Evidence map›Paper›PMID 28085211›Full record

ArticleNMR in biomedicine2017

Evaluating kurtosis-based diffusion MRI tissue models for white matter with fiber ball imaging.

Jens H Jensen, Emilie T McKinnon, G Russell Glenn, Joseph A Helpern

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in NMR in biomedicine, 2017. 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
  2. Article
  3. Challenges for biophysical modeling of microstructure.Journal of neuroscience methods · 2020
    Review
  4. Article
  5. Article
  6. Article
  7. Measuring intra-axonal TMagnetic resonance in medicine · 2019
    Article
  8. Article
  9. Article
  10. Double diffusion encoding MRI for the clinic.Magnetic resonance in medicine · 2018
    Article
  11. Article
  12. Article
  13. Article
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

4 authors.

Jens H JensenDepartment of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.
Emilie T McKinnonDepartment of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.
G Russell GlennDepartment of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.
Joseph A HelpernDepartment of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA.

Funding

TRAINING PROGRAM FOR MEDICAL SCIENTISTST32GM008716 · NIGMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DEMORE, NANCY · 1999 to 2024
$9.3M
Interdisciplinary Research Training in Otolaryngology and Communication SciencesT32DC014435 · NIDCD · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DUBNO, JUDY R · 2015 to 2024
$2.9M
Prediction of Motor Outcome after Acute Stroke using Diffusional Kurtosis ImagingR21NS085475 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ADKINS, DEANNA L, JENSEN, JENS H · 2014 to 2015
$411k
NIDCD NIH HHS T32 DC014435NIGMS NIH HHS T32 GM008716NINDS NIH HHS R21 NS085475
6 · The paper itself

Abstract

In order to quantify well-defined microstructural properties of brain tissue from diffusion MRI (dMRI) data, tissue models are typically employed that relate biological features, such as cell morphology and cell membrane permeability, to the diffusion dynamics. A variety of such models have been proposed for white matter, and their validation is a topic of active interest. In this paper, three different tissue models are tested by comparing their predictions for a specific microstructural parameter to a value measured independently with a recently proposed dMRI method known as fiber ball imaging (FBI). The three tissue models are all constructed with the diffusion and kurtosis tensors, and they are hence compatible with diffusional kurtosis imaging. Nevertheless, the models differ significantly in their details and predictions. For voxels with fractional anisotropies (FAs) exceeding 0.5, all three are reasonably consistent with FBI. However, for lower FA values, one of these, called the white matter tract integrity (WMTI) model, is found to be in much better accord with FBI than the other two, suggesting that the WMTI model has a broader range of applicability.

Indexed as

Models, NeurologicalBrainComputer SimulationDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingHumansImage EnhancementImage Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificityWhite Matterbraindiffusionfiber ball imagingkurtosisMRItensortissue modelwhite matter

Identifiers

PMID28085211
PMCPMC5867517

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Registered trials

None linked

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.