Physiological simulation of blood flow in the aorta: Comparison of hemodynamic indices as predicted by 3-D FSI, 3-D rigid wall and 1-D models

Computational fluid dynamics; a new diagnostic tool in giant intracerebral aneurysm treatment

Giant intracerebral aneurysms (GIA) comprise up to 5 % of all intracranial aneurysms. The indirect surgical strategy, which leaves the GIA untouched but reverses the blood flow by performing a bypass in combination with proximal parent artery occlusion is a useful method to achieve spontaneous aneurysm occlusion. The goal of this study was to assess the utility of computational fluid dynamics (CFD) in preoperative GIA treatment planning. We hypothesise that CFD simulations will predict treatment results. A fluid-structure interaction (FSI) CFD investigation was performed for the entire arterial brain circulation. The analyses were performed in three patient-specific CT angiogram models. The first served as the reference geometry with a C6 internal carotid artery (ICA) GIA, the second a proximal parent artery occlusion (PAO) and virtual bypass to the frontal M2 branch of the middle cerebral artery (MCA), and the third a proximal PAO in combination with a temporal M2 branch bypass. The volume of "old blood", flow residence time (FRT), dynamic viscosity and haemodynamic changes were also analysed. The "old blood" within the aneurysm in the bypass models reached 41 % after 20 cardiac cycles while in the reference model it was fully washed out. In Bypass 2 "old blood" was also observed in the main trunk of the MCA after 20 cardiac cycles. Extrapolation of the results yielded a duration of 4 years required to replace the "old blood" inside the aneurysm after bypass revascularization. In both bypass models a 7-fold increase in mean blood viscosity in the aneurysm region was noted. Bypass revascularization combined with proximal PAO favours thrombosis. Areas prone to thrombus formation, and subsequently the treatment outcomes, were accurately identified in the preoperative model. Virtual surgical operations can give a remarkable insight into haemodynamics that could support operative decision-making.

Simulation of plaque formation in a realistic geometry of a human aorta: effects of endothelial layer properties, heart rate, and hypertension

Nowadays, cardiovascular diseases are the most common cause of death worldwide. Besides, atherosclerosis is a cardiovascular disease that occurs with persistent narrowing of arteries, especially medium and large-sized arteries. Atherosclerosis begins with a local elevation in the permeability of the arterial wall as a result of endothelial inflammation. Subsequently, excess LDL permeates into the arterial wall. Then, through several chemical responses and reactions, foam cells are produced. These foam cells serve as a crucial indicator for assessing the development of atherosclerosis within the arteries. In this study, the effect of endothelial layer modeling, heart rate (HR) and hypertension on the foam cell accumulation is numerically investigated in a patient-specific geometry of the human thoracic aorta. Navier-Stokes, Darcy, and mass transfer equations are used to obtain the velocity and concentration field within the domain. Regarding the dependence of endothelial cell properties on time-averaged wall shear stress, it is observed that foam cells are mainly concentrated in the outer curvature of the aortic arch, downstream of the left subclavian artery. However, considering oscillatory-shear-rate as the determinant of endothelial cell properties leads to the accumulation of foam cells in the inner curvature of the descending aorta. Regarding the HR, with the increase of HR, the volume average concentration of the foam cell decreases. However, there is no substantial difference between the cases of different HRs. Moreover, foam cell concentration significantly increases in the hypertension case. This result implies that a slight increase in the blood pressure may induce irreparable problems in the circulatory system.

Development of idealized human aortic models for in vitro and in silico hemodynamic studies

Background

The aorta, a central component of the cardiovascular system, plays a pivotal role in ensuring blood circulation. Despite its importance, there is a notable lack of idealized models for experimental and computational studies.

Objective

This study aims to develop computer-aided design (CAD) models for the idealized human aorta, intended for studying hemodynamics or solid mechanics in both in vitro and in silico settings.

Methods

Various parameters were extracted from comprehensive literature sources to evaluate major anatomical characteristics of the aorta in healthy adults, including variations in aortic arch branches and corresponding dimensions. The idealized models were generated based on averages weighted by the cohort size of each study for several morphological parameters collected and compiled from image-based or cadaveric studies, as well as data from four recruited subjects. The models were used for hemodynamics assessment using particle image velocimetry (PIV) measurements and computational fluid dynamics (CFD) simulations.

Results

Two CAD models for the idealized human aorta were developed, focusing on the healthy population. The CFD simulations, which align closely with the PIV measurements, capture the main global flow features and wall shear stress patterns observed in patient-specific cases, demonstrating the capabilities of the designed models.

Conclusions

The collected statistical data on the aorta and the two idealized aorta models, covering prevalent arch variants known as Normal and Bovine types, are shown to be useful for examining the hemodynamics of the aorta. They also hold promise for applications in designing medical devices where anatomical statistics are needed.

A comprehensive MRI-based computational model of blood flow in compliant aorta using radial basis function interpolation

BACKGROUND

Properly understanding the origin and progression of the thoracic aortic aneurysm (TAA) can help prevent its growth and rupture. For a better understanding of this pathogenesis, the aortic blood flow has to be studied and interpreted in great detail. We can obtain detailed aortic blood flow information using magnetic resonance imaging (MRI) based computational fluid dynamics (CFD) with a prescribed motion of the aortic wall.

METHODS

We performed two different types of simulations-static (rigid wall) and dynamic (moving wall) for healthy control and a patient with a TAA. For the latter, we have developed a novel morphing approach based on the radial basis function (RBF) interpolation of the segmented 4D-flow MRI geometries at different time instants. Additionally, we have applied reconstructed 4D-flow MRI velocity profiles at the inlet with an automatic registration protocol.

RESULTS

The simulated RBF-based movement of the aorta matched well with the original 4D-flow MRI geometries. The wall movement was most dominant in the ascending aorta, accompanied by the highest variation of the blood flow patterns. The resulting data indicated significant differences between the dynamic and static simulations, with a relative difference for the patient of 7.47±14.18% in time-averaged wall shear stress and 15.97±43.32% in the oscillatory shear index (for the whole domain).

CONCLUSIONS

In conclusion, the RBF-based morphing approach proved to be numerically accurate and computationally efficient in capturing complex kinematics of the aorta, as validated by 4D-flow MRI. We recommend this approach for future use in MRI-based CFD simulations in broad population studies. Performing these would bring a better understanding of the onset and growth of TAA.

Hemodynamics and wall shear metrics in a pulmonary autograft: Comparing a fluid-structure interaction and computational fluid dynamics approach

OBJECTIVE

In young patients, aortic valve disease is often treated by placement of a pulmonary autograft (PA) which adapts to its new environment through growth and remodeling. To better understand the hemodynamic forces acting on the highly distensible PA in the acute phase after surgery, we developed a fluid-structure interaction (FSI) framework and comprehensively compared hemodynamics and wall shear-stress (WSS) metrics with a computational fluid dynamic (CFD) simulation.

METHODS

The FSI framework couples a prestressed non-linear hyperelastic arterial tissue model with a fluid model using the in-house coupling code CoCoNuT. Geometry, material parameters and boundary conditions are based on in-vivo measurements. Hemodynamics, time-averaged WSS (TAWSS), oscillatory shear index (OSI) and topological shear variation index (TSVI) are evaluated qualitatively and quantitatively for 3 different sheeps.

RESULTS

Despite systolic-to-diastolic volumetric changes of the PA in the order of 20 %, the point-by-point correlation of TAWSS and OSI obtained through CFD and FSI remains high (r > 0.9, p < 0.01) for TAWSS and (r > 0.8, p < 0.01) for OSI). Instantaneous WSS divergence patterns qualitatively preserve similarities, but large deformations of the PA leads to a decrease of the correlation between FSI and CFD resolved TSVI (r < 0.7, p < 0.01). Moderate co-localization between FSI and CFD is observed for low thresholds of TAWSS and high thresholds of OSI and TSVI.

CONCLUSION

FSI might be warranted if we were to use the TSVI as a mechano-biological driver for growth and remodeling of PA due to varying intra-vascular flow structures and near wall hemodynamics because of the large expansion of the PA.

Patient-Specific Numerical Simulations of Coronary Artery Hemodynamics and Biomechanics: A Pathway to Clinical Use

PURPOSE

Numerical models that simulate the behaviors of the coronary arteries have been greatly improved by the addition of fluid-structure interaction (FSI) methods. Although computationally demanding, FSI models account for the movement of the arterial wall and more adequately describe the biomechanical conditions at and within the arterial wall. This offers greater physiological relevance over Computational Fluid Dynamics (CFD) models, which assume the walls do not move or deform. Numerical simulations of patient-specific cases have been greatly bolstered by the use of imaging modalities such as Computed Tomography Angiography (CTA), Magnetic Resonance Imaging (MRI), Optical Coherence Tomography (OCT), and Intravascular Ultrasound (IVUS) to reconstruct accurate 2D and 3D representations of artery geometries. The goal of this study was to conduct a comprehensive review on CFD and FSI models on coronary arteries, and evaluate their translational potential.

METHODS

This paper reviewed recent work on patient-specific numerical simulations of coronary arteries that describe the biomechanical conditions associated with atherosclerosis using CFD and FSI models. Imaging modality for geometry collection and clinical applications were also discussed.

RESULTS

Numerical models using CFD and FSI approaches are commonly used to study biomechanics within the vasculature. At high temporal and spatial resolution (compared to most cardiac imaging modalities), these numerical models can generate large amount of biomechanics data.

CONCLUSIONS

Physiologically relevant FSI models can more accurately describe atherosclerosis pathogenesis, and help to translate biomechanical assessment to clinical evaluation.

Modelling large scale artery haemodynamics from the heart to the eye in response to simulated microgravity

We investigated variations in haemodynamics in response to simulated microgravity across a semi-subject-specific three-dimensional (3D) continuous arterial network connecting the heart to the eye using computational fluid dynamics (CFD) simulations. Using this model we simulated pulsatile blood flow in an upright Earth gravity case and a simulated microgravity case. Under simulated microgravity, regional time-averaged wall shear stress (TAWSS) increased and oscillatory shear index (OSI) decreased in upper body arteries, whilst the opposite was observed in the lower body. Between cases, uniform changes in TAWSS and OSI were found in the retina across diameters. This work demonstrates that 3D CFD simulations can be performed across continuously connected networks of small and large arteries. Simulated results exhibited similarities to low dimensional spaceflight simulations and measured data-specifically that blood flow and shear stress decrease towards the lower limbs and increase towards the cerebrovasculature and eyes in response to simulated microgravity, relative to an upright position in Earth gravity.

Learning reduced-order models for cardiovascular simulations with graph neural networks

Reduced-order models based on physics are a popular choice in cardiovascular modeling due to their efficiency, but they may experience loss in accuracy when working with anatomies that contain numerous junctions or pathological conditions. We develop one-dimensional reduced-order models that simulate blood flow dynamics using a graph neural network trained on three-dimensional hemodynamic simulation data. Given the initial condition of the system, the network iteratively predicts the pressure and flow rate at the vessel centerline nodes. Our numerical results demonstrate the accuracy and generalizability of our method in physiological geometries comprising a variety of anatomies and boundary conditions. Our findings demonstrate that our approach can achieve errors below 3% for pressure and flow rate, provided there is adequate training data. As a result, our method exhibits superior performance compared to physics-based one-dimensional models while maintaining high efficiency at inference time.

Integrated particle image velocimetry and fluid-structure interaction analysis for patient-specific abdominal aortic aneurysm studies

BACKGROUND

Understanding the hemodynamics of an abdominal aortic aneurysm (AAA) is crucial for risk assessment and treatment planning. This study introduces a low-cost, patient-specific in vitro AAA model to investigate hemodynamics using particle image velocimetry (PIV) and flow-simulating circuit, validated through fluid-structure interaction (FSI) simulations.

METHODS

In this study, 3D printing was employed to manufacture a flexible patient-specific AAA phantom using a lost-core casting technique. A pulsatile flow circuit was constructed using off-the-shelf components. A particle image velocimetry (PIV) setup was built using an affordable laser source and global shutter camera, and finally, the flow field inside the AAA was analyzed using open-source software. Fluid-structure interaction (FSI) simulations were performed to enhance our understanding of the flow field, and the results were validated by PIV analysis. Both steady-state and transient flow conditions were investigated.

RESULTS

Our experimental setup replicated physiological conditions, analyzing arterial wall deformations and flow characteristics within the aneurysm. Under constant flow, peak wall deformations and flow velocities showed deviations within - 12% to + 27% and - 7% to + 5%, respectively, compared to FSI simulations. Pulsatile flow conditions further demonstrated a strong correlation (Pearson coefficient 0.85) in flow velocities and vectors throughout the cardiac cycle. Transient phenomena, particularly the formation and progression of vortex structures during systole, were consistently depicted between experimental and numerical models.

CONCLUSIONS

By bridging high-fidelity experimental observations with comprehensive computational analyses, this study underscores the potential of integrated methodologies in enhancing our understanding of AAA pathophysiology. The convergence of realistic AAA phantoms, precise PIV measurements at affordable cost point, and validated FSI models heralds a new paradigm in vascular research, with significant implications for personalized medicine and bioengineering innovations.

Calibration of the Mechanical Boundary Conditions for a Patient-Specific Thoracic Aorta Model Including the Heart Motion Effect

OBJECTIVE

We propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect.

METHODS

We first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI. A rigid-wall fluid-dynamic simulation is performed to derive the time-varying wall pressure field. We build the finite element model considering patient-specific material properties and imposing the derived pressure field and the motion at the annulus boundary. The calibration, which involves the zero-pressure state computation, is based on purely structural simulations. After obtaining the vessel boundaries from the cine-MRI sequences, an iterative procedure is performed to minimize the distance between them and the corresponding boundaries derived from the deformed structural model. A strongly-coupled fluid-structure interaction (FSI) analysis is finally performed with the tuned parameters and compared to the purely structural simulation.

RESULTS AND CONCLUSION

The calibration with structural simulations allows to reduce maximum and mean distances between image-derived and simulation-derived boundaries from 8.64 mm to 6.37 mm and from 2.24 mm to 1.83 mm, respectively. The maximum root mean square error between the deformed structural and FSI surface meshes is 0.19 mm. This procedure may prove crucial for increasing the model fidelity in replicating the real aortic root kinematics.

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning

OBJECTIVE

In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides valuable information for the computation of new biomarkers using computational fluid dynamics (CFD). However, accurate segmentation of the aorta is required. Thus, our objective is to evaluate the performance of two automatic segmentation methods on the calculation of aortic wall pressure.

METHODS

Automatic segmentation of the aorta was performed with methods based on deep learning and multi-atlas using the systolic phase in the 4D flow MRI magnitude image of 36 patients. Using mesh morphing, isotopological meshes were generated, and CFD was performed to calculate the aortic wall pressure. Node-to-node comparisons of the pressure results were made to identify the most robust automatic method respect to the pressures obtained with a manually segmented model.

RESULTS

Deep learning approach presented the best segmentation performance with a mean Dice similarity coefficient and a mean Hausdorff distance (HD) equal to 0.92+/- 0.02 and 21.02+/- 24.20 mm, respectively. At the global level HD is affected by the performance in the abdominal aorta. Locally, this distance decreases to 9.41+/- 3.45 and 5.82+/- 6.23 for the ascending and descending thoracic aorta, respectively. Moreover, with respect to the pressures from the manual segmentations, the differences in the pressures computed from deep learning were lower than those computed from multi-atlas method.

CONCLUSION

To reduce biases in the calculation of aortic wall pressure, accurate segmentation is needed, particularly in regions with high blood flow velocities. Thus, the deep learning segmen-tation method should be preferred.

Wall shear stress and pressure patterns in aortic stenosis patients with and without aortic dilation captured by high-performance image-based computational fluid dynamics

Spatial patterns of elevated wall shear stress and pressure due to blood flow past aortic stenosis (AS) are studied using GPU-accelerated patient-specific computational fluid dynamics. Three cases of moderate to severe AS, one with a dilated ascending aorta and two within the normal range (root diameter less than 4cm) are simulated for physiological waveforms obtained from echocardiography. The computational framework is built based on sharp-interface Immersed Boundary Method, where aortic geometries segmented from CT angiograms are integrated into a high-order incompressible Navier-Stokes solver. The key question addressed here is, given the presence of turbulence due to AS which increases wall shear stress (WSS) levels, why some AS patients undergo much less aortic dilation. Recent case studies of AS have linked the existence of an elevated WSS hotspot (due to impingement of AS on the aortic wall) to the dilation process. Herein we further investigate the WSS distribution for cases with and without dilation to understand the possible hemodynamics which may impact the dilation process. We show that the spatial distribution of elevated WSS is significantly more focused for the case with dilation than those without dilation. We further show that this focal area accommodates a persistent pocket of high pressure, which may have contributed to the dilation process through an increased wall-normal forcing. The cases without dilation, on the contrary, showed a rather oscillatory pressure behaviour, with no persistent pressure "buildup" effect. We further argue that a more proximal branching of the aortic arch could explain the lack of a focal area of elevated WSS and pressure, because it interferes with the impingement process due to fluid suction effects. These phenomena are further illustrated using an idealized aortic geometry. We finally show that a restored inflow eliminates the focal area of elevated WSS and pressure zone from the ascending aorta.

Effect of aortic bifurcation geometry on pressure and peak wall stress in abdominal aorta: Fluid-structure interaction study

BACKGROUND AND OBJECTIVE

Geometry of aorto-iliac bifurcation may affect pressure and wall stress in aorta and thus potentially serve as a predictor of abdominal aortic aneurysm (AAA), similarly to hypertension.

METHODS

Effect of aorto-iliac bifurcation geometry was investigated via parametric analysis based on two-way weakly coupled fluid-structure interaction simulations. The arterial wall was modelled as isotropic hyperelastic monolayer, and non-Newtonian behaviour was introduced for the fluid. Realistic boundary conditions of the pulsatile blood flow were used on the basis of experiments in literature and their time shift was tailored to the pulse wave velocity in the model to obtain physiological wave shapes. Eighteen idealized and one patient-specific geometries of human aortic tree with common iliac and renal arteries were considered with different angles between abdominal aorta (AA) and both iliac arteries and different area ratios (AR) of iliac and aortic luminal cross sections.

RESULTS

Peak wall stress (PWS) and systolic blood pressure (SBP) were insensitive to the aorto-iliac angles but sensitive to the AR: when AR decreased by 50%, the PWS and SBP increased by up to 18.4% and 18.8%, respectively.

CONCLUSIONS

Lower AR (as a result of the iliac stenosis or aging), rather than the aorto-iliac angles increases the BP in the AA and may be thus a risk factor for the AAA development.

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.

Fluid-structure interaction study for biomechanics and risk factors in Stanford type A aortic dissection

Aortic dissection is a life-threatening condition with a rising prevalence in the elderly population, possibly as a consequence of the increasing population life expectancy. Untreated aortic dissection can lead to myocardial infarction, aortic branch malperfusion or occlusion, rupture, aneurysm formation and death. This study aims to assess the potential of a biomechanical model in predicting the risks of a non-dilated thoracic aorta with Stanford type A dissection. To achieve this, a fully coupled fluid-structure interaction model was developed under realistic blood flow conditions. This model of the aorta was developed by considering three-dimensional artery geometry, multiple artery layers, hyperelastic artery wall, in vivo-based physiological time-varying blood velocity profiles, and non-Newtonian blood behaviours. The results demonstrate that in a thoracic aorta with Stanford type A dissection, the wall shear stress (WSS) is significantly low in the ascending aorta and false lumen, leading to potential aortic dilation and thrombus formation. The results also reveal that the WSS is highly related to blood flow patterns. The aortic arch region near the brachiocephalic and left common carotid artery is prone to rupture, showing a good agreement with the clinical reports. The results have been translated into their potential clinical relevance by revealing the role of the stress state, WSS and flow characteristics as the main parameters affecting lesion progression, including rupture and aneurysm. The developed model can be tailored for patient-specific studies and utilised as a predictive tool to estimate aneurysm growth and initiation of wall rupture inside the human thoracic aorta.

Recasting Current Knowledge of Human Fetal Circulation: The Importance of Computational Models

Computational hemodynamic simulations are becoming increasingly important for cardiovascular research and clinical practice, yet incorporating numerical simulations of human fetal circulation is relatively underutilized and underdeveloped. The fetus possesses unique vascular shunts to appropriately distribute oxygen and nutrients acquired from the placenta, adding complexity and adaptability to blood flow patterns within the fetal vascular network. Perturbations to fetal circulation compromise fetal growth and trigger the abnormal cardiovascular remodeling that underlies congenital heart defects. Computational modeling can be used to elucidate complex blood flow patterns in the fetal circulatory system for normal versus abnormal development. We present an overview of fetal cardiovascular physiology and its evolution from being investigated with invasive experiments and primitive imaging techniques to advanced imaging (4D MRI and ultrasound) and computational modeling. We introduce the theoretical backgrounds of both lumped-parameter networks and three-dimensional computational fluid dynamic simulations of the cardiovascular system. We subsequently summarize existing modeling studies of human fetal circulation along with their limitations and challenges. Finally, we highlight opportunities for improved fetal circulation models.

Impact of wall displacements on the large-scale flow coherence in ascending aorta

In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics. In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS). From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.

Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease

Physics-based computational models of the cardiovascular system are increasingly used to simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and diseased states. While predictive models using computational fluid dynamics (CFD) originated primarily for use in surgical planning, their application now extends well beyond this purpose. In this review, we describe an increasingly wide range of modeling applications aimed at uncovering fundamental mechanisms of disease progression and development, performing model-guided design, and generating testable hypotheses to drive targeted experiments. Increasingly, models are incorporating multiple physical processes spanning a wide range of time and length scales in the heart and vasculature. With these expanded capabilities, clinical adoption of patient-specific modeling in congenital and acquired cardiovascular disease is also increasing, impacting clinical care and treatment decisions in complex congenital heart disease, coronary artery disease, vascular surgery, pulmonary artery disease, and medical device design. In support of these efforts, we discuss recent advances in modeling methodology, which are most impactful when driven by clinical needs. We describe pivotal recent developments in image processing, fluid-structure interaction, modeling under uncertainty, and reduced order modeling to enable simulations in clinically relevant timeframes. In all these areas, we argue that traditional CFD alone is insufficient to tackle increasingly complex clinical and biological problems across scales and systems. Rather, CFD should be coupled with appropriate multiscale biological, physical, and physiological models needed to produce comprehensive, impactful models of mechanobiological systems and complex clinical scenarios. With this perspective, we finally outline open problems and future challenges in the field.

Preliminary findings on left atrial appendage occlusion simulations applying different endocardial devices

Atrial fibrillation (AF) is one of the most investigated arrhythmias since it is associated with a five-fold increase in the risk of strokes. Left atrium dilation and unbalanced and irregular contraction caused by AF favour blood stasis and, consequently, stroke risk. The left atrial appendage (LAA) is the site of the highest clots formation, increasing the incidence of stroke in AF population. For many years oral anticoagulation therapy has been the most used AF treatment option available to decrease stroke risk. Unfortunately, several contraindications including bleeding risk increase, interference with other drugs and with multiorgan functioning, might outweigh its remarkable benefits on thromboembolic events. For these reasons, in recent years, other approaches have been designed, including LAA percutaneous closure. Unfortunately, nowadays, LAA occlusion (LAAO) is restricted to small subgroups of patients and require a certain level of expertise and training to successfully complete the procedure without complications. The most critical clinical problems associated with LAAO are represented by peri-device leaks and device related thrombus (DRT). The anatomical variability of the LAA plays a key role in the choice of the correct LAA occlusion device and in its correct positioning with respect to the LAA ostium during the implant. In this scenario, computational fluid dynamics (CFD) simulations could have a crucial role in improving LAAO intervention. The aim of this study was to simulate the fluid dynamics effects of LAAO in AF patients to predict hemodynamic changes due to the occlusion. LAAO was simulated by applying two different types of closure devices based on the plug and the pacifier principles on 3D LA anatomical models derived from real clinical data in five AF patients. CFD simulations were performed on the left atrium model before and after the LAAO intervention with each device. Blood velocity, particle washout and endothelial damage were computed to quantify flow pattern changes after the occlusion in relation to the thrombogenic risk. Our preliminary results confirmed an improved blood washout after the simulated implants and the capability of foreseeing thrombogenic risk based on endothelial damage and maximum blood velocities in different scenarios. This tool may help to identify effective device configurations in limiting stroke risk for patient-specific LA morphologies.

Automated generation of 0D and 1D reduced-order models of patient-specific blood flow

Three-dimensional (3D) cardiovascular fluid dynamics simulations typically require hours to days of computing time on a high-performance computing cluster. One-dimensional (1D) and lumped-parameter zero-dimensional (0D) models show great promise for accurately predicting blood bulk flow and pressure waveforms with only a fraction of the cost. They can also accelerate uncertainty quantification, optimization, and design parameterization studies. Despite several prior studies generating 1D and 0D models and comparing them to 3D solutions, these were typically limited to either 1D or 0D and a singular category of vascular anatomies. This work proposes a fully automated and openly available framework to generate and simulate 1D and 0D models from 3D patient-specific geometries, automatically detecting vessel junctions and stenosis segments. Our only input is the 3D geometry; we do not use any prior knowledge from 3D simulations. All computational tools presented in this work are implemented in the open-source software platform SimVascular. We demonstrate the reduced-order approximation quality against rigid-wall 3D solutions in a comprehensive comparison with N = 72 publicly available models from various anatomies, vessel types, and disease conditions. Relative average approximation errors of flows and pressures typically ranged from 1% to 10% for both 1D and 0D models, measured at the outlets of terminal vessel branches. In general, 0D model errors were only slightly higher than 1D model errors despite requiring only a third of the 1D runtime. Automatically generated ROMs can significantly speed up model development and shift the computational load from high-performance machines to personal computers.

A predictive patient-specific computational model of coronary artery bypass grafts for potential use by cardiac surgeons to guide selection of graft configurations

Cardiac surgeons face a significant degree of uncertainty when deciding upon coronary artery bypass graft configurations for patients with coronary artery disease. This leads to significant variation in preferred configuration between different surgeons for a particular patient. Additionally, for the majority of cases, there is no consensus regarding the optimal grafting strategy. This situation results in the tendency for individual surgeons to opt for a “one size fits all” approach and use the same grafting configuration for the majority of their patients neglecting the patient-specific nature of the diseased coronary circulation. Quantitative metrics to assess the adequacy of coronary bypass graft flows have recently been advocated for routine intraoperative use by cardiac surgeons. In this work, a novel patient-specific 1D-0D computational model called “COMCAB” is developed to provide the predictive haemodynamic parameters of functional graft performance that can aid surgeons to avoid configurations with grafts that have poor flow and thus poor patency. This model has significant potential for future expanded applications.

Effects of different bypass surgeries on LSA revascularization in patients with left subclavian occlusion

INTRO

Left subclavian artery bypass surgery is mainly carried out for patients with severe left subclavian occlusion. This paper aimed to evaluate the hemodynamic effects of different surgical bypass modes on left subclavian artery revascularization.

METHODS

Three-dimensional models of the aorta were reconstructed from CTA images of a patient with left subclavian artery occlusion, a patient with type B aortic dissection with left subclavian artery coverage during thoracic endovascular aortic repair, and a healthy 74 year-old man, resulting in six modes for each person: healthy left subclavian artery mode, left subclavian artery occlusion mode and four bypass modes. Hemodynamic parameters, including flow field, flow distribution, pressure gradient, and wall shear stress, were calculated using computational fluid dynamics.

RESULTS

After left subclavian artery bypass surgery, distal left subclavian artery blood flow resulting from left common carotid artery to distal left subclavian artery bypass was 100% of that in the healthy mode, while the other modes yielded flows at least 91%. Moreover, reversed flow only completely disappeared with left common carotid artery to distal left subclavian artery bypass, whereas reverse flow was observed in the other three modes in early systole.

CONCLUSION

Left common carotid artery to distal left subclavian artery bypass can effectively reduce reverse blood flow in the left vertebral artery, and it is a feasible, effective, and safe option for left subclavian artery revascularization in patients with left subclavian occlusion.

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.

An efficient, localised approach for the simulation of elastic blood vessels using the lattice Boltzmann method

Many numerical studies of blood flow impose a rigid wall assumption due to the simplicity of its implementation compared to a full coupling with a solid mechanics model. In this paper, we present a localised method for incorporating the effects of elastic walls into blood flow simulations using the lattice Boltzmann method implemented by the open-source code HemeLB. We demonstrate that our approach is able to more accurately capture the flow behaviour expected in elastic walled vessels than ones with rigid walls. Furthermore, we show that this can be achieved with no loss of computational performance and remains strongly scalable on high performance computers. We finally illustrate that our approach captures the same trends in wall shear stress distribution as those observed in studies using a rigorous coupling between fluid dynamics and solid mechanics models to solve flow in personalised vascular geometries. These results demonstrate that our model can be used to efficiently and effectively represent flows in elastic blood vessels.

In vitro pulsatile flow study in compliant and rigid ascending aorta phantoms by stereo particle image velocimetry

The aorta is a high risk region for cardiovascular disease (CVD). Haemodynamic patterns leading to CVD are not well established despite numerous experimental and numerical studies. Most overlook effects of arterial compliance and pulsatile flow. However, rigid wall assumptions can lead to overestimation of wall shear stress; a key CVD determinant. This work investigates the effect of compliance on aortic arch haemodynamics experiencing pulsatility. Rigid and compliant phantoms of the arch and brachiocephalic branch (BCA) were manufactured. Stereoscopic particle image velocimetry was used to observe velocity fields. Higher velocity magnitude was observed in the rigid BCA during acceleration. However, during deceleration, the compliant phantom experienced higher velocity. During deceleration, a low velocity region initiated and increased in size in the BCA of both phantoms with irregular shape in the compliant. At mid-deceleration, considerably larger recirculation was observed under compliance compared to rigid. Another recirculation region formed and increased in size on the inner wall of the arch in the compliant during late deceleration, but not rigid. The recirculation regions witnessed identify as high risk areas for atherosclerosis formation by a previous ex-vivo study. The results demonstrate necessity of compliance and pulsatility in haemodynamic studies to obtain highly relevant clinical outcomes.

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.

Numerical analysis of the hemodynamics of rat aorta based on magnetic resonance imaging and fluid-structure interaction

Murine models have been widely used to investigate the mechanobiology of aortic atherosclerosis and dissections, which develop preferably at different anatomic locations of aorta. Based MRI and finite element analysis with fluid-structure interaction, we numerically investigated factors that may affect the blood flow and structural mechanics of rat aorta. The results indicated that aortic root motion greatly increases time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), displacement of the aorta, and enhances helical flow pattern but has limited influence on effective stress, which is highly modulated by blood pressure. Moreover, the influence of the motion component on these indicators is different with axial motion more obvious than planar motion. Surrounding fixation of the intercostal arteries and the branch vessels on aortic arch would reduce the influence of aortic root motion. The compliance of the aorta has different influences at different regions, leading to decrease in TAWSS and helical flow, increase in OSI, RRT at the aortic arch, but has reversed effects on the branch vessels. When compared with the steady flow, the pulsatile blood flow would obviously increase the WSS, the displacement, and the effective stress in most regions. In conclusion, to accurately quantify the blood flow and structural mechanics of rat aorta, the motion of the aortic root, the compliance of aortic wall, and the pulsation of blood flow should be considered. However, when only focusing on the effective stress in rat aorta, the motion of the aortic root may be neglected.

Towards a Clinical Implementation of Measuring the Elastic Modulus of the Aorta from Cardiac Computed Tomography Images

OBJECTIVE

The elasticity of the aortic wall varies depending on age, vessel location, and the presence of aortic diseases. Noninvasive measurement will be a powerful tool to understand the mechanical state of the aorta in a living human body. This study aimed to determine the elastic modulus of the aorta using computed tomography images.

METHODS

We constructed our original formulae based on mechanics of materials. Then, we performed computed tomography scans of a silicon rubber tube by applying four pressure conditions to the lumen. The segment elastic modulus was calculated from the scanned images using our formulae. The actual modulus was measured using a tensile loading test for comparison.

RESULTS

The segment moduli of elasticity from the images were 0.525 [0.524, 0.527], 0.524 [0.520, 0.524], 0.520 [0.515, 0.523], and 0.522 [0.516, 0.532] (unit: MPa, median [25%, 75% quantiles]) for the four pressure conditions, respectively. The corresponding measurements in the tensile test were 0.548 [0.539, 0.566], 0.535 [0.528, 0.553], 0.526 [0.513, 0.543], and 0.523 [0.508, 0.530], respectively. These results indicated errors of 4.2%, 2.1%, 1.1%, and 0.2%, respectively.

CONCLUSION

Our formulae provided good estimations of the segment elastic moduli of a silicon rubber tube under physiological pressure conditions using the computed tomography images.

SIGNIFICANCE

In addition to the elasticity, the formulae provide the strain energy as well. These properties can be better predictors of aortic diseases. The formulae consist of clinical parameters commonly used in medical settings (pressure, diameter, and wall thickness).

Synthetic Database of Aortic Morphometry and Hemodynamics: Overcoming Medical Imaging Data Availability

Modeling of hemodynamics and artificial intelligence have great potential to support clinical diagnosis and decision making. While hemodynamics modeling is extremely time- and resource-consuming, machine learning (ML) typically requires large training data that are often unavailable. The aim of this study was to develop and evaluate a novel methodology generating a large database of synthetic cases with characteristics similar to clinical cohorts of patients with coarctation of the aorta (CoA), a congenital heart disease associated with abnormal hemodynamics. Synthetic data allows use of ML approaches to investigate aortic morphometric pathology and its influence on hemodynamics. Magnetic resonance imaging data (154 patients as well as of healthy subjects) of aortic shape and flow were used to statistically characterize the clinical cohort. The methodology generating the synthetic cohort combined statistical shape modeling of aortic morphometry and aorta inlet flow fields and numerical flow simulations. Hierarchical clustering and non-linear regression analysis were successfully used to investigate the relationship between morphometry and hemodynamics and to demonstrate credibility of the synthetic cohort by comparison with a clinical cohort. A database of 2652 synthetic cases with realistic shape and hemodynamic properties was generated. Three shape clusters and respective differences in hemodynamics were identified. The novel model predicts the CoA pressure gradient with a root mean square error of 4.6 mmHg. In conclusion, synthetic data for anatomy and hemodynamics is a suitable means to address the lack of large datasets and provide a powerful basis for ML to gain new insights into cardiovascular diseases.

Application of physics-based flow models in cardiovascular medicine: Current practices and challenges

Personalized physics-based flow models are becoming increasingly important in cardiovascular medicine. They are a powerful complement to traditional methods of clinical decision-making and offer a wealth of physiological information beyond conventional anatomic viewing using medical imaging data. These models have been used to identify key hemodynamic biomarkers, such as pressure gradient and wall shear stress, which are associated with determining the functional severity of cardiovascular diseases. Importantly, simulation-driven diagnostics can help researchers understand the complex interplay between geometric and fluid dynamic parameters, which can ultimately improve patient outcomes and treatment planning. The possibility to compute and predict diagnostic variables and hemodynamics biomarkers can therefore play a pivotal role in reducing adverse treatment outcomes and accelerate development of novel strategies for cardiovascular disease management.

Effect of percutaneous aortic valve position on stress map in ascending aorta: A fluid-structure interaction analysis

Transcatheter aortic valve implantation (TAVI) is an increasingly widespread procedure. Although this intervention is indicated for high and low surgical risk patients, some issues still remain, such as prosthesis positioning optimization in the aortic annulus. Coaxial positioning of the percutaneous prosthesis influences directly on the aortic wall stress map. The determination of the mechanical stress that acts on the vascular endothelium resulting from blood flow can be considered an important task, since TAVI positioning can lead to unfavorable hemodynamic patterns, resulting in changes in parietal stress, such as those found in post-stenotic dilatation region. This research aims to investigate the influence of the prosthetic valve inclination angle in the mechanical stresses acting in the ascending aortic wall. Aortic compliance and blood flow during cardiac cycle were numerically obtained using fluid structure interaction. The aortic model was developed through segmentation of a computed tomography image of a specific patient submitted to TAVI. When compared to standard position (coaxiality match between the prosthesis and the aortic annulus), the inclination of 4° directed to the left main coronary artery decreased the aortic wall area with high values of wall shear stress and pressure. Coaxial positioning optimization of percutaneous aortic prosthesis may decrease the high mechanical stress area. These changes may be important to reduce the aortic remodeling process, vascular calcification or even the prosthesis half-life. Computational fluid dynamics makes room for personalized medicine, with manufactured prosthesis tailored to each patient.

Multiscale modeling of blood flow to assess neurological complications in patients supported by venoarterial extracorporeal membrane oxygenation

Computational blood flow models in large arteries elucidate valuable relationships between cardiovascular diseases and hemodynamics, leading to improvements in treatment planning and clinical decision making. One such application with potential to benefit from simulation is venoarterial extracorporeal membrane oxygenation (VA-ECMO), a support system for patients with cardiopulmonary failure. VA-ECMO patients develop high rates of neurological complications, partially due to abnormal blood flow throughout the vasculature from the VA-ECMO system. To better understand these hemodynamic changes, it is important to resolve complex local flow parameters derived from three-dimensional (3D) fluid dynamics while also capturing the impact of VA-ECMO support throughout the systemic arterial system. As high-resolution 3D simulations of the arterial network remain computationally expensive and intractable for large studies, a validated, multiscale model is needed to compute both global effects and high-fidelity local hemodynamics. In this work, we developed and demonstrated a framework to model hemodynamics in VA-ECMO patients using coupled 3D and one-dimensional (1D) models (1D→3D). We demonstrated the ability of these multiscale models to simulate complex flow patterns in specific regions of interest while capturing bulk flow throughout the systemic arterial system. We compared 1D, 3D, and 1D→3D coupled models and found that multiscale models were able to sufficiently capture both global and local hemodynamics in the cerebral arteries and aorta in VA-ECMO patients. This study is the first to develop and compare 1D, 3D, and 1D→ 3D coupled models on the larger arterial system scale in VA-ECMO patients, with potential use for other large scale applications.

A nonlinear rotation-free shell formulation with prestressing for vascular biomechanics

We implement a nonlinear rotation-free shell formulation capable of handling large deformations for applications in vascular biomechanics. The formulation employs a previously reported shell element that calculates both the membrane and bending behavior via displacement degrees of freedom for a triangular element. The thickness stretch is statically condensed to enforce vessel wall incompressibility via a plane stress condition. Consequently, the formulation allows incorporation of appropriate 3D constitutive material models. We also incorporate external tissue support conditions to model the effect of surrounding tissue. We present theoretical and variational details of the formulation and verify our implementation against axisymmetric results and literature data. We also adapt a previously reported prestress methodology to identify the unloaded configuration corresponding to the medically imaged in vivo vessel geometry. We verify the prestress methodology in an idealized bifurcation model and demonstrate the significance of including prestress. Lastly, we demonstrate the robustness of our formulation via its application to mouse-specific models of arterial mechanics using an experimentally informed four-fiber constitutive model.

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.

The functional limits of the aneurysmal aortic root. A unique pressure testing apparatus

BACKGROUND

The aortic root has unique embryological development and is a highly sophisticated and complex structure. In studies that report on the biomechanical characteristics of the thoracic aorta, distinction between the aortic root and ascending aorta regions is nonexistent. Our objective is to determine the maximal pressures at which dissection occurs or tissue failure occurs in the aortic root compared to that of the ascending aorta in the presence of aortic aneurysms. This may help guide preoperative monitoring, diagnosis and the decision for operative intervention for aortic root aneurysms in the normal and susceptible populations.

METHODS

We developed a simple aortic root and ascending aorta pressure testing unit in series. Ten fresh porcine hearts were obtained from the local abattoir (n = 5 aortic root and n = 5 ascending aorta for comparison). Using a saline filled needle and syringe, artificial fluid-filled aneurysms were created between the intima and medial layers of the aortic root. The aorta lumen was then progressively filled with saline solution. Pressure measurement was taken at time of loss of tissue integrity, obvious tissue dissection or aneurysm rupture, and the tissue structure was then visually examined.

RESULTS

In the aortic root, mean maximal pressure (mmHg) at tissue failure was 208 mmHg. Macroscopic examination revealed luminal tears around the coronary ostia in 2/5 specimens, and in all specimens, there was propagation of the dissection in the aortic root in a circumferential direction. In all ascending aorta specimens, the maximal aortic pressures exceeded 300 mmHg without tissue failure or dissection, and eventual apparatus failure.

CONCLUSION

Our results indicate that the aneurysmal aortic root tissues are at greater risk of rupture and dissection propagation at lower aortic pressure. With further analysis, this could guide clinical and surgical management.

Hemodynamics and tissue biomechanics of the thoracic aorta with a trileaflet aortic valve at different phases of valve opening

In a normal cardiac cycle, the trileaflet aortic valve opening is progressive, which correlates with the phasic blood flow. Therefore, we aimed to determine the impact of including an anatomically accurate reconstructed trileaflet aortic valve within a fluid-structure interaction (FSI) simulation model and determine the cyclical hemodynamic forces imposed on the thoracic aortic walls from aortic valve opening to closure. A pediatric patient with a normal trileaflet valve was recruited. Using the Cardiac Magnetic Resonance Data (CMR), a 3D model of the aortic valve and thoracic aorta was reconstructed. FSI simulations were employed to assess the tissue stress during a cardiac cycle as the result of changes in the valve opening. The blood flow was simulated as a mixture of blood plasma and red blood cells to account for non-Newtonian effects. The computation was validated with phase-contrast CMR. Windkessel boundary conditions were employed to ensure physiological pressures during the cardiac cycle. The leaflets' dynamic motion during the cardiac cycle was defined with an analytic grid velocity function. At the beginning of the valve opening a thin jet is developing. From mid-open towards full opening the stress level increases where the jet impinges the convex wall. At peak systole two counter-rotating Dean-like vortex cores manifest in the ascending aorta, which correlates with increased integrated mean stress levels. An accurate trileaflet aortic valve is needed for capturing of both primary and secondary flow features that impact the forces on the thoracic aorta wall. Omitting the aortic valve underestimates the biomechanical response.

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.

A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics

Perturbed aorta hemodynamics, as for the carotid and the coronary artery, has been identified as potential predicting factor for cardiovascular diseases. In this study, we propose a parametric study based on the computational fluid dynamics with the aim of providing information regarding aortic disease. In particular, the blood flow inside a parametrized aortic arch is computed as a function of morphological changes of baseline aorta geometry. Flow patterns, wall shear stress, time average wall shear stress and oscillatory shear index were calculated during the cardiac cycle. The influence of geometrical changes on the hemodynamics and on these variables was evaluated. The results suggest that the distance between inflow and aortic arch and the angle between aortic arch and descending trunk are the most influencing parameters regarding the WSS-related indices while the effect of the inlet diameter seems limited. In particular, an increase of the aforementioned distance produces a reduction of the spatial distribution of the higher values of the time average wall shear stress and of the oscillatory shear index independently on the other two parameters while an increase of the angle produce an opposite effect. Moreover, as expected, the analysis of the wall shear stress descriptors suggests that the inlet diameter influences only the flow intensity. As conclusion, the proposed parametric study can be used to evaluate the aorta hemodynamics and could be also applied in the future, for analyzing pathological cases and virtual situations, such as pre- and/or post-operative cardiovascular surgical states that present enhanced changes in the aorta morphology yet promoting important variations on the considered indexes.

A class of analytic solutions for verification and convergence analysis of linear and nonlinear fluid-structure interaction algorithms

Fluid-structure interaction (FSI) problems are pervasive in the computational engineering community. The need to address challenging FSI problems has led to the development of a broad range of numerical methods addressing a variety of applicationspecific demands. While a range of numerical and experimental benchmarks are present in the literature, few solutions are available that enable both verification and spatiotemporal convergence analysis. In this paper, we introduce a class of analytic solutions to FSI problems involving shear in channels and pipes. Comprised of 16 separate analytic solutions, our approach is permuted to enable progressive verification and analysis of FSI methods and implementations, in two and three dimensions, for static and transient scenarios as well as for linear and hyperelastic solid materials. Results are shown for a range of analytic models exhibiting progressively complex behavior. The utility of these solutions for analysis of convergence behavior is further demonstrated using a previously published monolithic FSI technique. The resulting class of analytic solutions addresses a core challenge in the development of novel FSI algorithms and implementations, providing a progressive testbed for verification and detailed convergence analysis.

Hemodynamic of the patent ductus arteriosus in neonates with modified Blalock-Taussig shunts

BACKGROUND AND OBJECTIVE

Studying the hemodynamic effects of nonclosure of patent ductus arteriosus (PDA) on the modified Blalock-Taussig shunt (MBTS) is beneficial for surgical PDA management. In the present study, the effect of PDA on MBTS was investigated numerically. A series of parameters including energy loss, wall shear stress (WSS), and left/right Pulmonary artery (LPA/RPA) flow ratio were computed from simulations to analyze the hemodynamic effects of PDA on MBTS.

METHODS

To ensure the universality of the research conclusions, three typical models, including models with a well-developed RPA, a symmetrically-developed pulmonary artery(PA) and a well-developed LPA, were constructed based on patient-specific pre-surgery clinical data sets. A commercial CFD solver ANSYS-Fluent software was adopted for this study. A pressure-based solver for incompressible Newtonian flows, the K-omega based shear-stress-transport model and a second-order accurate numerical discretization scheme were employed for simulation.

RESULTS

Our results show that MBTS with nonclosure of PDA is accompanied by lower blood velocity, energy loss and WSS values at the MBT shunt; smaller vortex regions; higher oxygen content(Sao₂) and PA flow; and more uniform velocity distribution in the LPA and RPA than MBTS with closure of PDA. If the PDA was not closed when performing primary MBTS, a series of hemodynamic changes occurs during PDA closure in postoperative recovery: the energy loss, PA flow and Sao₂ decrease, while the oxygen delivery(Do2) and WSS values at the MBT shunt increase.

CONCLUSION

Nonclosure of PDA could provide a better hemodynamic environment and play an active role in preventing early acute shunt failure. It could be preferred for cases with very low PA overflow risk and may benefit patients with an underdeveloped myocardium due to its lower energy dissipation than PDA closure. However, excessive PA flow induced by nonclosure of PDA may result in a series of complications. Surgeon's decision-making process with respect to PDA management should consider the individual patient to achieve optimal postoperative recovery.

NUMERICAL SIMULATION OF DILATION PATTERNS OF THE ASCENDING AORTA IN AORTOPATHIES

Aortic dilation is associated with congenital bicuspid aortic valve (BAV) disease, and its etiology is still not completely understood. The aim of this study is to provide further insight into aortic hemodynamics in a BAV population with different degrees of aortic dilation and regurgitation in comparison with a patient without pathology. A fluid–structure interaction (FSI) numerical approach is implemented regarding patient-specific geometries, where the aortic valves are defined by analytical orifices. Results show that, while the patient without pathology displays a typical hemodynamic behavior of flows in bends, BAV-related aortas present an accelerated flow along the outer aortic wall. Wall shear stress (WSS) overload in the outer curvature is observed, more marked in more dilated aortas. Moreover, helices in the ascending aorta are present in these patients, enhanced with greater dilation. These findings support the fact that hemodynamic factors play an important role in aortic dilation onset and development in BAV patients, caused by a prolonged exposure of the outer ascending aortic curvature to altered WSS. Besides, our results suggest that greater aortic regurgitation may be associated with abnormal WSS distributions in the ascending aorta during diastole, which can facilitate aortic root dilation.

Fluid-structure interaction simulations of patient-specific aortic dissection

Credible computational fluid dynamic (CFD) simulations of aortic dissection are challenging, because the defining parallel flow channels-the true and the false lumen-are separated from each other by a more or less mobile dissection membrane, which is made up of a delaminated portion of the elastic aortic wall. We present a comprehensive numerical framework for CFD simulations of aortic dissection, which captures the complex interplay between physiologic deformation, flow, pressures, and time-averaged wall shear stress (TAWSS) in a patient-specific model. Our numerical model includes (1) two-way fluid-structure interaction (FSI) to describe the dynamic deformation of the vessel wall and dissection flap; (2) prestress and (3) external tissue support of the structural domain to avoid unphysiologic dilation of the aortic wall and stretching of the dissection flap; (4) tethering of the aorta by intercostal and lumbar arteries to restrict translatory motion of the aorta; and a (5) independently defined elastic modulus for the dissection flap and the outer vessel wall to account for their different material properties. The patient-specific aortic geometry is derived from computed tomography angiography (CTA). Three-dimensional phase contrast magnetic resonance imaging (4D flow MRI) and the patient's blood pressure are used to inform physiologically realistic, patient-specific boundary conditions. Our simulations closely capture the cyclical deformation of the dissection membrane, with flow simulations in good agreement with 4D flow MRI. We demonstrate that decreasing flap stiffness from [Formula: see text] to [Formula: see text] kPa (a) increases the displacement of the dissection flap from 1.4 to 13.4 mm, (b) decreases the surface area of TAWSS by a factor of 2.3, (c) decreases the mean pressure difference between true lumen and false lumen by a factor of 0.63, and (d) decreases the true lumen flow rate by up to 20% in the abdominal aorta. We conclude that the mobility of the dissection flap substantially influences local hemodynamics and therefore needs to be accounted for in patient-specific simulations of aortic dissection. Further research to accurately measure flap stiffness and its local variations could help advance future CFD applications.

Effects of Normal Variation in the Rotational Position of the Aortic Root on Hemodynamics and Tissue Biomechanics of the Thoracic Aorta

PURPOSE

Variation in the rotational position of the aortic root relative to the left ventricle is present in normal trileaflet aortic valves. Its impact on the resulting fluid mechanics of blood flow in the thoracic aorta and structural mechanics in the aortic wall are unknown. We aimed to determine the regional hemodynamic and biomechanical differences in different rotational positions of the normal aortic root (clockwise, central, and counterclockwise positions).

METHOD

Cardiac magnetic resonance imaging (CMR) data was acquired from a normal pediatric patient. These were used for reconstruction of the aortic valve and thoracic aorta 3D model. Fluid-structure interaction (FSI) simulations were employed to study the influence of the root rotation with a central position as compared to observed extreme variations. Patient-specific phase-encoding CMR data were used to assess the validity of computed blood flow. The 3D FSI model was coupled with Windkessel boundary conditions that were tuned for physiological pressures. A grid velocity function was adopted for the valve motion during the systolic period.

RESULTS

The largest wall shear stress level is detected in the clockwise positioned aortic root at the sinutubular junction. Two counter-rotating vortex cores are formed within the aortic root of both the central and extreme root configurations, however, in the clockwise root the vortex system becomes more symmetric. This also coincides with more entrainment of the valve jet and more turbulence production along the shear layer.

CONCLUSION

A clockwise rotational position of the aortic root imparts an increased wall shear stress at the sinutubular junction and proximal ascending aorta in comparison to other root rotation positions. This may pose increased risk for dilation of the sinutubular junction and ascending aorta in the patient with a clockwise positioned aortic root compared to other normal positional configurations.

An in silico study of the influence of vessel wall deformation on neointimal hyperplasia progression in peripheral bypass grafts

Neointimal hyperplasia (NIH) is a major obstacle to graft patency in the peripheral arteries. A complex interaction of biomechanical factors contribute to NIH development and progression, and although haemodynamic markers such as wall shear stress have been linked to the disease, these have so far been insufficient to fully capture its behaviour. Using a computational model linking computational fluid dynamics (CFD) simulations of blood flow with a biochemical model representing NIH growth mechanisms, we analyse the effect of compliance mismatch, due to the presence of surgical stitches and/or to the change in distensibility between artery and vein graft, on the haemodynamics in the lumen and, subsequently, on NIH progression. The model enabled to simulate NIH at proximal and distal anastomoses of three patient-specific end-to-side saphenous vein grafts under two compliance-mismatch configurations, and a rigid wall case for comparison, obtaining values of stenosis similar to those observed in the computed tomography (CT) scans. The maximum difference in time-averaged wall shear stress between the rigid and compliant models was 3.4 Pa, and differences in estimation of NIH progression were only observed in one patient. The impact of compliance on the haemodynamic-driven development of NIH was small in the patient-specific cases considered.