Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis.


Journal

NeuroImage. Clinical
ISSN: 2213-1582
Titre abrégé: Neuroimage Clin
Pays: Netherlands
ID NLM: 101597070

Informations de publication

Date de publication:
2019
Historique:
received: 29 01 2019
revised: 23 04 2019
accepted: 25 05 2019
pubmed: 9 6 2019
medline: 26 6 2020
entrez: 9 6 2019
Statut: ppublish

Résumé

Conventional MRI is not sensitive to many pathological processes underpinning multiple sclerosis (MS) ongoing in normal appearing brain tissue (NABT). Quantitative MRI (qMRI) and a multiparameter mapping (MPM) protocol are used to simultaneously quantify magnetization transfer (MT) saturation, transverse relaxation rate R2* (1/T2*) and longitudinal relaxation rate R1 (1/T1), and assess differences in NABT microstructure between MS patients and healthy controls (HC). This prospective cross-sectional study involves 36 MS patients (21 females, 15 males; age range 22-63 years; 15 relapsing-remitting MS - RRMS; 21 primary or secondary progressive MS - PMS) and 36 age-matched HC (20 females, 16 males); age range 21-61 years). The qMRI maps are computed and segmented in lesions and 3 normal appearing cerebral tissue classes: normal appearing cortical grey matter (NACGM), normal appearing deep grey matter (NADGM), normal appearing white matter (NAWM). Individual median values are extracted for each tissue class and MR parameter. MANOVAs and stepwise regressions assess differences between patients and HC. MS patients are characterized by a decrease in MT, R2* and R1 within NACGM (p < .0001) and NAWM (p < .0001). In NADGM, MT decreases (p < .0001) but R2* and R1 remain normal. These observations tend to be more pronounced in PMS. Quantitative MRI parameters are independent predictors of clinical status: EDSS is significantly related to R1 in NACGM and R2* in NADGM; the latter also predicts motor score. Cognitive score is best predicted by MT parameter within lesions. Multiparametric data of brain microstructure concord with the literature, predict clinical performance and suggest a diffuse reduction in myelin and/or iron content within NABT of MS patients.

Identifiants

pubmed: 31176293
pii: S2213-1582(19)30229-3
doi: 10.1016/j.nicl.2019.101879
pmc: PMC6555891
pii:
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

101879

Informations de copyright

Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

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Auteurs

Emilie Lommers (E)

GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium. Electronic address: elommers@chuliege.be.

Jessica Simon (J)

Psychology and Neurosciences of Cognition Research Unit, University of Liège, Belgium.

Gilles Reuter (G)

GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Neurosurgery Department, CHU Liège, Belgium.

Gaël Delrue (G)

Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium.

Dominique Dive (D)

Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium.

Christian Degueldre (C)

GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium.

Evelyne Balteau (E)

GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium.

Christophe Phillips (C)

GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; GIGA - in silico Medicine, University of Liège, Liège, Belgium.

Pierre Maquet (P)

GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium.

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