Evaluating the accuracy of cerebrovascular computational fluid dynamics modeling through time-resolved experimental validation.

Accurate modeling of cerebral hemodynamics is crucial for better understanding the hemodynamics of stroke, for which computational fluid dynamics (CFD) modeling is a viable tool to obtain information. However, a comprehensive study on the accuracy of cerebrovascular CFD models including both transient arterial pressures and flows does not exist. This study systematically assessed the accuracy of different outlet boundary conditions (BCs) comparing CFD modeling and an in-vitro experiment. The experimental setup consisted of an anatomical cerebrovascular phantom and high-resolution flow and pressure data acquisition. The CFD model of the same cerebrovascular geometry comprised five sets of stationary and transient BCs including established techniques and a novel BC, the phase modulation approach. The experiment produced physiological hemodynamics consistent with reported clinical results for total cerebral blood flow, inlet pressure, flow distribution, and flow pulsatility indices (PI). The in-silico model instead yielded time-dependent deviations between 19-66% for flows and 6-26% for pressures. For cerebrovascular CFD modeling, it is recommended to avoid stationary outlet pressure BCs, which caused the highest deviations. The Windkessel and the phase modulation BCs provided realistic flow PI values and cerebrovascular pressures, respectively. However, this study shows that the accuracy of current cerebrovascular CFD models is limited.

Assessing the impact of tear direction in coronary artery dissection on thrombosis development: A hemodynamic computational study.

OBJECTIVE: Iatrogenic coronary artery dissection is a complication of coronary intimal injury and dissection due to improper catheter manipulation. The impact of tear direction on the prognosis of coronary artery dissection (CAD) remains unclear. This study examines the hemodynamic effects of different tear directions (transverse and longitudinal) of CAD and evaluates the risk of thrombosis, rupture and further dilatation of CAD. METHODS: Two types of CAD models (Type I: transverse tear, Type II: longitudinal tear) were reconstructed from the aorto-coronary CTA dataset of 8 healthy cases. Four WSS-based indicators were analyzed, including time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and cross flow index (CFI). A thrombus growth model was also introduced to predict the trend of thrombus growth in CAD with two different tear directions. RESULTS: For most of the WSS-based indicators, including TAWSS, RRT, and CFI, no statistically significant differences were observed across the CAD models with varying tear directions, except for OSI, where a significant difference was noted (p < 0.05). Meanwhile, in terms of thrombus growth, the thrombus growing at the tear of the Type I (transverse tear) CAD model extended into the true lumen earlier than that of the Type II (longitudinal tear) model. CONCLUSIONS: Numerical simulations suggest that: (1) The CAD with transverse tear have a high risk of further tearing of the dissection at the distal end of the tear. (2) The CAD with longitudinal tear create a hemodynamic environment characterized by low TAWSS and high OSI in the false lumen, which may additionally increase the risk of vessel wall injury. (3) The CAD with transverse tear may have a higher risk of thrombosis and coronary obstruction and myocardial ischemia in the early phase of the dissection.

Hemodynamics and Wall Mechanics of Vascular Graft Failure.

Blood vessels are subjected to complex biomechanical loads, primarily from pressure-driven blood flow. Abnormal loading associated with vascular grafts, arising from altered hemodynamics or wall mechanics, can cause acute and progressive vascular failure and end-organ dysfunction. Perturbations to mechanobiological stimuli experienced by vascular cells contribute to remodeling of the vascular wall via activation of mechanosensitive signaling pathways and subsequent changes in gene expression and associated turnover of cells and extracellular matrix. In this review, we outline experimental and computational tools used to quantify metrics of biomechanical loading in vascular grafts and highlight those that show potential in predicting graft failure for diverse disease contexts. We include metrics derived from both fluid and solid mechanics that drive feedback loops between mechanobiological processes and changes in the biomechanical state that govern the natural history of vascular grafts. As illustrative examples, we consider application-specific coronary artery bypass grafts, peripheral vascular grafts, and tissue-engineered vascular grafts for congenital heart surgery as each of these involves unique circulatory environments, loading magnitudes, and graft materials.

Uncertainty quantification of the impact of peripheral arterial disease on abdominal aortic aneurysms in blood flow simulations.

Peripheral arterial disease (PAD) and abdominal aortic aneurysms (AAAs) often coexist and pose significant risks of mortality, yet their mutual interactions remain largely unexplored. Here, we introduce a fluid mechanics model designed to simulate the haemodynamic impact of PAD on AAA-associated risk factors. Our focus lies on quantifying the uncertainty inherent in controlling the flow rates within PAD-affected vessels and predicting AAA risk factors derived from wall shear stress. We perform a sensitivity analysis on nine critical model parameters through simulations of three-dimensional blood flow within a comprehensive arterial geometry. Our results show effective control of the flow rates using two-element Windkessel models, although specific outlets need attention. Quantities of interest like endothelial cell activation potential (ECAP) and relative residence time are instructive for identifying high-risk regions, with ECAP showing greater reliability and adaptability. Our analysis reveals that the uncertainty in the quantities of interest is 187% of that of the input parameters. Notably, parameters governing the amplitude and frequency of the inlet velocity exert the strongest influence on the risk factors' variability and warrant precise determination. This study forms the foundation for patient-specific simulations involving PAD and AAAs which should ultimately improve patient outcomes and reduce associated mortality rates.

Numerical investigation of LDL nanoparticle collision in coronary artery grafts with porous wall and different implantation angles and two state of inlet velocity.

This study aimed to reduce the risk of graft occlusion by evaluating the two-phase flow of blood and LDL nanoparticles in coronary artery grafts. The study considered blood as an incompressible Newtonian fluid, with the addition of LDL nanoparticles, and the artery wall as a porous medium. Two scenarios were compared, with constant inlet velocity (CIV) and other with pulsatile inlet velocity (PIV), with LDL nanoparticles experiencing drag, wall-induced lift, and induced Saffman lift forces, or drag force only. The study also evaluated the concentration polarization of LDLs (CP of LDLs) near the walls, by considering the artery wall with and without permeation. To model LDL nanoparticles, the study randomly injected 100, 500, and 1000 nanoparticles in three release states at each time step, using different geometries. Numerical simulations were performed using COMSOL software, and the results were presented as relative collision of nanoparticles to the walls in tables, diagrams, and shear stress contours. The study found that a graft implantation angle of 15° had the most desirable conditions compared to larger angles, in terms of nanoparticle collision with surfaces and occlusion. The nanoparticle release modes behaved similarly in terms of collision with the surfaces. A difference was observed between CIV and PIV. Saffman lift and wall-induced lift forces having no effect, possibly due to the assumption of a porous artery wall and perpendicular outlet flow. In case of permeable artery walls, relative collision of particles with the graft wall was larger, suggesting the effect of CP of LDLs.

T-wave inversion through inhomogeneous voltage diffusion within the FK3V cardiac model.

The heart beats are due to the synchronized contraction of cardiomyocytes triggered by a periodic sequence of electrical signals called action potentials, which originate in the sinoatrial node and spread through the heart's electrical system. A large body of work is devoted to modeling the propagation of the action potential and to reproducing reliably its shape and duration. Connection of computational modeling of cells to macroscopic phenomenological curves such as the electrocardiogram has been also intense, due to its clinical importance in analyzing cardiovascular diseases. In this work, we simulate the dynamics of action potential propagation using the three-variable Fenton-Karma model that can account for both normal and damaged cells through a the spatially inhomogeneous voltage diffusion coefficient. We monitor the action potential propagation in the cardiac tissue and calculate the pseudo-electrocardiogram that reproduces the R and T waves. The R-wave amplitude varies according to a double exponential law as a function of the (spatially homogeneous, for an isotropic tissue) diffusion coefficient. The addition of spatial inhomogeneity in the diffusion coefficient by means of a defected region representing damaged cardiac cells may result in T-wave inversion in the calculated pseudo-electrocardiogram. The transition from positive to negative polarity of the T-wave is analyzed as a function of the length and the depth of the defected region.

Tailoring left ventricular assist device cannula implantation using coupled multi-scale multi-objective optimization.

BACKGROUND: The frequent occurrence of thromboembolic cerebral events continues to limit the widespread implementation of Ventricular Assist Devices (VAD) despite continued advancements in VAD design and anti-coagulation treatments. Recent studies point to the optimal positioning of the outflow graft (OG) as a potential mitigator of post implantation thromboembolism. OBJECTIVE: This study aims to examine the tailoring of the OG implantation orientation with the goal of minimizing the number of thrombi reaching the cerebral vessels by means of a formal shape optimization scheme incorporated into a multi-scale hemodynamics analysis. METHODS: A 3-D patient-specific computational fluid dynamics model is loosely coupled in a two-way manner to a 0-D lumped parameter model of the peripheral circulation. A Lagrangian particle-tracking scheme models and tracks thrombi as non-interacting solid spheres. The loose coupling between CFD and LPM is integrated into a geometric shape optimization scheme which aims to optimize an objective function that targets a drop in cerebral embolization, and an overall reduction in particle residence times. RESULTS: The results elucidate the importance of OG anastomosis orientation and placement particularly in the case that studied particle release from the OG, as a fivefold decrease in cerebral embolization was observed between the optimal and non-optimal implantations. Another case considered particle release from the ventricle and aortic root walls, in which optimal implantation was achieved with a shallow insertion angle. Particle release from all three origins was investigated in the third case, demonstrating that the optimal configurations were generally characterized by VAD flow directed along the central lumen of the aortic arch. Because optimal configurations depended on the anatomic origin of the thrombus, it is important to determine, in clinical studies, the most likely sites of thrombus formation in VAD patients.

Coronary hemodynamic simulation study.

In this paper, a two-way fluid-structure coupling model is developed to simulate and analyze the hemodynamic process based on dynamic coronary angiography, and examine the influence of different hemodynamic parameters on coronary arteries in typical coronary stenosis lesions. Using the measured FFR pressure data of a patient, the pressure-time function curve is fitted to ensure the accuracy of the boundary conditions. The average error of the simulation pressure results compared to the test data is 6.74%. In addition, the results related to blood flow, pressure contour and wall shear stress contour in a typical cardiac cycle are obtained by simulation analysis. These results are found to be in good agreement with the laws of the real cardiac cycle, which verifies the rationality of the simulation. In conclusion, based on the modeling and hemodynamic simulation analysis process of dynamic coronary angiography, this paper proposes a method to assist the analysis and evaluation of coronary hemodynamic and functional parameters, which has certain practical significance.

Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall.

Computational fluid dynamics (CFD) is a valuable asset for patient-specific cardiovascular-disease diagnosis and prognosis, but its high computational demands hamper its adoption in practice. Machine-learning methods that estimate blood flow in individual patients could accelerate or replace CFD simulation to overcome these limitations. In this work, we consider the estimation of vector-valued quantities on the wall of three-dimensional geometric artery models. We employ group-equivariant graph convolution in an end-to-end SE(3)-equivariant neural network that operates directly on triangular surface meshes and makes efficient use of training data. We run experiments on a large dataset of synthetic coronary arteries and find that our method estimates directional wall shear stress (WSS) with an approximation error of 7.6% and normalised mean absolute error (NMAE) of 0.4% while up to two orders of magnitude faster than CFD. Furthermore, we show that our method is powerful enough to accurately predict transient, vector-valued WSS over the cardiac cycle while conditioned on a range of different inflow boundary conditions. These results demonstrate the potential of our proposed method as a plugin replacement for CFD in the personalised prediction of hemodynamic vector and scalar fields.

Computational approaches for mechanobiology in cardiovascular development and diseases.

The cardiovascular development in vertebrates evolves in response to genetic and mechanical cues. The dynamic interplay among mechanics, cell biology, and anatomy continually shapes the hydraulic networks, characterized by complex, non-linear changes in anatomical structure and blood flow dynamics. To better understand this interplay, a diverse set of molecular and computational tools has been used to comprehensively study cardiovascular mechanobiology. With the continual advancement of computational capacity and numerical techniques, cardiovascular simulation is increasingly vital in both basic science research for understanding developmental mechanisms and disease etiologies, as well as in clinical studies aimed at enhancing treatment outcomes. This review provides an overview of computational cardiovascular modeling. Beginning with the fundamental concepts of computational cardiovascular modeling, it navigates through the applications of computational modeling in investigating mechanobiology during cardiac development. Second, the article illustrates the utility of computational hemodynamic modeling in the context of treatment planning for congenital heart diseases. It then delves into the predictive potential of computational models for elucidating tissue growth and remodeling processes. In closing, we outline prevailing challenges and future prospects, underscoring the transformative impact of computational cardiovascular modeling in reshaping cardiovascular science and clinical practice.

Intracellular ion accumulation in the genesis of complex action potential dynamics under cardiac diseases.

Intracellular ions, including sodium (Na^{+}), calcium (Ca^{2+}), and potassium (K^{+}), etc., accumulate slowly after a change of the state of the heart, such as a change of the heart rate. The goal of this study is to understand the roles of slow ion accumulation in the genesis of cardiac memory and complex action-potential duration (APD) dynamics that can lead to lethal cardiac arrhythmias. We carry out numerical simulations of a detailed action potential model of ventricular myocytes under normal and diseased conditions, which exhibit memory effects and complex APD dynamics. We develop a low-dimensional iterated map (IM) model to describe the dynamics of Na^{+}, Ca^{2+}, and APD and use it to uncover the underlying dynamical mechanisms. The development of the IM model is informed by simulation results under the normal condition. We then use the IM model to perform linear stability analyses and computer simulations to investigate the bifurcations and complex APD dynamics, which depend on the feedback loops between APD and intracellular Ca^{2+} and Na^{+} concentrations and the steepness of the APD response to the ion concentrations. When the feedback between APD and Ca^{2+} concentration is positive, a Hopf bifurcation leading to periodic oscillatory behavior occurs as the steepness of the APD response to the ion concentrations increases. The negative feedback loop between APD and Na^{+} concentration is required for the Hopf bifurcation. When the feedback between APD and Ca^{2+} concentration is negative, period-doubling bifurcations leading to high periodicity and chaos occurs. In this case, Na^{+} accumulation plays little role in the dynamics. Finally, we carry out simulations of the detailed action potential model under two diseased conditions, which exhibit steep APD responses to ion concentrations. Under both conditions, Hopf bifurcations leading to slow oscillations or period-doubling bifurcations leading to high periodicity and chaotic APD dynamics occur, depending on the strength of the ion pump-Na^{+}-Ca^{2+} exchanger. Using functions reconstructed from the simulation data, the IM model accurately captures the bifurcations and dynamics under the two diseased conditions. In conclusion, besides using computer simulations of a detailed high-dimensional action-potential model to investigate the effects of slow ion accumulation and short-term memory on bifurcations and genesis of complex APD dynamics in cardiac myocytes under diseased conditions, this study also provides a low-dimensional mathematical tool, i.e., the IM model, to allow stability analyses for uncovering the underlying mechanisms.

Smoothed particle hydrodynamics based FSI simulation of the native and mechanical heart valves in a patient-specific aortic model.

The failure of the aortic heart valve is common, resulting in deterioration of the pumping function of the heart. For the end stage valve failure, bi-leaflet mechanical valve (most popular artificial valve) is implanted. However, due to its non-physiological behaviour, a significant alteration is observed in the normal haemodynamics of the aorta. While in-vivo experimentation of a human heart valve (native and artificial) is a formidable task, in-silico study using computational fluid dynamics (CFD) with fluid structure interaction (FSI) is an effective and economic tool for investigating the haemodynamics of natural and artificial heart valves. In the present work, a haemodynamic model of a natural and mechanical heart valve has been developed using meshless particle-based smoothed particle hydrodynamics (SPH). In order to further enhance its clinical relevance, this study employs a patient-specific vascular geometry and presents a successful validation against traditional finite volume method and 4D magnetic resonance imaging (MRI) data. The results have demonstrated that SPH is ideally suited to simulate the heart valve function due to its Lagrangian description of motion, which is a favourable feature for FSI. In addition, a novel methodology for the estimation of the wall shear stress (WSS) and other related haemodynamic parameters have been proposed from the SPH perspective. Finally, a detailed comparison of the haemodynamic parameters has been carried out for both native and mechanical aortic valve, with a particular emphasis on the clinical risks associated with the mechanical valve.

In vitro hemodynamic performance of a blood pump for self-powered venous assist in univentricular hearts.

Univentricular heart anomalies represent a group of severe congenital heart defects necessitating early surgical intervention in infancy. The Fontan procedure, the final stage of single-ventricle palliation, establishes a serial connection between systemic and pulmonary circulation by channeling venous return to the lungs. The absence of the subpulmonary ventricle in this peculiar circulation progressively eventuates in failure, primarily due to chronic elevation in inferior vena cava (IVC) pressure. This study experimentally validates the effectiveness of an intracorporeally-powered venous ejector pump (VEP) in reducing IVC pressure in Fontan patients. The VEP exploits a fraction of aortic flow to create a jet-venturi effect for the IVC, negating the external power requirement and driveline infections. An invitro Fontan mock-up circulation loop is developed and the impact of VEP design parameters and physiological conditions is assessed using both idealized and patient-specific total cavopulmonary connection (TCPC) phantoms. The VEP performance in reducing IVC pressure exhibited an inverse relationship with the cardiac output and extra-cardiac conduit (ECC) size and a proportional relationship with the transpulmonary pressure gradient (TPG) and mean arterial pressure (MAP). The ideal VEP with fail-safe features provided an IVC pressure drop of 1.82 ± 0.49, 2.45 ± 0.54, and 3.12 ± 0.43 mm Hg for TPG values of 6, 8, and 10 mm Hg, respectively, averaged over all ECC sizes and cardiac outputs. Furthermore, the arterial oxygen saturation was consistently maintained above 85% during full-assist mode. These results emphasize the potential utility of the VEP to mitigate elevated venous pressure in Fontan patients.

Mathematical modeling in assessing the risk of restenosis after carotid endarterectomy.

Carotid endarterectomy is the main way to combat atherosclerosis of the carotid arteries, which disrupts cerebral circulation. The generally accepted marker of atherogenesis risk are hemodynamic indices associated with near-wall shear stress. The purpose of the work is to conduct a comparative analysis of hemodynamic indices in various carotid bifurcation models. The influence of a virtual change in the geometric shape of the model in order to optimize hemodynamic indices is also being studied. On the basis of computed angiography data, carotid bifurcation models are constructed, in which critical zones of hemodynamic indices are built using computational fluid dynamics. A comparative analysis of the critical zones for different classes of models is carried out. Comparison of averaged indices for critical zones between 'normal' and post-operative groups gave more than 5-x worse results for the latter. The same results for the near-bifurcation parts of the zones give a 25% better result for postoperative models. Virtual 'removal' of insignificant plaques leads to a deterioration of the indices of up to 40% in the places of the plaque's former location. The described method makes it possible to build the indices critical zones and compare them for various types of models. A technique for virtual changing the shape of a vessel (virtual surgery) is proposed. The novelty of the approach lies in the use for comparative analysis both real vessel models and hypothetical 'improved' virtual ones, as well in the proposed division of post-operative model's critical zones into subzones of different genesis.

A multi-constituent model for assessing the effect of impeller shroud on the thrombosis potential of a centrifugal blood pump.

Centrifugal blood pumps can be used for treating heart failure patients. However, pump thrombosis has remained one of the complications that trouble clinical treatment. This study analyzed the effect of impeller shroud on the thrombosis risk of the blood pump, and predicted areas prone to thrombosis. Multi-constituent transport equations were presented, considering mechanical activation and biochemical activation. It was found that activated platelets concentration can increase with shear stress and adenosine diphosphate(ADP) concentration increasing, and the highest risk of thrombosis inside the blood pump was under extracorporeal membrane oxygenation (ECMO) mode. Under the same condition, ADP concentration and thrombosis index of semi-shroud impeller can increase by 7.3% and 7.2% compared to the closed-shroud impeller. The main reason for the increase in thrombosis risk was owing to elevated scalar shear stress and more coagulation promoting factor-ADP released. The regions with higher thrombosis potential were in the center hole, top and bottom clearance. As a novelty, the findings revealed that impeller shroud can influence mechanical and biochemical activation factors. It is useful for identifying potential risk regions of thrombus formation based on relative comparisons.

Numerical investigation of quantitative pulmonary pressure ratio in different degrees of stenosis.

BACKGROUND: Pulmonary artery stenosis endangers people's health. Quantitative pulmonary pressure ratio (QPPR) is very important for clinicians to quickly diagnose diseases and develop treatment plans. OBJECTIVE: Our purpose of this paper is to investigate the effects of different degrees (50% and 80%) of pulmonary artery stenosis on QPPR. METHODS: An idealized model is established based on the normal size of human pulmonary artery. The hemodynamic governing equations are solved using fluid-structure interaction. RESULTS: The results show that the QPPR decreases with the increase of stenosis degree, and it is closely related to the pressure drop at both ends of stenosis. Blood flow velocity and wall shear stress are sensitive to the stenosis degree. When the degree of stenosis is 80%, the amplitude of changes of blood flow velocity and wall shear stress at both ends of stenosis is lower. CONCLUSIONS: The results suggest that the degree of pulmonary artery stenosis has a significant impact on QPPR and hemodynamic changes. This study lays a theoretical foundation for further study of QPPR.

Influence of Wavy Arteries and Veins on Hemodynamic Characteristics: A Numerical Study.

The present work is focused on the study of hemodynamic characteristics for tortuous arteries/veins. Tortuosity in arteries/veins is defined by introducing waviness in the wall of the tube. Analysis is further extended for bifurcated veins with and without wavy walls. Waviness is defined by two geometric parameters; pitch and depth of the wave. Four different combinations of pitch and depth are studied and compared with a plain straight wall. The present study is carried out numerically by using a computational fluid dynamics tool. Hemodynamics for a steady flow of blood is investigated through pressure, velocity, and wall shear stress distribution. Waviness in the wall of arteries/veins creates a recirculation zone at the crest and trough of the wall. Occurrence of the recirculation zone leads to reduction in velocity which in turn reduces wall shear stress. Variation in the magnitude of the velocity and corresponding wall shear stress at the crest and trough of the wavy wall depends on the pitch and depth of the artery/veins (tube).

Validation of fluid-structure interaction simulations of the opening phase of phantom mitral heart valves under physiologically inspired conditions.

BACKGROUND AND OBJECTIVE: Atrioventricular valve disease is a common cause of heart failure, and successful surgical or interventional outcomes are crucial. Patient-specific fluid-structure interaction (FSI) modeling may provide valuable insights into valve dynamics and guidance of valve repair strategies. However, lack of validation has kept FSI modeling from clinical implementation. Therefore, this study aims to validate FSI simulations against in vitro benchmarking data, based on clinically relevant parameters for evaluating heart valve disease. METHODS: An FSI model that mimics the left heart was developed. The domain included a deformable mitral valve of different stiffnesses run with different inlet velocities. Five different cases were simulated and compared to in vitro data based on the pressure difference across the valve, the valve opening, and the velocity in the flow domain. RESULTS: The simulations underestimate the pressure difference across the valve by 6.8-14 % compared to catheter measurements. Evaluation of the valve opening showed an underprediction of 5.4-7.3 % when compared to cine MRI, 2D Echo, and 3D Echo data. Additionally, the simulated velocity through the valve showed a 7.9-8.4 % underprediction in relation to Doppler Echo measurements. Qualitative assessment of the velocity profile in the ventricle and the streamlines of the flow in the domain showed good agreement of the flow behavior. CONCLUSIONS: Parameters relevant to the diagnosis of heart valve disease estimated by FSI simulations showed good agreement when compared to in vitro benchmarking data, with differences small enough not to affect the grading of heart valve disease. The FSI model is thus deemed good enough for further development toward patient-specific cases.

Tube law parametrization using in vitro data for one-dimensional blood flow in arteries and veins: TUBE LAW PARAMETRIZATION IN ARTERIES AND VEINS.

The deformability of blood vessels in one-dimensional blood flow models is typically described through a pressure-area relation, known as the tube law. The most used tube laws take into account the elastic and viscous components of the tension of the vessel wall. Accurately parametrizing the tube laws is vital for replicating pressure and flow wave propagation phenomena. Here, we present a novel mathematical-property-preserving approach for the estimation of the parameters of the elastic and viscoelastic tube laws. Our goal was to estimate the parameters by using ovine and human in vitro data, while constraining them to meet prescribed mathematical properties. Results show that both elastic and viscoelastic tube laws accurately describe experimental pressure-area data concerning both quantitative and qualitative aspects. Additionally, the viscoelastic tube law can provide a qualitative explanation for the observed hysteresis cycles. The two models were evaluated using two approaches: (i) allowing all parameters to freely vary within their respective ranges and (ii) fixing some of the parameters. The former approach was found to be the most suitable for reproducing pressure-area curves.

Accelerated simulation methodologies for computational vascular flow modelling.

Vascular flow modelling can improve our understanding of vascular pathologies and aid in developing safe and effective medical devices. Vascular flow models typically involve solving the nonlinear Navier-Stokes equations in complex anatomies and using physiological boundary conditions, often presenting a multi-physics and multi-scale computational problem to be solved. This leads to highly complex and expensive models that require excessive computational time. This review explores accelerated simulation methodologies, specifically focusing on computational vascular flow modelling. We review reduced order modelling (ROM) techniques like zero-/one-dimensional and modal decomposition-based ROMs and machine learning (ML) methods including ML-augmented ROMs, ML-based ROMs and physics-informed ML models. We discuss the applicability of each method to vascular flow acceleration and the effectiveness of the method in addressing domain-specific challenges. When available, we provide statistics on accuracy and speed-up factors for various applications related to vascular flow simulation acceleration. Our findings indicate that each type of model has strengths and limitations depending on the context. To accelerate real-world vascular flow problems, we propose future research on developing multi-scale acceleration methods capable of handling the significant geometric variability inherent to such problems.