Human brain solute transport quantified by glymphatic MRI-informed biophysics during sleep and sleep deprivation

Abstract

Whether you are reading, running or sleeping, your brain and its fluid environment continuously interacts to distribute nutrients and clear metabolic waste. Yet, the precise mechanisms for solute transport within the human brain have remained hard to quantify using imaging techniques alone. From multi-modal human brain MRI data sets in sleeping and sleep-deprived subjects, we identify and quantify CSF tracer transport parameters using forward and inverse subject-specific computational modelling. Our findings support the notion that extracellular diffusion alone is not sufficient as a brain-wide tracer transport mechanism. Instead, we show that human MRI observations align well with transport by either substantially enhanced (3.5 times faster) extracellular diffusion in combination with local clearance rates corresponding to a tracer half-life of up to 5 hours, or by extracellular diffusion augmented by advection with brain-wide average flow speeds on the order of 1-9 micrometers/min. Reduced advection fully explains reduced tracer clearance after sleep-deprivation, supporting the role of sleep and sleep deprivation on human brain clearance.

Neural activity induces strongly coupled electro-chemo-mechanical interactions and fluid flow in astrocyte networks and extracellular space – a computational study

“…These velocities are dominated by an osmotic contribution in the intracellular compartment; without it, the estimated fluid velocities drop by a factor of × 34–45. Our estimates are very much in line with the interstitial bulk flow velocities of 5.5–14.5 μm/min [52, 53, 54], 10.5 μm/min [55], or 10.0 μm/min [56], as reported by Nicholson [57], the average interstitial bulk velocities in humans of 1–10 μm/min as quantified by Vinje et al [32], and in the lower range of the 7–50 μm/min bulk flow velocities identified by Ray et al [58]. Comparing with the pioneering modeling study by Asgari et al [37], they report baseline flow estimates resulting from a hydrostatic pressure difference (of unknown origin) alone of ≈1–3 · 10 -2 μm 3 /s.…”

“…Nicholson [57], the average interstitial bulk velocities in humans of 1-10 µm/min as quantified by Vinje et al [32], and in the lower range of the 7-50 µm/min bulk flow velocities identified by Ray et al [58]. Comparing with the pioneering modeling study by Asgari et al [37], they report baseline flow estimates resulting from a hydrostatic pressure difference (of unknown origin) alone of ≈1-3 • 10 −2 µm 3 /s.…”

“…In turn, even models at extreme morphological detail of intracellular and extracellular diffusion and reactions tend to ignore electrical drift and fluid mechanics [23, 24]. Moreover, while there has been a surge of computational fluid dynamics studies of the magnitude and mechanisms of cerebrospinal fluid flow, perivascular fluid flow [25, 26], and interstitial fluid flow [27, 28, 29] and their effect on brain solute transport [30, 31, 32, 33], almost all ignore electro-chemical and osmotic effects.…”

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

“…Regardless of model choice, we find that about a third of the infused CSF enters the brain from the SAS, as shown in Figure 10. We remark that it was reported in [67] that up to a third of the intrathecal contrast entered the brain.…”

Gaps in the wall of a perivascular space act as valves to produce a directed flow of cerebrospinal fluid: a hoop-stress model

“…Another study [35] found a dependence of solute transport on particle size and concluded that transport in the parenchyma is by diffusion alone: however, the basis of this finding has been questioned [28]. More recent studies have provided indirect experimental evidence for flow of ISF in the parenchyma [36–38]: these studies present models that show a better fit to tracer data when such a flow is included than when it is not. There is also a theoretical argument for parenchymal flow [18] based on the observed wake/sleep variation in solute clearance [7].…”