Simulation Of Blood Flow Research Articles

Lung Organoid on a Chip: A New Ensemble Model for Preclinical Studies.

The lung is a complex organ comprising a branched airway that connects the large airway and millions of terminal gas-exchange units. Traditional pulmonary biomedical research by using cell line model system have limitations such as lack of cellular heterogeneity, animal models also have limitations including ethical concern, race-to-race variations, and physiological differences found in vivo. Organoids and on-a-chip models offer viable solutions for these issues. Organoids are three-dimensional, self-organized construct composed of numerous cells derived from stem cells cultured with growth factors required for the maintenance of stem cells. On-a-chip models are biomimetic microsystems which are able to customize to use microfluidic systems to simulate blood flow in blood channels or vacuum to simulate human breathing. This review summarizes the key components and previous biomedical studies conducted on lung organoids and lung-on-a-chip models, and introduces potential future applications. Considering the importance and benefits of these model systems, we believe that the system will offer better platform to biomedical researchers on pulmonary diseases, such as emerging viral infection, progressive fibrotic pulmonary diseases, or primary or metastatic lung cancer.

Human whole-brain models of cerebral blood flow and oxygen transport

The cerebral vasculature plays a critical role in the transport of oxygen and other nutrients to brain tissue. However, the size, complexity, and paucity of detailed anatomical information of this system makes understanding cerebral behaviour in normal and pathological conditions, as well as its response to stimuli, highly challenging. Whole-brain mathematical models have a valuable role to play in the understanding and measurement of cerebral parameters. However, for the same reasons, whole-brain models are highly complex to construct. In this study, we propose a novel multi-compartment approach to blood flow and oxygen transport. Building on prior models, we propose a new formulation based on a multiple compartment porous medium approach. Using non-dimensional analysis, we derive the most compact form of the equations and constrain the parameter space using clinically measurable quantities, such as baseline perfusion and blood volume. We illustrate the spatially and temporally varying response of the brain by simulating the response to changes in both arterial blood pressure and arterial oxygen saturation, showing that the oxygen response is strongly dependent upon depth, with large but slow responses being found deep in the brain and small but fast responses nearer the surface, whereas the flow response is very rapid in comparison. Blood flow and oxygenation are thus shown to exhibit very different characteristic time scales. This has significant implications for how we consider the response of the brain to external stimuli, such the autoregulation and reactivity responses, and how we model the brain at different time scales.Statement of Significance: In this study we present a new mathematical model for simulations of blood flow and oxygen transport in the human brain. A compact representation is obtained from analysis of the governing equations and different time scales are identified. We show that the behaviour is strongly depth dependent and that 3D models exhibit very different behaviour from simplified 1D models. This will be important in developing further models of the brain, particularly in simulating its active response.

A semi-implicit finite volume scheme for blood flow in elastic and viscoelastic vessels

A novel staggered semi-implicit finite volume method for the simulation of one-dimensional blood flow in networks of elastic and viscoelastic vessels is proposed. The one-dimensional blood flow model is split into three subsystems: one containing the nonlinear convective terms, a second one for the viscoelastic terms and a final subsystem for the pressure-related terms. An explicit approach is then employed to discretize the convective subsystem, while the viscous and pressure terms are treated implicitly. This leads to a CFL-type time step restriction which depends only on the bulk velocity of the flow and not on the speed of the pressure waves or on the visco elasticity. As such, the method is computationally efficient in case of low speed index, which is equivalent to a low Mach regime for the Navier-Stokes equations. To extend the proposed methodology to the case of networks, a novel and very simple 3D approach for the treatment of junctions is proposed. Each junction is represented by a unique three-dimensional primal cell and the Euler equations are employed to approximate the velocity and pressure unknowns. A multidimensional numerical flux then takes into account the elementary information of the junction geometry, namely normal vectors and areas of the incident vessels, when approximating the blood flow at the cell interfaces embedded in the 3D cell. As such, the final scheme, based on guaranteeing mass and momentum conservation through the junction, is able to capture reflecting waves properly considering the effect of the different incident angles of vessels at a junction. The proposed methodology is carefully validated in the context of single elastic and viscoelastic vessels and small networks showing a good agreement with available analytical, experimental and numerical data.

Blood Flow Simulation of Aneurysmatic and Sane Thoracic Aorta Using OpenFOAM CFD Software

Cardiovascular diseases still represent one of the most deadly pathologies worldwide. Knowledge of the blood flow dynamics within the cardio-vascular system is crucial in preventing these diseases and analysing their physiology and physio-pathology. CFD simulations are highly effective in guiding clinical predictions and, more importantly, allow the evaluation of physical and clinical parameters that are difficult to measure with common diagnostic techniques. Therefore, in particular, this study is focused on investigating the hemodynamics of the thoracic aorta. Real aortic geometries regarding a sane and diseased patient presenting an aneurysm were considered. CFD simulations were performed with the OpenFOAM C++ library using patient-specific pulsatile blood flow waveforms and implementing the Windkessel pressure boundary condition for the artery outflow. The adopted methodology was preliminarily verified for assessing the numerical uncertainty and convergence. Then, the CFD results were evaluated against experimental data concerning pressure and velocity of the thoracic aorta measured with standard diagnostic techniques. The normal aorta’s blood flow was also compared against the pattern regarding the patient-specific aortic aneurysm. Parameters such as wall pressure, wall shear stress (WSS) and velocity distribution were investigated and discussed. The research highlighted that the blood flow in the aorta is strongly affected by the aneurysm onset, with the growth of recirculation zones being potentially hazardous. The outcomes of the investigation finally demonstrate how CFD simulation tools, capturing the detailed physics of the aortic flow, are powerful tools for supporting clinical activities of the cardio-vascular system.

Emerging Woman Leader in Technical Computing Tackles Cardiovascular Disease using HPC

SIGHPC is delighted to announce that Dr. Amanda Randles (Duke U.) is the winner of its 2023 Emerging Woman Leader in Technical Computing Award. She is recognized for her innovative work in developing new approaches to circulatory blood flow simulation at all scales of computing, as well as her dedicated mentorship and community service.

Experimental and numerical study of flow structure in a model of distal anastomosis of femoral artery

Physical and numerical simulation of the steady blood flow was carried out focusing on the distal end-to-side anastomosis of a graft to the femoral artery. The angle between the graft and the artery was 60°. Two Reynolds numbers were considered that corresponded to the physiological range when estimated using the average (Re = 240) and maximum (Re = 1640) blood flow through the human femoral artery over a single cardiac cycle. The experiment included flow visualization and measurements of instantaneous vector fields of velocity using an optical SIV (Smoke Image Velocimetry) technique. Direct numerical simulation (DNS) was employed for numerical study. The distribution of blood flows through the branches of the main artery was 80 % in the antegrade and 20 % in the retrograde direction. Main patterns in the distribution of velocity and its root-mean-square fluctuations in both branches of the main artery were revealed. Flow separation regions were observed in the branching area. Additionally, secondary flows (Prandtl’s vortices of the first kind) were revealed. The flow in the branching area was still laminar Re = 240, while the signs of transition to turbulence were documented within separation regions at Re = 1640. Distributions of streamwise and circumferential components of skin friction vector were estimated. In some regions of flow, these components were shown to be comparable in size. The location of regions was revealed in which the friction magnitude in the considered flow regimes was lower than the one in an unimpaired artery (developed laminar flow in a circular pipe) at appropriate Reynolds numbers.

A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries.

With the global rise of cardiovascular disease including atherosclerosis, there is a high demand for accurate diagnostic tools that can be used during a short consultation. In view of pathology, abnormal blood flow patterns have been demonstrated to be strong predictors of atherosclerotic lesion incidence, location, progression, and rupture. Prediction of patient-specific blood flow patterns can hence enable fast clinical diagnosis. However, the current state of art for the technique is by employing 3D-imaging-based Computational Fluid Dynamics (CFD). The high computational cost renders these methods impractical. In this work, we present a novel method to expedite the reconstruction of 3D pressure and shear stress fields using a combination of a reduced-order CFD modelling technique together with non-linear regression tools from the Machine Learning (ML) paradigm. Specifically, we develop a proof-of-concept automated pipeline that uses randomised perturbations of an atherosclerotic pig coronary artery to produce a large dataset of unique mesh geometries with variable blood flow. A total of 1,407 geometries were generated from seven reference arteries and were used to simulate blood flow using the CFD solver Abaqus. This CFD dataset was then post-processed using the mesh-domain common-base Proper Orthogonal Decomposition (cPOD) method to obtain Eigen functions and principal coefficients, the latter of which is a product of the individual mesh flow solutions with the POD Eigenvectors. Being a data-reduction method, the POD enables the data to be represented using only the ten most significant modes, which captures cumulatively greater than 95% of variance of flow features due to mesh variations. Next, the node coordinate data of the meshes were embedded in a two-dimensional coordinate system using the t-distributed Stochastic Neighbor Embedding (-SNE) algorithm. The reduced dataset for -SNE coordinates and corresponding vector of POD coefficients were then used to train a Random Forest Regressor (RFR) model. The same methodology was applied to both the volumetric pressure solution and the wall shear stress. The predicted pattern of blood pressure, and shear stress in unseen arterial geometries were compared with the ground truth CFD solutions on "unseen" meshes. The new method was able to reliably reproduce the 3D coronary artery haemodynamics in less than 10 s.

Computational fluid dynamics of coronary arteries with implanted stents: Effects of Newtonian and non‐Newtonian blood flows

AbstractThis study introduces and compares computational fluid dynamics of Newtonian and non‐Newtonian blood flows in coronary arteries, with and without considering stents. Three blood flow models, including Newtonian, Carreau, and non‐Newtonian power‐law models, were simulated to investigate their effect, and the solution algorithm includes drawing the geometry, creating the desired mesh, and then simulating Newtonian and non‐Newtonian blood flow different models and comparing them with each other, is presented in the article. A Newtonian fluid model has been commonly used in the simulation of blood flow, whereas blood has non‐Newtonian properties due to the nature of a solution containing suspended particles. The goal of this research is to investigate the differences between the models built with Newtonian and non‐Newtonian fluid assumptions. In addition, a stent was designed and the effect of the stent on blood flow parameters was investigated for all three flow models, including Newtonian, Carreau, and non‐Newtonian power‐law models. Stents are medical devices that can be placed in arteries to open up blood flow in a blocked vessel. Stents can affect the wall shear stress. Knowing the slight deformation of the shear stress makes the importance of stent implantation and also helps to optimize the design of the intravascular stent, which can affect the occlusion of the vessels. The distribution of the velocity, pressure, and wall shear stress in all blood flow models with and without considering the effect of stents have been investigated and finally compared. Therefore, in general, the innovation of this article is to find the effect of implanted stents on blood flow parameters with different blood flow models, both Newtonian and non‐Newtonian. A comparison of Newtonian and non‐Newtonian flows showed that in the case of the Carreau non‐Newtonian model, the wall shear stress was higher. In addition, in the results of the geometric model with a stent effect compared to the geometric model without a stent effect, it is evident that there was a higher velocity and wall shear stress.

Cellular Blood Flow Modeling with HemoCell.

Many of the intriguing properties of blood originate from its cellular nature. Bulk effects, such as viscosity, depend on the local shear rates and on the size of the vessels. While empirical descriptions of bulk rheology are available for decades, their validity is limited to the experimental conditions they were observed under. These are typically artificial scenarios (e.g., perfectly straight glass tube or in pure shear with no gradients). Such conditions make experimental measurements simpler; however, they do not exist in real systems (i.e., in a real human circulatory system). Therefore, as we strive to increase our understanding on the cardiovascular system and improve the accuracy of our computational predictions, we need to incorporate a more comprehensive description of the cellular nature of blood. This, however, presents several computational challenges that can only be addressed by high performance computing. In this chapter, we describe HemoCell ( https://www.hemocell.eu ), an open-source high-performance cellular blood flow simulation, which implements validated mechanical models for red blood cells and is capable of reproducing the emergent transport characteristics of such a complex cellular system. We discuss the accuracy and the range of validity, and demonstrate applications on a series of human diseases.

An aneurysm-specific preconditioning technique for the acceleration of Newton-Krylov method with application in the simulation of blood flows.

In this paper, we develop an algorithm to simulate blood flows in aneurysmal arteries and focus on the construction of robust and efficient multilevel preconditioners to speed up the convergence of both linear and nonlinear solvers. The work is motivated by the observation that in the local aneurysmal region, the flow is often quite complicated with one or more vortices, but in the healthy section of the artery, the principal component of blood flows along the centerline of the artery. Based on this observation, we introduce a novel two-level additive Schwarz method with a mixed-dimensional coarse preconditioner. The key components of the preconditioner include (1) a three-dimensional coarse preconditioner covering the aneurysm; (2) a one-dimensional coarse preconditioner covering the central line of the healthy section of the artery; (3) a collection of three-dimensional overlapping subdomain preconditioners covering the fine meshes of the entire artery; (4) extension/restriction operators constructed by radial basis functions. The blood flow is modeled by the unsteady incompressible Navier-Stokes equations with resistance outflow boundary conditions discretized by a stabilized finite element method on fully unstructured meshes and the second-order backward differentiation formula in time. The resulting large nonlinear algebraic systems are solved by a Newton-Krylov algorithm accelerated by the new preconditioner in two ways: (1) the initial guess of Newton is obtained by solving a linear system defined by the coarse preconditioner; (2) the Krylov solver of the Jacobian system is preconditioned by the new preconditioner. Numerical experiments indicate that the proposed preconditioner is highly effective and robust for complex flows in a patient-specific artery with aneurysm, and it significantly reduces the numbers of linear and nonlinear iterations.

Assessing the impact of turbulent kinetic energy boundary conditions on turbulent flow simulations using computational fluid dynamics

Computational fluid dynamics has been widely used to study hemodynamics, but accurately determining boundary conditions for turbulent blood flow remains challenging. This study aims to investigate the effect of patient-specific turbulence boundary conditions on the accuracy of turbulent flow simulation. Using a stenosis model with 50% severity in diameter, the post-stenosis turbulence flow region was simulated with different planes to obtain inlet boundary conditions and simulate downstream flows. The errors of simulated flow fields obtained with turbulence kinetic energy (TKE) boundary data and arbitrary turbulence intensity were compared. Additionally, the study tested various TKE data resolutions and noise levels to simulate experimental environments. The mean absolute error of velocity and TKE was investigated with various turbulence intensities and TKE mapping. While voxel size and signal-to-noise ratio of the TKE data affected the results, simulation with SNR > 5 and voxel size < 10% resulted in better accuracy than simulations with turbulence intensities. The simulation with appropriate TKE boundary data resulted in a more accurate velocity and turbulence field than those with arbitrary turbulence intensity boundary conditions. The study demonstrated the potential improvement of turbulent blood flow simulation with patient-specific turbulence boundary conditions, which can be obtained from recent measurement techniques.

The splitting-based semi-implicit finite-difference schemes for simulation of blood flow in arteries

This paper is devoted to construction and analysis of splitting-based finite-difference schemes for simulation of blood flow in applications of one-dimensional models. Proposed schemes are constructed for inviscid and viscid models of blood. The proposed approach is based on the modification of averaged incompressibility condition, rewritten for the square root of a cross-sectional area. It is approximated by an absolutely stable scheme with a skew-symmetric operator. The constructed schemes can be classified as semi-implicit. The stability of proposed schemes is analyzed by the method of energy inequalities. Sufficient stability conditions are obtained. For the problems with analytical solutions, it is demonstrated that a second-order convergence rate is achieved in practice.The proposed schemes are compared with the widely used explicit finite-difference schemes, such as Lax–Wendroff, Lax–Friedrichs and McCormack schemes. The benchmark problems for simulation of flows in the following vascular systems are considered: human carotid artery, human aorta with bifurcation, vessel with bifurcation and absorbing outflow conditions, and networks with 31, 63, and 127 vessels. It is demonstrated that the computations based on the splitting-based semi-implicit schemes can be performed much faster than for the explicit schemes with close values of relative errors.

Towards Dual-Use Training Simulator in Interventional Neuroradiology

Abstract Cerebral aneurysms are common lesions in the general population and are increasingly treated by endovascular procedures. Training of these methods not only improves the learning period of physicians but also increases patient safety. However, the use of traditional medical training methods such as training in living animal models is decreasing due to high costs and ethical issues, so computer simulations and 3D-printed phantoms are being used instead. A more realistic simulation requires pulsatile blood flow that can be customized and has body temperature. Current simulators that use 3D-printed phantoms are mainly used under X-Ray in an angiography intervention room, therefore a dual-use simulator that is easy to transport and can be used also without X-Ray is desirable. Either it could be used traditionally in an angiography intervention room or externally in any regular room with an image simulation according to rotational angiography. In this work, a prototype for blood flow simulation is presented as a first step towards such simulator and its application is demonstrated through different investigations. The fluid system is capable of simulating a given blood flow profile and the heating system can generate an accurate body temperature. The case can be easily integrated into a modular phantom system and is convenient to transport, although the weight could be further reduced.

A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal.

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.

Is Accurate Lumen Segmentation More Important than Outlet Boundary Condition in Image-Based Blood Flow Simulations for Intracranial Aneurysms?

PurposeImage-based blood flow simulations are increasingly used to investigate the hemodynamics in intracranial aneurysms (IAs). However, a strong variability in segmentation approaches as well as the absence of individualized boundary conditions (BCs) influence the quality of these simulation results leading to imprecision and decreased reliability. This study aims to analyze these influences on relevant hemodynamic parameters within IAs.MethodsAs a follow-up study of an international multiple aneurysms challenge, the segmentation results of five IAs differing in size and location were investigated. Specifically, five possible outlet BCs were considered in each of the IAs. These are comprised of the zero-pressure condition (BC1), a flow distribution based on Murray’s law with the exponents n = 2 (BC2) and n = 3 (BC3) as well as two advanced flow-splitting models considering the real vessels by including circular cross sections (BC4) or anatomical cross sections (BC5), respectively. In total, 120 time-dependent blood flow simulations were analyzed qualitatively and quantitatively, focusing on five representative intra-aneurysmal flow and five shear parameters such as vorticity and wall shear stress.ResultsThe outlet BC variation revealed substantial differences. Higher shear stresses (up to Δ9.69 Pa), intrasaccular velocities (up to Δ0.15 m/s) and vorticities (up to Δ629.22 1/s) were detected when advanced flow-splitting was applied compared to the widely used zero-pressure BC. The tendency of outlets BCs to over- or underestimate hemodynamic parameters is consistent across different segmentations of a single aneurysm model. Segmentation-induced variability reaches Δ19.58 Pa, Δ0.42 m/s and Δ957.27 1/s, respectively. Excluding low fidelity segmentations, however, (a) reduces the deviation drastically (>43%) and (b) leads to a lower impact of the outlet BC on hemodynamic predictions.ConclusionWith a more realistic lumen segmentation, the influence of the BC on the resulting hemodynamics is decreased. A realistic lumen segmentation can be ensured, e.g., by using high-resolved 2D images. Furthermore, the selection of an advanced outflow-splitting model is advised and the use of a zero-pressure BC and BC based on Murray’s law with exponent n = 3 should be avoided.

Application of microcatheter shaping based on computational fluid dynamics simulation of cerebral blood flow in the intervention of posterior communicating aneurysm of the internal carotid artery.

The present study aimed to investigate the application of the aneurysm embolization microcatheter plasticity method based on computational fluid dynamics (CFD) to simulate cerebral blood flow in the interventional treatment of posterior communicating aneurysms in the internal carotid artery and to evaluate its practicality and safety. A total of 20 patients with posterior internal carotid artery communicating aneurysms who used CFD to simulate cerebral flow lines from January 2020 to December 2022 in our hospital were analyzed. Microcatheter shaping and interventional embolization were performed according to the main cerebral flow lines, and the success rate, stability, and effect of the microcatheter being in place were analyzed. Among the 20 patients, the microcatheters were all smoothly placed and the catheters were stable during the in vitro model test. In addition, the microcatheters were all smoothly placed during the operation, with a success rate of 100%. The catheter tips were stable and well-supported intraoperatively, and no catheter prolapse was registered. The aneurysm was completely embolized in 19 cases immediately after surgery, and a small amount of the aneurysm neck remained in one case. There were no intraoperative complications related to the embolization catheter operation. Microcatheter shaping based on CFD simulation of cerebral blood flow, with precise catheter shaping, leads to a high success rate in catheter placing, stability, and good support, and greatly reduces the difficulty of catheter shaping. This catheter-shaping method is worthy of further study and exploration.

Convergence of Phase-Averaged, Transitional Flow in an Abdominal Aortic Aneurysmal Model.

Abdominal aortic aneurysm can exhibit transitional flow characteristics in laminar flow regimes. To report transitional flow characteristics, we examined the convergence of phase-averaged solutions by executing blood flow simulations of a patient-specific abdominal aortic aneurysmal model for 257 cardiac cycles with periodic, pulsatile boundary conditions. The phase-averaged solutions were computed by averaging the solutions over various numbers of cardiac cycles and compared against the ones averaged over 124 cycles. The phase-averaged solutions reported small differences when they were averaged over a large number of cardiac cycles. The instantaneous solutions, however, failed to exhibit fluctuations reported in the phase-averaged solutions. To study transitional blood flows in the aneurysmal region, we need to report phase-averaged solutions as they exhibit nonperiodic, disturbed flow characteristics. Additionally, when reporting phase-averaged solutions, it is preferred to compute an average over a large number of cardiac cycles to be able to represent flow structures of the converged phase-averaged solutions.

Analysis of Blood Flow in Human Brain Vessels for Newtonian and Non-Newtonian Blood Properties

The cerebral artery system can be affected by various diseases such as stroke, carotid stenosis, vertebral stenosis, intracranial stenosis, aneurysms, and vascular malformations. Understanding the blood flow specific to each patient's cerebral arteries can provide crucial information about how these diseases progress and guide potential treatment options. A patient-specific Magnetic Resonance Imaging (MRI) scan of a human brain was utilized to create a 3D model of the arterial system. Blood flow simulations were conducted using the ANSYS (Fluent) R2021 software package. The ICEM meshing tool within the ANSYS software was employed to prepare the models. The velocity rise and pressure drop were observed in the branching of the basilar artery. This can provide valuable patient specific information on various cerebral diseases, and drug delivery cases. The non-Newtonian properties of blood were established by inputting the Power Law parameters into the ANSYS Fluent system. It was observed that the effects of non-Newtonian properties of blood are relatively negligible for the large vessels studied (&gt; 200 um).

Numerical Simulation of Blood Flow in Aortoiliac Bifurcation with Increasing Degree of Stenosis

The worldwide lethal prevalence of atherosclerotic diseases has made it a crucial topic of research, the descending aorta is a major artery with complex geometry involving curvature, branches, and bifurcation leading to common iliac arteries. This paper aims to scrutinize the intricate blood flow patterns and the flow parameters with the increasing degree of stenosis in the infrarenal aorta, which has been accomplished through computational fluid dynamics modeling. A 3D CAD model of the healthy aortoiliac bifurcation was constructed from MR images, and three diseased models with 32%, 47%, and 71% occlusion in the infrarenal aorta region were constructed. At the inlet, pulsatile velocity and at the outlet pressure boundary conditions were applied, blood was considered Newtonian and turbulence was modeled using Large Eddy Simulation (LES). The numerical simulation was carried out using finite volume method on ANSYS. The predicted hemodynamic parameters like velocity, wall shear stress (WSS), oscillating shear index (OSI), Q-Criterion and turbulence intensity were post-processed for all the models, the analysis of which provides an insight into the myriad processes involved in the inception and evolution of atherosclerosis. The transition of blood flow from laminar to turbulent with increase in the degree of stenosis is a very eminent feature of this study, turbulence is identified in cases with 47%, and 71% occlusion and is dominant in the latter.

TAXINOMISIS: A cloud - based platform for risk profiling and patient specific management of the carotid artery disease.

Carotid Artery Disease is a complex multi-disciplinary medical condition causing strokes and several other disfunctions to individuals. Within this work, a cloud - based platform is proposed for clinicians and medical doctors that provides a comprehensive risk assessment tool for carotid artery disease. It includes three modeling levels: baseline data-driven risk assessment, blood flow simulations and plaque progression modeling. The proposed models, which have been validated through a wide set of studies within the TAXINOMISIS project, are delivered to the end users through an easy-to-use cloud platform. The architecture and the deployment of this platform includes interfaces for handling the electronic patient record, the 3D arterial reconstruction, blood flow simulations and risk assessment reporting. TAXINOMISIS, compared with both similar software approaches and with the current clinical workflow, assists clinicians to treat patients more effectively and more accurately by providing innovative and validated tools.Clinical Relevance - Asymptomatic carotid artery disease is a prevalent condition that affects a significant portion of the population, leading to an increased risk of stroke and other cardiovascular events. Early detection and appropriate treatment of this condition can significantly reduce the risk of adverse outcomes and improve patient outcomes. The development of a software tool to assist clinicians in the assessment and management of asymptomatic patients with carotid artery disease is therefore of great clinical relevance. By providing a comprehensive and reliable assessment of the disease and its risk factors, this tool will enable clinicians to make informed decisions regarding patient management and treatment. The impact of this tool on patient outcomes and the reduction of healthcare costs will be of great importance to both patients and the healthcare system.