Quantitative neuroimaging measures of myelin in the healthy brain and in multiple sclerosis

O’Muircheartaigh, Jonathan; Vavasour, Irene M.; Ljungberg, Emil; Li, David; Rauscher, Alexander; Levesque, Victoria; Garren, Hideki; Clayton, David; Tam, Roger; Traboulsee, Anthony; Kolind, Shannon

doi:10.1002/hbm.24510

Cited by 58 publications

(70 citation statements)

References 68 publications

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“…MT saturation is one of several MRI metrics commonly used to index myelin, including estimations of the myelin water fraction (MWF) (e.g., derived from multicomponent T1 and T2 relaxometry, Deoni, Rutt, Arun, Pierpaoli, & Jones, ), T1w/T2w ratio, or the longitudinal relaxation rate R1. While there is evidence for substantial correlations with histological measures of myelin for MT (Schmierer et al, ), MWF (Laule et al, ) and R1 (Stueber et al, ), imperfect correlations between these metrics suggest that each may be differentially sensitive to distinct aspects of tissue microstructure (Geeraert et al, ; Hagiwara et al, ; O'Muircheartaigh et al, ). Quantitative, or semi‐quantitative, MT related metrics are suggested as more robust measures of myelin compared to MWF (Dula, Gochberg, Valentine, Valentine, & Does, ) and T1w/T2w ratio (Hagiwara et al, ), as well as more specific to myelin compared to R1 and R2* (Callaghan et al, ), which show additional sensitivity to iron content.…”

Section: Discussionmentioning

confidence: 99%

White matter tract myelin maturation and its association with general psychopathology in adolescence and early adulthood

Vanes

Moutoussis

Ziegler

et al. 2019

Human Brain Mapping

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Adolescence is a time period associated with marked brain maturation that coincides with an enhanced risk for onset of psychiatric disorder. White matter tract myelination, a process that continues to unfold throughout adolescence, is reported to be abnormal in several psychiatric disorders. Here, we ask whether psychiatric vulnerability is linked to aberrant developmental myelination trajectories. We assessed a marker of myelin maturation, using magnetisation transfer (MT) imaging, in 10 major white matter tracts. We then investigated its relationship to the expression of a general psychopathology "p-factor" in a longitudinal analysis of 293 healthy participants between the ages of 14 and 24. We observed significant longitudinal MT increase across the full age spectrum in anterior thalamic radiation, hippocampal cingulum, dorsal cingulum and superior longitudinal fasciculus. MT increase in the inferior fronto-occipital fasciculus, inferior longitudinal fasciculus and uncinate fasciculus was pronounced in younger participants but levelled off during the transition into young adulthood. Crucially, longitudinal MT increase in dorsal cingulum and uncinate fasciculus decelerated as a function of mean p-factor scores over the study period. This suggests that an increased expression of psychopathology is closely linked to lower rates of myelin maturation in selective brain tracts over time. Impaired myelin growth in limbic association fibres may serve as a neural marker for emerging mental illness during the course of adolescence and early adulthood. K E Y W O R D S cingulum, general psychopathology, myelin, structural connectivity, uncinate fasciculus

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Section: Discussionmentioning

confidence: 99%

White matter tract myelin maturation and its association with general psychopathology in adolescence and early adulthood

Vanes

Moutoussis

Ziegler

et al. 2019

Human Brain Mapping

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“…A strong correlation between the MWF and independent measures of myelin has been demonstrated in various post-mortem studies (8)(9)(10). Over the past two decades, myelin water imaging (MWI) has been applied to mild traumatic brain injury (11), aging (12), spinal cord injury (13), neonates (14), and multiple sclerosis (15)(16)(17)(18), among others. The human brain's white matter is highly anisotropic.…”

Section: Introductionmentioning

confidence: 99%

Myelin water imaging depends on white matter fiber orientation in the human brain

Birkl

Doucette

Fan

et al. 2020

Preprint

Self Cite

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The multiexponential T 2 decay of the magnetic resonance imaging (MRI) signal from cerebral white matter can be separated into short components sensitive to myelin water and long components related to intra-and extracellular water. In this study we investigated to what degree the myelin water fraction (MWF) depends on the angle between white matter fibers and the main magnetic filed. Maps of MWF were acquired using multi echo CPMG and GRASE sequences. The CPMG sequence was acquired with a TR of 1073 ms, 1500 ms and 2000 ms. The fiber orientation was mapped with diffusion tensor imaging. By angle-wise pooling the voxels across the brain's white matter, an orientation dependent MWF curve was generated. We found that MWF varied between 25% and 35% across different fiber orientations. The orientation dependency of the MWF is characterized by a dipole-dipole interaction model. Furthermore, the selection of the TR influences the orientation dependent and global white matter MWF. White matter fiber orientation induces a strong systematic bias on the estimation of MWF. This finding has important implications for future research and the interpretation of MWI results in previously published studies.myelin water imaging | fiber orientation | white matter | magic angle | brain | quantitative MRI MethodsEight healthy volunteers (3 female, 5 male) with a mean age of 26 years (age range = 21 -33 years) and without any history of neurological disorder participated in this study, which was approved by the University of British Columbia Clinical Research Ethics Board. All volunteers gave written informed consent. MR imaging was performed on a 3 T MR system (Ingenia Elition, Philips Medical Systems, Best, The Netherlands) using a 32-channel SENSE head coil. MRI acquisition.A 3D T1 weighted sequence with echo time (TE) = 4.9 ms, TR = 9.8 ms, flip angle = 8°, a resolution of 0.8 x 0.8 x 0.8 mm 3 , a compressed SENSE (CS) factor of 3.6 and acquisition time of 5:50 min was acquired for anatomical overview. CS is a combination of compressed sensing (35,36) and SENSE (37). For the calculation of fiber orientation a DTI sequence with TE = 60 ms, TR = 4111 ms, b-value = 700 s/mm 2 , 60 diffusion directions, a resolution of 2.3 x 2.3 x 2.4 mm 3 , multi band factor 2 (38), SENSE factor 2.1 and

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“…In the theory section we propose a framework that relates MRI measurements of averages 74 of microstructure features to single axon conduction models, in order to predict white 75 matter conduction in vivo. For this purpose, we first identify a relevant axon model, and 76 the essential parameters in the model (section 2.1). Then, we describe the available qMRI 77 parameters that can be used to estimate those model parameters (section 2.2).…”

Section: Theorypredicting Conduction Latencies 73mentioning

confidence: 99%

“…Therefore, some of these methods require calibration, and/or may provide a poor estimate 168 of MVF in tissue that is not healthy white matter tissue (63,70,76). The myelin water 169 fraction is arguably the only specific MVF MRI measurement (67), yet it is currently hard 170 to measure in clinical scanners which often comes with a reduced signal to noise ratio 171 (SNR).…”

Section: Diffusion and Axon Properties 137mentioning

confidence: 99%

Modelling conduction delays in the corpus callosum using MRI-measured g-ratio

Berman

Filo

Mezer

2018

Preprint

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Conduction of action potentials along myelinated axons is affected by their structural features, such as the axonal g-ratio, the ratio between the inner and outer diameters of the myelin sheath surrounding the axon. The effect of g-ratio variance on conduction properties has been quantitatively evaluated using single-axon models. It has recently become possible to estimate a g-ratio weighted measurement in vivo using quantitative MRI. Nevertheless, it is still unclear whether the variance in the g-ratio in the healthy human brain leads to significant differences in conduction velocity. In this work we tested whether the g-ratio MRI measurement can be used to predict conduction delays in the corpus callosum.We present a novel framework in which the structural properties of fibers (i.e. length and g-ratio, measured using MRI), are incorporated in a biophysical model of axon conduction, to predict conduction delays of long-range white matter fibers. We applied this framework to the corpus callosum, and found conduction delay estimates that are compatible with previously estimated values of conduction delays. We account for the variance in the velocity given the axon diameter distribution in the splenium, mid-body and genu, to further compare the fibers within the corpus callosum.Conduction delays have been suggested to increase with age. Therefore, we investigated whether there are differences in the g-ratio and the fiber length between young and old adults, and whether this leads to a difference in conduction speed and delays. We found small but significant differences between the predicted delays of the two groups in the motor fibers of the corpus callosum. We also found that the motor fibers of the corpus callosum have the fastest conduction estimates. Using the axon diameter distributions, we found that the occipital fibers have the slowest estimations, while the frontal and motor fiber tracts have similar estimates.Our study provides a framework for predicting conduction latencies in vivo. The framework could have major implications for future studies of white matter diseases and large range network computations. Our results highlight the need for improving additional in vivo measurements of white matter microstructure.

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Quantitative neuroimaging measures of myelin in the healthy brain and in multiple sclerosis

Cited by 58 publications

References 68 publications

White matter tract myelin maturation and its association with general psychopathology in adolescence and early adulthood

White matter tract myelin maturation and its association with general psychopathology in adolescence and early adulthood

Myelin water imaging depends on white matter fiber orientation in the human brain

Modelling conduction delays in the corpus callosum using MRI-measured g-ratio

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