Measuring Glymphatic Flow in Man Using Quantitative Contrast-Enhanced MRI

Watts, Richard; Steinklein, Jared; Waldman, Leah; Zhou, Xiaoxia; Filippi, C.G.

doi:10.3174/ajnr.a5931

Cited by 67 publications

(94 citation statements)

References 17 publications

(17 reference statements)

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“…It is likely these differences were larger in the cranial SAS due to the 2D imaging technique that used a picture obtained for a single angle relative to the model, whereas, the CFD concentrations were precisely averaged across each 3 mm thick slice, including fluid located within the ventricles of the brain. Future work could potentially improve agreement of in vitro and numerical results by utilizing tomographic projection imaging [65] of the in vitro model or quantitative contrast enhanced MRI techniques [66].…”

Section: Limitationsmentioning

confidence: 99%

In vitro and numerical simulation of blood removal from cerebrospinal fluid: comparison of lumbar drain to Neurapheresis therapy

Khani

Sass

Sharp

et al. 2020

Fluids Barriers CNS

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Background: Blood removal from cerebrospinal fluid (CSF) in post-subarachnoid hemorrhage patients may reduce the risk of related secondary brain injury. We formulated a computational fluid dynamics (CFD) model to investigate the impact of a dual-lumen catheter-based CSF filtration system, called Neurapheresis ™ therapy, on blood removal from CSF compared to lumbar drain. Methods:A subject-specific multiphase CFD model of CSF system-wide solute transport was constructed based on MRI measurements. The Neurapheresis catheter geometry was added to the model within the spinal subarachnoid space (SAS). Neurapheresis flow aspiration and return rate was 2.0 and 1.8 mL/min, versus 0.2 mL/min drainage for lumbar drain. Blood was modeled as a bulk fluid phase within CSF with a 10% initial tracer concentration and identical viscosity and density as CSF. Subject-specific oscillatory CSF flow was applied at the model inlet. The dura and spinal cord geometry were considered to be stationary. Spatial-temporal tracer concentration was quantified based on time-average steady-streaming velocities throughout the domain under Neurapheresis therapy and lumbar drain. To help verify CFD results, an optically clear in vitro CSF model was constructed with fluorescein used as a blood surrogate. Quantitative comparison of numerical and in vitro results was performed by linear regression of spatial-temporal tracer concentration over 24-h. Results:After 24-h, tracer concentration was reduced to 4.9% under Neurapheresis therapy compared to 6.5% under lumbar drain. Tracer clearance was most rapid between the catheter aspiration and return ports. Neurapheresis therapy was found to have a greater impact on steady-streaming compared to lumbar drain. Steady-streaming in the cranial SAS was ~ 50× smaller than in the spinal SAS for both cases. CFD results were strongly correlated with the in vitro spatial-temporal tracer concentration under Neurapheresis therapy (R 2 = 0.89 with + 2.13% and − 1.93% tracer concentration confidence interval). Conclusion:A subject-specific CFD model of CSF system-wide solute transport was used to investigate the impact of Neurapheresis therapy on tracer removal from CSF compared to lumbar drain over a 24-h period. Neurapheresis therapy was found to substantially increase tracer clearance compared to lumbar drain. The multiphase CFD results were verified by in vitro fluorescein tracer experiments. © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article' s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article'

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Section: Limitationsmentioning

confidence: 99%

In vitro and numerical simulation of blood removal from cerebrospinal fluid: comparison of lumbar drain to Neurapheresis therapy

Khani

Sass

Sharp

et al. 2020

Fluids Barriers CNS

View full text Add to dashboard Cite

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“…An optimal mass transport analysis in SHRSP rats reveals reduced and slowed solute transport from CSF into the brain [139]. Though rare, opportunistic human studies show CSF solute transport into basal brain parenchyma over longer times with similar distributions [140][141][142].…”

Section: Mr Spectroscopy To Assess Metabolitesmentioning

confidence: 98%

A Review of Translational Magnetic Resonance Imaging in Human and Rodent Experimental Models of Small Vessel Disease

Stringer

Lee

Huuskonen

et al. 2020

Transl. Stroke Res.

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Cerebral small vessel disease (SVD) is a major health burden, yet the pathophysiology remains poorly understood with no effective treatment. Since much of SVD develops silently and insidiously, non-invasive neuroimaging such as MRI is fundamental to detecting and understanding SVD in humans. Several relevant SVD rodent models are established for which MRI can monitor in vivo changes over time prior to histological examination. Here, we critically review the MRI methods pertaining to salient rodent models and evaluate synergies with human SVD MRI methods. We found few relevant publications, but argue there is considerable scope for greater use of MRI in rodent models, and opportunities for harmonisation of the rodent-human methods to increase the translational potential of models to understand SVD in humans. We summarise current MR techniques used in SVD research, provide recommendations and examples and highlight practicalities for use of MRI SVD imaging protocols in pre-selected, relevant rodent models.

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“…MRI is also minimally invasive and therefore can be used to study the glymphatic system in vivo with minimum disruption in both animals and humans. Recent examinations of the human brain that utilized MRI provided evidence that suggested that the presence of the glymphatic system in the human brain is analogous to that found in the rodent brain [81][82][83][84][85][86][87]. Modeling the glymphatic system using data from MRI can provide insight into the glymphatic flow pathways.…”

Section: Magnetic Resonance Imaging (Mri) Detection and Modelingmentioning

confidence: 99%

Magnetic Resonance Imaging and Modeling of the Glymphatic System

et al. 2020

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The glymphatic system is a newly discovered waste drainage pathway in the brain; it plays an important role in many neurological diseases. Ongoing research utilizing various cerebrospinal fluid tracer infusions, either directly or indirectly into the brain parenchyma, is investigating clearance pathways by using distinct imaging techniques. In the present review, we discuss the role of the glymphatic system in various neurological diseases and efflux pathways of brain waste clearance based on current evidence and controversies. We mainly focus on new magnetic resonance imaging (MRI) modeling techniques, along with traditional computational modeling, for a better understanding of the glymphatic system function. Future sophisticated modeling techniques hold the potential to generate quantitative maps for glymphatic system parameters that could contribute to the diagnosis, monitoring, and prognosis of neurological diseases. The non-invasive nature of MRI may provide a safe and effective way to translate glymphatic system measurements from bench-to-bedside.

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Measuring Glymphatic Flow in Man Using Quantitative Contrast-Enhanced MRI

Cited by 67 publications

References 17 publications

In vitro and numerical simulation of blood removal from cerebrospinal fluid: comparison of lumbar drain to Neurapheresis therapy

In vitro and numerical simulation of blood removal from cerebrospinal fluid: comparison of lumbar drain to Neurapheresis therapy

A Review of Translational Magnetic Resonance Imaging in Human and Rodent Experimental Models of Small Vessel Disease

Magnetic Resonance Imaging and Modeling of the Glymphatic System

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