Evidence map›Paper›PMID 26885524›Full record

ArticleBioMed research international2016

Characterization of Enhancing MS Lesions by Dynamic Texture Parameter Analysis of Dynamic Susceptibility Perfusion Imaging.

Rajeev K Verma, Johannes Slotboom, Cäcilia Locher, Mirjam R Heldner, Christian Weisstanner, Eugenio Abela, Frauke Kellner-Weldon, Martin Zbinden, Christian P Kamm, Roland Wiest

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Article in BioMed research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

10 authors.

Rajeev K VermaSupport Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland; Tiefenau Hospital, Institute of Radiology, Spital-Netz Bern, 3004 Bern, Switzerland.
Johannes SlotboomSupport Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Cäcilia LocherSupport Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Mirjam R HeldnerDepartment of Neurology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Christian WeisstannerSupport Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Eugenio AbelaDepartment of Neurology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Frauke Kellner-WeldonSupport Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Martin ZbindenSupport Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Christian P KammDepartment of Neurology, Inselspital, University of Bern, 3010 Bern, Switzerland.
Roland WiestSupport Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, 3010 Bern, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose of this study was to investigate statistical differences with MR perfusion imaging features that reflect the dynamics of Gadolinium-uptake in MS lesions using dynamic texture parameter analysis (DTPA).

methodsWe investigated 51 MS lesions (25 enhancing, 26 nonenhancing lesions) of 12 patients. Enhancing lesions (n = 25) were prestratified into enhancing lesions with increased permeability (EL+; n = 11) and enhancing lesions with subtle permeability (EL-; n = 14). Histogram-based feature maps were computed from the raw DSC-image time series and the corresponding texture parameters were analyzed during the inflow, outflow, and reperfusion time intervals.

resultsSignificant differences (p < 0.05) were found between EL+ and EL- and between EL+ and nonenhancing inactive lesions (NEL). Main effects between EL+ versus EL- and EL+ versus NEL were observed during reperfusion (mainly in mean and standard deviation (SD): EL+ versus EL- and EL+ versus NEL), while EL- and NEL differed only in their SD during outflow.

conclusionDTPA allows grading enhancing MS lesions according to their perfusion characteristics. Texture parameters of EL- were similar to NEL, while EL+ differed significantly from EL- and NEL. Dynamic texture analysis may thus be further investigated as noninvasive endogenous marker of lesion formation and restoration.

Indexed as

Magnetic Resonance ImagingAdultAgedContrast MediaDisease SusceptibilityFemaleGadoliniumHumansImage EnhancementImage Interpretation, Computer-AssistedMaleMiddle AgedMultiple SclerosisPerfusion ImagingContrast MediaGadolinium

Identifiers

PMID26885524
PMCPMC4738712

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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.