Bulletin of the American Physical Society
77th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 24–26, 2024; Salt Lake City, Utah
Session ZC04: Lymphatic and CSF Flows II |
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Chair: Douglas Kelley, University of Rochester Room: Ballroom D |
Tuesday, November 26, 2024 12:50PM - 1:03PM |
ZC04.00001: Arterial pulsations drive flow in a hydraulic network model of the glymphatic system Keelin E Quirk, Kevin Turner, Patrick Drew, Douglas H Kelley The glymphatic system is hypothesized to serve as a brain waste clearance system, where cerebrospinal fluid (CSF) flows through perivascular channels around arteries into brain tissue. Previous in vivo experiments have demonstrated that arterial pulsations drive net CSF flow. Additionally, arterial pulsation can exhibit locally enhanced or reduced amplitudes in response to stimuli or injury. However, the effect of local pulsations on brain-wide flows is poorly understood. In this study, we propose a hydraulic resistance network model to simulate fluid transport caused by arterial pulsations. These pulsations are modeled as local pressure sources that drive flow proportional to the conductance of each segment. Directional valves into brain tissue ensure net flow. We compare networks experiencing a variety of pulsation waveforms, including brain-wide vasomotion and regionally reduced or enhanced vasomotion to match previous experiments. We observe that the model can drive significant flow into brain tissue, particularly when combined with a previously calculated steady pressure in surface perivascular channels. This model can be used to explore trends in brain-wide CSF motion in response to local events that disrupt arterial pulsations, such as stroke or traumatic brain injury. |
Tuesday, November 26, 2024 1:03PM - 1:16PM |
ZC04.00002: Abstract Withdrawn
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Tuesday, November 26, 2024 1:16PM - 1:29PM |
ZC04.00003: Investigating cerebrospinal fluid dynamics in brain using front tracking Aditya Ranjan, Yisen Guo, Kimberly A Boster, Douglas H Kelley Transport of solute in the brain is governed by advection and diffusion, though their relative contributions are debated. Hence, estimating the velocity fields that drive the advective transport would provide considerable insight. In vivo experiments are commonly performed wherein tracers are injected in the brain in the cerebrospinal fluid (CSF) and their distribution is imaged using the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). We developed a three-dimensional front tracking algorithm to estimate the velocity of the CSF from the time-varying solute concentration field. The algorithm tracks the evolution of fronts, or regions of constant concentration, to estimate the CSF velocity. In the present work, we investigated the accuracy of the front tracking algorithm using synthetic data that mimics the temporal and spatial distribution of concentration in a realistic mouse brain geometry. We also used front tracking to estimate CSF velocity in real MRI scans to acquire a detailed understanding of the forces governing the tracer transport which could be extended to studying therapeutic drug delivery as well. |
Tuesday, November 26, 2024 1:29PM - 1:42PM |
ZC04.00004: Fluid-structure interactions in non-axisymmetric perivascular spaces Nishanth Surianarayanan, Ivan C. Christov The brain’s perivascular spaces (PVSs) are annular channels bound by the cerebral blood vessel (as the inner wall) and the astrocyte endfeet layer (as the outer wall). The cerebrospinal fluid (CSF) flow in these PVSs drives the metabolic waste clearance in the brain. In vivo studies have shown the deformation of the brain tissue induced by CSF flow, emphasizing the need to consider fluid-structure interaction in modeling these flows. Here, we extend the work of Coenen et al. (JFM, 2021, doi:10.1017/jfm.2021.525) to incorporate two-way coupled fluid-structure interaction with the astrocyte endfeet, in addition to the pumping produced by arterial wall motion, under the lubrication approximation. Importantly, the relevant idealized geometries of the PVS consider its eccentricity and outer wall shape. This reduced-order model leads to a single nonlinear unsteady partial differential equation for the axial pressure variation. The parameters investigated are the blood vessel eccentricity, the imposed arterial wall motion (cardiac pulsation/functional hyperemia), and the stiffness of the endfeet layer. Specifically, we analyze their effect on flow quantities such as pressure, flow rate, mean flow rate, PVS resistance, and endfeet displacement. For flows driven by cardiac pulsation, we found that a rigid wall assumption can overestimate the mean flow rate by ≈ 547% and ≈ 17% compared to endfeet walls with compliance numbers of 3.44 × 10−4 and 3.44 × 10−5, respectively. |
Tuesday, November 26, 2024 1:42PM - 1:55PM |
ZC04.00005: How does neuromodulation improve outcomes after traumatic brain injury? Jeff Tithof, Cooper Gray, Dorothea Tse, Daehyun Kim, Turki Alturki, Thomas Ruhl, Silas Simpson, Anika Volker Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. A particularly dire complication following TBI is cerebral edema (i.e., brain tissue swelling) which increases the risk of death tenfold. Recent studies indicate that neuromodulation (specifically, electrical stimulation of cranial nerves) reduces brain edema and improves cognitive outcomes. However, the underlying mechanisms of this reduced secondary injury are not well-understood. We have recently shown that acute post-TBI edema results from suppression of fluid transport through the glymphatic system (a waste clearance pathway involving cerebrospinal fluid flow through the brain). In this talk, we will present preliminary data suggesting that neuromodulation reduces brain edema by restoring extracellular fluid transport via the glymphatic system. Our results have important implications that may lead to novel therapeutic approaches to TBI. |
Tuesday, November 26, 2024 1:55PM - 2:08PM |
ZC04.00006: Low Reynolds number peristaltic pumping near a poroelastic half space Avery Trevino, Thomas R Powers, Roberto Zenit, Mauro Rodriguez Low Reynolds number flow near a poroelastic interface can be found in biological and engineered systems. A particular medical interest is the flow of cerebrospinal fluid (CSF) through annular perivascular spaces between arteries and brain tissue. Vascular deformation from heartbeats has been hypothesized to induce directed CSF flow along these channels, functioning as a mechanism which clears neurodegenerative metabolic waste from surrounding extracellular tissue. We aim to characterize the effect of a nearby poroelastic solid on the overall efficiency of peristaltic pumping as well as find an optimum pumping frequency as a function of physical parameters. We develop a 2D Stokes flow model of peristaltically driven fluid motion near a poroelastic half space. In this geometry, the lower boundary is an infinite train of traveling waves which pump fluid along an open channel. The open fluid layer is bound above by a poroelastic half space, through which fluid can flow. Stresses at the fluid-porous interface produce elastic deformations within the solid. Consequently, porosity is not constant in time or space, leading to nonlinearities in the fluid-solid interactions. Velocities and deformations are thus solved numerically. We will present the scaling relationships between flow rate, peristaltic wave parameters, and poroelastic mechanics to identify the conditions of maximum and minimum CSF pumping, aiming to supplement recent theories of CSF flow in the brain. |
Tuesday, November 26, 2024 2:08PM - 2:21PM |
ZC04.00007: Artificial intelligence velocimetry for quantifying cerebral spinal fluid flow in the brain using physics-informed neural networks. Mohammad Vaezi, Jiatong Sun, Kimberly A Boster, Douglas H Kelley Penetrating perivascular spaces are key pathways that carry CSF deep into the brain tissue where solute exchange occurs, and failure of this process affects brain health and diseases such as Alzheimer's and small vessel disease. Measuring CSF flow in penetrating PVS is important for understanding brain waste clearance and nutrient distribution. Previously, researchers used particle tracking velocimetry (PTV) to measure speed and artificial intelligence velocimetry (AIV) to infer volume flow rates on the brain surface, but flow in penetrating PVSs has never been measured since the one-micron tracer particles used in PTV do not enter. In this study we demonstrated how AIV could be used to infer CSF flow in penetrating PVSs. We applied AIV to estimate flow rates in penetrating PVSs by inferring the flow at locations upstream and downstream of a bifurcation where a penetrating PVS diverges from a surface PVS. We first demonstrated the accuracy of the approach using synthetic data from a realistic PVS geometry where flow in the penetrating PVS is known. Then, using the same approach, we inferred the volume flow rate in penetrating PVSs for the first time. |
Tuesday, November 26, 2024 2:21PM - 2:34PM |
ZC04.00008: Experimental Investigation of Biomechanical Properties Influencing Electrode Deviation in Deep Brain Stimulation Siyu Chen, Rungun Nathan, Bchara Sidnawi, Qifu Wang, Chengyuan Wu, Ani Ural, Feroze Mohamed, Curtis Johnson, Qianhong Wu Parkinson's disease, a debilitating neurodegenerative disorder, is often treated with Deep Brain Stimulation (DBS) surgery, which requires precise electrode placement in specific brain regions for optimal outcomes. Understanding probe-tissue interaction during DBS is critical, especially because the brain is a highly non-homogeneous medium, presenting a significant challenge. To address this challenge, our study investigates factors influencing electrode deviation, focusing on the radiofrequency (RF) probe used in DBS surgery and the fluid-structure interaction (FSI) between the electrode and a multilayer agar gel model. The RF probe was initially inserted into the multilayer gel block, followed by the electrode after the RF probe's removal. Various gel interface angles and concentration gradients were systematically adjusted to study their effects. Mechanical properties of the gels were characterized using magnetic resonance elastography (MRE). High-speed imaging captured the dynamics of the probe channel's opening and closing, and the electrode's deflection relative to the target area. Our findings highlight the significant impact of gel interface angles on electrode deflection, identifying them as the most critical factor affecting precision. This research lays the groundwork for future studies involving actual brain tissue and aims to enhance the precision of DBS surgery, ultimately improving patient outcomes. |
Tuesday, November 26, 2024 2:34PM - 2:47PM |
ZC04.00009: Experimental Model of a Pore as a Valve Mechanism Athan Sanders, Yisen Guo, Douglas H Kelley Pores frequently occur in biological tissues. One such example is the gaps between the astrocyte endfeet that surround arteries in the brain. Flow through these pores often causes bending of the porous material. This raises questions: How does the pressure from fluid flow deform an elastic membrane? How does the newly deformed membrane, in turn, affect the flow? To address these questions, we used silicone sheets to make membranes with a single pore and subjected them to fluid flow. We were able to measure the flow rate at different pressures which allows us to estimate how the membrane has deformed. We found relatively good agreement between our results and simple estimates using plate bending and hydraulic resistance equations. Understanding how membranes deforming with oscillatory pressure act like a valve could help us explain the mechanism driving the flow of cerebrospinal fluid into the brain. |
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