Evidence map›Paper›PMID 26708035›Full record

ArticleMagnetic resonance imaging2016

Imaging signatures of meningioma and low-grade glioma: a diffusion tensor, magnetization transfer and quantitative longitudinal relaxation time MRI study.

Rory J Piper, Shadia Mikhael, Joanna M Wardlaw, David H Laidlaw, Ian R Whittle, Mark E Bastin

Abstract read
In one paragraph

Article in Magnetic resonance imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Applications of TFrontiers in oncology · 2022
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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

6 authors.

Rory J PiperCollege of Medicine and Veterinary Medicine, University of Edinburgh, UK. Electronic address: R.J.Piper@sms.ed.ac.uk.
Shadia MikhaelBrain Research Imaging Centre, University of Edinburgh, UK.
Joanna M WardlawCollege of Medicine and Veterinary Medicine, University of Edinburgh, UK; Brain Research Imaging Centre, University of Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, UK.
David H LaidlawComputer Science Department, Brown University, Providence, RI, United States.
Ian R WhittleCollege of Medicine and Veterinary Medicine, University of Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, UK.
Mark E BastinCollege of Medicine and Veterinary Medicine, University of Edinburgh, UK; Brain Research Imaging Centre, University of Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, UK.

Funding

MRI+DTI-Based Tools for Analyzing White Matter VariationR01EB004155 · NIBIB · BROWN UNIVERSITY · PI LAIDLAW, DAVID H · 2005 to 2008
$2.0M
Medical Research Council MR/K026992/1NIBIB NIH HHS R01 EB004155NIBIB NIH HHS R01 EB004155-03.
6 · The paper itself

Abstract

Differentiation of cerebral tumor pathology currently relies on interpretation of conventional structural MRI and in some cases histology. However, more advanced MRI methods may provide further insight into the organization of cerebral tumors and have the potential to aid diagnosis. The objective of this study was to use multimodal quantitative MRI to measure the imaging signatures of meningioma and low-grade glioma (LGG). Nine adults with meningioma and 11 with LGG were identified, and underwent standard structural, quantitative longitudinal relaxation time (T1) mapping, magnetization transfer and diffusion tensor MRI. Maps of mean (〈D〉), axial (λAX) and radial (λRAD) diffusivity, fractional anisotropy (FA), magnetization transfer ratio (MTR) and T1 were generated on a voxel-by-voxel basis. Using structural and echo-planar T2-weighted MRI, manual region-of-interest segmentation of brain tumor, edema, ipsilateral and contralateral normal-appearing white matter (NAWM) was performed. Differences in imaging signatures between the different tissue types, both absolute mean values and ratios relative to contralateral NAWM, were assessed using t-tests with statistical significance set at p<0.05. For both absolute mean values and ratios relative to contralateral NAWM, there were significant differences in 〈D〉, λAX, λRAD, FA, MTR and T1 between meningioma and LGG tumor tissue, respectively. Only T1 and FA differed significantly between edematous tissue associated with the two tumor types. These results suggest that multimodal MRI biomarkers are significantly different, particularly in tumor tissue, between meningioma and LGG. By using quantitative multimodal MRI it may be possible to identify tumor pathology non-invasively.

Indexed as

Diffusion Magnetic Resonance ImagingDiffusion Tensor ImagingAdultAnisotropyBrain NeoplasmsEdemaFemaleGliomaHumansMaleMeningeal NeoplasmsMeningiomaMiddle AgedMultimodal ImagingWhite MatterDiffusionLongitudinal relaxation timeLow-grade gliomaMagnetic resonance imagingMagnetization transferMeningioma

Identifiers

PMID26708035
PMCPMC4801649

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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.