Evidence map›Paper›PMID 29573042›Full record

ArticleJournal of magnetic resonance imaging : JMRI2018

Value of diffusion kurtosis imaging in assessing low-grade gliomas.

Mohammed Z Goryawala, Deborah O Heros, Ricardo J Komotar, Sulaiman Sheriff, Efrat Saraf-Lavi, Andrew A Maudsley

Abstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Pediatric low-grade glial, glioneuronal and neuronal tumors: a retrospective study of 85 cases.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2026
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  4. DKI andBMC medical imaging · 2024
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  14. The Association between Whole-Brain MR Spectroscopy and IDH Mutation Status in Gliomas.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2020
    Article
  15. Article
  16. 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

6 authors.

Mohammed Z GoryawalaDepartment of Radiology, University of Miami, Miami, Florida, USA.
Deborah O HerosDepartment of Neurology, University of Miami, Miami, Florida, USA.
Ricardo J KomotarDepartment of Neurological Surgery, University of Miami, Miami, Florida, USA.
Sulaiman SheriffDepartment of Radiology, University of Miami, Miami, Florida, USA.
Efrat Saraf-LaviDepartment of Radiology, University of Miami, Miami, Florida, USA.
Andrew A MaudsleyDepartment of Radiology, University of Miami, Miami, Florida, USA.

Funding

Multiparametric Volumetric MR Characterization of Intracranial LesionsR01CA172210 · NCI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI MAUDSLEY, ANDREW A. · 2014 to 2018
$2.7M
Development and Maintenance of Software for MR Spectroscopic ImagingR01EB016064 · NIBIB · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI MAUDSLEY, ANDREW A. · 2013 to 2021
$2.0M
NCI NIH HHS R01 CA172210NIBIB NIH HHS R01 EB016064
6 · The paper itself

Abstract

backgroundDiffusion kurtosis imaging (DKI) measures have been shown to provide increased sensitivity relative to diffusion tensor imaging (DTI) in detecting pathologies. PURPOSE: To compare the sensitivity of DKI-derived kurtosis and diffusion maps for assessment of low-grade gliomas (LGG). STUDY TYPE: Prospective study. POPULATION: In all, 19 LGG patients and 26 healthy control subjects were recruited. FIELD STRENGTH/SEQUENCE: Echo-planar-imaging diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner. ASSESSMENT: Maps for mean, axial, and radial diffusivity (MD, AD, and RD) and kurtosis (MK, AK, and RK), and fractional anisotropy (FA) were evaluated in the tumor, perilesional white matter, and contralateral normal-appearing white matter regions. STATISTICAL TESTING: General linear models (GLM), Cohen's d for effect size estimates, false discovery rate (FDR) for multiple corrections, Cochran Q-test.

resultsPairwise differences were observed for all diffusion and kurtosis measures between the studied regions (FDR P < 0.001), except an FA map that failed to show significant differences between the lesion and perilesional white matter (FDR P = 0.373). Effect size analysis showed that kurtosis metrics were found to be 18.8% (RK, P = 0.144) to 29.1% (AK, P < 0.05) more sensitive in discriminating perilesional regions from the lesion than corresponding diffusion metrics, whereas AK provided a 25.0% (P < 0.05) increase in sensitivity in discriminating perilesional and contralateral white matter. RK was found to be the most sensitive to contralateral white matter differences between low-grade gliomas and controls, with MK and RK providing a significantly greater sensitivity of 587.2% (P < 0.001) and 320.7% (P < 0.001) than MD and RD, respectively. DATA

conclusionKurtosis maps showed increased sensitivity, as compared to counterpart diffusion maps, for evaluation of microstructural changes in gliomas with a 3-6-fold increment in assessing changes in contralateral white matter. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;48:1551-1558.

Indexed as

Echo-Planar ImagingMagnetic Resonance ImagingAdolescentAdultAgedAlgorithmsBrain MappingBrain NeoplasmsCase-Control StudiesDiffusionDiffusion Tensor ImagingFemaleGliomaHumansImage Processing, Computer-AssistedLinear Modelsdiffusion kurtosis imagingdiffusion tensor imaginglow-grade gliomaperilesional white matter

Identifiers

PMID29573042
PMCPMC6151302

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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.