Hemodynamics In Cerebral Aneurysms Research Articles

Cerebral Aneurysm Hemodynamics in Low Hematocrit Conditions: Numerical Simulations and Analysis

Cerebral Aneurysm Hemodynamics in Low Hematocrit Conditions: Numerical Simulations and Analysis

Review of CFD Based Simulations to Study the Hemodynamics of Cerebral Aneurysms

Review of CFD Based Simulations to Study the Hemodynamics of Cerebral Aneurysms

Morphology and Hemodynamics of Cerebral Arteries and Aneurysms in a Rare Pair of Monozygotic Twins.

In this preliminary study, the underlying pathophysiology mechanisms of cerebral aneurysms (CAs) in monozygotic twins (MTs) were investigated via a rare pair of MTs (twin A and twin B) involving four reconstructed arterial models using preclinical information. First, dimensions and configurated outlines of three-perspective geometries were compared. Adopting an in-vitro validated numerical CA model, hemodynamic characteristics were investigated in the MTs, respectively. Despite expected genetic similarities, morphological comparisons show that configurations of cerebral arteries exhibit significant differences between the twins. The ICA size of twin A is larger than that in twin B (2.23~25.86%), varying with specific locations, attributing to variations during embryological developments and environmental influences. Numerical modeling indicates the MTs have some hemodynamic similarities such as pressure distributions (~13,400 Pa) and their oscillatory shear index (OSI) (0~0.49), but present significant differences in local regions. Specifically, the difference in blood flow rate in the MTs is from 16% to 221%, varying with specifically compared arteries. The maximum time-averaged wall shear stress (53.6 Pa vs. 37.8 Pa) and different local OSI distributions were also observed between the MTs. The findings revealed that morphological variations in MTs could be generated by embryological and environmental factors, further influencing hemodynamic characteristics on CA pathophysiology.

Influence of carotid tortuosity on the hemodynamics in cerebral aneurysms

Clinical observations indicate that the shape and tortuosity of the carotid siphon are some of the contributing factors to the initiation and growth of an aneurysm. The present study explores the validity of this observation by performing systematic numerical simulations. Computational fluid dynamics (CFD) based calculations are performed to compare and contrast four different types of patient-specific carotid siphons, viz., C-, S-, U-, and helical shape, to investigate the hemodynamic influences on flow features, secondary flow patterns, and helicity. Fewer curved regions and the presence of local acute curvature were found to result in higher velocity magnitude, leading to giant sidewall aneurysms in the distal end of this curvature. In contrast, a larger number of curved regions in the parent vessel resulted in disturbed flow and reduced maximum streamwise velocity. When the velocity is lower, smaller aneurysms are observed at the bifurcation carina. The influence of siphon tortuosity, which is exemplified through the Dean number and linked to secondary flows, causes higher helicity when the vessel is more tortuous. It is hypothesized that a highly tortuous vessel protects the further growth of an aneurysm. This is in contrast to a less tortuous vessel with single acute curvature and prone to further expansile behavior of an aneurysm.

Endothelial Responses to Curvature-Induced Flow Patterns in Engineered Cerebral Aneurysms.

Hemodynamic factors have long been associated with clinical outcomes in the treatment of cerebral aneurysms. Computational studies of cerebral aneurysm hemodynamics have provided valuable estimates of the mechanical environment experienced by the endothelium in both the parent vessel and aneurysmal dome walls and have correlated them with disease state. These computational-clinical studies have recently been correlated with the response of endothelial cells (EC) using either idealized or patient-specific models. Here, we present a robust workflow for generating anatomic-scale aneurysm models, establishing luminal cultures of ECs at physiological relevant flow profiles, and comparing EC responses to curvature mediated flow. We show that flow patterns induced by parent vessel curvature produce changes in wall shear stress (WSS) and wall shear stress gradients (WSSG) that are correlated with differences in cell morphology and cellular protein localization. Cells in higher WSS regions align better with the flow and display strong Notch1-extracellular domain (ECD) polarization, while, under low WSS, differences in WSSG due to curvature change were associated with less alignment and attenuation of Notch1-ECD polarization in ECs of the corresponding regions. These proof-of-concept results highlight the use of engineered cellularized aneurysm models for connecting computational fluid dynamics to the underlying endothelial biology that mediates disease.

Leveraging Patient-Specific Simulated Angiograms to Characterize Cerebral Aneurysm Hemodynamics using Computational Fluid Dynamics.

Cerebral aneurysms (CA) affect nearly 6% of the US population and its rupture is one of the major causes of hemorrhagic stroke. Neurointerventionalists performing endovascular therapy (ET) to treat CA rely on qualitative image sequences obtained under fluoroscopy guidance alone, and do not have access to crucial quantitative information regarding blood flow before, during and after treatment - partially contributing to a failure rate of up to 30%. Computational fluid dynamics (CFD) is a powerful tool that can provide a wealth of quantitative data; however, CFD has found limited utility in the clinic due to the challenges in obtaining hemodynamic boundary conditions for each patient. In this work, we present a novel CFD-based simulated angiogram approach (SAA) that resolves the blood flow physics and interaction between blood and injected contrast agent to extract quantitative hemodynamic parameters which can be used to design real-time parametric imaging analysis. The SAA enables correlating contrast agent transport to the underlying hemodynamic conditions via time-density curves (TDC) obtained at several points in the region of interest. The ability of the TDC and the SAA to provide critical hemodynamic parameters in and around CA anatomies, such as washout and local flow changes is explored and presented. This provides invaluable quantitative data to the clinician at the time of intervention, since it incorporates the physics of blood flow and correlates the contrast transport to hemodynamic parameters quantitatively - thereby enabling the clinician to take informed decisions that improve treatment outcomes.

Challenges in Modeling Hemodynamics in Cerebral Aneurysms Related to Arteriovenous Malformations.

The significantly higher incidence of aneurysms in patients with arteriovenous malformations (AVMs) suggests a strong hemodynamic relationship between these lesions. The presence of an AVM alters hemodynamics in proximal vessels by drastically changing the distal resistance, thus affecting intra-aneurysmal flow. This study discusses the challenges associated with patient-specific modeling of aneurysms in the presence of AVMs. We explore how the presence of a generic distal AVM affects upstream aneurysms by examining the relationship between distal resistance and aneurysmal wall shear stress using physiologically realistic estimates for the influence of the AVM on hemodynamics. Using image-based computational models of aneurysms and surrounding vasculature, aneurysmal wall-shear stress is calculated for a range of distal resistances corresponding to the presence of AVMs of various sizes and compared with a control case representing the absence of an AVM. In the patient cases considered, the alteration in aneurysmal wall shear stress due to the presence of an AVM is considerable, as much as 19 times the base case wall shear stress. Furthermore, the relationship between aneurysmal wall shear stress and distal resistance is shown to be highly geometry-dependent and nonlinear. In most cases, the range of physiologically realistic possibilities for AVM-related distal resistance are so large that patient-specific flow measurements are necessary for meaningful predictions of wall shear stress. The presented work offers insight on the impact of distal AVMs on aneurysmal wall shear stress using physiologically realistic computational models. Patient-specific modeling of hemodynamics in aneurysms and associated AVMs has great potential for understanding lesion pathogenesis, surgical planning, and assessing the effect of treatment of one lesion relative to another. However, we show that modeling approaches cannot usually meaningfully quantify the impact of AVMs if based solely on imaging data from CT and X-ray angiography, currently used in clinical practice. Based on recent studies, it appears that 4D flow MRI is one promising approach to obtaining meaningful patient-specific flow boundary conditions that improve modeling fidelity.

Abstract 1122‐000014: Effects of Patient‐Specific Blood Properties and Inflow Conditions on Hemodynamics in Cerebral Aneurysms

This meeting abstract was removed due to the OA licensing requirements of this journal. The full abstract is listed here : https://www.svin.org/files/SVIN_2021_Abstracts_for_Web.pdf

Prediction of Cerebral Aneurysm Hemodynamics With Porous-Medium Models of Flow-Diverting Stents via Deep Learning

The interventional treatment of cerebral aneurysm requires hemodynamics to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in calculating cerebral aneurysm hemodynamics before and after flow-diverting (FD) stent placement. However, the complex operation (such as the construction and placement simulation of fully resolved or porous-medium FD stent) and high computational cost of CFD hinder its application. To solve these problems, we applied aneurysm hemodynamics point cloud data sets and a deep learning network with double input and sampling channels. The flexible point cloud format can represent the geometry and flow distribution of different aneurysms before and after FD stent (represented by porous medium layer) placement with high resolution. The proposed network can directly analyze the relationship between aneurysm geometry and internal hemodynamics, to further realize the flow field prediction and avoid the complex operation of CFD. Statistical analysis shows that the prediction results of hemodynamics by our deep learning method are consistent with the CFD method (error function <13%), but the calculation time is significantly reduced 1,800 times. This study develops a novel deep learning method that can accurately predict the hemodynamics of different cerebral aneurysms before and after FD stent placement with low computational cost and simple operation processes.

Inflow Hemodynamics of Intracranial Aneurysms: A Comparison of Computational Fluid Dynamics and 4D Flow Magnetic Resonance Imaging

PurposeAlthough the inflow hemodynamics of cerebral aneurysms are key factors in their rupture and recurrence after endovascular treatments, the most available method for inflow hemodynamics evaluation remains unestablished. We compared the efficacy of inflow hemodynamics evaluation using computational fluid dynamics (CFD) analysis and that using four-dimensional (4D) flow magnetic resonance imaging (MRI). MethodsIn 23 unruptured cerebral aneurysms, the inflow hemodynamics was evaluated using both CFD and 4D flow MRI. The evaluated parameters included visually classified inflow jet patterns, the inflow rate ratio (the ratio of the inflow rate at the aneurysmal orifice to the flow rate in the proximal parent artery), and the velocity ratio (the ratio of the inflow velocity to the velocity in the proximal parent artery). The Shapiro-Wilk test was used to assess the normality of variable data, and logarithmic transformation was performed for variables with non-normal distributions. Data analysis was performed using Pearson correlation analyses and the chi-square test. ResultsThere was a significant correlation between inflow jet patterns evaluated by CFD and 4D flow MRI (p = 0.008). Moreover, there was a strong correlation between the inflow rate ratios evaluated by CFD and 4D flow MRI (r = 0.801; p <0.001). Furthermore, there was a moderate correlation between the velocity ratios measured by CFD and 4D flow MRI (r = 0.559; p = 0.008). ConclusionInflow hemodynamics evaluated by CFD analysis and 4D flow MRI showed good correlations in inflow jet pattern, inflow rate ratio, and velocity ratio.

Numerical Simulation of Flow Behavior in Basilar Bifurcation Aneurysms Based on 4-Dimensional Computed Tomography Angiography

Initiation, growth, and rupture of cerebral aneurysms are caused by hemodynamic factors. It is extensively accepted that the cerebral aneurysm wall is assumed to be rigid using computational fluid dynamics (CFD). Furthermore, fluid-structure interactions have been recently applied for simulation of an elastic cerebral aneurysm model. Herein, we examined cerebral aneurysm hemodynamics in a realistic moving boundary deformation model based on 4-dimensional computed tomographic angiography (4D-CTA) obtained by high time-resolution using numerical simulation. The aneurysm of the realistic moving deformation model based on 4D-CTA at each phase was constructed. The effect of small wall deformation on hemodynamic characteristics might be interested. So, four hemodynamic factors (wall shear stress, wall shear stress divergence, oscillatory shear index and residual residence time) were determined from the numerical simulation, and their behaviors were assessed in the basilar bifurcation aneurysm.

An Automated Workflow for Hemodynamic Computations in Cerebral Aneurysms.

In recent years, computational fluid dynamics (CFD) has become a valuable tool for investigating hemodynamics in cerebral aneurysms. CFD provides flow-related quantities, which have been shown to have a potential impact on aneurysm growth and risk of rupture. However, the adoption of CFD tools in clinical settings is currently limited by the high computational cost and the engineering expertise required for employing these tools, e.g., for mesh generation, appropriate choice of spatial and temporal resolution, and of boundary conditions. Herein, we address these challenges by introducing a practical and robust methodology, focusing on computational performance and minimizing user interaction through automated parameter selection. We propose a fully automated pipeline that covers the steps from a patient-specific anatomical model to results, based on a fast, graphics processing unit- (GPU-) accelerated CFD solver and a parameter selection methodology. We use a reduced order model to compute the initial estimates of the spatial and temporal resolutions and an iterative approach that further adjusts the resolution during the simulation without user interaction. The pipeline and the solver are validated based on previously published results, and by comparing the results obtained for 20 cerebral aneurysm cases with those generated by a state-of-the-art commercial solver (Ansys CFX, Canonsburg PA). The automatically selected spatial and temporal resolutions lead to results which closely agree with the state-of-the-art, with an average relative difference of only 2%. Due to the GPU-based parallelization, simulations are computationally efficient, with a median computation time of 40 minutes per simulation.

Hemodynamics of Cerebral Aneurysms: Connecting Medical Imaging and Biomechanical Analysis

In the last two decades, numerous studies have conducted patient-specific computations of blood flow dynamics in cerebral aneurysms and reported correlations between various hemodynamic metrics and aneurysmal disease progression or treatment outcomes. Nevertheless, intra-aneurysmal flow analysis has not been adopted in current clinical practice, and hemodynamic factors usually are not considered in clinical decision making. This review presents the state of the art in cerebral aneurysm imaging and image-based modeling, discussing the advantages and limitations of each approach and focusing on the translational value of hemodynamic analysis. Combining imaging and modeling data obtained from different flow modalities can improve the accuracy and fidelity of resulting velocity fields and flow-derived factors that are thought to affect aneurysmal disease progression. It is expected that predictive models utilizing hemodynamic factors in combination with patient medical history and morphological data will outperform current risk scores and treatment guidelines. Possible future directions include novel approaches enabling data assimilation and multimodality analysis of cerebral aneurysm hemodynamics.

Platelet Dynamics and Hemodynamics of Cerebral Aneurysms Treated with Flow-Diverting Stents.

Flow-diverting stents (FDS) are used to treat cerebral aneurysms. They promote the formation of a stable thrombus within the aneurysmal sac and, if successful, isolate the aneurysmal dome from mechanical stresses to prevent rupture. Platelet activation, a mechanism necessary for thrombus formation, is known to respond to biomechanical stimuli, particularly to the platelets' residence time and shear stress exposure. Currently, there is no reliable method for predicting FDS treatment outcomes, either a priori or after the procedure. Eulerian computational fluid dynamic (CFD) studies of aneurysmal flow have searched for predictors of endovascular treatment outcome; however, the hemodynamics of thrombus formation cannot be fully understood without considering the platelets' trajectories and their mechanics-triggered activation. Lagrangian analysis of the fluid mechanics in the aneurysmal vasculature provides novel metrics by tracking the platelets' residence time (RT) and shear history (SH). Eulerian and Lagrangian parameters are compared for 19 patient-specific cases, both pre- and post-treatment, to assess the degree of change caused by the FDS and subsequent treatment efficacy.

Fully Printed, Wireless, Stretchable Implantable Biosystem toward Batteryless, Real-Time Monitoring of Cerebral Aneurysm Hemodynamics.

This study introduces a high‐throughput, large‐scale manufacturing method that uses aerosol jet 3D printing for a fully printed stretchable, wireless electronics. A comprehensive study of nanoink preparation and parameter optimization enables a low‐profile, multilayer printing of a high‐performance, capacitance flow sensor. The core printing process involves direct, microstructured patterning of biocompatible silver nanoparticles and polyimide. The optimized fabrication approach allows for transfer of highly conductive, patterned silver nanoparticle films to a soft elastomeric substrate. Stretchable mechanics modeling and seamless integration with an implantable stent display a highly stretchable and flexible sensor, deployable by a catheter for extremely low‐profile, conformal insertion in a blood vessel. Optimization of a transient, wireless inductive coupling method allows for wireless detection of biomimetic cerebral aneurysm hemodynamics with the maximum readout distance of 6 cm through meat. In vitro demonstrations include wireless monitoring of flow rates (0.05–1 m s−1) in highly contoured and narrow human neurovascular models. Collectively, this work shows the potential of the printed biosystem to offer a high throughput, additive manufacturing of stretchable electronics with advances toward batteryless, real‐time wireless monitoring of cerebral aneurysm hemodynamics.

On the Impact of Flow-Diverters on the Hemodynamics of Human Cerebral Aneurysms

The impact of flow-diverters used for cerebral aneurysm treatment on human brain hemodynamics was evaluated qualitatively and quantitatively. Numerical simulation of flow-diverter placement in cerebral vessels with aneurysms was carried out for the case history of a real patient using the commercial ANSYS 17.2 package with different (Newtonian and non-Newtonian) hydrodynamic models for blood rheology in different parts of the vessel and aneurysm, which is due to experimental data. It is shown that after flow-diverter placement, the blood flow through the artery segment containing the aneurysm neck decreases, resulting in a redistribution of the cerebral blood flow, which becomes close to the blood flow in healthy subjects. Changes in wall shear stresses in the flow-diverter region are indicative of possible aneurysm recanalization.

Quantitative assessment of 4D hemodynamics in cerebral aneurysms using proper orthogonal decomposition

Background and purposeThe comparison of different time-varying three-dimensional hemodynamic data (4D) is a formidable task. The purpose of this study is to investigate the potential of the proper orthogonal decomposition (POD) for a quantitative assessment. MethodsThe complex spatial-temporal flow information was analyzed using proper orthogonal decomposition to reduce the complexity of the system. PC-MRI blood flow measurements and computational fluid dynamic simulations of two subject-specific IAs were used to compare the different flow modalities. The concept of Modal Assurance Criterion (MAC) provided a further detailed objective characterization of the most energetic individual modes. ResultsThe most energetic flow modes were qualitatively compared by visual inspection. The distribution of the kinetic energy on the modes was used to quantitatively compare pulsatile flow data, where the most energetic mode was associated to approximately 90% of the total kinetic energy. This distribution was incorporated in a single measure, termed spectral entropy, showing good agreement especially for Case 1. ConclusionThe proposed quantitative POD-based technique could be a valuable tool to reduce the complexity of the time-dependent hemodynamic data and to facilitate an easy comparison of 4D flows, e.g., for validation purposes.

Augmented Reality with Virtual Cerebral Aneurysms: A Feasibility Study

Advanced magnetic resonance imaging (MRI) acquisition methods such as 4D phase contrast magnetic resonance imaging (4D pcMRI) have found widespread applications in assessing hemodynamics in cerebral aneurysms. One of the goals is the identification of a hemodynamic scenario predictive of aneurysm rupture. Because of the technical complexity the 4D pcMRI technology, challenges exist in extracting and communicating the wealth of information contained in the MRI image data, in particular, to a multidisciplinary team of health professionals and basic scientists. Here we introduce a new resource in the form of a commercially available optical see-through head-mounted display, which allows augmenting the real world by computer-generated virtual objects. An image processing algorithm was presented for integrating 3D surface models derived from 3D rotational angiography data, 3D time-of-flight MRI data, and 4D pcMRI data into the augmented reality environment. This new approach was successfully evaluated on blood flow data acquired before and after flow diverter treatment in 6 patients harboring a cerebral aneurysm. Augmented reality may become an additional means for visualizing complex medical data, in particular complex flows as illustrated here.

Hemodynamic Assessment of Cerebral Aneurysms Using Computational Fluid Dynamics (CFD) Involving the Establishment of Non-Newtonian Fluid Properties

Objective: The hemodynamics of cerebral aneurysms was evaluated by computational fluid dynamics (CFD) analysis using the non-Newtonian (Casson’s) fluid model and the Newtonian fluid model obtained from measurements. The two fluid models were examined to clarify the influence of blood viscosity on hemodynamic parameters.

On the Impact of Flow-Diverters on the Hemodynamics of Human Cerebral Aneurysms

On the Impact of Flow-Diverters on the Hemodynamics of Human Cerebral Aneurysms