Evidence map›Paper›PMID 25356412›Full record

ArticleAnnals of clinical and translational neurology2014

Advanced MRI unravels the nature of tissue alterations in early multiple sclerosis.

Guillaume Bonnier, Alexis Roche, David Romascano, Samanta Simioni, Djalel Meskaldji, David Rotzinger, Ying-Chia Lin, Gloria Menegaz, Myriam Schluep, Renaud Du Pasquier and 5 more

Open access · goldAbstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

42 citing papers in PubMed, 77 citations in OpenAlex.

  1. Simultaneous TMagnetic resonance in medicine · 2026
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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

15 authors at 7 institutions in 3 countries.

Guillaume BonnierAdvanced Clinical Imaging Technology group, Siemens Healthcare IM BM PI Lausanne, Switzerland ; Neuro-immunology and Laboratoire de recherché en neuroimagérie, Neurology Division, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne, Switzerland ; LTS5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland.
Alexis RocheAdvanced Clinical Imaging Technology group, Siemens Healthcare IM BM PI Lausanne, Switzerland ; LTS5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland ; Department of Radiology, Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne, Switzerland.
David RomascanoAdvanced Clinical Imaging Technology group, Siemens Healthcare IM BM PI Lausanne, Switzerland ; LTS5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland.
Samanta SimioniNeuro-immunology and Laboratoire de recherché en neuroimagérie, Neurology Division, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne, Switzerland.
Djalel MeskaldjiLTS5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland.
David RotzingerDepartment of Radiology, Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne, Switzerland.
Ying-Chia LinDepartment of Computer Science, University of Verona Verona, Italy.
Gloria MenegazDepartment of Computer Science, University of Verona Verona, Italy.
Myriam SchluepNeuro-immunology and Laboratoire de recherché en neuroimagérie, Neurology Division, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne, Switzerland.
Renaud Du PasquierNeuro-immunology and Laboratoire de recherché en neuroimagérie, Neurology Division, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne, Switzerland.
Tilman Johannes SumpfBiomedizinische NMR Forschungs GmbH, Max Planck Institute for Biophysical Chemistry Goettingen, Germany.
Jens FrahmBiomedizinische NMR Forschungs GmbH, Max Planck Institute for Biophysical Chemistry Goettingen, Germany.
Jean-Philippe ThiranLTS5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland.
Gunnar KruegerAdvanced Clinical Imaging Technology group, Siemens Healthcare IM BM PI Lausanne, Switzerland ; Healthcare Sector IM&WS S, Siemens Schweiz AG Renens, Switzerland.
Cristina GranzieraAdvanced Clinical Imaging Technology group, Siemens Healthcare IM BM PI Lausanne, Switzerland ; Neuro-immunology and Laboratoire de recherché en neuroimagérie, Neurology Division, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne Lausanne, Switzerland ; LTS5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland.
École Polytechnique Fédérale de Lausanne · CHMax Planck Institute for Biophysical Chemistry · DESiemens (Germany) · DESiemens (Switzerland) · CHUniversity Hospital of Lausanne · CHUniversity of Lausanne · CHUniversity of Verona · IT

Funding

Swiss National Science Foundation 131914
6 · The paper itself

Abstract

introductionIn patients with multiple sclerosis (MS), conventional magnetic resonance imaging (MRI) provides only limited insights into the nature of brain damage with modest clinic-radiological correlation. In this study, we applied recent advances in MRI techniques to study brain microstructural alterations in early relapsing-remitting MS (RRMS) patients with minor deficits. Further, we investigated the potential use of advanced MRI to predict functional performances in these patients.

methodsBrain relaxometry (T1, T2, T2*) and magnetization transfer MRI were performed at 3T in 36 RRMS patients and 18 healthy controls (HC). Multicontrast analysis was used to assess for microstructural alterations in normal-appearing (NA) tissue and lesions. A generalized linear model was computed to predict clinical performance in patients using multicontrast MRI data, conventional MRI measures as well as demographic and behavioral data as covariates.

resultsQuantitative T2 and T2* relaxometry were significantly increased in temporal normal-appearing white matter (NAWM) of patients compared to HC, indicating subtle microedema (P = 0.03 and 0.004). Furthermore, significant T1 and magnetization transfer ratio (MTR) variations in lesions (mean T1 z-score: 4.42 and mean MTR z-score: -4.09) suggested substantial tissue loss. Combinations of multicontrast and conventional MRI data significantly predicted cognitive fatigue (P = 0.01, Adj-R (2) = 0.4), attention (P = 0.0005, Adj-R (2) = 0.6), and disability (P = 0.03, Adj-R (2) = 0.4).

conclusionAdvanced MRI techniques at 3T, unraveled the nature of brain tissue damage in early MS and substantially improved clinical-radiological correlations in patients with minor deficits, as compared to conventional measures of disease.

Identifiers

PMID25356412
PMCPMC4184670
OpenAlexW1976006947

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.