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Updated: Jan 30, 2026

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
Published on: July 19, 2019
Quantitative neuroimaging measures of myelin in the healthy brain and in multiple sclerosis
Jonathan O'Muircheartaigh1,2,3,4, Irene Vavasour5, Emil Ljungberg3
1Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, United Kingdom.
Abstract:
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 T1 and T2 (mcDESPOT) to measure MWF-D, magnetization-transfer imaging to measure magnetization-transfer ratio (MTR), and T1 relaxation to measure quantitative T1 (qT1 ). 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 qT1 (median ρ across tissue classes 0.8) and MWF-G and MWF-D (median ρ = 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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