Evidence map›Paper›PMID 38419077›Full record

ArticleFluids and barriers of the CNS2024

Large-scale in-silico analysis of CSF dynamics within the subarachnoid space of the optic nerve.

Diego Rossinelli, Gilles Fourestey, Hanspeter Esriel Killer, Albert Neutzner, Gianluca Iaccarino, Luca Remonda, Jatta Berberat

Open access · goldAbstract read
In one paragraph

Article in Fluids and barriers of the CNS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 2 countries.

Diego RossinelliInstitute for Computational and Mathematical Engineering (ICME), Center for Turbulence Research, Stanford University, Stanford, CA, 94305-3024, USA. rossinel@stanford.edu.
Gilles FouresteyScientific IT & Application Support (SCITAS), Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.
Hanspeter Esriel KillerDepartment of Biomedicine, University of Basel, Basel, Switzerland.
Albert NeutznerDepartment of Biomedicine, University of Basel, Basel, Switzerland.
Gianluca IaccarinoInstitute for Computational and Mathematical Engineering (ICME), Center for Turbulence Research, Stanford University, Stanford, CA, 94305-3024, USA.
Luca RemondaInstitute of Neuroradiology, Kantonsspital Aarau, 5000, Aarau, Switzerland.
Jatta BerberatInstitute of Neuroradiology, Kantonsspital Aarau, 5000, Aarau, Switzerland.
Stanford University · USUniversity of Basel · CHÉcole Polytechnique Fédérale de Lausanne · CHKantonsspital Aarau · CHUniversity of Geneva · CH

Funding

Forschungsrat des Kantonsspitals Aarau 1410.000.111Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 196877
6 · The paper itself

Abstract

backgroundImpaired cerebrospinal fluid (CSF) dynamics is involved in the pathophysiology of neurodegenerative diseases of the central nervous system and the optic nerve (ON), including Alzheimer's and Parkinson's disease, as well as frontotemporal dementia. The smallness and intricate architecture of the optic nerve subarachnoid space (ONSAS) hamper accurate measurements of CSF dynamics in this space, and effects of geometrical changes due to pathophysiological processes remain unclear. The aim of this study is to investigate CSF dynamics and its response to structural alterations of the ONSAS, from first principles, with supercomputers.

methodsLarge-scale in-silico investigations were performed by means of computational fluid dynamics (CFD) analysis. High-order direct numerical simulations (DNS) have been carried out on ONSAS geometry at a resolution of 1.625 μm/pixel. Morphological changes on the ONSAS microstructure have been examined in relation to CSF pressure gradient (CSFPG) and wall strain rate, a quantitative proxy for mass transfer of solutes.

resultsA physiological flow speed of 0.5 mm/s is achieved by imposing a hydrostatic pressure gradient of 0.37-0.67 Pa/mm across the ONSAS structure. At constant volumetric rate, the relationship between pressure gradient and CSF-accessible volume is well captured by an exponential curve. The ONSAS microstructure exhibits superior mass transfer compared to other geometrical shapes considered. An ONSAS featuring no microstructure displays a threefold smaller surface area, and a 17-fold decrease in mass transfer rate. Moreover, ONSAS trabeculae seem key players in mass transfer.

conclusionsThe present analysis suggests that a pressure drop of 0.1-0.2 mmHg over 4 cm is sufficient to steadily drive CSF through the entire subarachnoid space. Despite low hydraulic resistance, great heterogeneity in flow speeds puts certain areas of the ONSAS at risk of stagnation. Alterations of the ONSAS architecture aimed at mimicking pathological conditions highlight direct relationships between CSF volume and drainage capability. Compared to the morphological manipulations considered herein, the original ONSAS architecture seems optimized towards providing maximum mass transfer across a wide range of pressure gradients and volumetric rates, with emphasis on trabecular structures. This might shed light on pathophysiological processes leading to damage associated with insufficient CSF flow in patients with optic nerve compartment syndrome.

Indexed as

HydrodynamicsIntraocular PressureCerebrospinal FluidCerebrospinal Fluid PressureHumansOptic NerveSubarachnoid SpaceCerebrospinal fluidComputational fluid dynamicsDispersionHomeostasisIdiopathic intracranial hypertensionIntracranial pressureNormal-Tension GlaucomaOptic nerveOptic nerve compartment syndromeSubarachnoid space

Identifiers

PMID38419077
PMCPMC10900650
OpenAlexW4392239540

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.