Evidence map›Paper›PMID 25046481›Full record

ArticleMagnetic resonance in medicine2015

A model for extra-axonal diffusion spectra with frequency-dependent restriction.

Wilfred W Lam, Saâd Jbabdi, Karla L Miller

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

  1. Article
  2. Diffusion time dependency of extracellular diffusion.Magnetic resonance in medicine · 2023
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  6. Review
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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

3 authors.

Wilfred W LamCentre for Functional MRI of the Brain, University of Oxford, Oxford, UK.
Saâd JbabdiCentre for Functional MRI of the Brain, University of Oxford, Oxford, UK.
Karla L MillerCentre for Functional MRI of the Brain, University of Oxford, Oxford, UK.

Funding

Medical Research Council G0800578Medical Research Council MR/L009013/1Wellcome Trust 091509/Z/10/Z
6 · The paper itself

Abstract

purposeIn the brain, there is growing interest in using the temporal diffusion spectrum to characterize axonal geometry in white matter because of the potential to be more sensitive to small pores compared to conventional time-dependent diffusion. However, analytical expressions for the diffusion spectrum of particles have only been derived for simple, restricting geometries such as cylinders, which are often used as a model for intra-axonal diffusion. The extra-axonal space is more complex, but the diffusion spectrum has largely not been modeled. We propose a model for the extra-axonal space, which can be used for interpretation of experimental data. THEORY AND

methodsAn empirical model describing the extra-axonal space diffusion spectrum was compared with simulated spectra. Spectra were simulated using Monte Carlo methods for idealized, regularly and randomly packed axons over a wide range of packing densities and spatial scales. The model parameters are related to the microstructural properties of tortuosity, axonal radius, and separation for regularly packed axons and pore size for randomly packed axons.

resultsForward model predictions closely matched simulations. The model fitted the simulated spectra well and accurately estimated microstructural properties.

conclusionsThis simple model provides expressions that relate the diffusion spectrum to biologically relevant microstructural properties.

Indexed as

AxonsDiffusion Magnetic Resonance ImagingImage Processing, Computer-AssistedModels, TheoreticalMonte Carlo MethodWhite Matterdiffusion MRIdiffusion spectrumextra-axonal spaceextracellular spacehindered diffusionrestricted diffusion

Identifiers

PMID25046481
PMCPMC4682484

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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.