Intracranial aneurysm wall displacement depicted by amplified Flow predicts growth.

BACKGROUND: Abnormal intracranial aneurysm (IA) wall motion has been associated with IA growth and rupture. Recently, a new image processing algorithm called amplified Flow (aFlow) has been used to successfully track IA wall motion by combining the amplification of cine and four-dimensional (4D) Flow MRI. We sought to apply aFlow to assess wall motion as a potential marker of IA growth in a paired-wise analysis of patients with growing versus stable aneurysms. METHODS: In this retrospective case-control study, 10 patients with growing IAs and a matched cohort of 10 patients with stable IAs who had baseline 4D Flow MRI were included. The aFlow was used to amplify and extract IA wall displacements from 4D Flow MRI. The associations of aFlow parameters with commonly used risk factors and morphometric features were assessed using paired-wise univariate and multivariate analyses. RESULTS: aFlow quantitative results showed significantly (P=0.035) higher wall motion displacement depicted by mean±SD 90th% values of 2.34±0.72 in growing IAs versus 1.39±0.58 in stable IAs with an area under the curve of 0.85. There was also significantly (P<0.05) higher variability of wall deformation across IA geometry in growing versus stable IAs depicted by the dispersion variables including 121-150% larger standard deviation ([Formula: see text]) and 128-161% wider interquartile range [Formula: see text]. CONCLUSIONS: aFlow-derived quantitative assessment of IA wall motion showed greater wall motion and higher variability of wall deformation in growing versus stable IAs.

Standardized viscosity as a source of error in computational fluid dynamic simulations of cerebral aneurysms.

BACKGROUND: Computational fluid dynamics (CFD) simulations are a powerful tool for studying cerebral aneurysms, capable of evaluating hemodynamics in a way that is infeasible with imaging alone. However, the difficulty of incorporating patient-specific information and inherent obstacles of in vivo validation have limited the clinical usefulness of CFD of cerebral aneurysms. In this work we investigate the effect of using standardized blood viscosity values in CFD simulations of cerebral aneurysms when compared to simulations of the same aneurysms using patient-specific viscosity values derived from hematocrit measurements. PURPOSE: The objective of this work is to determine the level of error, on average, that is, caused by using standardized values of viscosity in CFD simulations of cerebral aneurysms. By quantifying this error, we demonstrate the need for incorporating patient-specific viscosity in future CFD investigations of cerebral aneurysms. METHODS: CFD simulations of forty-one cerebral aneurysms were conducted using patient-specific boundary conditions. For each aneurysm two simulations were conducted, one utilizing patient-specific blood viscosity derived from hematocrit measurements and another using a standardized value for blood viscosity. Hemodynamic parameters such as wall shear stress (WSS), wall shear stress gradient (WSSG), and the oscillatory shear index (OSI) were calculated for each of the simulations for each aneurysm. Paired t-tests for differences in the time-averaged maps of these hemodynamic parameters between standardized and patient-specific viscosity simulations were conducted for each aneurysm. Bland-Altman analysis was used to examine the cohort-wide changes in the hemodynamic parameters. Subjects were broken into two groups, those with higher than standard viscosity and those with lower than standard viscosity. An unpaired t-test was used to compare the percent change in WSS, WSSG, and OSI between patient-specific and standardized viscosity simulations for the two cohorts. The percent changes in hemodynamic parameters were correlated against the direction and magnitude of percent change in viscosity, aneurysm size, and aneurysm location. For all t-tests, a Bonferroni-corrected significance level of 0.0167 was used. RESULTS: 63.2%, 41.5%, and 48.7% of aneurysms showed statistically significant differences between patient-specific and standardized viscosity simulations for WSS, WSSG, and OSI respectively. No statistically significant difference was found in the percent changes in WSS, WSSG, and OSI between the group with higher than standard viscosity and those with lower than standard viscosity, indicating an increase in viscosity can cause either an increase or decrease in each of the hemodynamic parameters. On a study-wide level no significant bias was found in either direction for WSS, WSSG, or OSI between the simulation groups due to the bidirectional effect of changing viscosity. No correlation was found between percent change of viscosity and percent change of WSS, WSSG, or OSI, meaning an after-the-fact correction for patient-specific viscosity is not feasible. CONCLUSION: Standardizing viscosity values in CFD of cerebral aneurysms has a large and unpredictable impact on the calculated WSS, WSSG, and OSI when compared to CFD simulations of the same aneurysms using a patient-specific viscosity. We recommend implementing hematocrit-based patient-specific blood viscosity values for all CFD simulations of cerebral aneurysms.

Improving the accuracy of computational fluid dynamics simulations of coiled cerebral aneurysms using finite element modeling.

Cerebral aneurysms are a serious clinical challenge, with ∼half resulting in death or disability. Treatment via endovascular coiling significantly reduces the chances of rupture, but the techniquehas failure rates of ∼20 %. This presents a pressing need to develop a method fordetermining optimal coildeploymentstrategies. Quantification of the hemodynamics of coiled aneurysms using computational fluid dynamics (CFD) has the potential to predict post-treatment outcomes, but representing the coil mass in CFD simulations remains a challenge. We use the Finite Element Method (FEM) for simulating patient-specific coil deployment for n = 4 ICA aneurysms for which 3D printed in vitro models were also generated, coiled, and scanned using ultra-high resolution synchrotron micro-CT. The physical and virtual coil geometries were voxelized onto a binary structured grid and porosity maps were generated for geometric comparison. The average binary accuracy score is 0.8623 and the average error in porosity map is 4.94 %. We then conduct patient-specific CFD simulations of the aneurysm hemodynamics using virtual coils geometries, micro-CT generated oil geometries, and using the porous medium method to represent the coil mass. Hemodynamic parameters including Neck Inflow Rate (Qneck) and Wall Shear Stress (WSS) were calculated for each of the CFD simulations. The average relative error in Qneck and WSS from CFD using FEM geometry were 6.6 % and 21.8 % respectively, while the error from CFD using a porous media approximation resulted in errors of 55.1 % and 36.3 % respectively; demonstrating a marked improvement in the accuracy of CFD simulations using FEM generated coil geometries.

Modeling the Mechanical Microenvironment of Coiled Cerebral Aneurysms.

Successful occlusion of cerebral aneurysms using coil embolization is contingent upon stable thrombus formation, and the quality of the thrombus depends upon the biomechanical environment. The goal of this study was to investigate how coil embolization alters the mechanical micro-environment within the aneurysm dome. Inertialess particles were injected in three-dimensional, computational simulations of flow inside patient aneurysms using patient-specific boundary conditions. Coil embolization was simulated as a homogenous porous medium of known permeability and inertial constant. Lagrangian particle tracking was used to calculate the residence time and shear stress history for particles in the flow before and after treatment. The percentage of particles entering the aneurysm dome correlated with the neck surface area before and after treatment (pretreatment: R2 = 0.831, P < 0.001; post-treatment: R2 = 0.638, P < 0.001). There was an inverse relationship between the change in particles entering the dome and coil packing density (R2 = 0.600, P < 0.001). Following treatment, the particles with the longest residence times tended to remain within the dome even longer while accumulating lower shear stress. A significant correlation was observed between the treatment effect on residence time and the ratio of the neck surface area to porosity (R2 = 0.390, P = 0.007). The results of this study suggest that coil embolization triggers clot formation within the aneurysm dome via a low shear stress-mediated pathway. This hypothesis links independently observed findings from several benchtop and clinical studies, furthering our understanding of this treatment strategy.

Patient-specific computational fluid dynamic simulation of cerebrospinal fluid flow in the intracranial space.

BACKGROUND: Abnormal cerebrospinal fluid (CSF) flow is associated with a variety of poorly understood neurological disorders such as Alzheimer's Disease and hydrocephalus. The lack of comprehensive understanding of the fluid and solid mechanics of CSF flow remains a critical barrier in the development of diagnostic assessment and potential treatment options for these diseases. We have developed a whole brain, patient-specific computational fluid dynamics (CFD) simulation of CSF flow in the cranial cavity as a step towards comprehensive understanding of CSF dynamics and how they relate to neurodegenerative diseases. METHODS: A patient-specific 3D geometry of the CSF filled spaces was segmented from structural MRI. Patient-specific boundary conditions were measured using phase contrast MRI. A rigid wall three-dimensional CFD simulation was conducted using only patient-specific waveforms as boundary conditions. Deformation of brain tissue is accounted for using volumetric flowrate boundary conditions calculated via the conservation of mass. Phase contrast MRI measurement of maximum velocity at the cerebral aqueduct was used to validate the simulation with excellent agreement. RESULTS: The CSF dynamics across the cardiac cycle are presented, illustrating the relationship between arterial flow and CSF flow. Flow in and out of the ventricles was shown to have a slight phase delay (∼20 % of the cardiac cycle) from flow in the subarachnoid space. Intracranial pressure dynamics are presented, with pressure in the Lateral Ventricles demonstrating less significant transient effects than pressure in the subarachnoid space. CONCLUSIONS: This work presents a quantitatively validated whole-brain simulation of CSF flow for a single healthy subject. The computational methodology improves over the state of the art by eliminating non-physiological boundary conditions and unnecessary assumptions about the mechanical properties of brain tissue, providing an essential step towards clinically useful tools for assessing the development of neurodegenerative disorders.