Evaluation of Peak Wall Stress in an Ascending Thoracic Aortic Aneurysm Using FSI Simulations: Effects of Aortic Stiffness and Peripheral Resistance

Computational Fluid-Structure Interaction in Microfluidics

Micro elastofluidics is a transformative branch of microfluidics, leveraging the fluid-structure interaction (FSI) at the microscale to enhance the functionality and efficiency of various microdevices. This review paper elucidates the critical role of advanced computational FSI methods in the field of micro elastofluidics. By focusing on the interplay between fluid mechanics and structural responses, these computational methods facilitate the intricate design and optimisation of microdevices such as microvalves, micropumps, and micromixers, which rely on the precise control of fluidic and structural dynamics. In addition, these computational tools extend to the development of biomedical devices, enabling precise particle manipulation and enhancing therapeutic outcomes in cardiovascular applications. Furthermore, this paper addresses the current challenges in computational FSI and highlights the necessity for further development of tools to tackle complex, time-dependent models under microfluidic environments and varying conditions. Our review highlights the expanding potential of FSI in micro elastofluidics, offering a roadmap for future research and development in this promising area.

The predictive capability of aortic stiffness index for aortic dissection among dilated ascending aortas

OBJECTIVE

We created a finite element model to predict the probability of dissection based on imaging-derived aortic stiffness and investigated the link between stiffness and wall tensile stress using our model.

METHODS

Transthoracic echocardiogram measurements were used to calculate aortic diameter change over the cardiac cycle. Aortic stiffness index was subsequently calculated based on diameter change and blood pressure. A series of logistic models were developed to predict the binary outcome of aortic dissection using 1 or more series of predictor parameters such as aortic stiffness index or patient characteristics. Finite element analysis was performed on a subset of diameter-matched patients exhibiting patient-specific material properties.

RESULTS

Transthoracic echocardiogram scans of patients with type A aortic dissection (n = 22) exhibited elevated baseline aortic stiffness index when compared with aneurysmal patients' scans with tricuspid aortic valve (n = 83, P < .001) and bicuspid aortic valve (n = 80, P < .001). Aortic stiffness index proved an excellent discriminator for a future dissection event (area under the curve, 0.9337, odds ratio, 2.896). From the parametric finite element study, we found a correlation between peak longitudinal wall tensile stress and stiffness index (ρ = .6268, P < .001, n = 28 pooled).

CONCLUSIONS

Noninvasive transthoracic echocardiogram-derived aortic stiffness measurements may serve as an impactful metric toward predicting aortic dissection or quantifying dissection risk. A correlation between longitudinal stress and stiffness establishes an evidence-based link between a noninvasive stiffness parameter and stress state of the aorta with clinically apparent dissection events.

Implantable Pressure-Sensing Devices for Monitoring Abdominal Aortic Aneurysms in Post-Endovascular Aneurysm Repair

Over the past two decades, there has been extensive research into surveillance methods for the post-endovascular repair of abdominal aortic aneurysms, highlighting the importance of these technologies in supplementing or even replacing conventional image-screening modalities. This review aims to provide an overview of the current status of alternative surveillance solutions for endovascular aneurysm repair, while also identifying potential aneurysm features that could be used to develop novel monitoring technologies. It offers a comprehensive review of these recent clinical advances, comparing new and standard clinical practices. After introducing the clinical understanding of abdominal aortic aneurysms and exploring current treatment procedures, the paper discusses the current surveillance methods for endovascular repair, contrasting them with recent pressure-sensing technologies. The literature on three commercial pressure-sensing devices for post-endovascular repair surveillance is analyzed. Various pre-clinical and clinical studies assessing the safety and efficacy of these devices are reviewed, providing a comparative summary of their outcomes. The review of the results from pre-clinical and clinical studies suggests a consistent trend of decreased blood pressure in the excluded aneurysm sac post-repair. However, despite successful pressure readings from the aneurysm sac, no strong link has been established to translate these measurements into the presence or absence of endoleaks. Furthermore, the results do not allow for a conclusive determination of ongoing aneurysm sac growth. Consequently, a strong clinical need persists for monitoring endoleaks and aneurysm growth following endovascular repair.

Heat transfer mechanism in idealized healthy and diseased aortas using fluid-structure interaction method

The heat transfer mechanism inside the human aorta may be related to the physiological function and lesion formation of the aortic wall. The objective of this study was to acquire the temperature distribution in the three-dimensional idealized aorta. An idealized healthy aortic geometry and three representative diseased aortas: aortic aneurysm, coarctation of the aorta, and aortic dissection were constructed. Advanced fluid-structure interaction (FSI) computational framework was applied to predict the aortic temperature distribution. The movement of the aortic root due to the heartbeat was also considered. The displacement distribution of the aortic vessel wall was consistent with clinical observation. The lesser curvature of the aortic arch, aneurysm body, coarctation region, and false lumen were all exposed to relatively high temperatures (over 310.006 K). We found that the rigid wall assumption slightly underestimated the magnitude of the whole aortic wall-averaged temperature while the changing trend and local temperature were like the results of the FSI method. Besides, the wall-averaged temperature would increase and the temperature inflection point would advance when the aortic vessel wall was loaded with a high heat flux. This pilot study revealed the aortic heat transfer mechanism and temperature distribution, and the findings may help to understand the physiological characteristics of the aortic vessel wall.

Structural numerical analysis of a branched modular stent-graft for aneurysms encompassing all zones of the aortic arch

The development of stent-grafts for the total repair of aneurysms in the aortic arch is still a technical challenge due mainly to the anatomical complexity of this region. Research performed here structurally evaluated a modular branched stent-graft for aneurysms encompassing all zones of the aortic arch by means of numerical simulations using fluid-structure interaction. The geometric domain obtained by means of computed tomography was subjected to physiological boundary conditions. The blood was modelled as non-Newtonian by the Carreau model, and the arterial wall was modelled as anisotropic hyperelastic by the Holzapfel model. The material adopted for the stents was Nitinol, and expanded polytetrafluoroethylene (ePTFE) was used for the graft. A comparison of the structural behaviour of the aneurysmal aortic arch before and after stent-graft implantation was performed. The numerical flow model was experimentally verified in vitro on a representative test bench of blood flow in the aortic arch. The stent-graft was shown to minimally modify arterial wall dynamics and was not susceptible to migration and endoleak. Peak stresses and strains were found in the stents and graft, respectively, while the stresses in the aneurysm sac were significantly reduced, of the order of 97.5%, due to the isolation of the arterial wall by the stent-graft.

The role of aorta distal to stent in the occurrence of distal stent graft-induced new entry tear: A computational fluid dynamics and morphological study

Distal stent graft-induced new entry tear (dSINE) is an important complication of thoracic endovascular aortic repair (TEVAR) for the treatment of type B aortic dissection (TBAD). This study aims to explore whether the aorta distal to the stent plays an important role in the occurrence of dSINE. Sixty-nine patient-specific geometrical models of twenty-three enrolled patients were reconstructed from preoperative, postoperative, and predSINE computed tomography scans. Computational fluid dynamics (CFD) simulations were performed to calculate the von Mises stress in the CFD group. Meanwhile, morphological measurements were performed in all patients, including measurements of the inverted pyramid index at different follow-up time points and the postoperative true lumen volume change rate. In the CFD study, the time-averaged von Mises stress of the true lumen distal to the stent in dSINE patients was significantly higher than that in the CFD controls (20.42 kPa vs. 15.47 kPa). In the morphological study, a special aortic plane (plane A) with an extremely small area distal to the stent was observed in dSINE patients, which resulted in an inverted pyramid structure in the true lumen distal to the stent. This structure in dSINE patients became increasingly obvious during the follow-up period and finally reached the maximum value before dSINE occurred (mean, 3.91 vs. 1.23). At the same time, enlargement of the true lumen distal to the stent occurs before dSINE, manifesting as a continuous increase in the true lumen volume (mean, 0.70 vs. 013). A new theory of what causes dSINE to occur has been proposed: the inverted pyramid structure of the true lumen distal to the stent caused an increase in the von Mises stress in this region and aortic enlargement, which ultimately led to the occurrence of dSINE.

Statistical shape representation of the thoracic aorta: accounting for major branches of the aortic arch

Statistical shape modeling (SSM) is an emerging tool for risk assessment of thoracic aortic aneurysm. However, the head branches of the aortic arch are often excluded in SSM. We introduced an SSM strategy based on principal component analysis that accounts for aortic branches and applied it to a set of patient scans. Computational fluid dynamics were performed on the reconstructed geometries to identify the extent to which branch model accuracy affects the calculated wall shear stress (WSS) and pressure. Surface-averaged and location-specific values of pressure did not change significantly, but local WSS error was high near branches when inaccurately modeled.

Regional biomechanical characterization of human ascending aortic aneurysms: Microstructure and biaxial mechanical response

The ascending thoracic aortic aneurysm (ATAA) is a permanent dilatation of the vessel with a high risk of adverse events, and shows heterogeneous properties. To investigate regional differences in the biomechanical properties of ATAAs, tissue samples were collected from 10 patients with tricuspid aortic valve phenotype and specimens from minor, anterior, major, and posterior regions were subjected to multi-ratio planar biaxial extension tests and second-harmonic generation (SHG) imaging. Using the data, parameters of a microstructure-motivated constitutive model were obtained considering fiber dispersion. SHG imaging showed disruptions in the organization of the layers. Structural and material parameters did not differ significantly between regions. The non-symmetric fiber dispersion model proposed by Holzapfel et al. [25] was used to fit the data. The mean angle of collagen fibers was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. The experimental data collected in this study contribute to the biomechanical data available in the literature on human ATAAs. Region-specific parameters for the constitutive models are fundamental to improve the current risk stratification strategies, which are mainly based on aortic size. Such investigations can facilitate the development of more advanced finite element models capable of capturing the regional heterogeneity of pathological tissues. STATEMENT OF SIGNIFICANCE: Tissue samples of human ascending thoracic aortic aneurysms (ATAA) were collected. Samples from four regions underwent multi-ratio planar biaxial extension tests and second-harmonic generation imaging. Region-specific parameters of a microstructure-motivated model considering fiber dispersion were obtained. Structural and material parameters did not differ significantly between regions, however, the mean fiber angle was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. This study provides a unique set of mechanical and structural data, supporting the microstructural influence on the tissue response. It may facilitate the development of better finite element models capable of capturing the regional tissue heterogeneity.

A review on the biomechanical behaviour of the aorta

Large aortic aneurysm and acute and chronic aortic dissection are pathologies of the aorta requiring surgery. Recent advances in medical intervention have improved patient outcomes; however, a clear understanding of the mechanisms leading to aortic failure and, hence, a better understanding of failure risk, is still missing. Biomechanical analysis of the aorta could provide insights into the development and progression of aortic abnormalities, giving clinicians a powerful tool in risk stratification. The complexity of the aortic system presents significant challenges for a biomechanical study and requires various approaches to analyse the aorta. To address this, here we present a holistic review of the biomechanical studies of the aorta by categorising articles into four broad approaches, namely theoretical, in vivo, experimental and combined investigations. Experimental studies that focus on identifying mechanical properties of the aortic tissue are also included. By reviewing the literature and discussing drawbacks, limitations and future challenges in each area, we hope to present a more complete picture of the state-of-the-art of aortic biomechanics to stimulate research on critical topics. Combining experimental modalities and computational approaches could lead to more comprehensive results in risk prediction for the aortic system.

Comparative study between 1-way and 2-way coupled fluid-structure interaction in numerical simulation of aortic arch aneurysms

Hemodynamic forces are related to pathological variations of the cardiovascular system, and numerical simulations for fluid-structure interaction have been systematically used to analyze the behavior of blood flow and the arterial wall in aortic aneurysms. This paper proposes a comparative analysis of 1-way and 2-way coupled fluid-structure interaction for aortic arch aneurysm. The coupling models of fluid-structure interaction were conducted using 3D geometry of the thoracic aorta from computed tomography. Hyperelastic anisotropic properties were estimated for the Holzapfel arterial wall model. The rheological behavior of the blood was modeled by the Carreau-Yasuda model. The results showed that the 1-way approach tends to underestimate von Mises stress, displacement, and strain over the entire cardiac cycle, compared to the 2-way approach. In contrast, the behavior of the variables of flow field, velocity, wall shear stress, and Reynolds number when coupled by the 1-way model was overestimated at the systolic moment and tends to be equal at the diastolic moment. The quantitative differences found, especially during the systole, suggest the use of 2-way coupling in numerical simulations of aortic arch aneurysms due to the hyperelastic nature of the arterial wall, which leads to a strong iteration between the fluid and the arterial wall.

In-silico investigations of haemodynamic parameters for a blunt thoracic aortic injury case

Accounting for 1.5% of thoracic trauma, blunt thoracic aortic injury (BTAI) is a rare disease with a high mortality rate that nowadays is treated mostly via thoracic endovascular aortic repair (TEVAR). Personalised computational models based on fluid-solid interaction (FSI) principals not only support clinical researchers in studying virtual therapy response, but also are capable of predicting eventual outcomes. The present work studies the variation of key haemodynamic parameters in a clinical case of BTAI after successful TEVAR, using a two-way FSI model. The three-dimensional (3D) patient-specific geometries of the patient were coupled with three-element Windkessel model for both prior and post intervention cases, forcing a correct prediction of blood flow over each section. Results showed significant improvement in velocity and pressure distribution after stenting. High oscillatory, low magnitude shear (HOLMES) regions require careful examination in future follow-ups, since thrombus formation was confirmed in some previously clinically reported cases of BTAI treated with TEVAR. The strength of swirling flows along aorta was also damped after stent deployment. Highlighting the importance of haemodynamic parameters in case-specific therapies. In future studies, compromising motion of aortic wall due to excessive cost of FSI simulations can be considered and should be based on the objectives of studies to achieve a more clinical-friendly patient-specific CFD model.

Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms

Thoracic aortic aneurysm (TAA) is a localized dilatation of the aorta that can lead to life-threatening dissection or rupture. In vivo assessments of TAA progression are largely limited to measurements of aneurysm size and growth rate. There is promise, however, that computational modelling of the evolving biomechanics of the aorta could predict future geometry and properties from initiating mechanobiological insults. We present an integrated framework to train a deep operator network (DeepONet)-based surrogate model to identify TAA contributing factors using synthetic finite-element-based datasets. For training, we employ a constrained mixture model of aortic growth and remodelling to generate maps of local aortic dilatation and distensibility for multiple TAA risk factors. We evaluate the performance of the surrogate model for insult distributions varying from fusiform (analytically defined) to complex (randomly generated). We propose two frameworks, one trained on sparse information and one on full-field greyscale images, to gain insight into a preferred neural operator-based approach. We show that this continuous learning approach can predict the patient-specific insult profile associated with any given dilatation and distensibility map with high accuracy, particularly when based on full-field images. Our findings demonstrate the feasibility of applying DeepONet to support transfer learning of patient-specific inputs to predict TAA progression.

Aortic local biomechanical properties in ascending aortic aneurysms

Ascending aortic aneurysm (AsAA) is a high-risk cardiovascular disease with an increased incidence over years. In this study, we compare different risk factors based on the pre-failure behavior (from a biomechanical point of view) obtained ex-vivo from an equi-biaxial tensile test. A total of 100 patients (63 ± 12 years, 72 males) with AsAA replacement, were recruited. Equi-biaxial tensile tests of AsAA walls were performed on freshly sampled aortic wall tissue after ascending aortic replacement. The aneurysmal aortic walls were divided into four quadrants (medial, anterior, lateral, and posterior) and two directions (longitudinal and circumferential) were considered. The stiffness was represented by the maximum Young Modulus (MYM). Based on patient information, the following subgroups were considered: age, gender, hypertension, obesity, dyslipidemia, diabetes, smoking history, aortic insufficiency, aortic stenosis, coronary artery disease, aortic diameter and aortic valve type. In general, when the aortic diameter increased, the aortic wall became thicker. In terms of the MYM, the longitudinal direction was significantly higher than that in the circumferential direction. In the multivariant analysis, the impact factors of age (p = 0.07), smoking (p = 0.05), diabetes (p = 0.03), aortic stenosis (p = 0.02), coronary artery disease (p < 10^-3), and aortic diameters (p = 0.02) were significantly influencing the MYM. There was no significant MYM difference when the patients presented arterial hypertension, dyslipidemia, obesity, or bicuspid aortic valve. To conclude, the pre-failure aortic stiffness is multi-factorial, according to our population of 100 patients with AsAA. STATEMENT OF SIGNIFICANCE: : Our research on the topic of "Aortic local biomechanical properties in case of ascending aortic aneurysms" is about the biomechanical properties on one hundred aortic samples according to the aortic wall quadrants and the direction. More than ten factors and risks which may impact ascending aortic aneurysms have been studied. According to our knowledge, so far, this article involved the largest population on this topic. It will be our pleasure to share this information with all the readers.

Component quantification of aortic blood flow energy loss using computational fluid-structure interaction hemodynamics

BACKGROUND AND OBJECTIVES

The aorta serves as the main tube of the human blood circulation system. Energy loss (EL) occurs when blood flows through the aorta and there may be a potential correlation between EL and aortic diseases. However, the components of blood flow EL are still not fully understood. This study aims to quantitatively reveal the EL components in healthy and diseased aortas.

METHODS

We construct an idealized healthy aorta and three idealized representative diseased aortas: aortic aneurysm, coarctation of the aorta, and aortic dissection. Computational hemodynamic studies are carried out by using the fluid-structure interaction simulation framework.

RESULTS

Four kinds of EL components: viscous friction, turbulence dissipation, wall deformation, and local lesion are firstly acquired in healthy and diseased aortas based on the high-resolution blood flow information. Viscous friction contributes most to the EL (45.69%-57.22%). EL caused by the deformation of the aortic wall ranks second (15.18%-33.12%). The proportions of turbulence dissipation and local lesion depend on individual geometric characteristics. Besides, the buffering efficiency of the healthy and diseased aorta is about 80%.

CONCLUSIONS

This study quantitatively reports the components of blood flow EL in healthy and diseased aortas, the finding may provide novel insights into the pathogenesis of aortic diseases.

The Effects of the Mechanical Properties of Vascular Grafts and an Anisotropic Hyperelastic Aortic Model on Local Hemodynamics during Modified Blalock-Taussig Shunt Operation, Assessed Using FSI Simulation

Cardiovascular surgery requires the use of state-of-the-art artificial materials. For example, microporous polytetrafluoroethylene grafts manufactured by Gore-Tex^® are used for the treatment of cyanotic heart defects (i.e., modified Blalock–Taussig shunt). Significant mortality during this palliative operation has led surgeons to adopt mathematical models to eliminate complications by performing fluid–solid interaction (FSI) simulations. To proceed with FSI modeling, it is necessary to know either the mechanical properties of the aorta and graft or the rheological properties of blood. The properties of the aorta and blood can be found in the literature, but there are no data about the mechanical properties of Gore-Tex^® grafts. Experimental studies were carried out on the mechanical properties vascular grafts adopted for modified pediatric Blalock–Taussig shunts. Parameters of two models (the five-parameter Mooney–Rivlin model and the three-parameter Yeoh model) were determined by uniaxial experimental curve fitting. The obtained data were used for patient-specific FSI modeling of local blood flow in the “aorta-modified Blalock–Taussig shunt–pulmonary artery” system in three different shunt locations: central, right, and left. The anisotropic model of the aortic material showed higher stress values at the peak moment of systole, which may be a key factor determining the strength characteristics of the aorta and pulmonary artery. Additionally, this mechanical parameter is important when installing a central shunt, since it is in the area of the central anastomosis that an increase in stress on the aortic wall is observed. According to computations, the anisotropic model shows smaller values for the displacements of both the aorta and the shunt, which in turn may affect the success of preoperative predictions. Thus, it can be concluded that the anisotropic properties of the aorta play an important role in preoperative modeling.

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

The assessment of cardiovascular hemodynamics with computational techniques is establishing its fundamental contribution within the world of modern clinics. Great research interest was focused on the aortic vessel. The study of aortic flow, pressure, and stresses is at the basis of the understanding of complex pathologies such as aneurysms. Nevertheless, the computational approaches are still affected by sources of errors and uncertainties. These phenomena occur at different levels of the computational analysis, and they also strongly depend on the type of approach adopted. With the current study, the effect of error sources was characterized for an aortic case. In particular, the geometry of a patient-specific aorta structure was segmented at different phases of a cardiac cycle to be adopted in a computational analysis. Different levels of surface smoothing were imposed to define their influence on the numerical results. After this, three different simulation methods were imposed on the same geometry: a rigid wall computational fluid dynamics (CFD), a moving-wall CFD based on radial basis functions (RBF) CFD, and a fluid-structure interaction (FSI) simulation. The differences of the implemented methods were defined in terms of wall shear stress (WSS) analysis. In particular, for all the cases reported, the systolic WSS and the time-averaged WSS (TAWSS) were defined.

Hemodynamic effects of stent-graft introducer sheath during thoracic endovascular aortic repair

Thoracic endovascular aortic repair (TEVAR) has become the standard treatment of a variety of aortic pathologies. The objective of this study is to evaluate the hemodynamic effects of stent-graft introducer sheath during TEVAR. Three idealized representative diseased aortas were designed: aortic aneurysm, coarctation of the aorta, and aortic dissection. Computational fluid dynamics studies were performed in the above idealized aortic geometries. An introducer sheath routinely used in the clinic was virtually placed into diseased aortas. Comparative analysis was carried out to evaluate the hemodynamic effects of the introducer sheath. Results show that the blood flow to the supra-aortic branches would increase above 9% due to the obstruction of the introducer sheath. The region exposed to high endothelial cell activation potential (ECAP) expands in the scenarios of coarctation of the aorta and aortic dissection, which indicates that the probability of thrombus formation may increase during TEVAR. The pressure magnitude in peak systole shows an obvious rise, and a similar phenomenon is not observed in early diastole. The blood viscosity in the aortic arch and descending aorta is remarkably altered by the introducer sheath. The uneven viscosity distribution confirms the necessity of using non-Newtonian models, and high-viscosity region with high ECAP further promotes thrombosis. Our results highlight the hemodynamic effects of stent-graft introducer sheath during TEVAR, which may associate with perioperative complications.

Atlas-Based Evaluation of Hemodynamic in Ascending Thoracic Aortic Aneurysms

Atlas-based analyses of patients with cardiovascular diseases have recently been explored to understand the mechanistic link between shape and pathophysiology. The construction of probabilistic atlases is based on statistical shape modeling (SSM) to assess key anatomic features for a given patient population. Such an approach is relevant to study the complex nature of the ascending thoracic aortic aneurysm (ATAA) as characterized by different patterns of aortic shapes and valve phenotypes. This study was carried out to develop an SSM of the dilated aorta with both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV), and then assess the computational hemodynamic of virtual models obtained by the deformation of the mean template for specific shape boundaries (i.e., ±1.5 standard deviation, σ). Simulations demonstrated remarkable changes in the velocity streamlines, blood pressure, and fluid shear stress with the principal shape modes such as the aortic size (Mode 1), vessel tortuosity (Mode 2), and aortic valve morphologies (Mode 3). The atlas-based disease assessment can represent a powerful tool to reveal important insights on ATAA-derived hemodynamic, especially for aneurysms which are considered to have borderline anatomies, and thus challenging decision-making. The utilization of SSMs for creating probabilistic patient cohorts can facilitate the understanding of the heterogenous nature of the dilated ascending aorta.

Fully-Coupled FSI Computational Analyses in the Ascending Thoracic Aorta Using Patient-Specific Conditions and Anisotropic Material Properties

Computational hemodynamics has become increasingly important within the context of precision medicine, providing major insight in cardiovascular pathologies. However, finding appropriate compromise between speed and accuracy remains challenging in computational hemodynamics for an extensive use in decision making. For example, in the ascending thoracic aorta, interactions between the blood and the aortic wall must be taken into account for the sake of accuracy, but these fluid structure interactions (FSI) induce significant computational costs, especially when the tissue exhibits a hyperelastic and anisotropic response. The objective of the current study is to use the Small On Large (SOL) theory to linearize the anisotropic hyperelastic behavior in order to propose a reduced-order model for FSI simulations of the aorta. The SOL method is tested for fully-coupled FSI simulations in a patient-specific aortic geometry presenting an Ascending Thoracic Aortic Aneurysm (aTAA). The same model is also simulated with a fully-coupled FSI with non-linear material behavior, without SOL linearization. Eventually, the results and computational times with and without the SOL are compared. The SOL approach is demonstrated to provide a significant reduction of computational costs for FSI analysis in the aTAA, and the results in terms of stress state distribution are comparable. The method is implemented in ANSYS and will be further evaluated for clinical applications.

Patient-Specific Analysis of Ascending Thoracic Aortic Aneurysm with the Living Heart Human Model

In ascending thoracic aortic aneurysms (ATAAs), aneurysm kinematics are driven by ventricular traction occurring every heartbeat, increasing the stress level of dilated aortic wall. Aortic elongation due to heart motion and aortic length are emerging as potential indicators of adverse events in ATAAs; however, simulation of ATAA that takes into account the cardiac mechanics is technically challenging. The objective of this study was to adapt the realistic Living Heart Human Model (LHHM) to the anatomy and physiology of a patient with ATAA to assess the role of cardiac motion on aortic wall stress distribution. Patient-specific segmentation and material parameter estimation were done using preoperative computed tomography angiography (CTA) and ex vivo biaxial testing of the harvested tissue collected during surgery. The lumped-parameter model of systemic circulation implemented in the LHHM was refined using clinical and echocardiographic data. The results showed that the longitudinal stress was highest in the major curvature of the aneurysm, with specific aortic quadrants having stress levels change from tensile to compressive in a transmural direction. This study revealed the key role of heart motion that stretches the aortic root and increases ATAA wall tension. The ATAA LHHM is a realistic cardiovascular platform where patient-specific information can be easily integrated to assess the aneurysm biomechanics and potentially support the clinical management of patients with ATAAs.

Fluid-structure interaction: Insights into biomechanical implications of endograft after thoracic endovascular aortic repair

Thoracic endovascular aortic repair (TEVAR) has developed to be the most effective treatment for aortic diseases. This study aims to evaluate the biomechanical implications of the implanted endograft after TEVAR. We present a novel image-based, patient-specific, fluid-structure computational framework. The geometries of blood, endograft, and aortic wall were reconstructed based on clinical images. Patient-specific measurement data was collected to determine the parameters of the three-element Windkessel. We designed three postoperative scenarios with rigid wall assumption, blood-wall interaction, blood-endograft-wall interplay, respectively, where a two-way fluid-structure interaction (FSI) method was applied to predict the deformation of the composite stent-wall. Computational results were validated with Doppler ultrasound data. Results show that the rigid wall assumption fails to predict the waveforms of blood outflow and energy loss (EL). The complete storage and release process of blood flow energy, which consists of four phases is captured by the FSI method. The endograft implantation would weaken the buffer function of the aorta and reduce mean EL by 19.1%. The closed curve area of wall pressure and aortic volume could indicate the EL caused by the interaction between blood flow and wall deformation, which accounts for 68.8% of the total EL. Both the FSI and endograft have a slight effect on wall shear stress-related-indices. The deformability of the composite stent-wall region is remarkably limited by the endograft. Our results highlight the importance of considering the interaction between blood flow, the implanted endograft, and the aortic wall to acquire physiologically accurate hemodynamics in post-TEVAR computational studies and the deformation of the aortic wall is responsible for the major EL of the blood flow.

Significance of Hemodynamics Biomarkers, Tissue Biomechanics and Numerical Simulations in the Pathogenesis of Ascending Thoracic Aortic Aneurysms

Guidelines for the treatment of aortic wall diseases are based on measurements of maximum aortic diameter. However, aortic rupture or dissections do occur for small aortic diameters. Growing scientific evidence underlines the importance of biomechanics and hemodynamics in aortic disease development and progression. Wall shear stress (WWS) is an important hemodynamics marker that depends on aortic wall morphology and on the aortic valve function. WSS could be helpful to interpret aortic wall remodeling and define personalized risk criteria. The complementarity of Computational Fluid Dynamics and 4D Magnetic Resonance Imaging as tools for WSS assessment is a promising reality. The potentiality of these innovative technologies will provide maps or atlases of hemodynamics biomarkers to predict aortic tissue dysfunction. Ongoing efforts should focus on the correlation between these non-invasive imaging biomarkers and clinico-pathologic situations for the implementation of personalized medicine in current clinical practice.

FSI modeling on the effect of artery-aneurysm thickness and coil embolization in patient cases

BACKGROUND AND OBJECTIVE

The attainment of a methodology to simulate the hemodynamic in patient-specific cerebral vessels with aneurysms is still a challenge. The novelty of this work is focused on the effect of coil embolization in a realistic cerebral aneurysm, according to the vessel wall thickness and aneurysm thickness, through transient FSI simulations.

METHODS

The quality of the mesh for simulations was checked with a specific mesh convergence study; and the numerical methodology was validated using numerical research data of the literature. The model was implemented in ANSYS® software. The total deformation and equivalent stress evolution in the studied cases, before and after coil embolization, were compared. More than 20 different models were employed due to different arterial wall thickness and aneurysm wall thickness combinations.

RESULTS

The obtained results have showed that deformation and stress values are highly influenced with the sac thickness. The thinner sac aneurysm thickness is, the greater deformation and stress are. The results after coil embolization process have highlighted that considering typical values of arterial wall thickness and aneurysm thickness 0.3 mm and 0.15 mm respectively, a deformation reduction around 50% and a stress reduction around 70% can be achieved.

CONCLUSIONS

The proposed methodology is a step forward in the personalized medicine, quantifying the aneurysm rupture risk reduction, and helping the medical team in the preoperative planning, or to deciding the optimal treatment.

Aortic hemodynamics assessment prior and after valve sparing reconstruction: A patient-specific 4D flow-based FSI model

INTRODUCTION

Valve-sparing root replacement (VSRR) of the ascending aorta is a life-saving procedure for the treatment of aortic aneurysms, but patients remain at risk for post-operative events involving the downstream native aorta, the mechanism for which is uncertain. It is possible that proximal graft replacement of the ascending aorta induces hemodynamics alterations in the descending aorta, which could trigger adverse events. Herein, we present a fluid-structure interaction (FSI) protocol, based on patient-specific geometry and boundary conditions, to assess impact of proximal aortic grafts on downstream aortic hemodynamics and distensibility.

METHODS

Cardiac magnetic resonance (CMR), including MRA, cine-CMR and 4D flow sequences, was performed prior and after VSRR on one subject. Central blood pressure was non-invasively acquired at the time of the CMR: data were used to reconstruct the pre- and post-VSRR model and derive patient-specific boundary conditions for the FSI and a computational fluid dynamic (CFD) analysis with the same settings. Results were validated comparing the predicted velocity field against 4D flow dataset, over four landmarks along the aorta, and the predicted distensibility against the cine-CMR derived value.

RESULTS

Instantaneous velocity magnitudes extracted from 4D flow and FSI were similar (p > 0.05), while CFD-predicted velocity was significantly higher (p < 0.001), especially in the descending aorta of the pre-VSRR model (v_max was 73 cm/s, 76 cm/s and 99 cm/s, respectively). As measured in cine-CMR, FSI predicted an increase in descending aorta distensibility after grafting (i.e., 4.02 to 5.79 10^-3 mmHg^-1). In the descending aorta, the post-VSRR model showed increased velocity, aortic distensibility, stress and strain and wall shear stress.

CONCLUSIONS

Our Results indicate that i) the distensibility of the wall cannot be neglected, and hence the FSI method is necessary to obtain reliable results; ii) graft implantation induces alterations in the hemodynamics and biomechanics along the thoracic aorta, that may trigger adverse vessel remodeling.

Coupling hemodynamics with mechanobiology in patient-specific computational models of ascending thoracic aortic aneurysms

BACKGROUND AND OBJECTIVE

The prevention of ascending thoracic aortic aneurysms (ATAAs), which affect thousands of persons every year worldwide, remains a major issue. ATAAs may be caused by anything that weakens the aortic wall. Altered hemodynamics, which concerns a majority of patients with bicuspid aortic valves, has been shown to be related to such weakening and to contribute to ATAA development and progression. However the underlying mechanisms remain unclear and computational modeling in this field could help significantly to elucidate how hemodynamics and mechanobiology interact in ATAAs.

METHODS

Accordingly, we propose a numerical framework combining computational fluid dynamics and 4D flow magnetic resonance imaging (MRI) coupled with finite element (FE) analyses to simulate growth and remodeling (G&R) occurring in patient-specific aortas in relation with altered hemodynamics. The geometries and the blood velocities obtained from 4D flow MRI are used as boundary conditions for CFD simulations. CFD simulations provide an estimation of the wall shear stress (WSS) and relative residence time (RRT) distribution across the luminal surface of the wall. An initial insult is then applied to the FE model of the aortic wall, assuming that the magnitude of the insult correlates spatially with the normalized RRT distribution obtained from CFD simulations. G&R simulations are then performed. The material behavior of each Gauss point in these FE models is evolved continuously to compensate for the deviation of the actual wall stress distribution from the homeostatic state after the initial insult. The whole approach is illustrated on two healthy and two diseased subjects. The G&R parameters are calibrated against previously established statistical models of ATAA growth rates.

RESULTS

Among the variety of results provided by G&R simulations, the analysis focused especially on the evolution of the wall stiffness, which was shown to be a major risk factor for ATAAs. It was shown that the G&R parameters, such as for instance the rate of collagen production or cell mechanosensitivity, play a critical role in ATAA progression and remodeling.

CONCLUSIONS

These preliminary findings show that patient-specific computational modeling coupling hemodynamics with mechanobiology is a promising approach to explore aneurysm progression.

Estimating aortic thoracic aneurysm rupture risk using tension-strain data in physiological pressure range: an in vitro study

Previous studies have shown that the rupture properties of an ascending thoracic aortic aneurysm (ATAA) are strongly correlated with the pre-rupture response features. In this work, we present a two-step machine learning method to predict where the rupture is likely to occur in ATAA and what safety reserve the structure may have. The study was carried out using ATAA specimens from 15 patients who underwent surgical intervention. Through inflation test, full-field deformation data and post-rupture images were collected, from which the wall tension and surface strain distributions were computed. The tension-strain data in the pressure range of 9-18 kPa were fitted to a third-order polynomial to characterize the response properties. It is hypothesized that the region where rupture is prone to initiate is associated with a high level of tension buildup. A machine learning method is devised to predict the peak risk region. The predicted regions were found to match the actual rupture sites in 13 samples out of the total 15. In the second step, another machine learning model is utilized to predict the tissue's rupture strength in the peak risk region. Results suggest that the ATAA rupture risk can be reasonably predicted using tension-strain response in the physiological range. This may open a pathway for evaluating the ATAA rupture propensity using information of in vivo response.

Numerical knockouts-In silico assessment of factors predisposing to thoracic aortic aneurysms

Myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contribute to the development and enlargement of thoracic aortic aneurysms. Detailed analyses of clinical data and longitudinal studies of murine models continue to provide insight into the natural history of these potentially lethal conditions. Yet, because of the co-existence of multiple risk factors in most cases, it has been difficult to isolate individual effects of the many different factors or to understand how they act in combination. In this paper, we use a data-informed computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing risk factors both in isolation and in combination; these factors include localized losses of elastic fiber integrity, aberrant collagen remodeling, reduced smooth muscle contractility, and dysfunctional mechanosensing or mechanoregulation of extracellular matrix along with superimposed hypertension and aortic aging. In most cases, mild-to-severe localized losses in cellular function or matrix integrity give rise to varying degrees of local dilatations of the thoracic aorta, with enlargement typically exacerbated in cases wherein predisposing risk factors co-exist. The simulations suggest, for the first time, that effects of compromised smooth muscle contractility are more important in terms of dysfunctional mechanosensing and mechanoregulation of matrix than in vessel-level control of diameter and, furthermore, that dysfunctional mechanobiological control can yield lesions comparable to those in cases of compromised elastic fiber integrity. Particularly concerning, therefore, is that loss of constituents such as fibrillin-1, as in Marfan syndrome, can compromise both elastic fiber integrity and mechanosensing.

Aneurysms are local dilatations of the arterial wall that are responsible for significant disability and death. Detailed analyses of clinical data continue to provide insight into the natural history of these potentially lethal conditions, with myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contributing to their development and enlargement. Yet, because of the co-existence of these risk factors in most cases, it has been difficult to isolate individual effects or to understand how they act in combination. In this paper, we use a computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing factors both in isolation and in combination as well as with superimposed hypertension and aging. The present study recovers many findings from mouse models but with new and important observations that promise to guide in vivo and ex vivo studies as we seek to understand and eventually better treat these complex, multi-factorial lesions, with data-informed patient-specific computations eventually the way forward.

A novel formulation for the study of the ascending aortic fluid dynamics with in vivo data

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by applying a rigid wall simplification, on the other side the FSI simulation requires a lot of assumptions for the material properties definition and high computational costs. The aim of this study is to investigate the feasibility of a new strategy, based on Radial Basis Functions (RBF) mesh morphing technique and transient simulations, able to introduce the patient-specific changes in aortic geometry during the cardiac cycle. Starting from medical images, aorta models at different phases of cardiac cycle were reconstructed and a transient shape deformation was obtained by proper activating incremental RBF solutions during the simulation process. The results, in terms of main hemodynamic parameters, were compared with two performed CFD simulations for the aortic model at minimum and maximum volume. Our implemented strategy copes the actual arterial variation during cardiac cycle with high accuracy, capturing the impact of geometrical variations on fluid dynamics, overcoming the complexity of a standard FSI approach.

4D flow imaging of the thoracic aorta: is there an added clinical value?

Four-dimensional (4D) flow MRI has emerged as a powerful non-invasive technique in cardiovascular imaging, enabling to analyse in vivo complex flow dynamics models by quantifying flow parameters and derived features. Deep knowledge of aortic flow dynamics is fundamental to better understand how abnormal flow patterns may promote or worsen vascular diseases. In the perspective of an increasingly personalized and preventive medicine, growing interest is focused on identifying those quantitative functional features which are early predictive markers of pathological evolution. The thoracic aorta and its spectrum of diseases, as the first area of application and development of 4D flow MRI and supported by an extensive experimental validation, represents the ideal model to introduce this technique into daily clinical practice. The purpose of this review is to describe the impact of 4D flow MRI in the assessment of the thoracic aorta and its most common affecting diseases, providing an overview of the actual clinical applications and describing the potential role of derived advanced hemodynamic measures in tailoring follow-up and treatment.

A Proof of Concept of a Non-Invasive Image-Based Material Characterization Method for Enhanced Patient-Specific Computational Modeling

PURPOSE

Computational models of cardiovascular structures rely on their accurate mechanical characterization. A validated method able to infer the material properties of patient-specific large vessels is currently lacking. The aim of the present study is to present a technique starting from the flow-area (QA) method to retrieve basic material properties from magnetic resonance (MR) imaging.

METHODS

The proposed method was developed and tested, first, in silico and then in vitro. In silico, fluid-structure interaction (FSI) simulations of flow within a deformable pipe were run with varying elastic modules (E) between 0.5 and 32 MPa. The proposed QA-based formulation was assessed and modified based on the FSI results to retrieve E values. In vitro, a compliant phantom connected to a mock circulatory system was tested within MR scanning. Images of the phantom were acquired and post-processed according to the modified formulation to infer E of the phantom. Results of in vitro imaging assessment were verified against standard tensile test.

RESULTS

In silico results from FSI simulations were used to derive the correction factor to the original formulation based on the geometrical and material characteristics. In vitro, the modified QA-based equation estimated an average E = 0.51 MPa, 2% different from the E derived from tensile tests (i.e. E = 0.50 MPa).

CONCLUSION

This study presented promising results of an indirect and non-invasive method to establish elastic properties from solely MR images data, suggesting a potential image-based mechanical characterization of large blood vessels.

Recent Advances in Biomechanical Characterization of Thoracic Aortic Aneurysms

Thoracic aortic aneurysm (TAA) is a focal enlargement of the thoracic aorta, but the etiology of this disease is not fully understood. Previous work suggests that various genetic syndromes, congenital defects such as bicuspid aortic valve, hypertension, and age are associated with TAA formation. Though occurrence of TAAs is rare, they can be life-threatening when dissection or rupture occurs. Prevention of these adverse events often requires surgical intervention through full aortic root replacement or implantation of endovascular stent grafts. Currently, aneurysm diameters and expansion rates are used to determine if intervention is warranted. Unfortunately, this approach oversimplifies the complex aortopathy. Improving treatment of TAAs will likely require an increased understanding of the biological and biomechanical factors contributing to the disease. Past studies have substantially contributed to our knowledge of TAAs using various ex vivo, in vivo, and computational methods to biomechanically characterize the thoracic aorta. However, any singular approach typically focuses on only material properties of the aortic wall, intra-aneurysmal hemodynamics, or in vivo vessel dynamics, neglecting combinatorial factors that influence aneurysm development and progression. In this review, we briefly summarize the current understanding of TAA causes, treatment, and progression, before discussing recent advances in biomechanical studies of TAAs and possible future directions. We identify the need for comprehensive approaches that combine multiple characterization methods to study the mechanisms contributing to focal weakening and rupture. We hope this summary and analysis will inspire future studies leading to improved prediction of thoracic aneurysm progression and rupture, improving patient diagnoses and outcomes.

Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

Arterial aneurysms are pathological dilations of blood vessels, which can be of clinical concern due to thrombosis, dissection, or rupture. Aneurysms can form throughout the arterial system, including intracranial, thoracic, abdominal, visceral, peripheral, or coronary arteries. Currently, aneurysm diameter and expansion rates are the most commonly used metrics to assess rupture risk. Surgical or endovascular interventions are clinical treatment options, but are invasive and associated with risk for the patient. For aneurysms in locations where thrombosis is the primary concern, diameter is also used to determine the level of therapeutic anticoagulation, a treatment that increases the possibility of internal bleeding. Since simple diameter is often insufficient to reliably determine rupture and thrombosis risk, computational hemodynamic simulations are being developed to help assess when an intervention is warranted. Created from subject-specific data, computational models have the potential to be used to predict growth, dissection, rupture, and thrombus-formation risk based on hemodynamic parameters, including wall shear stress, oscillatory shear index, residence time, and anomalous blood flow patterns. Generally, endothelial damage and flow stagnation within aneurysms can lead to coagulation, inflammation, and the release of proteases, which alter extracellular matrix composition, increasing risk of rupture. In this review, we highlight recent work that investigates aneurysm geometry, model parameter assumptions, and other specific considerations that influence computational aneurysm simulations. By highlighting modeling validation and verification approaches, we hope to inspire future computational efforts aimed at improving our understanding of aneurysm pathology and treatment risk stratification.

Fluid-structure interaction simulations outperform computational fluid dynamics in the description of thoracic aorta haemodynamics and in the differentiation of progressive dilation in Marfan syndrome patients

Abnormal fluid dynamics at the ascending aorta may be at the origin of aortic aneurysms. This study was aimed at comparing the performance of computational fluid dynamics (CFD) and fluid-structure interaction (FSI) simulations against four-dimensional (4D) flow magnetic resonance imaging (MRI) data; and to assess the capacity of advanced fluid dynamics markers to stratify aneurysm progression risk. Eight Marfan syndrome (MFS) patients, four with stable and four with dilating aneurysms of the proximal aorta, and four healthy controls were studied. FSI and CFD simulations were performed with MRI-derived geometry, inlet velocity field and Young's modulus. Flow displacement, jet angle and maximum velocity evaluated from FSI and CFD simulations were compared to 4D flow MRI data. A dimensionless parameter, the shear stress ratio (SSR), was evaluated from FSI and CFD simulations and assessed as potential correlate of aneurysm progression. FSI simulations successfully matched MRI data regarding descending to ascending aorta flow rates (R 2 = 0.92) and pulse wave velocity (R 2 = 0.99). Compared to CFD, FSI simulations showed significantly lower percentage errors in ascending and descending aorta in flow displacement (-46% ascending, -41% descending), jet angle (-28% ascending, -50% descending) and maximum velocity (-37% ascending, -34% descending) with respect to 4D flow MRI. FSI- but not CFD-derived SSR differentiated between stable and dilating MFS patients. Fluid dynamic simulations of the thoracic aorta require fluid-solid interaction to properly reproduce complex haemodynamics. FSI- but not CFD-derived SSR could help stratifying MFS patients.

Identification of in vivo nonlinear anisotropic mechanical properties of ascending thoracic aortic aneurysm from patient-specific CT scans

Accurate identification of in vivo nonlinear, anisotropic mechanical properties of the aortic wall of individual patients remains to be one of the critical challenges in the field of cardiovascular biomechanics. Since only the physiologically loaded states of the aorta are given from in vivo clinical images, inverse approaches, which take into account of the unloaded configuration, are needed for in vivo material parameter identification. Existing inverse methods are computationally expensive, which take days to weeks to complete for a single patient, inhibiting fast feedback for clinicians. Moreover, the current inverse methods have only been evaluated using synthetic data. In this study, we improved our recently developed multi-resolution direct search (MRDS) approach and the computation time cost was reduced to 1~2 hours. Using the improved MRDS approach, we estimated in vivo aortic tissue elastic properties of two ascending thoracic aortic aneurysm (ATAA) patients from pre-operative gated CT scans. For comparison, corresponding surgically-resected aortic wall tissue samples were obtained and subjected to planar biaxial tests. Relatively close matches were achieved for the in vivo-identified and ex vivo-fitted stress-stretch responses. It is hoped that further development of this inverse approach can enable an accurate identification of the in vivo material parameters from in vivo image data.

Influence of coupled hemodynamics-arterial wall interaction on compliance in a realistic pulmonary artery with variable intravascular wall properties

Pulmonary hypertension is characterized by elevation of pulmonary artery (PA) pressure (p) and structural remodeling of the PA wall, leading to reduction in arterial compliance (c). As a step towards improving diagnosis of pulmonary disease, we use the PA branch geometry (main pulmonary artery (MPA) branching into left (LPA) and right (RPA) pulmonary arteries) obtained from MRI in conjunction with an inverse algorithm to obtain the pre-stress level in the artery walls. Next, a coupled blood-wall interaction (BWI) calculation provides hemodynamic information as well as compliance of the PA walls. We show that the computed load-free geometry from the inverse algorithm exhibits a 27.8% lower inner diameter (d) and 18.5% lower outer d compared to the in vivo geometry from MRI. Further, the mean p computed from the BWI computation in the main PA (p_MPA-n) is within 4% of the mean p_MPA-e (n-numerical; e-experimental). Also, the mean Q computed in the left PA (Q_LPA-n) is within 10% of the mean Q_LPA-e. Finally, the compliance c_MPA-n is computed to be 27% lower than c_MPA-e, while the c_LPA-n is computed to be 20.4% lower than c_LPA-e. Importantly, the PA shows significant intra-vascular variation in compliance, with the MPA showing higher overall compliance compared to the LPA (3.5-4 times).

Computational modeling of bicuspid aortopathy: Towards personalized risk strategies

This paper describes current advances on the application of in-silico for the understanding of bicuspid aortopathy and future perspectives of this technology on routine clinical care. This includes the impact that artificial intelligence can provide to develop computer-based clinical decision support system and that wearable sensors can offer to remotely monitor high-risk bicuspid aortic valve (BAV) patients. First, we discussed the benefit of computational modeling by providing tangible examples of in-silico software products based on computational fluid-dynamic (CFD) and finite-element method (FEM) that are currently transforming the way we diagnose and treat cardiovascular diseases. Then, we presented recent findings on computational hemodynamic and structural mechanics of BAV to highlight the potentiality of patient-specific metrics (not-based on aortic size) to support the clinical-decision making process of BAV-associated aneurysms. Examples of BAV-related personalized healthcare solutions are illustrated.