Evidence map›Paper›PMID 27271991›Full record

ArticlePhysics in medicine and biology2016

Simulations on the influence of myelin water in diffusion-weighted imaging.

K D Harkins, M D Does

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  5. TJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
    Article
  6. Article
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  8. Review
  9. Article
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  12. 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

2 authors.

K D HarkinsDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
M D DoesDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.

Funding

Postdoctoral Training in Biomedical MRI and MRST32EB001628 · NIBIB · VANDERBILT UNIVERSITY MEDICAL CENTER · PI John C Gore · 2003 to 2026
$7.0M
Sub-Voxel Tissue Characterization With In-Vivo MRIR01EB001744 · NIBIB · VANDERBILT UNIVERSITY · PI DOES, MARK D · 2003 to 2014
$3.3M
NIBIB NIH HHS R01 EB001744NIBIB NIH HHS T32 EB001628
6 · The paper itself

Abstract

While myelinated axons present an important barrier to water diffusion, many models used to interpret DWI signal neglect other potential influences of myelin. In this work, Monte Carlo simulations were used to test the sensitivity of DWI results to the diffusive properties of water within myelin. Within these simulations, the apparent diffusion coefficient (D app) varied slowly over several orders of magnitude of the coefficient of myelin water diffusion (D m), but exhibited important differences compared to D app values simulated that neglect D m (=0). Compared to D app, the apparent diffusion kurtosis (K app) was generally more sensitive to D m. Simulations also tested the sensitivity of D app and K app to the amount of myelin present. Unique variations in D app and K app caused by differences in the myelin volume fraction were diminished when myelin water diffusion was included. Also, expected trends in D app and K app with experimental echo time were reduced or inverted when accounting for myelin water diffusion, and these reduced/inverted trends were seen experimentally in ex vivo rat brain DWI experiments. In general, myelin water has the potential to subtly influence DWI results and bias models of DWI that neglect these components of white matter.

Indexed as

Diffusion Magnetic Resonance ImagingModels, BiologicalAnimalsDiffusionFemaleMonte Carlo MethodMyelin SheathRatsWaterWater

Identifiers

PMID27271991
PMCPMC4928706

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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.