Gray Matter Alterations in Early and Late Relapsing-Remitting Multiple Sclerosis Evaluated with Synthetic Quantitative Magnetic Resonance Imaging.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
31 05 2019
Historique:
received: 23 10 2018
accepted: 21 05 2019
entrez: 1 6 2019
pubmed: 1 6 2019
medline: 31 10 2020
Statut: epublish

Résumé

Extensive gray matter (GM) involvement has been demonstrated in multiple sclerosis (MS) patients. This study was aimed to identify GM alterations in relapsing-remitting MS (RRMS) patients using synthetic quantitative MRI (qMRI). We assessed myelin volume fraction (MVF) in each voxel on the basis of R1 and R2 relaxation rates and proton density in 14 early and 28 late (disease duration ≤5 and >5 years, respectively) RRMS patients, and 15 healthy controls (HCs). The MVF and myelin volumes of GM (GM-MyVol) were compared between groups using GM-based spatial statistics (GBSS) and the Kruskal-Wallis test, respectively. Correlations between MVF or GM-MyVol and disease duration or expanded disability status scale were also evaluated. RRMS patients showed a lower MVF than HCs, predominantly in the limbic and para-limbic areas, with more extensive areas noted in late RRMS patients. Late-RRMS patients had the smallest GM-MyVol (20.44 mL; early RRMS, 22.77 mL; HCs, 23.36 mL). Furthermore, the GM-MyVol in the RRMS group was inversely correlated with disease duration (r = -0.43, p = 0.005). In conclusion, the MVF and MyVol obtained by synthetic qMRI can be used to evaluate GM differences in RRMS patients.

Identifiants

pubmed: 31148572
doi: 10.1038/s41598-019-44615-3
pii: 10.1038/s41598-019-44615-3
pmc: PMC6544650
doi:

Substances chimiques

Protons 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

8147

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Auteurs

Christina Andica (C)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.

Akifumi Hagiwara (A)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan. a-hagiwara@juntendo.ac.jp.
Department of Radiology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan. a-hagiwara@juntendo.ac.jp.

Koji Kamagata (K)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.

Kazumasa Yokoyama (K)

Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan.

Keigo Shimoji (K)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Department of Radiology, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan.

Asami Saito (A)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.

Yuki Takenaka (Y)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan.

Misaki Nakazawa (M)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.

Masaaki Hori (M)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.

Julien Cohen-Adad (J)

Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.
Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, Quebec, Canada.

Mariko Yoshida Takemura (MY)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.

Nobutaka Hattori (N)

Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan.

Shigeki Aoki (S)

Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.

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