Biology subjects

Mardal, K.-A.

Publications and source records attributed to Mardal, K.-A..

12 recordsLinked to original sources

bioRxiv2026

Low-rank tensor decompositions reveal coupled spatiotemporal patterns of CSF tracer transport in the human brain

Intrathecal contrast-enhanced longitudinal MRI, or glymphatic MRI (gMRI), provides a unique clinical window into human cerebrospinal fluid (CSF) transport, interstitial fluid (ISF) interaction, and the glymphatic system. However, standard analyses flatten these multi-subject longitudinal data into univariate comparisons across regions of interest, destroying the underlying multi-way structure and obscuring coupled spatiotemporal dynamics. Here we analyze gMRI data from 92 patients (43 diagnosed with idiopathic normal pressure hydrocephalus [iNPH] and 49 reference subjects [REF]) using unsupervised non-negative low-rank tensor decompositions that treat tracer signal in CSF and brain parenchyma simultaneously. The analysis is stratified by sex to avoid confounding diagnosis with the sex imbalance between cohorts. We recover four replicable components, three of which resolve distinct transport pathways capturing CSF--ISF interaction: distribution of tracer in the supratentorial subarachnoid space and cerebral gray and white matter at 24 hours; transient early influx in regions consistent with transport along major cerebral arteries; and tracer influx to ventricular CSF, also called ventricular reflux. The first two components are positively correlated and thus establish a direct quantitative link between early-stage influx and 24-hour tracer distribution. Moreover, the expression of the two influx pathways varies significantly between REF and iNPH cohorts, demonstrating how unsupervised tensor decompositions provide an automated, data-driven framework to stratify patient groups and derive quantitative markers of solute transport in the human brain.

neuroscience↗

bioRxiv2025

The impact of human brain geometry on the transport of an intrathecal tracer

BackgroundIntrathecal contrast-enhanced magnetic resonance imaging (MRI), utilizing the contrast agent gadobutrol as cerebrospinal fluid (CSF) tracer is emerging as a useful method to study glymphatic function in the human brain. A consistent finding with this technique is large inter-individual variability regarding tracer propagation. In this study, we outline an approach which predicts the distribution of tracer in the parenchyma based only on geometric information from brain tissue as captured by MRI, addressing one possible explanation for this variability. MethodsRegistrations are computed from pre-injection MRI, and used to map images at 24 hours after tracer injection to perform predictions of tracer enrichment in the parenchyma in other patients. We apply the method to a dataset of human brain MRI of 134 patients examined for different tentative diagnoses including idiopathic normal pressure hydrocephalus, spontaneous intracranial hypotension and idiopathic intracranial hypertension, as well as a group of reference patients. ResultsTracer enrichment mapped between patients by image registration correlate strongly with actual observed enrichment. For patients in the reference group, the relative root mean squared error on our predictions is on average 26% in the gray matter, and 15% or less in other brain regions. Predictions are generally less reliable in the gray matter, and for patients with identified CSF leaks. ConclusionWe show that predictions made from purely geometrical considerations correlate strongly with actual MRI tracer enrichment for patients with similar diagnoses, thus quantifying the role of geometry in tracer enrichment.

neuroscience↗

bioRxiv2025

Modeling glioma-induced impairments on the glymphatic system

Altered glymphatic function is observed for many neurological diseases. Glioma, one of the most common brain cancers, is known to have altered fluid dynamics in terms of edema and blood-brain-barrier breakdown, both features potentially impacting the glymphatic function. To study glioma and its fluid dynamics, we propose a flexible mathematical model, including the tumor, the peri-tumoral edema as well as the healthy tissue. From a mechanical point of view, we consider the brain as a multicompartment porous medium and model both the fluid movement in the brain and the clearance of solutes that are convected but also diffuse in the extra-cellular space. Our results indicate that the impairment on the glymphatic system due to glioma growth is two-fold. First, edema resulting from leakage of fluid from the blood vessels or occlusion of the peri-vascular spaces, considered as an exit route, result in a local high pressure zone, consequently impairing negatively glymphatic clearance. Second, local changes of porosities (volume fraction of certain compartments such as perivascular or extracellular spaces), result in a disruption of the transport of solutes in the brain. Our results indicate that an effect similar to the enhanced permeability and retention is obtained using biologically relevant changes of parameter values of our model. Our mathematical model can be viewed as the first step towards a digital twin for drug or contrast product delivery within the cerebro-spinal fluid directly (e.g. from intrathecal injection) for patients suffering from gliomas.

biophysics↗

bioRxiv2025

Numerical experiments for reconstructing cerebrospinal fluid flow based on contrast enhanced magnetic resonance images in the lower subarachnoid compartments of the brain

In this paper we test various numerical methods for flow reconstruction based on both manufactured, idealized data and real patient data based on contrast enhanced magnetic resonance imaging after intrathecal contrast injection. As shown in previous studies, the imaging often display contrast gradients in localized regions although large areas have very small gradients. Velocities may as such be hard to assess in areas of low gradients. We compare optimal mass transfer with adjoint based data assimilation constrained by a convection diffusion equation. With well-chosen parameters the manufactured problems can be solved well in the idealized setting, but the performance is in general significantly worse in the patient specific setting. The methods predict maximal velocities well, but fail to reconstruct accurate velocity fields in areas without contrast gradients.

bioengineering↗

bioRxiv2024

Estimation of fluid flow velocities in cortical brain tissue driven by the microvasculature

We present a modelling framework for describing bulk fluid flow in brain tissue. Within this framework, using computational simulation, we estimate bulk flow velocities in the gray matter parenchyma due to static or slowly varying water potential gradients--hydrostatic pressure gradients and osmotic pressure gradients. Working with the situation that experimental evidence and some model parameter estimates, as we point out, are presently insufficient to estimate velocities precisely, we explore feasible parameter ranges resulting in a range of estimates. We consider the effect of realistic microvascular architecture (extracted from mouse cortical gray matter). Although the estimated velocities are small in magnitude (e.g. in comparison to blood flow velocities), the passive transport of solutes with the bulk fluid can be a relevant process when considering larger molecules transported over larger distances. We compare velocity magnitudes resulting from filtration and pulsations. Filtration can lead to continuous directed fluid flow in the parenchyma, while pulsation-driven flow is (at least partly) reversible. For the first time, we consider the effect of the vascular architecture on the velocity distribution in a tissue sample of ca. 1 mm3 cortical gray matter tissue. We conclude that both filtration and pulsations are potentially potent drivers for fluid flow. Summary (lay abstract)Fluid transport through brain tissue is dynamic, but the basic properties of this flow and its variability are poorly characterised. Disturbed fluid transport was linked to Alzheimers disease. Moreover, fluid flow may be exploited to administer drugs to the brain. Using computer simulations, we estimate bulk flow velocities in the gray matter functional brain tissue due to changes in blood pressure and solute concentrations in unseen detail. We show that microvessel pulsations as filtration across the blood capillaries are potentially potent drivers of fluid flow in brain tissue.

biophysics↗

bioRxiv2024

Modeling CSF circulation and the glymphatic system during infusion using subject specific intracranial pressures and brain geometries

BackgroundInfusion testing is an established method for assessing CSF resistance in patients with idiopathic normal pressure hydrocephalus (iNPH). To what extent the increased resistance is related to the glymphatic system is an open question. Here we introduce a computational model that includes the glymphatic system and enables us to determine the importance of 1) brain geometry, 2) intracranial pressure and 3) physiological parameters on the outcome of and response to an infusion test. MethodsWe implemented a seven-compartment multiple network porous medium model with subject specific geometries from MR images. The model consists of the arterial, capillary and venous blood vessels, their corresponding perivascular spaces, and the extracellular space (ECS). Both subject specific brain geometries and subject specific infusion tests were used in the modeling of both healthy adults and iNPH patients. Furthermore, we performed a systematic study of the effect of variations in model parameters. ResultsBoth the iNPH group and the control group reached a similar steady state solution when subject specific geometries under identical boundary conditions was used in simulation. The difference in terms of average fluid pressure and velocity between the iNPH and control groups, was found to be less than 6 % during all stages of infusion in all compartments. With subject specific boundary conditions, the largest computed difference was a 75 % greater fluid speed in the arterial perivascular space (PVS) in the iNPH group compared to the control group. Changes to material parameters changed fluid speeds by several orders of magnitude in some scenarios. A considerable amount of the CSF pass through the glymphatic pathway in our models during infusion, i.e., 28% and 38% in the healthy and iNPH patients, respectively. ConclusionsUsing computational models, we have found the relative importance of subject specific geometries to be less important than individual differences in terms of fluid pressure and flow rate during infusion. Model parameters such as permeabilities and inter-compartment transfer parameters are uncertain but important and have large impact on the simulation results. The computations predicts that a considerable amount of the infused volume pass through the brain either through the perivascular spaces or the extracellular space.

neuroscience↗

bioRxiv2022

Estimates for the astrocyte endfoot sheath permeability of the extra-cellular pathway

BackgroundAstrocyte endfoot processes are believed to cover all micro-vessels in the brain cortex and may play a significant role in fluid and substance transport into and out of the brain parenchyma. Detailed fluid mechanical models of diffusive and advective transport in the brain are promising tools to investigate theories of transport. MethodsWe derive theoretical estimates of astrocyte endfoot sheath permeability for advective and diffusive transport and its variation in microvascular networks from mouse brain cortex. The networks are based on recently published experimental data and generated endfoot patterns are based on Voronoi tessellations of the perivascular surface. We estimate corrections for projection errors in previously published data. ResultsWe provide structural-functional relationships between vessel radius and resistance that can be directly used in flow and transport simulations. We estimate endfoot sheath filtration coefficients in the range Lp = 0.2 x 10-10 m Pa-1 s-1 to 2.7 x 10-10 m Pa-1 s-1, diffusion membrane coefficients in the range CM = 0.5 x 103 m-1 to 6 x 103 m-1, and gap area fractions in the range 0.2 % to 0.6 %. ConclusionsThe astrocyte endfoot sheath surrounding microvessels forms a secondary barrier to extra-cellular transport, separating the extra-cellular space of the parenchyma and the perivascular space outside the endothelial layer. The filtration and membrane diffusion coefficients of the endfoot sheath are estimated to be an order of magnitude lower than the extra-cellular matrix while being two orders of magnitude higher than the vessel wall.

biophysics↗

bioRxiv2022

Sleep cycle-dependent vascular dynamics enhance perivascular cerebrospinal fluid flow and solute transport

Perivascular spaces (PVS) are important highways for fluid and solute transport in the brain enabling efficient waste clearance during sleep. Using two-photon imaging of naturally sleeping mice we demonstrate sleep cycle-dependent PVS dynamics - slow, large-amplitude oscillations in NREM, a reduction in REM and an enlargement upon awakening at the end of a sleep cycle. By biomechanical modeling we demonstrate that these sleep cycle-dependent PVS dynamics drive fluid flow and solute transport.

neuroscience↗

bioRxiv2022

CSF circulation and dispersion yield rapid clearancefrom intracranial compartments

In this paper we used a computational model to estimate the clearance of tracer driven by circulation of cere-brospinal fluid (CSF) produced in the choroid plexus (CP) located within the lateral ventricles. CSF was assumed to exit the subarachnoid space (SAS) via different outflow routes such as the parasagittal dura, cribriform plate and/or meningeal lymphatics. We also modelled a reverse case where fluid was produced within the spinal canal and absorbed in the CP in line with observation on certain iNPH patients. No directional interstitial fluid flow was assumed within the brain parenchyma. Tracers were injected into the foramen magnum. The models demonstrate that convection in the SAS yield rapid clearance from both the SAS and the brain interstitial fluid (ISF) and can speed up intracranial clearance from years, as would be the case for purely diffusive flow, to days.

neuroscience↗

bioRxiv2020

The mechanisms behind perivascular fluid flow

Flow of cerebrospinal fluid (CSF) in perivascular spaces (PVS) is one of the key concepts involved in theories concerning clearance from the brain. Experimental studies have demonstrated both net and oscillatory movement of microspheres in PVS (Mestre et al. (2018), Bedussi et al. (2018)). The oscillatory particle movement has a clear cardiac component, while the mechanisms involved in net movement remain disputed. Using computational fluid dynamics, we computed the CSF velocity and pressure in a PVS surrounding a cerebral artery subject to different forces, representing arterial wall expansion, systemic CSF pressure changes and rigid motions of the artery. The arterial wall expansion generated velocity amplitudes of 60–260 µm/s, which is in the upper range of previously observed values. In the absence of a static pressure gradient, predicted net flow velocities were small (<0.5 µm/s), though reaching up to 7 µm/s for non-physiological PVS lengths. In realistic geometries, a static systemic pressure increase of physiologically plausible magnitude was sufficient to induce net flow velocities of 20–30 µm/s. Moreover, rigid motions of the artery added to the complexity of flow patterns in the PVS. Our study demonstrates that the combination of arterial wall expansion, rigid motions and a static CSF pressure gradient generates net and oscillatory PVS flow, quantitatively comparable with experimental findings. The static CSF pressure gradient required for net flow is small, suggesting that its origin is yet to be determined.Significance Statement Cerebrospinal fluid flow along perivascular spaces is hypothesized to be instrumental for clearance of metabolic waste from the brain, such as e.g. clearance of amyloid-beta, a protein known to accumulate as plaque within the brain in Alzheimer’s patients. Arterial pulsations have been proposed as the main driving mechanism for perivascular fluid flow, but it is unclear whether this mechanism alone is sufficient. Our results show that arterial pulsations drive oscillatory movement in perivascular spaces, but also indicate that a pressure gradient is required for net flow. However, the required pressure gradient is relatively small, thus suggesting that its origins can be associated with physiological processes within the brain and/or experimental procedures.Competing Interest StatementThe authors have declared no competing interest.View Full Text

physiology↗

bioRxiv2019

Intracranial pressure elevation alters CSF clearance pathways

BackgroundInfusion testing is a common procedure to determine whether shunting will be beneficial in patients with normal pressure hydrocephalus. The method has a well-developed theoretical foundation and corresponding mathematical models that describe the CSF circulation from the choroid plexus to the arachnoid granulations. Here, we investigate to what extent the proposed glymphatic or paravascular pathway (or similar pathways) modifies the results of the traditional mathematical models.\n\nMethodsWe used a two-compartment model consisting of the subarachnoid space and the paravascular spaces. For the arachnoid granulations, the cribriform plate, capillaries and paravascular spaces, resistances were calculated and used to estimate flow before and during an infusion test. Next, pressure in the subarachnoid space and paravascular spaces were computed. Finally, different variations to the model were tested to evaluate the sensitivity of selected parameters.\n\nResultsAt baseline, we found a very small paravascular flow directed into the subarachnoid space, while 60% of the fluid left through the arachnoid granulations and 40% left through the cribriform plate. However, during the infusion, paravascular flow reversed and 25% of the fluid left through these spaces, while 60% went through the arachnoid granulations and only 15% through the cribriform plate.\n\nConclusionsThe relative distribution of CSF flow to different clearance pathways depends on intracranial pressure (ICP), with the arachnoid granulations as the main contributor to outflow. As such, ICP increase is an important factor that should be addressed when determining the pathways of injected substances in the subarachnoid space.

bioengineering↗

bioRxiv2018

Can the presence of neural probes be neglected in computational modeling of extracellular potentials?

AbstractO_ST_ABSObjectiveC_ST_ABSMechanistic modeling of neurons is an essential component of computational neuroscience that enables scientists to simulate, explain, and explore neural activity. The conventional approach to simulation of extracellular neural recordings first computes transmembrane currents using the cable equation and then sums their contribution to model the extracellular potential. This two-step approach relies on the assumption that the extracellular space is an infinite and homogeneous conductive medium, while measurements are performed using neural probes. The main purpose of this paper is to assess to what extent the presence of the neural probes of varying shape and size impacts the extracellular field and how to correct for them.\n\nApproachWe apply a detailed modeling framework allowing explicit representation of the neuron and the probe to study the effect of the probes and thereby estimate the effect of ignoring it. We use meshes with simplified neurons and different types of probe and compare the extracellular action potentials with and without the probe in the extracellular space. We then compare various solutions to account for the probes presence and introduce an efficient probe correction method to include the probe effect in modeling of extracellular potentials.\n\nMain resultsOur computations show that microwires hardly influence the extracellular electric field and their effect can therefore be ignored. In contrast, Multi-Electrode Arrays (MEAs) significantly affect the extracellular field by magnifying the recorded potential. While MEAs behave similarly to infinite insulated planes, we find that their effect strongly depends on the neuron-probe alignment and probe orientation.\n\nSignificanceIgnoring the probe effect might be deleterious in some applications, such as neural localization and parameterization of neural models from extracellular recordings. Moreover, the presence of the probe can improve the interpretation of extracellular recordings, by providing a more accurate estimation of the extracellular potential generated by neuronal models.

bioengineering↗