Jana Korte

The rupture of an intracranial aneurysm (IA) has been linked to local hemodynamic environments, but it remains unclear how transient physiological states such as elevated heart rate modulate those environments, and whether different aneurysm geometries respond similarly. Here, we used volumetric particle tracking velocimetry (PTV) to measure 3D velocity fields in two patient-specific IA phantoms, a right middle cerebral artery (MCA) aneurysm and a left vertebral artery (LVA) aneurysm, under three heart rates representative of rest (60 bpm), active movement (100 bpm), and exercise (137 bpm). From these measurements, we quantified coherent structures, turbulent kinetic energy (TKE), wall shear stress (WSS), and oscillatory shear index (OSI). Increasing heart rate did not simply increase peak inflow; it altered the temporal organization of the flow. In the MCA aneurysm, higher heart rates produced a stronger, more anchored intra-saccular vortex and elevated coherent-structure strength and TKE that persisted into mid- and end-diastole, along with broader spatial coverage of elevated WSS that remained high beyond peak systole. The LVA aneurysm exhibited a more muted response, with minimal changes in streamline topology and WSS across heart rates. These results show that heart rate can drive prolonged high-shear, high-energy loading within the cardiac cycle, but that this amplification is morphology-dependent and non-monotonic rather than universal.

Computational fluid dynamics (CFD) carry the potential to provide detailed insights into intraventricular hemodynamics and complement in vivo flow measurement techniques. A variety of CFD approaches emerged in recent years, mostly building solely on medical image data as patient‐specific input. While the utilized medical imaging method and chosen CFD approach both influence the computed hemodynamics, thereto related differences are rarely investigated. The present study addresses this issue with an inter‐(imaging)‐modality and inter‐model comparison of intracardiac flow computations. Magnetic resonance imaging (MRI) and transthoracic echocardiography (TTE) data of a volunteer were acquired and used to reconstruct the anatomical structures. For each modality, the reconstructed shapes were applied in two previously introduced CFD approaches to compute whole‐cycle ventricular flow patterns. While both methods involved benefits and challenges, similar valve velocities were computed, being in accordance with in vivo 4D flow MRI and pulsed‐wave Doppler velocity measurements (systolic peak velocity: 1.24–1.26 m/s (MRI), 0.9–1.25 m/s (TTE); diastolic peak velocity: 0.54 m/s (MRI), 0.59–0.75 m/s (TTE)). A detailed flow analysis with vortex formation, kinetic energy, and mid‐ventricular velocities indicated the computed inter‐modality differences to be larger than inter‐method ones. Quantitatively, this could be observed in the direct flow rate ( inter‐modality: 13, inter‐method, 3). These results help to gain trust in CFD approaches to compute intraventricular flow and emphasize the importance of standardized input data. Future studies, however, should consider a broader data base.

Purpose: Hemodynamics play an important role in the assessment of intracranial aneurysm (IA) development and rupture risk. The purpose of this study was to examine the impact of complex vasculatures onto the intra-vessel and intra-aneurysmal blood flow. Methods: Complex segmentation of a subject-specific, 60-outlet and 3-inlet circle of Willis model captured with 7T magnetic resonance imaging was performed. This model was trimmed to a 10-outlet model version. Two patient-specific IAs were added onto both models yielding two pathological versions, and image-based blood flow simulations of the four resulting cases were carried out. To capture the differences between complex and trimmed model, time-averaged and centerline velocities were compared. The assessment of intra-saccular blood flow within the IAs involved the evaluation of wall shear stresses (WSS) at the IA wall and neck inflow rates (NIR). Results: Lower flow values are observed in the majority of the complex model. However, at specific locations (left middle cerebral artery 0.5 m/s, left posterior cerebral artery 0.25 m/s), higher flow rates were visible when compared to the trimmed counterpart. Furthermore, at the centerlines the total velocity values reveal differences up to 0.15 m/s. In the IAs, the reduction in the neck inflow rate and WSS in the complex model was observed for the first IA (IA-A δNIRmean = − 0.07ml/s, PCA.l δWSSmean = − 0.05 Pa). The second IA featured an increase in the neck inflow rate and WSS (IA-B δNIRmean = 0.04 ml/s, PCA.l δWSSmean = 0.07 Pa). Conclusion: Both the magnitude and shape of the flow distribution vary depending on the model’s complexity. The magnitude is primarily influenced by the global vessel model, while the shape is determined by the local structure. Furthermore, intra-aneurysmal flow strongly depends on the location in the vessel tree, emphasizing the need for complex model geometries for realistic hemodynamic assessment and rupture risk analysis.

The Circle of Willis (CoW) describes the arterial system in the human brain enabling the neurovascular blood supply. Neurovascular diseases like intracranial aneurysms (IAs) can occur within the CoW and carry the risk of rupture, which can lead to subarachnoid hemorrhage. The assessment of hemodynamic information in these pathologies is crucial for their understanding regarding detection, diagnosis and treatment. Multi-dimensional in silico approaches exist to evaluate these hemodynamics based on patient-specific input data. The approaches comprise low-scale (zero-dimensional, one-dimensional) and high-scale (three-dimensional) models as well as multi-scale coupled models. The input data can be derived from medical imaging, numerical models, literature-based assumptions or from measurements within healthy subjects. Thus, the most realistic description of neurovascular hemodynamics is still controversial. Within this systematic review, first, the models of the three scales (0D, 1D, 3D) and second, the multi-scale models, which are coupled versions of the three scales, were discussed. Current best practices in describing neurovascular hemodynamics most realistically and their clinical applicablility were elucidated. The performance of 3D simulation entails high computational expenses, which could be reduced by analyzing solely the region of interest in detail. Medical imaging to establish patient-specific boundary conditions is usually rare, and thus, lower dimensional models provide a realistic mimicking of the surrounding hemodynamics. Multi-scale coupling, however, is computationally expensive as well, especially when taking all dimensions into account. In conclusion, the 0D–1D–3D multi-scale approach provides the most realistic outcome; nevertheless, it is least applicable. A 1D–3D multi-scale model can be considered regarding a beneficial trade-off between realistic results and applicable performance.

Background The novel Contour Neurovascular System (Contour) has been reported to be efficient and safe for the treatment of intracranial, wide-necked bifurcation aneurysms. Flow in the aneurysm and posterior cerebral arteries (PCAs) after Contour deployment has not been analyzed in detail yet. However, this information is crucial for predicting aneurysm treatment outcomes. Methods Time-resolved three-dimensional velocity maps in 14 combinations of patient-based basilar tip aneurysm models with and without Contour devices (sizes between 5 and 14 mm) were analyzed using four-dimensionsal (4D) flow MRI and numerical/image-based flow simulations. A complex virtual processing pipeline was developed to mimic the experimental shape and position of the Contour together with the simulations. Results On average, the Contour significantly reduced intra-aneurysmal flow velocity by 67% (mean w/ = 0.03m/s; mean w/o = 0.12m/s; p-value=0.002), and the time-averaged wall shear stress by more than 87% (mean w/ = 0.17Pa; mean w/o = 1.35Pa; p-value=0.002), as observed both by numerical simulations and 4D flow MRI. Furthermore, a significant reduction in flow (PConclusions This study showed the high efficacy of the Contour device in reducing flow within aneurysms regardless of the exact position. However, we observed an effect on the flow in PCAs, which needs to be investigated further.

Introduction: In this study, phase-contrast magnetic resonance imaging (PC-MRI) 4D flow data for patients with bicuspid aortic valve (BAV) were analyzed based on the spatial resolution of the images. BAV is a congenital heart defect characterized by the presence of two cusps in the aortic valve, leading to various complications. PC-MRI is a noninvasive imaging technique used to assess the hemodynamics in patients. However, interpretation of PC-MRI data can be challenging due to complex hemodynamics, which makes numerical simulations necessary to complement the results. Methods:Within this study PC-MRI 4D flow data in the aortic arch (AA) were compared with hemodynamic numerical simulations based on the MRI resolution for six patient-specific AAs with BAV. First, the segmentations were reconstructed and divided into three groups based on the resolution. Second, the numerical simulations were performed and resulting hemodynamics compared to PC-MRI results at three time points in the cardiac cycle using velocity and wall shear stress. Results: Results from group 1 (highest resolution) show an overestimation of wall shear stress (WSS) values during peaksystole in the three arteries and along the AA and descending aorta (DAo). Nevertheless, velocity mean values show an overall good agreement. Group 2 shows higher velocity magnitudes in the simulation than in PC-MRI. Within group 3, velocity values differ from the measurements. Conclusion: The study shows that with a low resolution, flow patterns can already be evaluated based on PC-MRI, but to get an insight into the flow quantitatively a higher resolution is necessary.

Purpose: Image-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. Methods: As 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. Results: The 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. Conclusion: With 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.