Journal
HUMAN BRAIN MAPPING
Volume 40, Issue 7, Pages 2104-2116Publisher
WILEY
DOI: 10.1002/hbm.24510
Keywords
individual differences; magnetization transfer ratio; multiple sclerosis; myelin; myelin water imaging; quantitative MRI; relaxometry
Funding
- Royal Society [206675/Z/17/Z]
- Wellcome Trust/EPSRC Centre for Medical Engineering [WT 203148/Z/16/Z]
- F. Hoffman-La Roche AG
- Genentech
- F. Hoffmann La Roche
- Sanofi Genzyme
- Milan & Maureen Ilich Foundation
- Michael Smith Foundation for Health Research
- Chugai
- Roche
- Novartis
- Genzyme
- Biogen
- General Electric (GE) Healthcare
- National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust
- King's College London
- Canada Research Chairs
- Canadian Institute of Health Research
- Multiple Sclerosis Society of Canada
- Academy of Health Care Learning
- Biogen-Idec
- Consortium of MS Centers
- Sanofi-Genzyme
- Teva
- Merck-Serono
- Wellcome Trust
- MRC [MR/N026063/1] Funding Source: UKRI
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Quantitative magnetic resonance imaging (MRI) techniques have been developed as imaging biomarkers, aiming to improve the specificity of MRI to underlying pathology compared to conventional weighted MRI. For assessing the integrity of white matter (WM), myelin, in particular, several techniques have been proposed and investigated individually. However, comparisons between these methods are lacking. In this study, we compared four established myelin-sensitive MRI techniques in 56 patients with relapsing-remitting multiple sclerosis (MS) and 38 healthy controls. We used T2-relaxation with combined GRadient And Spin Echoes (GRASE) to measure myelin water fraction (MWF-G), multi-component driven equilibrium single pulse observation of T-1 and T-2 (mcDESPOT) to measure MWF-D, magnetization-transfer imaging to measure magnetization-transfer ratio (MTR), and T-1 relaxation to measure quantitative T-1 (qT(1)). Using voxelwise Spearman correlations, we tested the correspondence of methods throughout the brain. All four methods showed associations that varied across tissue types; the highest correlations were found between MWF-D and qT(1) (median rho across tissue classes 0.8) and MWF-G and MWF-D (median rho = 0.59). In eight WM tracts, all measures showed differences (p < 0.05) between MS normal-appearing WM and healthy control WM, with qT1 showing the highest number of different regions (8), followed by MWF-D and MTR (6), and MWF-G (n = 4). Comparing the methods in terms of their statistical sensitivity to MS lesions in WM, MWF-D demonstrated the best accuracy (p < 0.05, after multiple comparison correction). To aid future power analysis, we provide the average and standard deviation volumes of the four techniques, estimated from the healthy control sample.
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