Evidence map›Paper›PMID 26449628›Full record

ArticleNMR in biomedicine2015

Evaluation of skeletal muscle DTI in patients with duchenne muscular dystrophy.

M T Hooijmans, B M Damon, M Froeling, M J Versluis, J Burakiewicz, J J G M Verschuuren, E H Niks, A G Webb, H E Kan

Open access · greenAbstract readEvaluation Study
In one paragraph

Article in NMR in biomedicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 3% 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

66 citing papers in PubMed, 1 synthesis or guideline pooled it, 125 citations in OpenAlex.

  1. Pooled it
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  7. Review
  8. Article
  9. Article
  10. Magnetic Resonance Imaging Biomarkers of Muscle.Tomography (Ann Arbor, Mich.) · 2024
    Review
  11. Compositional and Functional MRI of Skeletal Muscle: A Review.Journal of magnetic resonance imaging : JMRI · 2024
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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6 more citing papers are in PubMed but not listed here.

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

9 authors at 5 institutions in 3 countries.

M T HooijmansDepartment of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands.
B M DamonDepartments of Radiology and Radiological Sciences, Biomedical Engineering, and Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA.
M FroelingDepartment of Radiology, Utrecht Medical Center, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0003-3841-0497
M J VersluisPhilips Healthcare, Benelux, The Netherlands.
J BurakiewiczDepartment of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands.
J J G M VerschuurenDepartment of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.
E H NiksDepartment of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.
A G WebbDepartment of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands.
H E KanDepartment of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands.ORCID http://orcid.org/0000-0002-5772-7177
Leiden University · NLLeiden University Medical Center · NLPhilips (Finland) · FIUniversity Medical Center Utrecht · NLVanderbilt University · US

Funding

Biophysical Basis of Muscle Functional MRIR01AR050101 · NIAMS · VANDERBILT UNIVERSITY · PI DAMON, BRUCE M. · 2005 to 2014
$3.1M
NIAMS NIH HHS R01 AR050101
6 · The paper itself

Abstract

Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal-to-noise ratio (SNR), %fat, and tissue T2. The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in-vivo measures of mean water T2, %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles (p<0.05) and an increased mean diffusivity (p<0.05) and λ3 (p<0.05) in the TA muscle of DMD patients. In-vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient (p<0.009) and λ3 in the TA and GCL muscles (p<0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and λ3, these between-group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T2, %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences.

Indexed as

AdolescentChildChild, PreschoolDiffusion Tensor ImagingFemaleHumansLegMaleMuscle, SkeletalMuscular Dystrophy, DuchenneReproducibility of ResultsSensitivity and SpecificitySignal-To-Noise Ratiodiffusion tensor imagingDuchenne muscular dystrophyfat fractionmean water T2signal-to-noise ratio

Identifiers

PMID26449628
PMCPMC4670831
OpenAlexW1961133757

What OpenQuestion holds

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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.