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Gray matter network reorganization in multiple sclerosis from 7-Tesla and 3-Tesla MRI data.

Authors :
Gonzalez-Escamilla G
Ciolac D
De Santis S
Radetz A
Fleischer V
Droby A
Roebroeck A
Meuth SG
Muthuraman M
Groppa S
Source :
Annals of clinical and translational neurology [Ann Clin Transl Neurol] 2020 Apr; Vol. 7 (4), pp. 543-553. Date of Electronic Publication: 2020 Apr 07.
Publication Year :
2020

Abstract

Objective: The objective of this study was to determine the ability of 7T-MRI for characterizing brain tissue integrity in early relapsing-remitting MS patients compared to conventional 3T-MRI and to investigate whether 7T-MRI improves the performance for detecting cortical gray matter neurodegeneration and its associated network reorganization dynamics.<br />Methods: Seven early relapsing-remitting MS patients and seven healthy individuals received MRI at 7T and 3T, whereas 30 and 40 healthy controls underwent separate 3T- and 7T-MRI sessions, respectively. Surface-based cortical thickness (CT) and gray-to-white contrast (GWc) measures were used to model morphometric networks, analyzed with graph theory by means of modularity, clustering coefficient, path length, and small-worldness.<br />Results: 7T-MRI had lower CT and higher GWc compared to 3T-MRI in MS. CT and GWc measures robustly differentiated MS from controls at 3T-MRI. 7T- and 3T-MRI showed high regional correspondence for CT (r = 0.72, P = 2e-78) and GWc (r = 0.83, P = 5.5e-121) in MS patients. MS CT and GWc morphometric networks at 7T-MRI showed higher modularity, clustering coefficient, and small-worldness than 3T, also compared to controls.<br />Interpretation: 7T-MRI allows to more precisely quantify morphometric alterations across the cortical mantle and captures more sensitively MS-related network reorganization. Our findings open new avenues to design more accurate studies quantifying brain tissue loss and test treatment effects on tissue repair.<br /> (© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association.)

Details

Language :
English
ISSN :
2328-9503
Volume :
7
Issue :
4
Database :
MEDLINE
Journal :
Annals of clinical and translational neurology
Publication Type :
Academic Journal
Accession number :
32255566
Full Text :
https://doi.org/10.1002/acn3.51029