Contrast-enhanced ultrasound (CEUS) is capable of assessing flow in microvascular geometries. However, experimental validation of this technique is hindered by the lack of ground-truth data. The performance of CEUS can instead be assessed through simulation, such as with PROTEUS, which requires independent reference data for validation. PROTEUS has not previously been validated under high-frame-rate and high-frequency acquisition conditions. This study therefore validates PROTEUS-simulated Doppler flow reconstruction against computational fluid dynamics (CFD) reference data in two microvascular models: a cylindrical pipe with a diameter of 100 μm and a symmetric bifurcation consisting of a 200 μm parent vessel branching into two 160 μm daughter vessels.

The reference CFD data were generated in Ansys Fluent and integrated into PROTEUS, demonstrating the feasibility of coupling PROTEUS with an external CFD solver such as Ansys. Within PROTEUS, synthetic radiofrequency data were generated and processed through a conventional Doppler pipeline, including beamforming, power Doppler imaging, spectrogram generation, and velocity extraction, as well as a directional Doppler pipeline to assess flow direction. The extracted mean axial velocities closely matched the CFD reference, with relative errors of −0.17% in the pipe and −0.38% in the bifurcation's parent branch, while the daughter branches showed larger errors (−20.6% and +30.6%), potentially attributable to differences in focal depth and vessel orientation. Directional Doppler processing correctly resolved flow direction in both models.

Vessel diameter was additionally estimated using the full width at half maximum (FWHM) method with a 6 dB cutoff on power Doppler images. This method consistently overestimated the reference diameter across all vessels, with the largest error observed for the 100 μm vessel (+128.6%) and the smallest for the 200 μm vessel (+32.6%). In conclusion, high-frame-rate Doppler acquisition in PROTEUS reliably reconstructs mean velocity fields, although accuracy depends on the orientation and position of the vessel. Moreover, it is unable to reliably resolve vessel diameters near or below the transducer's axial resolution limit using the FWHM method, a constraint relevant to quantitative imaging of small-diameter microvasculature.
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Introduction: Medial calcification in the internal carotid artery (ICA) are associated with an increased risk of stroke among elder patients and cerebral small vessel disease. This type of calcification causes stiffening and reduces compliance and distensibility. Despite their common occurrence, few computational modelling studies have researched the effect of medial calcification on the arterial wall and blood flow. To address this gap, a 3-layered FSI model of the ICA was created to study the effect of circular extent, radial thickness and location of medial calcifications on the arterial wall and blood flow.
Method: Using the centreline from an ICA, a fluid mesh was created with the same diameter throughout the artery. The intima, media and adventitia layers were generated by lofting concentric rings. Material properties and boundary conditions were applied, and a mesh sensitivity analysis was performed.
Seven variations of this models was created, with varying calcification shapes and locations.
Results & Discussion: It was found that a 3-layer model of the arterial wall is needed to predict the distribution of stresses throughout the arterial wall, and a 1-layer model does not suffice. Calcifications with a larger angular extent showed a decrease in displacement and effective stress. The radial thickness of the calcification displayed a smaller effect on the arterial wall. The location of the calcification caused a different distribution of the displacement and effective stress.
Conclusion: The findings in this study suggest that to determine the impact of a medial calcification, the angular extent and location are more important to consider than the radial thickness. ... Read more

Functional assessment of stenosis severity is possible by estimating the trans-stenotic pressure drop from velocity data obtained from duplex ultrasound imaging or by intravenous pressure measurements. However, the simplified and extended Bernoulli methods, which are most common in clinical practice, leave room for improvement. Previous work has shown that the Modified Bernoulli method can predict the trans-stenotic pressure drop more accurately than these methods for an idealized one-in-one-out stenosis model, by explicitly including flow regime-dependent losses. In this work this method has been applied to a branching vessel with a stenosed branch, more specifically a stenosis in the superior mesenteric artery. Due to the complex and patient-specific collateral network, patients suffering from a stenosis in this artery in particular could benefit from more accurate functional testing, because a sufficient collateral network can prevent ischaemia even if a stenosis is present. Flow through two idealized geometries, one with the stenosis close to the branching point and one further distal, was simulated using Shear Stress Transport k-ω computational fluid dynamics simulations. It was found that the Modified Bernoulli method could accurately predict the pressure drop for the proximal stenosis location with an average error of 1.4% ± 0.2%, whereas the standard and extended Bernoulli methods had an average error of 19.8% ± 0.2% and 10.4% ± 0.2%, respectively. Pressure drop results for the distal stenosis were nearly identical with an average error of 1.5% ± 0.2% for the Modified Bernoulli method, 19.7% ± 0.1% for the simplified Bernoulli method and 10.3% ± 0.1% for the extended Bernoulli method. To investigate simulation dependence on the turbulence model used, a Large Eddy Simulation was found to differ significantly from SST k-ω results for a single flow case, with the jet flow caused by the stenosis breaking down over a length of 56.5 mm from the stenosis throat rather than 25.0 mm as predicted by SST. The pressure recovery however was similar at only 1.9% or 18 Pa higher. This work shows that according to SST k-ω simulations the Modified Bernoulli method can be succesfully applied to branching stenosed vessels, but that further validation of the simulation results is required. ... Read more

Ascending thoracic aortic aneurysms (ATAA) are associated with an increased risk of life-threatening dissection and rupture. Wall shear stress (WSS) is an important haemodynamic marker for aneurysm progression, but its computation using computational fluid dynamics (CFD) is computationally expensive, motivating the development of machine-learning (ML) surrogate models. Existing PointNet-based WSS surrogates predict WSS from vessel geometry alone and have not evaluated whether incorporating inlet velocity information improves prediction accuracy.

This study investigated the value of inlet velocity information through a controlled ablation study comparing two PointNet-based models: Model A, using only three-dimensional wall coordinates, and Model B, augmenting these coordinates with six scalar descriptors of the inlet velocity profile. Both models were evaluated using leave-one-geometry-out cross-validation across eight synthetic ATAA geometries generated from CFD simulations with varying inlet velocity profiles.

Model A consistently outperformed Model B across all evaluation metrics and folds, achieving a mean normalised mean absolute error (NMAE) of 7.63% compared with 13.44% for Model B, and a mean Pearson correlation coefficient of 0.49 compared with 0.19 (Wilcoxon signed-rank test, p = 0.0078). Model B additionally produced spatially inverted predictions in two out of eight folds, while both models systematically underestimated the highest WSS values.

The results demonstrate that, within the evaluated dataset and architecture, the tested six-scalar representation of inlet velocity did not provide additional predictive value and instead reduced WSS prediction accuracy. This finding does not imply that inlet velocity is unimportant for the underlying haemodynamics; rather, it suggests that compressed global velocity descriptors may be insufficient for improving geometry-based WSS surrogates. Future work should investigate spatially resolved velocity representations, larger and more diverse training datasets, and validation using patient-specific CFD data. ... Read more

Abdominal aortic aneurysm (AAA) morphology is a strong determinant of hemodynamics and post-repair complications, yet clinical assessment still relies on simple one-dimensional metrics such as maximum diameter and neck length, which cannot capture the three-dimensional complexity of the aortoiliac anatomy. This study develops a statistical shape model (SSM) of the full infrarenal aortoiliac anatomy, built from 99 patient-specific geometries using multi-level non-rigid registration and principal component analysis (PCA), and uses it to assess the hemodynamic effect of anatomical shape variation via computational fluid dynamics (CFD). The model captures 95% of geometric variance in 26 modes, with a bootstrap-based stability criterion identifying 23 modes as structurally meaningful and distinguishing genuine anatomical variation from noise. Leading modes correspond to clinically interpretable features, including aneurysm axial extent, aortic tortuosity, and iliac bifurcation angle. Despite the anatomical complexity, the model generalizes well, reconstructing unseen geometries with sub-2 mm mean error. Varying the first three principal components independently in CFD simulations shows that these shape modes drive measurable, mode-specific changes in Endothelial Cell Activation Potential (ECAP), a hemodynamic marker of thrombotic risk. Lastly, this study presents the results of a proof-of-concept principal component based gaussian process interpolation model for 99th percentile of ECAP as a function of leading principal components. ... Read more

Endovascular aneurysm repair (EVAR) is widely used for the treatment of abdominal aortic aneurysms, but thrombotic complications such as iliac limb occlusion and intraluminal thrombus formation remain clinically relevant. Previous computational studies have shown that post-EVAR hemodynamics are influenced by aorto-iliac geometry, yet the isolated relation between iliac coronal angulation and prothrombotic near-wall flow indicators remains insufficiently characterised. This thesis addresses this gap using a parametrically controlled idealised aorto-iliac computational fluid dynamics (CFD) model, in which the iliac coronal angle was varied from 15° to 75° while all other parameters were kept constant. Pulsatile, non-Newtonian simulations were performed in ANSYS Fluent, and the near-wall environment was assessed using time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP). The idealised sweep was complemented by statistical shape model (SSM)-derived geometries, representing native, non-stented anatomy, to test whether the same tendencies appeared in more realistic shapes.

When the angle was varied in isolation, the adverse hemodynamic area did not grow with angle: the low-TAWSS area decreased from 61.5% to 58.0% of the analysed wall between 15° and 75°, the elevated-RRT area decreased similarly, and the high-OSI and high-ECAP areas increased from a negligible base. In the SSM-derived geometries, by contrast, the low-TAWSS area increased with the measured coronal bifurcation angle, from 86.4% to 94.0%, and showed the strongest fitted trend of any metric (R² = 0.95), while OSI, RRT, and ECAP showed no consistent trend. That the low-TAWSS area moves in opposite directions when angle is varied alone versus together with realistic anatomy is the central finding: the adverse shear response attributed to angulation arises from the combined geometry that accompanies it, not from the angle by itself.

For clinical interpretation, this suggests that iliac angulation is best interpreted not as a stand-alone marker of thrombus-prone conditions, but as one geometric factor to be assessed together with the surrounding anatomy and device. Extending the analysis towards an explicit EVAR stent-graft within realistic geometries is needed before such metrics could support patient-specific risk assessment.
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Aortic valve neocuspidization (AVNeo) reconstructs the aortic valve by suturing three glutaraldehyde-treated autologous pericardial leaflets to the native annulus. Clinical observations suggest that complications can arise at the attachment line, indicating that the stresses and strains introduced during suturing may be mechanically relevant. Yet this suturing-induced mechanical state is difficult to characterise experimentally, and numerical models of AVNeo commonly begin from a post-suturing configuration, neglecting the pre-stretch generated during leaflet attachment. Moreover, collagen fibre orientation in pericardium is not determined intraoperatively, introducing uncertainty in the fibre alignment of the implanted leaflet. This study investigates how fibre-orientation variability influences suturing-induced pre-stretch along the AVNeo attachment region using finite element analysis. A finite element virtual suturing workflow was developed by pairing leaflet and annulus edge nodes and prescribing their mapping along the attachment curve. Leaflets were modelled with an anisotropic fibre-reinforced hyperelastic formulation for three in-plane fibre orientations (0°, 45°, 90°), with an isotropic Yeoh model as reference. Simulations used an idealised aortic root, with a patient-specific proof-of-concept. To compare the resulting suturing-induced deformation across configurations, strain was quantified using the 95th-percentile maximum principal Green–Lagrange strain in the nadir region. Across anisotropic fibre orientations, the nadir maximum strain ranged from 0.367 for the radial configuration to 0.383 for the oblique configuration, corresponding to an uncertainty of approximately 4%. In contrast, the isotropic material model predicted a substantially lower nadir strain (0.159), representing an underestimation exceeding 50%. Application of the workflow to a patient-specific geometry reproduced similar folding behaviour and strain localisation, demonstrating its applicability to anatomically realistic configurations. These results indicate that suturing establishes a pre-stretched mechanical state in AVNeo leaflets prior to physiological loading. Differences in collagen fibre orientation produce measurable variability in suturing-induced strain despite identical geometry, prescribed motion, and numerical settings. Accounting for suturing mechanics and fibre-oriented tissue behaviour therefore contributes to defining a physically meaningful initial state for AVNeo leaflet modelling. ... Read more

Blood pressure is a crucial parameter in haemodynamic monitoring, providing an indication of tissue perfusion in critical situations. Commonplace in (paediatric) intensive care units ((P)ICU) are arterial catheters, inserted in the radial artery, which are an invasive means of continuously measuring blood pressure. However, quantifying the degree to which arterial catheter geometries modify the pressure measurement, especially for paediatrics, remains seemingly unexplored in research, while discrepancies between non-invasive and invasive blood pressure monitoring methods have been observed in Erasmus MC (P)ICU departments.

Using FEBio, a computational fluid dynamics (CFD) model was developed to investigate the influence of catheter geometries on the pressure generated at the catheter tip (taken to be the measured pressure) for six age groups ranging from <2 years to 18 years of age. For three age groups (2-5 years, 12-14 years, and 15-18 years), simulations were run with two different catheter gauges (diameters).

Hence, a total of nine different sets of age and catheter gauge were investigated. Apart from comparison between simulations with and without a catheter, the effect of the position of the catheter in the vessel (eccentricity ratio) and changing catheter lengths in the vessel were studied. The results show that arterial catheters (substantially) influence the pressure measured by the catheter. In the worst-case scenarios simulated, namely that in which the catheter is in the centre of the vessel with an intraluminal catheter length equal to 80% of its total length, eight of the nine cases investigated showed systolic pressure values higher than the target values used in the
PICU. Thus, the results suggest that the presence of the catheter may be enough to modify a normal blood pressure into appearing elevated (hypertensive), potentially influencing patient treatment. Shorter catheter lengths were associated with lower pressure overestimations, as was moving the catheter towards the vessel wall. Consequently, these results are clinically significant, and may help physicians in making more informed haemodynamic assessments. ... Read more

Complications following endovascular aneurysm repair (EVAR), such as Type IA endoleaks (TIAEL) and limb graft occlusions (LGO), remain a clinical concern. However, existing research aimed at resolving these complications is limited, mainly due to difficulties in visualizing and quantifying the deformation of stent fabric in standard postoperative images. This thesis presents a novel in vitro framework to visualize and quantify stent graft fabric folding in abdominal aortic aneurysm (AAA) phantoms. Silicone phantoms with representative AAA
anatomy were fabricated and validated using a combination of compression tests and a clinical evaluation of elasticity by experienced clinicians. Each phantom was implanted with an
Endurant II stent grafts under varying oversizing conditions. Micro-CT imaging was used to visualize the endograft fabric within the phantoms. A custom convolutional neural network-
based segmentation pipeline was developed to quantify fold severity as the proportion between the total phantom area and the stented lumen. Preliminary comparison with finite element simulations (PrediSurge) demonstrated the feasibility of the method. Therefore, this thesis establishes a validated methodology for fabric fold visualization and quantification, supporting future studies on the relationship between stent graft folding and post-EVAR complications. ... Read more

The aortic arch plays a vital role in the cardiovascular system, connecting the ascending and descending thoracic aorta and giving rise to three major arteries that supply oxygenated blood to the upper body and central nervous system. Its complex geometry and high inter-patient variability pose significant challenges for thoracic surgical planning and the design of endovascular devices. Despite its clinical importance, systematic characterization of aortic arch shape variation remains limited, particularly in cases involving the supra-aortic branches. This study addresses this gap by applying Statistical Shape Modeling (SSM), a data-driven method that captures anatomical variability with precision. The methodology includes data collection, geometric preprocessing, and shape registration, culminating in an interpretable statistical model of the aortic arch. Furthermore, the study explores how these models can be integrated into Computational Fluid Dynamics (CFD) simulations to assess the performance of branched stent grafts used in Thoracic Endovascular Aortic Repair (TEVAR). The aim is to evaluate their ability to restore physiological blood flow. Ultimately, this approach supports the development of more effective, patient-specific interventions. ... Read more

Accurate diagnosis of Chronic Mesenteric Ischemia (CMI) requires a comprehensive understanding of both anatomical and hemodynamic factors affecting mesenteric blood flow. This study employed Computational Fluid Dynamics (CFD) simulations to assess blood flow in the superior mesenteric artery (SMA) under varying conditions. Simulations on idealized geometries demonstrated the significant impact of hyperemia on flow dynamics in stenosed vessels, particularly in moderate stenosis. The presence of a collateral vessel from a patent celiac artery (CA) was shown to enhance distal SMA perfusion and reduce pressure gradients. A patient-specific computational workflow was also developed, incorporating CT-based segmentation, boundary condition setup, simulation, and post-processing. Results underscore that anatomical stenosis severity alone is insufficient to determine the functional significance of an SMA lesion. Instead, patient-specific hemodynamics, especially the presence and configuration of collateral pathways, must be considered. While promising, these findings require further validation with larger patient datasets.
link to dataset:
https://doi.org/10.4121/845085c4-9999-41bd-8a4f-02cbdea61164 ... Read more

Background: Cerebrovascular diseases, which often involve a disruption in blood flow in the Circle of Willis (CoW) and its branching arteries, pose a major global health risk. Computational fluid dynamics (CFD) analyses present an opportunity to study their pathophysiology but require high-quality vessel segmentations. Methods: To generate pseudo-labeled training data, computed tomography angiography (CTA) images were preprocessed and inference was run using two pretrained models: an nnU-Net for multi-class CoW segmentation and a DTUNet for binary cerebral vessel segmentation. These outputs were combined using a region-growing approach; the resulting pseudolabels were used to train an nnU-Net V2 with a topologyaware loss function. CFD analyses were performed on both a model-generated segmentation and a ground truth segmentation derived from a CTA scan which had been expert-labeled by a neuroradiologist. The resulting velocity, pressure and wall shear stress (WSS) profiles for both segmentations were compared across 10 cross-sections of the middle cerebral artery (MCA). Results: After filtering out inaccurate labels, 1,709 of 2,201 pseudo-labeled images were retained for training and testing. Common errors included over-segmentation of small vessels, under-segmentation of large vessels and poor separation of the anterior cerebral arteries when compared to expert-annotated ground truth segmentations. The proposed segmentation model was evaluated on the test set, which used pseudo-labels as a reference standard, and achieved a mean Dice score of 62%, clDice of 40%, IoU of 51%, a HD of 16.9 voxels and an ASD of 3.9 voxels. In terms of centerline-based metrics, the model achieved a mean overlap (OV) of 72% and an average ASCD of 4.26 voxels. In CFD simulations, the predicted segmentation yielded absolute errors of 48.96 �} 30.69 mm/s, 7.47 �} 6.07 Pa and 1.22 �} 0.81 Pa for blood flow velocity, pressure and WSS, respectively, compared to the expert-annotated reference (p < 0.05 for all). Conclusions: This study demonstrates that a deep learning model, trained using pseudo-labels, can successfully generate anatomically plausible multi-class segmentations of the CoW suitable for downstream CFD analysis. However, discrepancies in key hemodynamic metrics compared to expert-annotated data highlight the need for improved pseudo-label accuracy, especially in regions of complex vascular geometry. ... Read more

Vascular calcification, the deposition of calcium in the vessel wall, is associated with several vascular diseases, including atherosclerosis, diabetes mellitus, and hypertension.
Fluid-structure interaction (FSI) is recommended to simulate blood flow incorporating vascular calcification. However, FSI applied to a three-dimensional (3D) model takes several days to simulate.
To reduce the computational complexity, 1D reduced order models (ROMs) are often used instead.

Reduced order modeling decreases the computational complexity of a model by removing dimensions of the coordinate system within a model. The cylindrical coordinate system is used in hemodynamics, especially in ROMs. The 1D ROM for hemodynamics is obtained by removing the azimuthal dimension (accomplished by assuming axial symmetry for all properties within arteries) and the radial dimension (accomplished by applying a predefined velocity profile to blood flow) from the 3D model. However, incorporating vascular calcification can make the geometry of arteries and flow within arteries asymmetric. A 2D ROM can increase the accuracy of the 1D ROM by including one of the two removed dimensions. Research regarding 2D blood flow mainly focuses on including the radial dimension, which cannot implement asymmetric calcification since axisymmetry is assumed.

This study obtains a 2D ROM for blood flow by removing the dimension corresponding to the radial distance from the three-dimensional model and by assuming that axial velocity is continuous in the neighborhood near the artery's origin. The 2D ROM obtains axisymmetric velocity by only allowing a single velocity profile. However, enabling a family of velocity profiles can make flow within arteries asymmetric. Hence, this study contributes to hemodynamics by studying blood flow that allows a family of velocity profiles.

A non-physiological steady-state solution has been obtained analytically, in which the volumetric flow rate vanishes, and numerical methods are developed to simulate the 2D ROM, which incorporates dimensional (Godunov) splitting, linear approximate solvers, and high-resolution methods. Jump-discontinuities within the mechanical properties of the vascular walls are smoothened for the 2D simulations. Numerical methods for the 2D ROM yield significant errors within the smoothening region for simulations with coarse grids.
The numerical method obtains the non-physiological steady-state solutions for arteries without calcification and has a relative error of O(Δx^1.500) for arteries with axisymmetric calcification. The 2D ROM cannot numerically obtain the non-physiological steady-state solution for arteries with asymmetric calcification due to the numerical errors within the smoothening range.

 3D and 2D numerical simulations with pulsatile blood flow are compared. The 3D simulation without calcification has a significantly higher diastolic pressure, larger inner wall radii, and larger volumetric flow rates than the 2D simulation. The differences in blood flow observed between pulsatile blood flow without calcification and with calcification match decently between the 3D simulations and the 2D simulations, except for locations within the smoothening region. ... Read more

Cerebral small vessel disease (CSVD) is a leading cause of stroke and dementia, making the study of small vessel hemodynamics vital for advancing diagnostic and therapeutic strategies. This research focuses on fabricating microfluidic devices that replicate the lateral lenticulostriate arteries (LSA) to validate computational flow models of small cerebral vessels. A key challenge in studying CSVD is the lack of experimental validation for computational fluid dynamics (CFD) models, which are widely used to simulate hemodynamics. To address this, additive masked Stereolithography (mSLA) was employed to fabricate a microfluidic model of the LSAs. The study explored the impact of orientation, exposure time, and layer height on the roundness and error of the intended area of printed micro-pores, to optimize the manufacturing of a microfluidic device. The smallest printed pore measured 270 μm in diameter. Pores printed at a larger angle as assessed from the build plate were more likely to remain open, but exhibited a larger decrease in area compared to smaller angles. A lower exposure time exhibited a larger pore area, whereas a larger layer height showed a decrease in area from intended. The layer height and angle did not influence the roundness, whereas an increase in exposure time decreased the roundness of the pores. Additionally, flow experiments were conducted using a 3D printed microfluidic device to compare empirical data with CFD and analytical simulations. The encountered resistance was larger for the experimental results (3.19 ⋅10^11 Pa⋅s/m^3) compared to the analytical result (1.96 ⋅10^11 Pa⋅s/m^3) and the computational result (1.90 ⋅10^11 Pa⋅s/m^3), likely due to deviation from the intended size. Finally, arterial microfluidic devices were printed and flow was induced to showcase their functionality. Achieving precise channel dimensions remains the primary challenge in mSLA printing due to cumulative dosage effects.
This research bridges the gap between computational modeling and experimental validation, providing a platform for studying cerebral microcirculation. The findings demonstrate the feasibility of using commercially available 3D-printed microfluidic devices to replicate small cerebral vessels. The outcomes of this study contribute to the advancement of vascular biomodeling, with implications for future clinical applications in stroke and neurovascular research.
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Altered blood flow dynamics play a vital role in cerebrovascular diseases, such as cerebral small vessel disease (CSVD), an umbrella term encompassing various pathologies that affect small arteries, arterioles, capillaries, and venules. Understanding the complex relation between vascular geometry and local flow conditions requires high-resolution insight into microscale local hemodynamics. Nonetheless, in vivo imaging lacks the spatial resolution necessary to visualize flow in small vessels, and computational models require experimental validation to ensure modeling accuracy.

This thesis presents an integrated framework using 3D printed microfluidic models, particle image velocimetry (PIV), and computational fluid dynamics (CFD) to investigate hemodynamics on a microscale. Transparent 3D printed vascular models with simplified, straight, bifurcated, and pathological geometries were successfully fabricated using a direct 3D printing method employing a masked stereolithography (MSLA) 3D printer, achieving a minimum channel diameter of 0.5 mm. A developed post-processing method increased optical transparency, and a refractive index-matched working fluid was developed to minimize distortion. Microscopy and micro-CT imaging were used for morphological characterization, and flow experiments were conducted under steady-state laminar conditions. A microfluidic control system was employed to obtain global flow and pressure data, while micro-PIV was utilized to capture local velocity fields and wall shear stress (WSS). In the straight channels, the experimental results were compared with the analytical Hagen–Poiseuille approximation. The computational model was then validated using both analytical and experimental data for the straight geometries, followed by experimental validation of the computational model in the bifurcated and pathological geometries.

Velocity profiles between the computational and experimental results showed good agreement, exhibiting similar flow features with relative errors ranging from 5% to 17%. Experimental velocities were generally lower than those predicted by analytical and CFD methods, primarily due to limitations in near-wall resolution and visualization, as well as averaging over the depth-of-correlation (DOC) and the finite spatial resolution of PIV. These limitations were particularly pronounced in the sub-millimeter channel (0.5 mm) and at a lower magnification (4x objective). The wall shear stress comparison shows that the near-wall spatial resolution is the limiting factor rather than model physics. For the 4x objective or for the smaller-sized channels (0.5 mm and 1 mm channel), with a lower spatial resolution, the WSS was underestimated and showed significant deviations (15% to 40%) depending on the geometry. For the 2.0 mm channel and the middle section of the stenotic model at 10x magnification, the results matched well with an average error of 2.6%.

The thesis objective was achieved, and the integrated experimental-computational approach demonstrates that micro-PIV data from 3D printed vascular models can effectively be used to validate CFD simulations of microscale hemodynamics. The developed methodology provides a foundation for future work involving more complex patient-specific geometries, compliant walls, or non-Newtonian fluids, ultimately supporting the validation of numerical models for cerebrovascular flow under physiologically realistic conditions.
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Background
When the heart cannot fully contract, less oxygen-rich blood is delivered to organs and tissues in the body, which can lead to organ failure and eventually death. A left ventricular assist device (LVAD) supports the heart by increasing blood flow from the left ventricle to the aorta. A novel LVAD is being developed that consists of an inflatable balloon, which is placed in the left ventricle via a small insertion in the groin. The balloon is actuated at high frequencies by making use of a diaphragm pump, which is placed next to the patient’s bed and is connected to the balloon with a catheter filled with helium. The diaphragm pump can inflate the balloon by compressing the helium and deflate the balloon with expansion of the helium. Actuating the diaphragm at high frequencies generates heat in the pressure chambers of the pump due to friction. However, the maximum temperature of parts of the system that can come into contact with a patient or medical personal, cannot exceed 41◦C according to medical regulation. Therefore, the aim of this project is to create a concept design for cooling the helium gas flow used to inflate and deflate an intraventricular balloon at high frequencies for a novel left ventricle assist device.

Method
First, an overview of existing cooling techniques is created. Eight of the 24 cooling techniques explored met the list of requirements. These eight techniques are assessed against the list of weighted criteria using the Harris profile method. A concept design is created for the three best scoring techniques: thermoelectric cooling, vortex cooling, and forced convection using air for which the forced convection concept design appears to be most feasible. The final cooling concept features two air fans blowing air through a heat sink incorporated in the aluminium base structure around the pressure chambers. To verify the concept, a (simplified) simulation model is created in Ansys Fluent.

Results
The simulation model is used to simulate air flow through the channels and heat conduction in the base structure around the pressure chambers. The optimal fan velocity is determined by analysing the pressure drop and the temperature behaviour of the system. Furthermore, the model is 3D printed in plastic to validate the simulation model by performing velocity and pressure tests. Since the test results match the simulation results, the simulation model is considered validated.

Conclusion
In conclusion, after assessing different cooling techniques, a concept based on forced convection is developed in detail. The design is verified with a simulation model, and the simulation results are validated with a 3D printed plastic model. Although the concept design allows for room for optimization, it has proven to be a feasible solution for cooling the pressure chambers, and thus the helium gas, in the diaphragm pump of the novel LVAD. ... Read more

Cerebrovascular diseases, including stroke and dementia, rank among the top 10 causes of death globally. Where the Circle of Willis is an anatomical structure at the base of the brain that redistributes blood flow. Vrselja et al. challenged the traditional view that the primary function of the Circle of Willis is to provide collateral circulation, suggesting instead that it dissipates high pressures in the cerebrovasculature.

One-dimensional (1D) modeling, based on the simplified Navier-Stokes equations, offers a way to accurately predict blood flow with only a fraction of the computational expense of a three-dimensional (3D) model. SimVascular, a computational modeling software tailored for representing blood flow, recently added a 1D modeling feature. This study assessess the suitability of the 1D model in SimVascular for representing the cerebrovasculature, by testing it on the Circle of Willis. Additionally, preliminary research investigates whether the Circle of Willis functions as a pressure dissipative system, particularly through its communicating arteries.

The modeling pipeline included centerline extraction, mesh generation, boundary conditions, material model and solver parameters. Challenges were identified during centerline extraction, as SimVascular is inherently unable to handle loops, and inlet boundary conditions, where it could not manage multiple inlets. Considering these limitations, a series of 1D linear elastic models were created from the 3D geometry of the Circle of Willis to test whether it serves as a pressure dissipative system.

While SimVascular was unable to handle closed-loop geometries and multiple inlets, results indicated that the absence of a communicating artery induced relatively minor pressure oscillations. This suggests first, that SimVascular, in its current form, is not well-suited for 1D modeling of the cerebrovascular system's complexities, including loops and multiple inlets. Second, that the hypothesis of the Circle of Willis functioning primarily as a pressure dissipative system holds promise but requires further validation. ... Read more

The study of haemodynamics, or the mechanics of blood flow, has been a topic of significant interest since ancient times, as it provides critical insights into both the normal functioning of the circulatory system and the mechanisms underlying various diseases. A robust scientific understanding of these dynamics facilitates the development of innovative prevention and intervention strategies, such as advanced, less invasive surgical techniques and cost-effective medical devices, which can dramatically improve global health outcomes. Over the centuries, experimental, analytical, and, more recently, computational methods have enhanced our knowledge of cardiovascular and cerebrovascular conditions, leading to improved diagnostic and therapeutic approaches that enhance life quality and expectancy.

Despite these advancements, substantial challenges remain, particularly in diagnosing and understanding haemodynamic complications such as stroke, stenosis, and regurgitation. Modern imaging techniques like MRI and sonography are limited by spatial and temporal resolution, requiring significant hardware improvements to overcome these constraints. Moreover, while analytical models have evolved to address the complex nature of blood flow and vessel behavior, they often struggle to accurately represent in vivo scenarios, especially in areas like the cerebral vasculature that are difficult to image. The presence of anomalies such as medial calcifications - which are responsible behind numerous life altering conditions and diseases such as, diabetes, kidney disease and hypertension - further complicates the accurate modeling of blood flow dynamics by introducing departure from axisymmetry, changes in material properties of the tissue and impacting the physics at localized scale.

To address the impact of medial calcifications, this thesis presents a detailed approach starting with the development of a three-dimensional (3D) model that represents the physiological fluid-structure interaction (FSI) phenomenon of pulsatile blood flow through an Internal Carotid Artery (ICA) with medial calcification. ICA is a critical vessel within the Circle of Willis which itself is one of the most crucial cerebro-vascular networks. Following this, a physics based one-dimensional (1D) Reduced Order Model (ROM) is developed, integrated with which is a data-driven constitutive modelling framework trained on the 3D simulation data, to account for changes in material proeprties introduced by medial calcifications. This ROM aims to provide a computationally efficient yet accurate representation of the physiological changes caused by medial calcifications. The thesis includes a comprehensive theoretical framework, detailed validation and verification processes, and comparisons between the 1D and 3D models to ensure accuracy and clinical relevance. The overarching goal is to create a well-validated ROM that maintains essential physical details while reducing computational costs, with an emphasis on evaluating its performance in clinical scenarios and exploring its potential applications and future research directions. ... Read more

Trans-catheter aortic valve replacement (TAVR) has been widely used for treating Aortic stenosis (AoS). Numerical simulation of TAVR process is valuable in terms of reducing surgical risk for patients and cost for valve design. Finite element simulations are performed in this thesis to investigate the risk of coronary obstruction for patients who went through Aortic Valve Neo-cuspitization (AVNeo or Ozaki) procedure. The Expected Leaflet-to-ostium Distance was used as a criterion for assessing coronary obstruction risk. This value in 3 different deployment configurations is compared to determine the optimal deployment strategy. It is found that there is a large risk of coronary obstruction after TAVR for such patients under distal and midplane configuration but no risk under proximal configuration. ... Read more

Ascending thoracic aortic aneurysm is a dangerous condition which is hard to locate in patients. CFD can be used to assess someone’s risk of suffering from such an aneurysm and also to assess any possible relation of an aneurysm with relevant parameters, like the shape of the aorta or how blood flows into the aorta.

Existing research on ascending aortic CFD flow generally focuses on assessing relatively high wall shear stress, seen as the cause for aortic wall damage and aneurysms, in patients and not much on any possible relationships between aortic shape and inflow with ascending aortic aneurysm. Work that does exist often uses 4D flow MRI, shown to produce results regarding peak wall shear stresses with less accuracy compared to CFD.

This thesis aims to supply that information using an aortic geometry from a large dataset of synthetically generated aortas together with synthetically generated inlet velocity profiles, showing a possibility to work with-out the need for patient measurements. The main work in this thesis focuses on finding any possible relationship between aortic inflow angle and relatively high wall shear stress, such that the results may better explain how aortic inflow can influence the appearance of aneurysms.

For this, a workflow has been established that allows working with large aortic geometry and inflow profile datasets with relative ease. This workflow process uses a mix of OpenFoam and Ansys Fluent usage.

Results have shown that the flow jet angle in the core of the flow has a significant negative correlation with peak WSS within the ascending aorta for the chosen aortic geometry. This is in contrast with other work showing positive correlations with WSS. This may suggest aortic geometry dependence together with the need to look at other flow variables, like jet impingement angle, to explain how aortic inflow can influence high WSS within the ascending aorta.

Recommendations for future work include: The same study but with a focus on aortas of healthy young people to see if aortas at risk can be found, as existing work mainly focuses on old people with ascending thoracic aortic aneurysm, a similar study with a focus on the inclusion of various aortic geometries to find how aortic geometry may influence the effect inflow variables can have on high WSS, the creation of a tool to easily calculate the impingement angle from aortic flow data and research into if aortic jet flow disruption could reduce peak WSS in the ascending aorta for use in aortic reconstruction. ... Read more