Phase contrast reflectance confocal brain imaging at 1650 nm.

Significance: The imaging depth of microscopy techniques is limited by the ability of light to penetrate biological tissue. Recent research has addressed this limitation by combining a reflectance confocal microscope with the NIR-II (or shortwave infrared) spectrum. This approach offers significant imaging depth, is straightforward in design, and remains cost-effective. However, the imaging system, which relies on intrinsic signals, could benefit from adjustments in its optical design and post-processing methods to differentiate cortical cells, such as neurons and small blood vessels. Aim: We implemented a phase contrast detection scheme to a reflectance confocal microscope using NIR-II spectral range as illumination. Approach: We analyzed the features retrieved in the images while testing the imaging depth. Moreover, we introduce an acquisition method for distinguishing dynamic signals from the background, allowing the creation of vascular maps similar to those produced by optical coherence tomography. Results: The phase contrast implementation is successful to retrieve deep images in the cortex up to 800 µm using a cranial window. Vascular maps were retrieved at similar cortical depth and the possibility of combining multiple images can provide a vessel network. Conclusions: Phase contrast reflectance confocal microscopy can improve the outlining of cortical cell bodies. With the presented framework, angiograms can be retrieved from the dynamic signal in the biological tissue. Our work presents an optical implementation and analysis techniques from a former microscope design.

Impact of stalling events on microcirculatory hemodynamics in the aged brain.

OBJECTIVE: The role of cerebral microvasculature in cognitive dysfunction can be investigated by identifying the impact of blood flow on cortical tissue oxygenation. In this paper, the impact of capillary stalls on microcirculatory characteristics such as flow and hematocrit (Ht) in the cortical angioarchitecture is studied. METHODS: Using a deterministic mathematical model to simulate blood flow in a realistic mouse cortex, hemodynamics parameters, including pressure, flow, vessel diameter-adjustable hematocrit, and transit time are calculated as a function of stalling events. RESULTS: Using a non-linear plasma skimming model, it is observed that Ht increases in the penetrating arteries from the pial vessels as a function of cortical depth. The incidence of stalling on Ht distribution along the blood network vessels shows reduction of RBCs around the tissue near occlusion sites and decreased Ht concentration downstream from the blockage points. Moreover, upstream of the occlusion, there is a noticeable increase of the Ht, leading to larger flow resistance due to higher blood viscosity. We predicted marked changes in transit time behavior due to stalls which match trends observed in mice in vivo. CONCLUSIONS: These changes to blood cell quantity and quality may be implicated in the development of Alzheimer's disease and contribute to the course of the illness.

Vascular synthesis based on hemodynamic efficiency principle recapitulates measured cerebral circulation properties in the human brain.

Quantifying anatomical and hemodynamical properties of the brain vasculature in vivo is difficult due to limited spatiotemporal resolution neuroimaging, variability between subjects, and bias between acquisition techniques. This work introduces a metabolically inspired vascular synthesis algorithm for creating a digital representation of the cortical blood supply in humans. Spatial organization and segment resistances of a cortical vascular network were generated. Cortical folding and macroscale arterial and venous vessels were reconstructed from anatomical MRI and MR angiography. The remaining network, including ensembles representing the parenchymal capillary bed, were synthesized following a mechanistic principle based on hydrodynamic efficiency of the cortical blood supply. We evaluated the digital model by comparing its simulated values with in vivo healthy human brain measurements of macrovessel blood velocity from phase contrast MRI and capillary bed transit times and bolus arrival times from dynamic susceptibility contrast. We find that measured and simulated values reasonably agree and that relevant neuroimaging observables can be recapitulated in silico. This work provides a basis for describing and testing quantitative aspects of the cerebrovascular circulation that are not directly observable. Future applications of such digital brains include the investigation of the organ-wide effects of simulated vascular and metabolic pathologies.

Determination of spinal tracer dispersion after intrathecal injection in a deformable CNS model.

Background: Traditionally, there is a widely held belief that drug dispersion after intrathecal (IT) delivery is confined locally near the injection site. We posit that high-volume infusions can overcome this perceived limitation of IT administration. Methods: To test our hypothesis, subject-specific deformable phantom models of the human central nervous system were manufactured so that tracer infusion could be realistically replicated in vitro over the entire physiological range of pulsating cerebrospinal fluid (CSF) amplitudes and frequencies. The distribution of IT injected tracers was studied systematically with high-speed optical methods to determine its dependence on injection parameters (infusion volume, flow rate, and catheter configurations) and natural CSF oscillations in a deformable model of the central nervous system (CNS). Results: Optical imaging analysis of high-volume infusion experiments showed that tracers spread quickly throughout the spinal subarachnoid space, reaching the cervical region in less than 10 min. The experimentally observed biodispersion is much slower than suggested by the Taylor-Aris dispersion theory. Our experiments indicate that micro-mixing patterns induced by oscillatory CSF flow around microanatomical features such as nerve roots significantly accelerate solute transport. Strong micro-mixing effects due to anatomical features in the spinal subarachnoid space were found to be active in intrathecal drug administration but were not considered in prior dispersion theories. Their omission explains why prior models developed in the engineering community are poor predictors for IT delivery. Conclusion: Our experiments support the feasibility of targeting large sections of the neuroaxis or brain utilizing high-volume IT injection protocols. The experimental tracer dispersion profiles acquired with an anatomically accurate, deformable, and closed in vitro human CNS analog informed a new predictive model of tracer dispersion as a function of physiological CSF pulsations and adjustable infusion parameters. The ability to predict spatiotemporal dispersion patterns is an essential prerequisite for exploring new indications of IT drug delivery that targets specific regions in the CNS or the brain.

A mechanistic pharmacokinetic model for intrathecal administration of antisense oligonucleotides.

Intrathecal administration is an important mode for delivering biological agents targeting central nervous system (CNS) diseases. However, current clinical practices lack a sound theorical basis for a quantitative understanding of the variables and conditions that govern the delivery efficiency and specific tissue targeting especially in the brain. This work presents a distributed mechanistic pharmacokinetic model (DMPK) for predictive analysis of intrathecal drug delivery to CNS. The proposed DMPK model captures the spatiotemporal dispersion of antisense oligonucleotides (ASO) along the neuraxis over clinically relevant time scales of days and weeks as a function of infusion, physiological and molecular properties. We demonstrate its prediction capability using biodistribution data of antisense oligonucleotide (ASO) administration in non-human primates. The results are in close agreement with the observed ASO pharmacokinetics in all key compartments of the central nervous system. The model enables determination of optimal injection parameters such as intrathecal infusion volume and duration for maximum ASO delivery to the brain. Our quantitative model-guided analysis is suitable for identifying optimal parameter settings to target specific brain regions with therapeutic drugs such as ASOs.

Mesh-free high-resolution simulation of cerebrocortical oxygen supply with fast Fourier preconditioning.

Oxygen transfer from blood vessels to cortical brain tissue is representative of a class of problems with mixed-domain character. Large-scale efficient computation of tissue oxygen concentration is dependent on the manner in which the tubular network of blood vessels is coupled to the tissue mesh. Models which explicitly resolve the interface between the tissue and vasculature with a contiguous mesh are prohibitively expensive for very dense cerebral microvasculature. We propose a mixed-domain mesh-free technique whereby a vascular anatomical network (VAN) represented as a thin directed graph serves for convection of blood oxygen, and the surrounding extravascular tissue is represented as a Cartesian grid of 3D voxels throughout which oxygen is transported by diffusion. We split the network and tissue meshes by the Schur complement method of domain decomposition to obtain a reduced set of system equations for the tissue oxygen concentration at steady state. The use of a Cartesian grid allows the corresponding matrix equation to be solved approximately with a fast Fourier transform-based Poisson solver, which serves as an effective preconditioner for Krylov subspace iteration. The performance of this method enables the steady-state simulation of cortical oxygen perfusion for anatomically accurate vascular networks down to single micron resolution without the need for supercomputers.

MESH-FREE HIGH-RESOLUTION SIMULATION OF CEREBROCORTICAL OXYGEN SUPPLY WITH FAST FOURIER PRECONDITIONING.

Oxygen transfer from blood vessels to cortical brain tissue is representative of a class of problems with mixed-domain character. Large-scale efficient computation of tissue oxygen concentration is dependent on the manner in which the tubular network of blood vessels is coupled to the tissue mesh. Models which explicitly resolve the interface between the tissue and vasculature with a contiguous mesh are prohibitively expensive for very dense cerebral microvasculature. We propose a mixed-domain mesh-free technique whereby a vascular anatomical network (VAN) represented as a thin directed graph serves for convection of blood oxygen, and the surrounding extravascular tissue is represented as a Cartesian grid of 3D voxels throughout which oxygen is transported by diffusion. We split the network and tissue meshes by the Schur complement method of domain decomposition to obtain a reduced set of system equations for the tissue oxygen concentration. The use of a Cartesian grid allows the corresponding matrix equation to be solved approximately with a fast Fourier transform based Poisson solver, which serves as an effective preconditioner for Krylov subspace iteration. The performance of this method enables the steady state simulation of cortical oxygen perfusion for anatomically accurate vascular networks down to single micron resolution without the need for supercomputers. Practitioner Points: We present a novel mixed-domain framework for efficiently modeling O 2 extraction kinetics in the brain. Model equations are generated by graph-theoretic methods for mixed domains.Dual mesh domain decomposition with FFT preconditioning yields very fast simulation times for extremely high spatial resolution.

Cerebrospinal fluid dynamics coupled to the global circulation in holistic setting: Mathematical models, numerical methods and applications.

This paper presents a mathematical model of the global, arterio-venous circulation in the entire human body, coupled to a refined description of the cerebrospinal fluid (CSF) dynamics in the craniospinal cavity. The present model represents a substantially revised version of the original Müller-Toro mathematical model. It includes one-dimensional (1D), non-linear systems of partial differential equations for 323 major blood vessels and 85 zero-dimensional, differential-algebraic systems for the remaining components. Highlights include the myogenic mechanism of cerebral blood regulation; refined vasculature for the inner ear, the brainstem and the cerebellum; and viscoelastic, rather than purely elastic, models for all blood vessels, arterial and venous. The derived 1D parabolic systems of partial differential equations for all major vessels are approximated by hyperbolic systems with stiff source terms following a relaxation approach. A major novelty of this paper is the coupling of the circulation, as described, to a refined description of the CSF dynamics in the craniospinal cavity, following Linninger et al. The numerical solution methodology employed to approximate the hyperbolic non-linear systems of partial differential equations with stiff source terms is based on the Arbitrary DERivative Riemann problem finite volume framework, supplemented with a well-balanced formulation, and a local time stepping procedure. The full model is validated through comparison of computational results against published data and bespoke MRI measurements. Then we present two medical applications: (i) transverse sinus stenoses and their relation to Idiopathic Intracranial Hypertension; and (ii) extra-cranial venous strictures and their impact in the inner ear circulation, and its implications for Ménière's disease.

A Suite of Neurophotonic Tools to Underpin the Contribution of Internal Brain States in fMRI.

Recent developments in optical microscopy, applicable for large-scale and longitudinal imaging of cortical activity in behaving animals, open unprecedented opportunities to gain a deeper understanding of neurovascular and neurometabolic coupling during different brain states. Future studies will leverage these tools to deliver foundational knowledge about brain state-dependent regulation of cerebral blood flow and metabolism as well as regulation as a function of brain maturation and aging. This knowledge is of critical importance to interpret hemodynamic signals observed with functional magnetic resonance imaging (fMRI).

Mathematical synthesis of the cortical circulation for the whole mouse brain-part II: Microcirculatory closure.

Recent advancements in multiphoton imaging and vascular reconstruction algorithms have increased the amount of data on cerebrovascular circulation for statistical analysis and hemodynamic simulations. Experimental observations offer fundamental insights into capillary network topology but mainly within a narrow field of view typically spanning a small fraction of the cortical surface (less than 2%). In contrast, larger-resolution imaging modalities, such as computed tomography (CT) or magnetic resonance imaging (MRI), have whole-brain coverage but capture only larger blood vessels, overlooking the microscopic capillary bed. To integrate data acquired at multiple length scales with different neuroimaging modalities and to reconcile brain-wide macroscale information with microscale multiphoton data, we developed a method for synthesizing hemodynamically equivalent vascular networks for the entire cerebral circulation. This computational approach is intended to aid in the quantification of patterns of cerebral blood flow and metabolism for the entire brain. In part I, we described the mathematical framework for image-guided generation of synthetic vascular networks covering the large cerebral arteries from the circle of Willis through the pial surface network leading back to the venous sinuses. Here in part II, we introduce novel procedures for creating microcirculatory closure that mimics a realistic capillary bed. We demonstrate our capability to synthesize synthetic vascular networks whose morphometrics match empirical network graphs from three independent state-of-the-art imaging laboratories using different image acquisition and reconstruction protocols. We also successfully synthesized twelve vascular networks of a complete mouse brain hemisphere suitable for performing whole-brain blood flow simulations. Synthetic arterial and venous networks with microvascular closure allow whole-brain hemodynamic predictions. Simulations across all length scales will potentially illuminate organ-wide supply and metabolic functions that are inaccessible to models reconstructed from image data with limited spatial coverage.

Voxelized simulation of cerebral oxygen perfusion elucidates hypoxia in aged mouse cortex.

Departures of normal blood flow and metabolite distribution from the cerebral microvasculature into neuronal tissue have been implicated with age-related neurodegeneration. Mathematical models informed by spatially and temporally distributed neuroimage data are becoming instrumental for reconstructing a coherent picture of normal and pathological oxygen delivery throughout the brain. Unfortunately, current mathematical models of cerebral blood flow and oxygen exchange become excessively large in size. They further suffer from boundary effects due to incomplete or physiologically inaccurate computational domains, numerical instabilities due to enormous length scale differences, and convergence problems associated with condition number deterioration at fine mesh resolutions. Our proposed simple finite volume discretization scheme for blood and oxygen microperfusion simulations does not require expensive mesh generation leading to the critical benefit that it drastically reduces matrix size and bandwidth of the coupled oxygen transfer problem. The compact problem formulation yields rapid and stable convergence. Moreover, boundary effects can effectively be suppressed by generating very large replica of the cortical microcirculation in silico using an image-based cerebrovascular network synthesis algorithm, so that boundaries of the perfusion simulations are far removed from the regions of interest. Massive simulations over sizeable portions of the cortex with feature resolution down to the micron scale become tractable with even modest computer resources. The feasibility and accuracy of the novel method is demonstrated and validated with in vivo oxygen perfusion data in cohorts of young and aged mice. Our oxygen exchange simulations quantify steep gradients near penetrating blood vessels and point towards pathological changes that might cause neurodegeneration in aged brains. This research aims to explain mechanistic interactions between anatomical structures and how they might change in diseases or with age. Rigorous quantification of age-related changes is of significant interest because it might aide in the search for imaging biomarkers for dementia and Alzheimer's disease.

Constitutive relationship and governing physical properties for magnetophoresis.

Magnetophoresis is an important physical process with application to drug delivery, biomedical imaging, separation, and mixing. Other than empirically, little is known about how the magnetic field and magnetic properties of a solution affect the flux of magnetic particles. A comprehensive explanation of these effects on the transport of magnetic particles has not been developed yet. Here we formulate a consistent, constitutive equation for the magnetophoretic flux of magnetic nanoparticles suspended in a medium exposed to a stationary magnetic field. The constitutive relationship accounts for contributions from magnetic diffusion, magnetic convection, residual magnetization, and electromagnetic drift. We discovered that the key physical properties governing the magnetophoresis are magnetic diffusion coefficient, magnetic velocity, and activity coefficient, which depend on relative magnetic energy and the molar magnetic susceptibility of particles. The constitutive equation also reveals previously unknown ballistic and diffusive limits for magnetophoresis wherein the paramagnetic particles either aggregate near the magnet or diffusive away from the magnet, respectively. In the diffusive limit, the particle concentration is linearly proportional to the relative magnetic energy of the suspension of paramagnetic particles. The region of the localization of paramagnetic particles near the magnet decreases with increasing the strength of the magnet. The dynamic accumulation of nanoparticles, measured as the thickness of the nanoparticle aggregate, near the magnet compares well with the theoretical prediction. The effect of convective mixing on the rate of magnetophoresis is also discussed for the magnetic targeting applications.

2D parametric contrast time-density analysis for the prediction of complete aneurysm occlusion at six months' post-flow diversion stent.

OBJECTIVE: Indications for the treatment of cerebral aneurysms with flow diversion stents are expanding. The current aneurysm occlusion rate at six months ranges between 60 and 80%. Predictability of complete vs. partial aneurysm occlusion is poorly defined. Here, we evaluate the angiographic contrast time-density as a predictor of aneurysm occlusion rate at six months' post-flow diversion stents. METHODS: Patients with unruptured cerebral aneurysms proximal to the internal carotid artery terminus treated with single flow diversion stents were included. 2D parametric parenchymal blood flow software (Siemens-Healthineers, Forchheim, Germany) was used to calculate contrast time-density within the aneurysm and in the proximal adjacent internal carotid artery. The area under the curve ratio between the two regions of interests was assessed at baseline and after flow diversion stents deployment. The area under the curve ratio between completely vs. partially occluded aneurysms at six months' follow-up was compared. RESULTS: Thirty patients with 31 aneurysms were included. Mean aneurysm diameter was 8 mm (range 2-28 mm). Complete occlusion was obtained in 19 aneurysms. Younger patients (P = 0.006) and smaller aneurysms (P = 0.046) presented higher chance of complete obliteration. Incomplete occlusion of the aneurysm was more likely if the area under the curve contrast time-density ratio showed absolute (P = 0.001) and relative percentage (P = 0.001) decrease after flow diversion stents deployment. Area under ROC curve was 0.85. CONCLUSION: Negative change in the area under the curve ratio indicates less contrast stagnation in the aneurysm and lower chance of occlusion. These data provide a real-time analysis after aneurysm treatment. If validated in larger datasets, this can prompt input to the surgeon to place a second flow diversion stents.

Quantification of blood flow patterns in the cerebral arterial circulation of individual (human) subjects.

There is a growing research interest in quantifying blood flow distribution for the entire cerebral circulation to sharpen diagnosis and improve treatment options for cerebrovascular disease of individual patients. We present a methodology to reconstruct subject-specific cerebral blood flow patterns in accordance with physiological and fluid mechanical principles and optimally informed by in vivo neuroimage data of cerebrovascular anatomy and arterial blood flow rates. We propose an inverse problem to infer blood flow distribution across the visible portion of the arterial network that best matches subject-specific anatomy and a given set of volumetric flow measurements. The optimization technique also mitigates the effect of uncertainties by reconciling incomplete flow data and by dissipating unavoidable acquisition errors associated with medical imaging data.

Drug Delivery Applications of Nanoparticles in the Spine.

Nanoparticles offer several applications in the field of medicine such as targeted drug delivery, controlled drug release, and imaging applications. The central nervous system (CNS), in particular, has remained a challenge for drug delivery. This is mainly due to barriers such as the blood-brain barrier (BBB) and blood-cerebrospinal fluid barrier (BCSFB), which hinder drug molecules from reaching the brain and spinal cord tissue. Although researchers have mainly focused on applying nanotechnology in the brain, there is an increase in applications of nanomaterials in the spine as well. This chapter focuses on the potential of nanomedicine for medical applications in the spine, including unique drug delivery systems and gene therapy applications, and for enhancement of medical imaging. We look at the problems and recent advances in the development of nanoparticles for spine-related applications and provide a comprehensive review on recent research work.

In Vivo Intrathecal Tracer Dispersion in Cynomolgus Monkey Validates Wide Biodistribution Along Neuraxis.

OBJECTIVE: It is commonly believed that in intrathecal (IT) drug delivery, agent distribution is confined to a narrow region close to the injection site, thereby undermining the efficacy of the method. METHODS: To test the claim, multimodal in vivo imaging was used to experimentally observe the effects of IT infusion in cynomolgus monkey, looking at cerebrospinal fluid flow, anatomy, and dispersion of a radiolabeled tracer. RESULTS: At high infusion rates, the tracer reached the cervical region after only 2 h, demonstrating rapid and wide distribution. The same in vivo nonhuman primate imaging data also provided evidence in support of a computational fluid dynamic model for the prediction of drug distribution following IT injection. Tracer dispersion was predicted in two specimens matching the distribution acquired with positron emission tomography (PET). For the third specimen, tracer dispersion simulations were conducted as a blind study: predictions were made before in vivo biodistribution data was known. In all cases, the computational fluid dynamics (CFD) predictions of drug dispersion after IT administration showed close spatio-temporal agreement with tracer biodistribution in vivo. CONCLUSION: Validation by in vivo nonhuman primate data confirms our ability to predict the biodistribution of intrathecally administered agents in subject-specific models of the central nervous system from first principles. SIGNIFICANCE: The experiments reinstate IT delivery as a viable administration method when targeting molecules to the whole spine or the brain. The proposed computational methodology enables rational design of novel therapies for neurological diseases that require reliable, efficient, and safe delivery of therapeutic agents to specific target sites in the central nervous system.

Ratio of Arteriovenous Malformation Draining Vein to Adjacent Venous Sinus Diameter Is Associated with Increased Risk of Venous Stenosis.

BACKGROUND: The development of venous outflow stenosis in cerebral arteriovenous malformation (AVM) is poorly understood. The location of stenosis within the AVM draining vein in relation to the adjacent venous sinus and the hypothesis that the ratio of draining vein to adjacent sinus diameter might predict the development of venous stenosis were explored. METHODS: Patients with supratentorial AVMs (1997-2018) were reviewed (N = 290). AVM draining vein and adjacent venous sinus diameters, degree of draining vein stenosis, and distance from the maximal stenotic point to the junction of the adjacent draining sinus were recorded. Correlation between percentage of AVM draining vein stenosis and the ratio of AVM draining vein to venous sinus diameters was analyzed. RESULTS: A total of 360 draining veins in 243 AVMs with complete angiographic data were measured. Venous stenosis (in 131 draining veins) was observed within 20 mm of the junction to the adjacent draining sinus in 85% of our sample. The ratio of draining vein to adjacent sinus diameter correlated positively with the percentage of venous stenosis (P < 0.01, r = 0.21). The ratio between 0.51-1.0 and >1.0 showed significant tighter stenosis compared with the ratio ≤0.5 (25.9% and 28.9% vs. 10.0%, respectively; P < 0.01). CONCLUSIONS: AVM venous outflow stenosis is observed close to the adjacent venous sinus junction. The degree of venous stenosis is greater when the ratio of AVM draining vein/adjacent venous sinus diameter is >0.5. This may be related to more turbulent flow at the junction of the draining vein and venous sinus, especially in larger draining veins, which causes venous stenosis to develop over time.

Mathematical synthesis of the cortical circulation for the whole mouse brain-part I. theory and image integration.

Microcirculation plays a significant role in cerebral metabolism and blood flow control, yet explaining and predicting functional mechanisms remains elusive because it is difficult to make physiologically accurate mathematical models of the vascular network. As a precursor to the human brain, this paper presents a computational framework for synthesizing anatomically accurate network models for the cortical blood supply in mouse. It addresses two critical deficiencies in cerebrovascular modeling. At the microscopic length scale of individual capillaries, we present a novel synthesis method for building anatomically consistent capillary networks with loops and anastomoses (=microcirculatory closure). This overcomes shortcomings in existing algorithms which are unable to create closed circulatory networks. A second critical innovation allows the incorporation of detailed anatomical features from image data into vascular growth. Specifically, computed tomography and two photon laser scanning microscopy data are input into the novel synthesis algorithm to build the cortical circulation for the entire mouse brain in silico. Computer predictions of blood flow and oxygen exchange executed on synthetic large-scale network models are expected to elucidate poorly understood functional mechanisms of the cerebral circulation.

An efficient full space-time discretization method for subject-specific hemodynamic simulations of cerebral arterial blood flow with distensible wall mechanics.

A computationally inexpensive mathematical solution approach using orthogonal collocations for space discretization with temporal Fourier series is proposed to compute subject-specific blood flow in distensible vessels of large cerebral arterial networks. Several models of wall biomechanics were considered to assess their impact on hemodynamic predictions. Simulations were validated against in vivo blood flow measurements in six human subjects. The average root-mean-square relative differences were found to be less than 4.3% for all subjects with a linear elastic wall model. This discrepancy decreased further in a viscoelastic Kelvin-Voigt biomechanical wall. The results provide support for the use of collocation-Fourier series approach to predict clinically relevant blood flow distribution and collateral blood supply in large portions of the cerebral circulation at reasonable computational costs. It thus opens the possibility of performing computationally inexpensive subject-specific simulations that are robust and fast enough to predict clinical results in real time on the same day.

Cerebral arteriovenous malformation venous stenosis is associated with hemodynamic changes at the draining vein-venous sinus junction.

Cerebral arteriovenous malformations (AVMs) are an uncommon vascular anomaly that carry the risk of rupture and hemorrhage. Several factors have been implicated in the propensity of an AVM to bleed. One such factor is stenosis of AVM draining veins, as impairment of the AVM venous drainage system is associated with increased risk of intracranial hemorrhage. Currently, our understanding of the pathogenesis of AVM venous outflow stenosis is limited, as there is insufficient data on the blood flow patterns and local hemodynamic parameters of these draining veins. The angioarchitecture of AVMs features a nidus lacking a high resistance capillary network. Accordingly, our previous studies on AVM arterial feeders have demonstrated an abnormally high flow volume rate along with low pulsatility and resistance indices on quantitative magnetic resonance angiography. As such, AVM vessels endure high, non-physiologic levels of flow that may partially contribute to ectasia or stenosis depending on whether wall shear stress (WSS) is high or low, respectively. We hypothesize that AVM venous outflow stenosis occurs most commonly near the junction of the draining vein and the dural venous sinus. Increased flow volume rate through the AVM circuit coupled with the variation in compliance and rigidity between the walls of the draining vein and the dural venous sinus likely create turbulence of blood flow. The resulting flow separation, low WSS, and departure from axially aligned, unidirectional flow may create atherogenic conditions that can be implicated in venous intimal hyperplasia and outflow stenosis. We have previously found there to be a significant association between intimal hyperplasia risk factors and venous outflow stenosis. Additionally, we have found a significant association between age and likelihood as well as degree of stenosis, suggesting a progressive disease process. Similar conditions have been demonstrated in the pathophysiology of stenosis of the carotid artery and dialysis arteriovenous fistulas. In both of these conditions, the use of computational fluid dynamics (CFD) has been employed to characterize the local hemodynamic features that contribute to the pathogenesis of intimal hyperplasia and stenosis. We recommend the utilization of CFD to characterize the anatomic and hemodynamic features of AVM venous outflow stenosis. An improved understanding of the possible causative features of venous outflow stenosis may impact how clinicians choose to manage the treatment of patients with AVMs.