Evidence map›Paper›PMID 25393722›Full record

ArticlePloS one2014

Multi-parametric representation of voxel-based quantitative magnetic resonance imaging.

Maria Engström, Jan B M Warntjes, Anders Tisell, Anne-Marie Landtblom, Peter Lundberg

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Quantitative TImaging neuroscience (Cambridge, Mass.) · 2025
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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

5 authors at 1 institution in 1 country.

Maria EngströmDivision of Radiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Jan B M WarntjesCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; SyntheticMR AB, Linköping, Sweden.
Anders TisellCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Division of Radiation Physics, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Anne-Marie LandtblomCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Division of Neurology, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
Peter LundbergCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Division of Radiation Physics, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Linköping University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the study was to explore the possibilities of multi-parametric representations of voxel-wise quantitative MRI data to objectively discriminate pathological cerebral tissue in patients with brain disorders. For this purpose, we recruited 19 patients with Multiple Sclerosis (MS) as benchmark samples and 19 age and gender matched healthy subjects as a reference group. The subjects were examined using quantitative Magnetic Resonance Imaging (MRI) measuring the tissue structure parameters: relaxation rates, R(1) and R(2), and proton density. The resulting parameter images were normalized to a standard template. Tissue structure in MS patients was assessed by voxel-wise comparisons with the reference group and with correlation to a clinical measure, the Expanded Disability Status Scale (EDSS). The results were visualized by conventional geometric representations and also by multi-parametric representations. Data showed that MS patients had lower R(1) and R(2), and higher proton density in periventricular white matter and in wide-spread areas encompassing central and sub-cortical white matter structures. MS-related tissue abnormality was highlighted in posterior white matter whereas EDSS correlation appeared especially in the frontal cortex. The multi-parameter representation highlighted disease-specific features. In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes. Results from voxel-based statistical analysis, as exemplified in the present work, may guide radiologists where in the image to inspect for signs of disease. Future clinical studies must validate the usability of the method in clinical practice.

Indexed as

Brain MappingDisease ProgressionFemaleFrontal LobeHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedMultiple SclerosisRadiographyWhite Matter

Identifiers

PMID25393722
PMCPMC4230947
OpenAlexW2094018237

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.