Accuracy of computational cerebral aneurysm hemodynamics using patient-specific endovascular measurements

Endothelial Cell Transcription Modulation in Cerebral Aneurysms After Endovascular Flow Diversion

PURPOSE

Flow diverting stents (FDS) are used to treat cerebral aneurysms, by promoting thrombosis and occlusion of the aneurysm sac. However, retreatment is required in some cases, and the biologic basis behind treatment outcome is not known. The goal of this study was to understand how changes in hemodynamic flow after FDS placement affect aneurysmal endothelial cell (EC) activity.

METHODS

Three-dimensional models of patient-specific aneurysms were created to quantify the EC response to FDS placement. Computational fluid dynamic simulations were used to determine the hemodynamic impact of FDS. Two identical models were created for each patient; into one a FDS was inserted. Each model was then populated with human carotid ECs and subjected to patient-specific pulsatile flow for 24 h. ECs were isolated from aneurysm dome from each model and bulk RNA sequencing was performed.

RESULTS

Paired untreated and treated models were created for four patients. Aneurysm dome EC analysis revealed 366 (2.6%) significant gene changes between the untreated and FDS conditions, out of 13909 total expressed genes. Gene set enrichment analysis of the untreated models demonstrated enriched gene ontology terms related to cell adhesion, growth/tensile activity, cytoskeletal organization, and calcium ion binding. In the FDS models, enriched terms were related to cellular proliferation, ribosomal activity, RNA splicing, and protein folding.

CONCLUSION

Treatment of cerebral aneurysms with FDS induces significant EC gene transcription changes related to aneurysm hemodynamics in patient-specific in vitro 3D-printed models subjected to pulsatile flow. Further investigation is needed into the relationship between transcriptional change and treatment outcome.

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.

A Novel Patient-Specific Computational Fluid Dynamics Study of the Activation of Primary Collateral Pathways in the Circle of Willis During Vasospasm

The Circle of Willis (CoW) is a redundant network of blood vessels that perfuses the brain. The ringlike anatomy mitigates the negative effects of stroke by activating collateral pathways that help maintain physiological perfusion. Previous studies have investigated the activation of these pathways during embolic stroke and internal carotid artery occlusion. However, the role of collateral pathways during cerebral vasospasm-an involuntary constriction of blood vessels after subarachnoid hemorrhage-is not well-documented. This study presents a novel technique to create patient-specific computational fluid dynamics (CFD) simulations of the Circle of Willis before and during vasospasm. Computed tomographic angiography (CTA) scans are segmented to model the vasculature, and transcranial Doppler ultrasound (TCD) measurements of blood flow velocity are applied as boundary conditions. Bayesian analysis leverages information about the uncertainty in the measurements of vessel diameters and velocities to find an optimized parameter set that satisfies mass conservation and that is applied in the final simulation. With this optimized parameter set, the diameters, velocities, and flow rates fall within typical literature values. Virtual angiograms modeled using passive scalar transport agree closely with clinical angiography. A sensitivity analysis quantifies the changes in collateral flow rates with respect to changes in the inlet and outlet flow rates. This analysis can be applied in the future to a cohort of patients to investigate the relationship between the locations and severities of vasospasm, the patient-to-patient anatomical variability in the Circle of Willis, and the activation of collateral pathways.

Modeling Flow in Cerebral Aneurysm After Coils Embolization Treatment: A Realistic Patient-Specific Porous Model Approach

PURPOSE

Computational fluid dynamics (CFD) has been used to evaluate the efficiency of endovascular treatment in coiled cerebral aneurysms. The explicit geometry of the coil mass cannot typically be incorporated into CFD simulations since the coil mass cannot be reconstructed from clinical images due to its small size and beam hardening artifacts. The existing methods use imprecise porous medium representations. We propose a new porous model taking into account the porosity heterogeneity of the coils deployed in the aneurysm.

METHODS

The porosity heterogeneity of the coil mass deployed inside two patients' cerebral aneurysm phantoms is first quantified based on 3D X-ray synchrotron images. These images are also used to compute the permeability and the inertial factor arising in porous models. A new homogeneous porous model (porous crowns model), considering the coil's heterogeneity, is proposed to recreate the flow within the coiled aneurysm. Finally, the validity of the model is assessed through comparisons with coil-resolved simulations.

RESULTS

The strong porosity gradient of the coil measured close to the aneurysmal wall is well captured by the porous crowns model. The permeability and the inertial factor values involved in this model are closed to the ideal homogeneous porous model leading to a mean velocity in the aneurysmal sac similar as in the coil-resolved model.

CONCLUSION

The porous crowns model allows for an accurate description of the mean flow within the coiled cerebral 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.

Lagrangian Trajectory Simulation of Platelets and Synchrotron Microtomography Augment Hemodynamic Analysis of Intracranial Aneurysms Treated With Embolic Coils

As frequency of endovascular treatments for intracranial aneurysms increases, there is a growing need to understand the mechanisms for coil embolization failure. Computational fluid dynamics (CFD) modeling often simplifies modeling the endovascular coils as a homogeneous porous medium (PM), and focuses on the vascular wall endothelium, not considering the biomechanical environment of platelets. These assumptions limit the accuracy of computations for treatment predictions. We present a rigorous analysis using X-ray microtomographic imaging of the coils and a combination of Lagrangian (platelet) and Eulerian (endothelium) metrics. Four patient-specific, anatomically accurate in vitro flow phantoms of aneurysms are treated with the same patient-specific endovascular coils. Synchrotron tomography scans of the coil mass morphology are obtained. Aneurysmal hemodynamics are computationally simulated before and after coiling, using patient-specific velocity/pressure measurements. For each patient, we analyze the trajectories of thousands of platelets during several cardiac cycles, and calculate residence times (RTs) and shear exposure, relevant to thrombus formation. We quantify the inconsistencies of the PM approach, comparing them with coil-resolved (CR) simulations, showing the under- or overestimation of key hemodynamic metrics used to predict treatment outcomes. We fully characterize aneurysmal hemodynamics with converged statistics of platelet RT and shear stress history (SH), to augment the traditional wall shear stress (WSS) on the vascular endothelium. Incorporating microtomographic scans of coil morphology into hemodynamic analysis of coiled intracranial aneurysms, and augmenting traditional analysis with Lagrangian platelet metrics improves CFD predictions, and raises the potential for understanding and clinical translation of computational hemodynamics for intracranial aneurysm treatment outcomes.

How patient-specific do internal carotid artery inflow rates need to be for computational fluid dynamics of cerebral aneurysms?

BACKGROUND

Computational fluid dynamics (CFD) has become a popular tool for studying 'patient-specific' blood flow dynamics in cerebral aneurysms; however, rarely are the inflow boundary conditions patient-specific. We aimed to test the impact of widespread reliance on generalized inflow rates.

METHODS

Internal carotid artery (ICA) flow rates were measured via 2D cine phase-contrast MRI for 24 patients scheduled for endovascular therapy of an ICA aneurysm. CFD models were constructed from 3D rotational angiography, and pulsatile inflow rates imposed as measured by MRI or estimated using an average older-adult ICA flow waveform shape scaled by a cycle-average flow rate (Q_avg) derived from the patient's ICA cross-sectional area via an assumed inlet velocity.

RESULTS

There was good overall qualitative agreement in the magnitudes and spatial distributions of time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and spectral power index (SPI) using generalized versus patient-specific inflows. Sac-averaged quantities showed moderate to good correlations: R²=0.54 (TAWSS), 0.80 (OSI), and 0.68 (SPI). Using patient-specific Q_avg to scale the generalized waveform shape resulted in near-perfect agreement for TAWSS, and reduced bias, but not scatter, for SPI. Patient-specific waveform had an impact only on OSI correlations, which improved to R²=0.93.

CONCLUSIONS

Aneurysm CFD demonstrates the ability to stratify cases by nominal hemodynamic 'risk' factors when employing an age- and vascular-territory-specific recipe for generalized inflow rates. Q_avg has a greater influence than waveform shape, suggesting some improvement could be achieved by including measurement of patient-specific Q_avg into aneurysm imaging protocols.

Review of Biomedical Applications of Contactless Imaging of Neonates Using Infrared Thermography and Beyond

The sick preterm infant monitoring is an intriguing job that medical staff in Neonatal Intensive Care Units (NICU) must deal with on a daily basis. As a standards monitoring procedure, preterm infants are monitored via sensors and electrodes that are firmly attached to their fragile and delicate skin and connected to processing monitors. However, an alternative exists in contactless imaging to record such physiological signals (we call it as Physio-Markers), detecting superficial changes and internal structures activities which can be used independently of, or aligned with, conventional monitors. Countless advantages can be gained from unobtrusive monitoring not limited to: (1) quick data generation; (2) decreasing physical and direct contact with skin, which reduces skin breakdown and minimizes risk of infection; and (3) reduction of electrodes and probes connected to clinical monitors and attached to the skin, which allows greater body surface-area for better care. This review is an attempt to build a solid ground for and to provide a clear perspective of the potential clinical applications of technologies inside NICUs that use contactless imaging modalities such as Visible Light Imaging (VLI), Near Infrared Spectroscopy (NIRS), and Infrared Thermography (IRT).

Quantifying Hemodynamic Changes in Moyamoya Disease Based on Two-Dimensional Cine Phase-Contrast Magnetic Resonance Imaging and Computational Fluid Dynamics

OBJECTIVE

To investigate hemodynamic changes in moyamoya disease (MMD) via two-dimensional cine phase-contrast magnetic resonance imaging and computational fluid dynamics.

METHODS

In 18 patients with MMD and 10 healthy control subjects, phase-contrast magnetic resonance imaging was performed to quantify flow rate of main supplying arteries, including internal carotid arteries (ICAs) and vertebral arteries. Mean flow rate in these vessels was adopted as the patient-specific boundary condition for computational fluid dynamics simulation of the circle of Willis in MMD and control groups. Pressure drop in both ICAs and their difference, wall shear stress and secondary flow in the carotid siphon of ICAs, and flow rate and size of posterior communicating arteries (PComAs) were compared between MMD and control groups. Four patients with MMD underwent follow-up scans for longitudinal comparison.

RESULTS

Phase-contrast magnetic resonance imaging data revealed significantly different flow rate in the left ICA and right vertebral arteries between MMD and control groups. Computational fluid dynamics simulation demonstrated similar wall shear stress and similar secondary flow of both ICAs but significantly higher pressure drop in left ICA, higher pressure drop difference between left ICA and right ICA, and higher flow rate in PComAs in patients with MMD compared with control subjects. Significantly increased size of left PComA in patients with MMD was also found. Follow-up results confirmed that the combination of pressure drop difference, flow rate, and size of PComAs can potentially assist long-term prognosis after surgery.

CONCLUSIONS

Pressure drop difference, flow rate, and size of PComAs can be used to evaluate impairments in cerebrovascular reserve and indicate long-term prognosis in MMD.

A Highly Automated Computational Method for Modeling of Intracranial Aneurysm Hemodynamics

Intracranial aneurysms manifest in a vast variety of morphologies and their growth and rupture risk are subject to patient-specific conditions that are coupled with complex, non-linear effects of hemodynamics. Thus, studies that attempt to understand and correlate rupture risk to aneurysm morphology have to incorporate hemodynamics, and at the same time, address a large enough sample size so as to produce reliable statistical correlations. In order to perform accurate hemodynamic simulations for a large number of aneurysm cases, automated methods to convert medical imaging data to simulation-ready configuration with minimal (or no) human intervention are required. In the present study, we develop a highly-automated method based on the immersed boundary method framework to construct computational models from medical imaging data which is the key idea is the direct use of voxelized contrast information from the 3D angiograms to construct a level-set based computational “mask” for the hemodynamic simulation. Appropriate boundary conditions are provided to the mask and the dynamics of blood flow inside the vessels and aneurysm is simulated by solving the Navier-Stokes equations on the Cartesian grid using the sharp-interface immersed boundary method. The present method does not require body conformal surface/volume mesh generation or other intervention for model clean-up. The viability of the proposed method is demonstrated for a number of distinct aneurysms derived from actual, patient-specific data.

Efficient simulation of a low-profile visualized intraluminal support device: a novel fast virtual stenting technique

Background

The low-profile visualized intraluminal support (LVIS) stent has become a promising endovascular option for treating intracranial aneurysms. To achieve better treatment of aneurysms using LVIS, we developed a fast virtual stenting technique for use with LVIS (F-LVIS) to evaluate hemodynamic changes in the aneurysm and validate its reliability.

Methods

A patient-specific aneurysm was selected for making comparisons between the real LVIS (R-LVIS) and the F-LVIS. To perform R-LVIS stenting, a hollow phantom based on a patient-specific aneurysm was fabricated using a three-dimensional printer. An R-LVIS was released in the phantom according to standard procedure. F-LVIS was then applied successfully in this aneurysm model. The computational fluid dynamics (CFD) values were calculated for both the F-LVIS and R-LVIS models. Qualitative and quantitative comparisons of the two models focused on hemodynamic parameters.

Results

The hemodynamic characteristics for R-LVIS and F-LVIS were well matched. Representative contours of velocities and wall shear stress (WSS) were consistently similar in both distribution and magnitude. The velocity vectors also showed high similarity, although the R-LVIS model showed faster and more fluid streams entering the aneurysm. Variation tendencies of the velocity in the aneurysm and the WSS on the aneurysm wall were also similar in the two models, with no statistically significant differences in either velocity or WSS.

Conclusions

The results of the computational hemodynamics indicate that F-LVIS is suitable for evaluating hemodynamic factors. This novel F-LVIS is considered efficient, practical, and effective.

Phase-contrast MRI versus numerical simulation to quantify hemodynamical changes in cerebral aneurysms after flow diverter treatment

Cerebral aneurysms are a major risk factor for intracranial bleeding with devastating consequences for the patient. One recently established treatment is the implantation of flow-diverters (FD). Methods to predict their treatment success before or directly after implantation are not well investigated yet. The aim of this work was to quantitatively study hemodynamic parameters in patient-specific models of treated cerebral aneurysms and its correlation with the clinical outcome. Hemodynamics were evaluated using both computational fluid dynamics (CFD) and phase contrast (PC) MRI. CFD simulations and in vitro MRI measurements were done under similar flow conditions and results of both methods were comparatively analyzed. For preoperative and postoperative distribution of hemodynamic parameters, CFD simulations and PC-MRI velocity measurements showed similar results. In both cases where no occlusion of the aneurysm was observed after six months, a flow reduction of about 30-50% was found, while in the clinically successful case with complete occlusion of the aneurysm after 6 months, the flow reduction was about 80%. No vortex was observed in any of the three models after treatment. The results are in agreement with recent studies suggesting that CFD simulations can predict post-treatment aneurysm flow alteration already before implantation of a FD and PC-MRI could validate the predicted hemodynamic changes right after implantation of a FD.

Virtual endovascular treatment of intracranial aneurysms: models and uncertainty

Virtual endovascular treatment models (VETMs) have been developed with the view to aid interventional neuroradiologists and neurosurgeons to pre-operatively analyze the comparative efficacy and safety of endovascular treatments for intracranial aneurysms. Based on the current state of VETMs in aneurysm rupture risk stratification and in patient-specific prediction of treatment outcomes, we argue there is a need to go beyond personalized biomechanical flow modeling assuming deterministic parameters and error-free measurements. The mechanobiological effects associated with blood clot formation are important factors in therapeutic decision making and models of post-treatment intra-aneurysmal biology and biochemistry should be linked to the purely hemodynamic models to improve the predictive power of current VETMs. The influence of model and parameter uncertainties associated to each component of a VETM is, where feasible, quantified via a random-effects meta-analysis of the literature. This allows estimating the pooled effect size of these uncertainties on aneurysmal wall shear stress. From such meta-analyses, two main sources of uncertainty emerge where research efforts have so far been limited: (1) vascular wall distensibility, and (2) intra/intersubject systemic flow variations. In the future, we suggest that current deterministic computational simulations need to be extended with strategies for uncertainty mitigation, uncertainty exploration, and sensitivity reduction techniques. WIREs Syst Biol Med 2017, 9:e1385. doi: 10.1002/wsbm.1385 For further resources related to this article, please visit the WIREs website.

Uncertainty quantification of wall shear stress in intracranial aneurysms using a data-driven statistical model of systemic blood flow variability

Adverse wall shear stress (WSS) patterns are known to play a key role in the localisation, formation, and progression of intracranial aneurysms (IAs). Complex region-specific and time-varying aneurysmal WSS patterns depend both on vascular morphology as well as on variable systemic flow conditions. Computational fluid dynamics (CFD) has been proposed for characterising WSS patterns in IAs; however, CFD simulations often rely on deterministic boundary conditions that are not representative of the actual variations in blood flow. We develop a data-driven statistical model of internal carotid artery (ICA) flow, which is used to generate a virtual population of waveforms used as inlet boundary conditions in CFD simulations. This allows the statistics of the resulting aneurysmal WSS distributions to be computed. It is observed that ICA waveform variations have limited influence on the time-averaged WSS (TAWSS) on the IA surface. In contrast, in regions where the flow is locally highly multidirectional, WSS directionality and harmonic content are strongly affected by the ICA flow waveform. As a consequence, we argue that the effect of blood flow variability should be explicitly considered in CFD-based IA rupture assessment to prevent confounding the conclusions.

Computational fluid dynamics of cerebral aneurysm coiling using high-resolution and high-energy synchrotron X-ray microtomography: comparison with the homogeneous porous medium approach

BACKGROUND

Computational modeling of intracranial aneurysms provides insights into the influence of hemodynamics on aneurysm growth, rupture, and treatment outcome. Standard modeling of coiled aneurysms simplifies the complex geometry of the coil mass into a homogeneous porous medium that fills the aneurysmal sac. We compare hemodynamics of coiled aneurysms modeled from high-resolution imaging with those from the same aneurysms modeled following the standard technique, in an effort to characterize sources of error from the simplified model.

MATERIALS

Physical models of two unruptured aneurysms were created using three-dimensional printing. The models were treated with coil embolization using the same coils as those used in actual patient treatment and then scanned by synchrotron X-ray microtomography to obtain high-resolution imaging of the coil mass. Computational modeling of each aneurysm was performed using patient-specific boundary conditions. The coils were modeled using the simplified porous medium or by incorporating the X-ray imaged coil surface, and the differences in hemodynamic variables were assessed.

RESULTS

X-ray microtomographic imaging of coils and incorporation into computational models were successful for both aneurysms. Porous medium calculations of coiled aneurysm hemodynamics overestimated intra-aneurysmal flow, underestimated oscillatory shear index and viscous dissipation, and over- or underpredicted wall shear stress (WSS) and WSS gradient compared with X-ray-based coiled computational fluid dynamics models.

CONCLUSIONS

Computational modeling of coiled intracranial aneurysms using the porous medium approach may inaccurately estimate key hemodynamic variables compared with models incorporating high-resolution synchrotron X-ray microtomographic imaging of complex aneurysm coil geometry.

Predictive modeling and in vivo assessment of cerebral blood flow in the management of complex cerebral aneurysms

Cerebral aneurysms are weakened blood vessel dilatations that can result in spontaneous, devastating hemorrhage events. Aneurysm treatment aims to reduce hemorrhage events, and strategies for complex aneurysms often require surgical bypass or endovascular stenting for blood flow diversion. Interventions that divert blood flow from their normal circulation patterns have the potential to result in unintentional ischemia. Recent developments in computational modeling and in vivo assessment of hemodynamics for cerebral aneurysm treatment have entered into clinical practice. Herein, we review how these techniques are currently utilized to improve risk stratification and treatment planning.

Computational Modeling of Venous Sinus Stenosis in Idiopathic Intracranial Hypertension

BACKGROUND AND PURPOSE

Idiopathic intracranial hypertension has been associated with dural venous sinus stenosis in some patients, but the hemodynamic environment of the dural venous sinuses has not been quantitatively described. Here, we present the first such computational fluid dynamics model by using patient-specific blood pressure measurements.

MATERIALS AND METHODS

Six patients with idiopathic intracranial hypertension and at least 1 stenosis or atresia at the transverse/sigmoid sinus junction underwent MR venography followed by cerebral venography and manometry throughout the dural venous sinuses. Patient-specific computational fluid dynamics models were created by using MR venography anatomy, with venous pressure measurements as boundary conditions. Blood flow and wall shear stress were calculated for each patient.

RESULTS

Computational models of the dural venous sinuses were successfully reconstructed in all 6 patients with patient-specific boundary conditions. Three patients demonstrated a pathologic pressure gradient (≥8 mm Hg) across 4 dural venous sinus stenoses. Small sample size precludes statistical comparisons, but average overall flow throughout the dural venous sinuses of patients with pathologic pressure gradients was higher than in those without them (1041.00 ± 506.52 mL/min versus 358.00 ± 190.95 mL/min). Wall shear stress was also higher across stenoses in patients with pathologic pressure gradients (37.66 ± 48.39 Pa versus 7.02 ± 13.60 Pa).

CONCLUSIONS

The hemodynamic environment of the dural venous sinuses can be computationally modeled by using patient-specific anatomy and physiologic measurements in patients with idiopathic intracranial hypertension. There was substantially higher blood flow and wall shear stress in patients with pathologic pressure gradients.

Development of a Numerical Method for Patient-Specific Cerebral Circulation Using 1D-0D Simulation of the Entire Cardiovascular System with SPECT Data

The detailed flow information in the circle of Willis (CoW) can facilitate a better understanding of disease progression, and provide useful references for disease treatment. We have been developing a one-dimensional-zero-dimensional (1D-0D) simulation method for the entire cardiovascular system to obtain hemodynamics information in the CoW. This paper presents a new method for applying 1D-0D simulation to an individual patient using patient-specific data. The key issue is how to adjust the deviation of physiological parameters, such as peripheral resistance, from literature data when patient-specific geometry is used. In order to overcome this problem, we utilized flow information from single photon emission computed tomography (SPECT) data. A numerical method was developed to optimize physiological parameters by adjusting peripheral cerebral resistance to minimize the difference between the resulting flow rate and the SPECT data in the efferent arteries of the CoW. The method was applied to three cases using different sets of patient-specific data in order to investigate the hemodynamics of the CoW. The resulting flow rates in the afferent arteries were compared to those of the phase-contrast magnetic resonance angiography (PC-MRA) data. Utilization of the SPECT data combined with the PC-MRA data showed a good agreement in flow rates in the afferent arteries of the CoW with those of PC-MRA data for all three cases. The results also demonstrated that application of SPECT data alone could provide the information on the ratios of flow distributions among arteries in the CoW.

In vitro validation of endovascular Doppler-derived flow rates in models of the cerebral circulation

This study presents validation of endovascular Doppler velocimetry-based volumetric flow rate measurements conducted in a pulsatile flow loop simulating conditions in both the internal carotid and basilar artery. In vitro models of cerebral vessels, each containing an aneurysm, were fabricated from patient anatomies extracted from 3D rotational angiography. Flow velocity measurements were collected with three different experimental techniques: an endovascular Doppler wire, Particle Image Velocimetry, and a time-resolved ultrasonic flow meter. Womersley's theory of pulsatile flow in a cylindrical vessel was used to compute time-resolved volumetric flow rates from the endovascular Doppler velocity. The volumetric flow rates computed from the Doppler measurements were compared to those from the Particle Image Velocimetry profile measurements, and the direct measurements from the ultrasonic flow meter. The study establishes confidence intervals for any systematic or random errors associated with the wire-derived flow rates as benchmarked to the other two modalities. There is an approximately 10% random error in the Doppler-derived peak and time-averaged flow rates. There is a measurable uniform bias, about 15% too low, in the time-averaged Doppler-derived flow rates. There is also a small proportional bias in the peak systolic Doppler-derived flow rates. Potential sources of error are also discussed.

Hemodynamics in growing and stable cerebral aneurysms

Objective

The detailed mechanisms of cerebral aneurysm evolution are poorly understood but are important for objective aneurysm evaluation and improved patient management. The purpose of this study was to identify hemodynamic conditions that may predispose aneurysms to growth.

Methods

A total of 33 intracranial unruptured aneurysms longitudinally followed with three-dimensional imaging were studied. Patient-specific computational fluid dynamics models were constructed and used to quantitatively characterize the hemodynamic environments of these aneurysms. Hemodynamic characteristics of growing (n=16) and stable (n=17) aneurysms were compared. Logistic regression statistical models were constructed to test the predictability of aneurysm growth by hemodynamic features.

Results

Growing aneurysms had significantly smaller shear rate ratios (p=0.01), higher concentration of wall shear stress (p=0.03), smaller vorticity ratios (p=0.01), and smaller viscous dissipation ratios (p=0.01) than stable aneurysms. They also tended to have larger areas under low wall shear stress (p=0.06) and larger aspect ratios (p=0.18), but these trends were not significant. Mean wall shear stress was not significantly different between growing and stable aneurysms. Logistic regression models based on hemodynamic variables were able to discriminate between growing and stable aneurysms with a high degree of accuracy (94–100%).

Conclusions

Growing aneurysms tend to have complex intrasaccular flow patterns that induce non-uniform wall shear stress distributions with areas of concentrated high wall shear stress and large areas of low wall shear stress. Statistical models based on hemodynamic features seem capable of discriminating between growing and stable aneurysms.