation process was performed within the software Slice-O-Matic in order to obtain a cloud of points, which then was used to build the CAD model. The latter was conceived using dierent surface reconstruction techniques executed by the modeling software CATIA while maintaining the highest possible accuracy. Dierent kinds of meshes were generated into the Ansys ICEM CFD meshing software to better achieve the Finite Volume Method (FVM) analysis. The meshed model was the