Rapid whole cerebrum myelin water imaging using a 3D GRASE sequence

Inherent spatial structure in myelin water fraction maps

Myelin water fraction (MWF) images in brain tend to be spatially noisy with unknown or no apparent spatial patterns structure, so values are therefore typically averaged over large white matter (WM) volumes. We investigated the existence of an inherent spatial structure in MWF maps and explored the benefits of examining MWF values along diffusion tensor imaging (DTI)-derived white matter tracts. We compared spatial anisotropy between MWF and the more widely-used fractional anisotropy (FA) measure. Sixteen major white matter fibre bundles were extracted based on DTI data from 41 healthy subjects. MWF coefficients of variation (CoV) were computed in sub-segments along each fibre tract and compared to MWF CoVs from the surrounding "tubes" - i.e. voxels just exterior to the tract - of each segment. We further assessed the consistency of the MWF along fibre bundles across subjects and investigated the benefit of examining MWF values in sections along each fibre bundle rather than integrating over the whole tract. CoVs of MWF and FA were lower in fibre bundles compared to their enclosing tubes in all investigated tracts. Both measures possessed a spatial gradient of CoV that was smaller aligned along, compared to perpendicular to, the fibre bundles. All WM tracts showed MWF profiles along their trajectory that were consistent across subjects and were more accurate than the mean overall fibre MWF value in estimating ages of the subjects. We conclude that, although less obvious visually, the spatial MWF distribution in white matter consistently follows a distinct pattern along underlying fibre bundles across subjects. Assessing MWF in sections along white matter tracts may provide a sensitive and robust way to assess myelin across subjects.

Quantitative age-dependent differences in human brainstem myelination assessed using high-resolution magnetic resonance mapping

Previous in-vivo magnetic resonance imaging (MRI)-based studies of age-related differences in the human brainstem have focused on volumetric morphometry. These investigations have provided pivotal insights into regional brainstem atrophy but have not addressed microstructural age differences. However, growing evidence indicates the sensitivity of quantitative MRI to microstructural tissue changes in the brain. These studies have largely focused on the cerebrum, with very few MR investigations addressing age-dependent differences in the brainstem, in spite of its central role in the regulation of vital functions. Several studies indicate early brainstem alterations in a myriad of neurodegenerative diseases and dementias. The paucity of MR-focused investigations is likely due in part to the challenges imposed by the small structural scale of the brainstem itself as well as of substructures within, requiring accurate high spatial resolution imaging studies. In this work, we applied our recently developed approach to high-resolution myelin water fraction (MWF) mapping, a proxy for myelin content, to investigate myelin differences with normal aging within the brainstem. In this cross-sectional investigation, we studied a large cohort (n = 125) of cognitively unimpaired participants spanning a wide age range (21-94 years) and found a decrease in myelination with age in most brainstem regions studied, with several regions exhibiting a quadratic association between myelin and age. We believe that this study is the first investigation of MWF differences with normative aging in the adult brainstem. Further, our results provide reference MWF values.

Myelin Water Atlas: A Template for Myelin Distribution in the Brain

BACKGROUND AND PURPOSE

Myelin water imaging (MWI) is a magnetic resonance imaging technique that quantifies myelin in-vivo. Although MWI has been extensively applied to study myelin-related diseases in groups, clinical use in individual patients is challenging mainly due to population heterogeneity. The purpose of this study was twofold: (1) create a normative brain myelin water atlas depicting the population mean and regional variability of myelin content; and (2) apply the myelin atlas to assess the degree of demyelination in individuals with multiple sclerosis (MS).

METHODS

3T MWI was performed on 50 healthy adults (25 M/25 F, mean age 25 years [range 17-42 years]). The myelin water atlas was created by averaging coregistered myelin water fraction (MWF) maps from all healthy individuals. To illustrate the preliminary utility of the atlas, white matter (WM) regional MWF variations were evaluated and voxel-wise z-score maps (z < -1.96) from the MWI of three MS participants were produced to assess individually the degree of demyelination.

RESULTS

The myelin water atlas demonstrated significant MWF variation across control WM. No significant MWF differences were found between male and female healthy participants. MS z-score maps revealed diffuse regions of demyelination in the two participants with Expanded Disability Status Scale (EDSS) = 2.0 but not in the participant with EDSS = 0.

CONCLUSIONS

The myelin water atlas can be used as a reference (URL: https://sourceforge.net/projects/myelin-water-atlas/) to demonstrate areas of demyelination in individual MS participants. Future studies will expand the atlas age range, account for education, and other variables that may affect myelination.

The role of iron and myelin in orientation dependent R2* of white matter

Brain myelin and iron content are important parameters in neurodegenerative diseases such as multiple sclerosis (MS). Both myelin and iron content influence the brain's R₂^* relaxation rate. However, their quantification based on R₂^* maps requires a realistic tissue model that can be fitted to the measured data. In structures with low myelin content, such as deep gray matter, R₂^* shows a linear increase with increasing iron content. In white matter, R₂^* is not only affected by iron and myelin but also by the orientation of the myelinated axons with respect to the external magnetic field. Here, we propose a numerical model which incorporates iron and myelin, as well as fibre orientation, to simulate R₂^* decay in white matter. Applying our model to fibre orientation-dependent in vivo R₂^* data, we are able to determine a unique solution of myelin and iron content in global white matter. We determine an averaged myelin volume fraction of 16.02 ± 2.07% in non-lesional white matter of patients with MS, 17.32 ± 2.20% in matched healthy controls, and 18.19 ± 2.98% in healthy siblings of patients with MS. Averaged iron content was 35.6 ± 8.9 mg/kg tissue in patients, 43.1 ± 8.3 mg/kg in controls, and 47.8 ± 8.2 mg/kg in siblings. All differences in iron content between groups were significant, while the difference in myelin content between MS patients and the siblings of MS patients was significant. In conclusion, we demonstrate that a model that combines myelin-induced orientation-dependent and iron-induced orientation-independent components is able to fit in vivo R₂^* data.

Developing therapeutic strategies to promote myelin repair in multiple sclerosis

Introduction: Approved disease-modifying therapies for multiple sclerosis (MS) lessen inflammatory disease activity that causes relapses and MRI lesions. However, chronic inflammation and demyelination lead to axonal degeneration and neuronal loss, for which there currently is no effective treatment. There has been increasing interest in developing repair-promoting strategies, but there are important unanswered questions regarding the mechanisms and appropriate methods to evaluate these treatments. Areas covered: The rationale for remyelinating agents in MS is discussed, with an overview of both myelin physiology and endogenous repair mechanisms. This is followed by a discussion of the identification and development of potential remyelinating drugs. Potential biomarkers of remyelination are reviewed, including considerations regarding measuring remyelination in clinical trials. Information and data were obtained from a search of recent literature through PubMed. Peer-reviewed original articles and review articles were included. Expert opinion: There are several obstacles to the translation of potential remyelinating agents to clinical trials, particularly uncertainty regarding the most appropriate study population and method to monitor remyelination. Refinements in clinical trial design and outcome measurement, potentially via advanced imaging techniques, are needed to optimize detection of repair in patients with MS.

Rapid myelin water imaging for the assessment of cervical spinal cord myelin damage

Background

Rapid myelin water imaging (MWI) using a combined gradient and spin echo (GRASE) sequence can produce myelin specific metrics for the human brain. Spinal cord MWI could be similarly useful, but technical challenges have hindered routine application. GRASE rapid MWI was recently successfully implemented for imaging of healthy cervical spinal cord and may complement other advanced imaging methods, such as diffusion tensor imaging (DTI) and quantitative T₁ (qT₁).

Objective

To demonstrate the feasibility of cervical cord GRASE rapid MWI in multiple sclerosis (MS), primary lateral sclerosis (PLS) and neuromyelitis optica spectrum disorder (NMO), with comparison to DTI and qT₁ metrics.

Methods

GRASE MWI, DTI and qT₁ data were acquired in 2 PLS, 1 relapsing-remitting MS (RRMS), 1 primary-progressive MS (PPMS) and 2 NMO subjects, as well as 6 age (±3 yrs) and sex matched healthy controls (HC). Internal cord structure guided template registrations, used for region of interest (ROI) analysis. Z score maps were calculated for the difference between disease subject and mean HC metric values.

Results

PLS subjects had low myelin water fraction (MWF) in the lateral funiculi compared to HC. RRMS subject MWF was heterogeneous within the cord. The PPMS subject showed no trends in ROI results but had a region of low MWF Z score corresponding to a focal lesion. The NMO subject with a longitudinally extensive transverse myelitis lesion had low values for whole cord mean MWF of 12.8% compared to 24.3% (standard deviation 2.2%) for HC. The NMO subject without lesions also had low MWF compared to HC. DTI and qT₁ metrics showed similar trends, corroborating the MWF results and providing complementary information.

Conclusion

GRASE is sufficiently sensitive to detect decreased myelin within MS spinal cord plaques, NMO lesions, and PLS diffuse spinal cord injury. Decreased MWF in PLS is consistent with demyelination secondary to motor neuron degeneration. GRASE MWI is a feasible method for rapid assessment of myelin content in the cervical spinal cord and provides complementary information to that of DTI and qT₁ measures.

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Downstream myelin changes in motor tracts of primary lateral sclerosis spinal cord.

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Low myelin water fraction in multiple sclerosis and neuromyelitis optica cord lesions.

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Diffuse demyelination evidence in neuromyelitis optica normal-appearing white matter.

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Myelin water imaging provides complementary information to diffusion and T₁ metrics.

The influence of brain iron on myelin water imaging

With myelin playing a vital role in normal brain integrity and function and thus in various neurological disorders, myelin sensitive magnetic resonance imaging (MRI) techniques are of great importance. In particular, multi-exponential T₂ relaxation was shown to be highly sensitive to myelin. The myelin water imaging (MWI) technique allows to separate the T₂ decay into short components, specific to myelin water, and long components reflecting the intra- and extracellular water. The myelin water fraction (MWF) is the ratio of the short components to all components. In the brain's white matter (WM), myelin and iron are closely linked via the presence of iron in the myelin generating oligodendrocytes. Iron is known to decrease T₂ relaxation times and may therefore mimic myelin. In this study, we investigated if variations in WM iron content can lead to apparent MWF changes. We performed MWI in post mortem human brain tissue prior and after chemical iron extraction. Histology for iron and myelin confirmed a decrease in iron content and no change in myelin content after iron extraction. In MRI, iron extraction lead to a decrease in MWF by 26%-28% in WM. Thus, a change in MWF does not necessarily reflect a change in myelin content. This observation has important implications for the interpretation of MWI findings in previously published studies and future research.

Iron, Myelin, and the Brain: Neuroimaging Meets Neurobiology

Although iron is crucial for neuronal functioning, many aspects of cerebral iron biology await clarification. The ability to quantify specific iron forms in the living brain would open new avenues for diagnosis, therapeutic monitoring, and understanding pathogenesis of diseases. A modality that allows assessment of brain tissue composition in vivo, in particular of iron deposits or myelin content on a submillimeter spatial scale, is magnetic resonance imaging (MRI). Multimodal strategies combining MRI with complementary analytical techniques ex vivo have emerged, which may lead to improved specificity. Interdisciplinary collaborations will be key to advance beyond simple correlative analyses in the biological interpretation of MRI data and to gain deeper insights into key factors leading to iron accumulation and/or redistribution associated with neurodegeneration.

Myelin Water Fraction Imaging of the Brain in Children with Prenatal Alcohol Exposure

BACKGROUND

Prenatal alcohol exposure (PAE) is linked to alterations of cerebral white matter, including volume and nonspecific diffusion magnetic resonance imaging (MRI) indices of microstructure in humans. Some animal models of PAE have demonstrated myelination deficiencies, but myelin levels have not yet been evaluated in individuals with PAE. Multiecho T₂ MRI offers a quantitative method to estimate myelin water fraction (MWF; related to myelin content) noninvasively, which was used here to evaluate brain myelination in children with PAE.

METHODS

Participants with PAE (n = 10, 6 females, mean age 13.9 years, range 7 to 18 years) and controls (n = 14, 11 females, mean age 13.2 years, range 9 to 16 years) underwent 3T MRI of the brain. T₂ images (15 minutes acquisition for 32 echoes) were used to create MWF maps from which mean MWF was measured in 12 regions of interest (ROIs) including 8 in white matter and 4 in deep gray matter.

RESULTS

As expected, across the combined sample, MWF was highest for major white matter tracts such as the internal capsule and genu/splenium of the corpus callosum (10 to 18%) while the caudate and putamen had MWF less than 5%. Mean MWF was similar across 11/12 brain white and gray matter regions for the PAE and control groups (L/R internal capsule, major forceps, putamen, caudate nucleus, L minor forceps, genu and splenium of corpus callosum). In the PAE group, MWF was positively correlated with age in the genu of corpus callosum and right minor forceps, notably 2 frontal tracts.

CONCLUSIONS

Given comparable MRI-derived myelination fraction measures in PAE relative to controls, white matter alterations shown in other imaging studies, such as diffusion tensor imaging, may reflect microstructural anomalies related to axon caliber and density.

Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures

Various MRI techniques, including myelin water imaging, T1w/T2w ratio mapping and diffusion-based imaging can be used to characterize tissue microstructure. However, surprisingly few studies have examined the degree to which these MRI measures are related within and between various brain regions. Therefore, whole-brain MRI scans were acquired from 31 neurologically-healthy participants to empirically measure and compare myelin water fraction (MWF), T1w/T2w ratio, fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) in 25 bilateral (10 grey matter; 15 white matter) regions-of-interest (ROIs). Except for RD vs. T1w/T2w, MD vs. T1w/T2w, moderately significant to highly significant correlations (p < 0.001) were found between each of the other measures across all 25 brain structures [T1w/T2w vs. MWF (Pearson r = 0.33, Spearman ρ = 0.31), FA vs. MWF (r = 0.73, ρ = 0.75), FA vs. T1w/T2w (r = 0.25, ρ = 0.22), MD vs. AD (r = 0.57, ρ = 0.58), MD vs. RD (r = 0.64, ρ = 0.61), AD vs. MWF (r = 0.43, ρ = 0.36), RD vs. MWF (r = −0.49, ρ = −0.62), MD vs. MWF (r = −0.22, ρ = −0.29), RD vs. FA (r = −0.62, ρ = −0.75) and MD vs. FA (r = −0.22, ρ = −0.18)]. However, while all six MRI measures were correlated with each other across all structures, there were large intra-ROI and inter-ROI differences (i.e., with no one measure consistently producing the highest or lowest values). This suggests that each quantitative MRI measure provides unique, and potentially complimentary, information about underlying brain tissues – with each metric offering unique sensitivity/specificity tradeoffs to different microstructural properties (e.g., myelin content, tissue density, etc.).

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

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.

MR fingerprinting enables quantitative measures of brain tissue relaxation times and myelin water fraction in the first five years of life

Quantitative assessments of normative brain development using MRI are of critical importance to gain insights into healthy neurodevelopment. However, quantitative MR imaging poses significant technical challenges and requires prohibitively long acquisition times, making it impractical for pediatric imaging. This is particularly relevant for healthy subjects, where imaging under sedation is not clinically indicated. MR Fingerprinting (MRF), a novel MR imaging framework, provides rapid, efficient, and simultaneous quantification of multiple tissue properties. In this study, a 2D MR Fingerprinting method was developed that achieves a spatial resolution of 1 × 1 × 3 mm³ with rapid and simultaneous quantification of T₁, T₂ and myelin water fraction (MWF). Phantom experiments demonstrated that accurate measurements of T₁ and T₂ relaxation times were achieved over a wide range of T₁ and T₂ values. MRF images were acquired cross-sectionally from 28 typically developing children, 0 to five years old, who were enrolled in the UNC/UMN Baby Connectome Project. Differences associated with age of R1 (=1/T₁), R2 (=1/T₂) and MWF were obtained from several predefined white matter regions. Both R1 and R2 exhibit a marked increase until ∼20 months of age, followed by a slower increase for all WM regions. In contrast, the MWF remains at a negligible level until ∼6 months of age for all predefined ROIs and gradually increases afterwards. Depending on the brain region, rapid increases are observed between 6 and 12 months to 6-18 months, followed by a slower pace of increase in MWF. Neither relaxivities nor MWF were significantly different between the left and right hemispheres. However, regional differences in age-related R1 and MWF measures were observed across different white matter regions. In conclusion, our results demonstrate that the MRF technique holds great potential for multi-parametric assessments of normative brain development in early childhood.

Inter-Vendor Reproducibility of Myelin Water Imaging Using a 3D Gradient and Spin Echo Sequence

Myelin water imaging can be achieved using multicomponent T₂ relaxation analysis to quantify in vivo measurement of myelin content, termed the myelin water fraction (MWF). Therefore, myelin water imaging can be a valuable tool to better understand the underlying white matter pathology in demyelinating diseases, such as multiple sclerosis. To apply myelin water imaging in multisite studies and clinical applications, it must be acquired in a clinically feasible scan time (less than 15 min) and be reproducible across sites and scanner vendors. Here, we assessed the reproducibility of MWF measurements in regional and global white matter in 10 healthy human brains across two sites with two different 3 T magnetic resonance imaging scanner vendors (Philips and Siemens), using a 32-echo gradient and spin echo (GRASE) sequence. A strong correlation was found between the MWF measurements in the global white matter (Pearson's r = 0.91; p < 0.001) for all participants across the two sites. The mean intersite MWF coefficient of variation across participants was 2.77% in the global white matter and ranged from 4.47% (splenium of the corpus callosum) to 17.89% (genu of the corpus callosum) in white matter regions of interest. Bland-Altman analysis showed a good agreement in MWF measurements between the two sites with small bias of 0.002. Overall, MWF estimates were in good agreement across the two sites and scanner vendors. Our findings support the use of quantitative multi-echo T₂ relaxation metrics, such as the MWF, in multicenter studies and clinical trials to gain deeper understanding about the pathological processes resulting from the underlying disease progression in neurodegenerative diseases.

A new analysis approach for T2 relaxometry myelin water quantification: Orthogonal Matching Pursuit

Purpose

In vivo myelin quantification can provide valuable noninvasive information on neuronal maturation and development, as well as insights into neurological disorders. Multiexponential analysis of multiecho T₂ relaxation is a powerful and widely applied method for the quantification of the myelin water fraction (MWF). In recent literature, the MWF is most commonly estimated using a regularized nonnegative least squares algorithm.

Methods

The orthogonal matching pursuit algorithm is proposed as an alternative method for the estimation of the MWF. The orthogonal matching pursuit is a greedy sparse reconstruction algorithm with a low computation complexity. For validation, both methods are compared to a ground truth using numerical simulations and a phantom model using comparable computation times. The numerical simulations were used to measure the theoretical errors, as well as the effects of varying the SNR, strength of the regularization, and resolution of the basis set. Additionally, a phantom model was used to estimate the performance of the 2 methods while including errors occurring due to the MR measurement. Lastly, 4 healthy subjects were scanned to evaluate the in vivo performance.

Results

The results in simulations and phantoms demonstrate that the MWFs determined with the orthogonal matching pursuit are 1.7 times more accurate as compared to the nonnegative least squares, with a comparable precision. The remaining bias of the MWF is shown to be related to the regularization of the nonnegative least squares algorithm and the Rician noise present in magnitude MR images.

Conclusion

The orthogonal matching pursuit algorithm provides a more accurate alternative for T₂ relaxometry myelin water quantification.

On the accuracy and precision of PLANET for multiparametric MRI using phase-cycled bSSFP imaging

Purpose

In this work we demonstrate how sequence parameter settings influence the accuracy and precision in T₁, T₂, and off‐resonance maps obtained with the PLANET method for a single‐component signal model. In addition, the performance of the method for the particular case of a two‐component relaxation model for white matter tissue was assessed.

Methods

Numerical simulations were performed to investigate the influence of sequence parameter settings on the accuracy and precision in the estimated parameters for a single‐component model, as well as for a two‐component white matter model. Phantom and in vivo experiments were performed for validation. In addition, the effects of Gibbs ringing were investigated.

Results

By making a proper choice for sequence parameter settings, accurate and precise parameter estimation can be achieved for a single‐component signal model over a wide range of relaxation times at realistic SNR levels. Due to the presence of a second myelin‐related signal component in white matter, an underestimation of approximately 30% in T₁ and T₂ was observed, predicted by simulations and confirmed by measurements. Gibbs ringing artifacts correction improved the precision and accuracy of the parameter estimates.

Conclusion

For a single‐component signal model there is a broad “sweet spot” of sequence parameter combinations for which a high accuracy and precision in the parameter estimates is achieved over a wide range of relaxation times. For a multicomponent signal model, the single‐component PLANET reconstruction results in systematic errors in the parameter estimates as expected.

Age-Related Measurements of the Myelin Water Fraction derived from 3D multi-echo GRASE reflect Myelin Content of the Cerebral White Matter

Myelin Water Fraction (MWF) measurements derived from quantitative Myelin Water Imaging (MWI) may detect demyelinating changes of the cerebral white matter (WM) microstructure. Here, we investigated age-related alterations of the MWF in normal aging brains of healthy volunteers utilizing two fast and clinically feasible 3D gradient and spin echo (GRASE) MWI sequences with 3 mm and 5 mm isotropic voxel size. In 45 healthy subjects (age range: 18–79 years), distinct regions of interest (ROI) were defined in the cerebral WM including corticospinal tracts. For the 3 mm sequence, significant correlations of the mean MWF with age were found for most ROIs (r < −0.8 for WM ROIs; r = −0.55 for splenium of corpus callosum; r = −0.75 for genu of corpus callosum; p < 0.001 for all ROIs). Similar correlations with age were found for the ROIs of the 5 mm sequence. No significant correlations were found for the corticospinal tract and the occipital WM (p > 0.05). Mean MWF values obtained from the 3 mm and 5 mm sequences were strongly comparable. The applied 3D GRASE MWI sequences were found to be sensitive for age-dependent myelin changes of the cerebral WM microstructure. The reported MWF values might be of substantial use as reference for further investigations in patient studies.

Myelin Water Fraction Imaging Reveals Hemispheric Asymmetries in Human White Matter That Are Associated with Genetic Variation in PLP1

Myelination of axons in the central nervous system is critical for human cognition and behavior. The predominant protein in myelin is proteolipid protein-making PLP1, the gene that encodes for proteolipid protein, one of the primary candidate genes for white matter structure in the human brain. Here, we investigated the relation of genetic variation within PLP1 and white matter microstructure as assessed with myelin water fraction imaging, a neuroimaging technique that has the advantage over conventional diffusion tensor imaging in that it allows for a more direct assessment of myelin content. We observed significant asymmetries in myelin water fraction that were strongest and rightward in the parietal lobe. Importantly, these parietal myelin water fraction asymmetries were associated with genetic variation in PLP1. These findings support the assumption that genetic variation in PLP1 affects white matter myelination in the healthy human brain.

Myelin water imaging to detect demyelination and remyelination and its validation in pathology

Damage to myelin is a key feature of multiple sclerosis (MS) pathology. Magnetic resonance imaging (MRI) has revolutionized our ability to detect and monitor MS pathology in vivo. Proton density, T1 and T2 can provide qualitative contrast weightings that yield superb in vivo visualization of central nervous system tissue and have proved invaluable as diagnostic and patient management tools in MS. However, standard clinical MR methods are not specific to the types of tissue damage they visualize, and they cannot detect subtle abnormalities in tissue that appears otherwise normal on conventional MRIs. Myelin water imaging is an MR method that provides in vivo measurement of myelin. Histological validation work in both human brain and spinal cord tissue demonstrates a strong correlation between myelin water and staining for myelin, validating myelin water as a marker for myelin. Myelin water varies throughout the brain and spinal cord in healthy controls, and shows good intra- and inter-site reproducibility. MS plaques show variably decreased myelin water fraction, with older lesions demonstrating the greatest myelin loss. Longitudinal study of myelin water can provide insights into the dynamics of demyelination and remyelination in plaques. Normal appearing brain and spinal cord tissues show reduced myelin water, an abnormality which becomes progressively more evident over a timescale of years. Diffusely abnormal white matter, which is evident in 20%-25% of MS patients, also shows reduced myelin water both in vivo and postmortem, and appears to originate from a primary lipid abnormality with relative preservation of myelin proteins. Active research is ongoing in the quest to refine our ability to image myelin and its perturbations in MS and other disorders of the myelin sheath.

Pathological Insights From Quantitative Susceptibility Mapping and Diffusion Tensor Imaging in Ice Hockey Players Pre and Post-concussion

Myelin sensitive MRI techniques, such as diffusion tensor imaging and myelin water imaging, have previously been used to reveal changes in myelin after sports-related concussions. What is not clear from these studies, however, is how myelin is affected: whether it becomes degraded and possibly removed, or whether the myelin sheath loosens and becomes “decompacted”. Previously, our team revealed myelin specific changes in ice hockey players 2 weeks post-concussion using myelin water imaging. In that study, 45 subjects underwent a pre-season baseline scan, 11 of which sustained a concussion during play and received follow-up scans: eight were scanned within 3 days, 10 were scanned at 14 days, and nine were scanned at 60 days. In the current retrospective analysis, we used quantitative susceptibility mapping, along with the diffusion tensor imaging measures axial diffusivity and radial diffusivity, to investigate this myelin disruption. If sports-related concussive hits lead to myelin fragmentation in regions of lowered MWF, this should result in a measurable increase in magnetic susceptibility, due to the anisotropic myelin fragmenting into isotropic myelin debris, and the diamagnetic myelin tissue being removed, while no such changes should be expected if the myelin sheath simply loosens and becomes decompacted. An increase in radial diffusivity would likewise reveal myelin fragmentation, as myelin sheaths block water diffusion out of the axon, with little to no changes expected for myelin sheath loosening. Statistical analysis of the same voxels-of-interest that were found to have reduced myelin water fraction 2 weeks post-concussion, revealed no statistically significant changes in magnetic susceptibility, axial diffusivity, or radial diffusivity at any time-point post-concussion. This suggests that myelin water fraction changes are likely due to a loosening of the myelin sheath structure, as opposed to fragmentation and removal of myelin debris.

Use of the NESMA Filter to Improve Myelin Water Fraction Mapping with Brain MRI

BACKGROUND AND PURPOSE

Myelin water fraction (MWF) mapping permits direct visualization of myelination patterns in the developing brain and in pathology. MWF is conventionally measured through multiexponential T₂ analysis which is very sensitive to noise, leading to inaccuracies in derived MWF estimates. Although noise reduction filters may be applied during postprocessing, conventional filtering can introduce bias and obscure small structures and edges. Advanced nonblurring filters, while effective, exhibit a high level of complexity and the requirement for supervised implementation for optimal performance. The purpose of this paper is to demonstrate the ability of the recently introduced nonlocal estimation of multispectral magnitudes (NESMA) filter to greatly improve the determination of MWF parameter estimates from gradient and spin echo (GRASE) imaging data.

METHODS

We evaluated the performance of the NESMA filter for MWF mapping from clinical GRASE imaging data of the human brain, and compared the results to those calculated from unfiltered images. Numerical and in vivo analyses of the brains of three subjects, representing different ages, were conducted.

RESULTS

Our results demonstrated the potential of the NESMA filter to permit high-quality in vivo MWF mapping. Indeed, NESMA permits substantial reduction of random variation in derived MWF estimates while preserving accuracy and detail.

CONCLUSIONS

In vivo estimation of MWF in the human brain from GRASE imaging data was markedly improved through use of the NESMA filter. The use of NESMA may contribute to the goal of high-quality MWF mapping in clinically feasible imaging times.

Using 3D spatial correlations to improve the noise robustness of multi component analysis of 3D multi echo quantitative T2 relaxometry data

PURPOSE

We present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1⁺-inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone.

METHODS

Simulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al.) and our previously proposed 2D multi-slice spatial regularization spatial regularization approach. We also investigated whether the inter-sequence correlations and agreements improved as a result of the proposed approach. MWF-quantifications from two sequences, 3DNS-MESE vs 3DNS-gradient and spin echo (3DNS-GRASE), were compared for both reconstruction approaches to assess correlations and agreements between inter-sequence MWF-value pairs. MWF values from whole-brain data of six volunteers and two multiple sclerosis patients are being reported as well.

RESULTS

In comparison with competing approaches such as Prasloski's method or our previously proposed 2D multi-slice spatial regularization method, the proposed method showed better agreements with simulated truths using regression analyses and Bland-Altman analyses. For 3DNS-MESE data, MWF-maps reconstructed using the proposed algorithm provided better depictions of white matter structures in subcortical areas adjoining gray matter which agreed more closely with corresponding contrasts on T2-weighted images than MWF-maps reconstructed with the method by Prasloski et al. We also achieved a higher level of correlations and agreements between inter-sequence (3DNS-MESE vs 3DNS-GRASE) MWF-value pairs.

CONCLUSION

The proposed algorithm provides more noise-robust fits to T2-decay data and improves MWF-quantifications in white matter structures especially in the sub-cortical white matter and major white matter tract regions.

Microstructural correlates of 3D steady-state inhomogeneous magnetization transfer (ihMT) in the human brain white matter assessed by myelin water imaging and diffusion tensor imaging

PURPOSE

To compare the recently introduced inhomogeneous magnetization transfer (ihMT) technique with more established MRI techniques including myelin water imaging (MWI) and diffusion tensor imaging (DTI), and to evaluate the microstructural attributes correlating with this new contrast method in the human brain white matter.

METHODS

Eight adult healthy volunteers underwent T₁ -weighted, ihMT, MWI, and DTI imaging on a 3T human scanner. The ihMT ratio (ihMTR), myelin water fraction (MWF), fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and mean diffusivity (MD) values were calculated from different white matter tracts. The angle ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>θ</mml:mi></mml:math> ) between the directions of the principal eigenvector, as measured by DTI, and the main magnetic field was calculated for all voxels from various fiber tracts. The ihMTR was correlated with MWF and DTI metrics.

RESULTS

A strong correlation was found between ihMTR and MWF (ρ = 0.77, P < 0.0001). This was followed by moderate to weak correlations between ihMTR and DTI metrics: RD (ρ = -0.30, P < 0.0001), FA (ρ = 0.20, P < 0.0001), MD (ρ = -0.19, P < 0.0001), AD (ρ = 0.02, P < 0.0001). A strong correlation was found between ihMTR and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>θ</mml:mi></mml:math> (ρ = -0.541, P < 0.0001).

CONCLUSION

The strong correlation with myelin water imaging and its low coefficient of variation suggest that ihMT has the potential to become a new structural imaging marker of myelin. The substantial orientational dependence of ihMT should be taken into account when evaluating and quantitatively interpreting ihMT results.

Microstructural imaging in the spinal cord and validation strategies

In vivo histology using magnetic resonance imaging (MRI) is a newly emerging research field that aims to non-invasively characterize tissue microstructure. The implications of in vivo histology are many, from discovering novel biomarkers to studying human development, to providing tools for disease diagnosis and monitoring the effects of novel treatments on tissue. This review focuses on quantitative MRI (qMRI) techniques that are used to map spinal cord microstructure. Opening with a rationale for non-invasive imaging of the spinal cord, this article continues with a brief overview of the existing MRI techniques for axon and myelin imaging, followed by the specific challenges and potential solutions for acquiring and processing such data. The final part of this review focuses on histological validation, with suggested tissue preparation, acquisition and processing protocols for large-scale microscopy.

Can T1 w/T2 w ratio be used as a myelin-specific measure in subcortical structures? Comparisons between FSE-based T1 w/T2 w ratios, GRASE-based T1 w/T2 w ratios and multi-echo GRASE-based myelin water fractions

Given the growing popularity of T₁ -weighted/T₂ -weighted (T₁ w/T₂ w) ratio measurements, the objective of the current study was to evaluate the concordance between T₁ w/T₂ w ratios obtained using conventional fast spin echo (FSE) versus combined gradient and spin echo (GRASE) sequences for T₂ w image acquisition, and to compare the resulting T₁ w/T₂ w ratios with histologically validated myelin water fraction (MWF) measurements in several subcortical brain structures. In order to compare these measurements across a relatively wide range of myelin concentrations, whole-brain T₁ w magnetization prepared rapid acquisition gradient echo (MPRAGE), T₂ w FSE and three-dimensional multi-echo GRASE data were acquired from 10 participants with multiple sclerosis at 3 T. Then, after high-dimensional, non-linear warping, region of interest (ROI) analyses were performed to compare T₁ w/T₂ w ratios and MWF estimates (across participants and brain regions) in 11 bilateral white matter (WM) and four bilateral subcortical grey matter (SGM) structures extracted from the JHU_MNI_SS 'Eve' atlas. Although the GRASE sequence systematically underestimated T₁ w/T₂ w values compared to the FSE sequence (revealed by Bland-Altman and mountain plots), linear regressions across participants and ROIs revealed consistently high correlations between the two methods (r² = 0.62 for all ROIs, r² = 0.62 for WM structures and r² = 0.73 for SGM structures). However, correlations between either FSE-based or GRASE-based T₁ w/T₂ w ratios and MWFs were extremely low in WM structures (FSE-based, r² = 0.000020; GRASE-based, r² = 0.0014), low across all ROIs (FSE-based, r² = 0.053; GRASE-based, r² = 0.029) and moderate in SGM structures (FSE-based, r² = 0.20; GRASE-based, r² = 0.17). Overall, our findings indicated a high degree of correlation (but not equivalence) between FSE-based and GRASE-based T₁ w/T₂ w ratios, and low correlations between T₁ w/T₂ w ratios and MWFs. This suggests that the two T₁ w/T₂ w ratio approaches measure similar facets of subcortical tissue microstructure, whereas T₁ w/T₂ w ratios and MWFs appear to be sensitized to different microstructural properties. On this basis, we conclude that multi-echo GRASE sequences can be used in future studies to efficiently elucidate both general (T₁ w/T₂ w ratio) and myelin-specific (MWF) tissue characteristics.

Quantitative Ex Vivo MRI Changes due to Progressive Formalin Fixation in Whole Human Brain Specimens: Longitudinal Characterization of Diffusion, Relaxometry, and Myelin Water Fraction Measurements at 3T

Purpose

Postmortem MRI can be used to reveal important pathologies and establish radiology-pathology correlations. However, quantitative MRI values are altered by tissue fixation. Therefore, the purpose of this study was to investigate time-dependent effects of formalin fixation on MRI relaxometry (T₁ and T₂), diffusion tensor imaging (fractional anisotropy, FA; and mean diffusivity, MD), and myelin water fraction (MWF) measurements throughout intact human brain specimens.

Methods

Two whole, neurologically-healthy human brains were immersed in 10% formalin solution and scanned at 13 time points between 0 and 1,032 h. Whole-brain maps of longitudinal (T₁) and transverse (T₂) relaxation times, FA, MD, and MWF were generated at each time point to illustrate spatiotemporal changes, and region-of-interest analyses were then performed in eight brain structures to quantify temporal changes with progressive fixation.

Results

Although neither of the diffusion measures (FA nor MD) showed significant changes as a function of formalin fixation time, both T₁ and T₂-relaxation times significantly decreased, and MWF estimates significantly increased with progressive fixation until (and likely beyond) our final measurements were taken at 1,032 h.

Conclusion

These results suggest that T₁-relaxation, T₂-relaxation and MWF estimates must be performed quite early in the fixation process to avoid formalin-induced changes compared to in vivo values; and furthermore, that different ex vivo scans within an experiment must be acquired at consistent (albeit still early) fixation intervals to avoid fixative-related differences between samples. Conversely, ex vivo diffusion measures (FA and MD) appear to depend more on other factors (e.g., pulse sequence optimization, sample temperature, etc.).

Recent neuroimaging, neurophysiological, and neuropathological advances for the understanding of NPC

Niemann–Pick disease type C (NPC) is a rare autosomal recessive lysosomal storage disorder with extensive biological, molecular, and clinical heterogeneity. Recently, numerous studies have tried to shed light on the pathophysiology of the disease, highlighting possible disease pathways common to other neurodegenerative disorders, such as Alzheimer’s disease and frontotemporal dementia, and identifying possible candidate biomarkers for disease staging and response to treatment. Miglustat, which reversibly inhibits glycosphingolipid synthesis, has been licensed in the European Union and elsewhere for the treatment of NPC in both children and adults. A number of ongoing clinical trials might hold promise for the development of new treatments for NPC. The objective of the present work is to review and evaluate recent literature data in order to highlight the latest neuroimaging, neurophysiological, and neuropathological advances for the understanding of NPC pathophysiology. Furthermore, ongoing developments in disease-modifying treatments will be briefly discussed.

Inferring brain tissue composition and microstructure via MR relaxometry

MRI relaxometry is sensitive to a variety of tissue characteristics in a complex manner, which makes it both attractive and challenging for characterizing tissue. This article reviews the most common water proton relaxometry measures, T₁, T₂, and T₂^*, and reports on their development and current potential to probe the composition and microstructure of brain tissue. The development of these relaxometry measures is challenged by the need for suitably accurate tissue models, as well as robust acquisition and analysis methodologies. MRI relaxometry has been established as a tool for characterizing neural tissue, particular with respect to myelination, and the potential for further development exists.

Test-retest reliability of myelin imaging in the human spinal cord: Measurement errors versus region- and aging-induced variations

PURPOSE

To implement a statistical framework for assessing the precision of several quantitative MRI metrics sensitive to myelin in the human spinal cord: T1, Magnetization Transfer Ratio (MTR), saturation imposed by an off-resonance pulse (MTsat) and Macromolecular Tissue Volume (MTV).

METHODS

Thirty-three healthy subjects within two age groups (young, elderly) were scanned at 3T. Among them, 16 underwent the protocol twice to assess repeatability. Statistical reliability indexes such as the Minimal Detectable Change (MDC) were compared across metrics quantified within different cervical levels and white matter (WM) sub-regions. The differences between pathways and age groups were quantified and interpreted in context of the test-retest repeatability of the measurements.

RESULTS

The MDC was respectively 105.7ms, 2.77%, 0.37% and 4.08% for T1, MTR, MTsat and MTV when quantified over all WM, while the standard-deviation across subjects was 70.5ms, 1.34%, 0.20% and 2.44%. Even though particular WM regions did exhibit significant differences, these differences were on the same order as test-retest errors. No significant difference was found between age groups for all metrics.

CONCLUSION

While T1-based metrics (T1 and MTV) exhibited better reliability than MT-based measurements (MTR and MTsat), the observed differences between subjects or WM regions were comparable to (and often smaller than) the MDC. This makes it difficult to determine if observed changes are due to variations in myelin content, or simply due to measurement error. Measurement error remains a challenge in spinal cord myelin imaging, but this study provides statistical guidelines to standardize the field and make it possible to conduct large-scale multi-center studies.

Advances in noninvasive myelin imaging

Myelin is important for the normal development and healthy function of the nervous system. Recent developments in MRI acquisition and tissue modeling aim to provide a better characterization and more specific markers for myelin. This allows for specific monitoring of myelination longitudinally and noninvasively in the healthy brain as well as assessment of treatment and intervention efficacy. Here, we offer a nontechnical review of MRI techniques developed to specifically monitor myelin such as magnetization transfer (MT) and myelin water imaging (MWI). We further summarize recent studies that employ these methods to measure myelin in relation to development and aging, learning and experience, and neuropathology and psychiatric disorders. © 2017 The Authors. Developmental Neurobiology Published by Wiley Periodicals, Inc. Develop Neurobiol 78: 136–151, 2018

Imaging the Role of Myelin in Concussion

Myelin water imaging (MWI) provides mild traumatic brain injury (mTBI) researchers with a specific myelin biomarker and helps to further elucidate microstructural and microarchitectural changes of white matter after mTBI. Improvement of scanner hardware and software with the implementation of MWI across scanner platforms will likely result in increased research regarding the role of myelin in traumatic brain injury (TBI). Future research should include detailed investigation of myelin between 2 weeks and 2 months after injury, the use of MWI in moderate and severe TBI, and investigation of the role of myelin in chronic TBI.

Myelin plasticity and behaviour-connecting the dots

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Changes in white matter and myelin are associated with learning during adulthood across species.

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The causal link between myelin plasticity and behaviour remains elusive.

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Preventing the differentiation of new OLs can impair learning within the first few hours.

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Myelin remodelling may occur through many different routes and mechanism.

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The functional arrangement of myelination along axons can be complex and diverse.

Myelin sheaths in the vertebrate nervous system enable faster impulse propagation, while myelinating glia provide vital support to axons. Once considered a static insulator, converging evidence now suggests that myelin in the central nervous system can be dynamically regulated by neuronal activity and continues to participate in nervous system plasticity beyond development. While the link between experience and myelination gains increased recognition, it is still unclear what role such adaptive myelination plays in facilitating and shaping behaviour. Additionally, fundamental mechanisms and principles underlying myelin remodelling remain poorly understood. In this review, we will discuss new insights into the link between myelin plasticity and behaviour, as well as mechanistic aspects of myelin remodelling that may help to elucidate this intriguing process.

Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls

Myelin imaging is a form of quantitative magnetic resonance imaging (MRI) that measures myelin content and can potentially allow demyelinating diseases such as multiple sclerosis (MS) to be detected earlier. Although focal lesions are the most visible signs of MS pathology on conventional MRI, it has been shown that even tissues that appear normal may exhibit decreased myelin content as revealed by myelin-specific images (i.e., myelin maps). Current methods for analyzing myelin maps typically use global or regional mean myelin measurements to detect abnormalities, but ignore finer spatial patterns that may be characteristic of MS. In this paper, we present a machine learning method to automatically learn, from multimodal MR images, latent spatial features that can potentially improve the detection of MS pathology at early stage. More specifically, 3D image patches are extracted from myelin maps and the corresponding T1-weighted (T1w) MRIs, and are used to learn a latent joint myelin-T1w feature representation via unsupervised deep learning. Using a data set of images from MS patients and healthy controls, a common set of patches are selected via a voxel-wise t-test performed between the two groups. In each MS image, any patches overlapping with focal lesions are excluded, and a feature imputation method is used to fill in the missing values. A feature selection process (LASSO) is then utilized to construct a sparse representation. The resulting normal-appearing features are used to train a random forest classifier. Using the myelin and T1w images of 55 relapse-remitting MS patients and 44 healthy controls in an 11-fold cross-validation experiment, the proposed method achieved an average classification accuracy of 87.9% (SD = 8.4%), which is higher and more consistent across folds than those attained by regional mean myelin (73.7%, SD = 13.7%) and T1w measurements (66.7%, SD = 10.6%), or deep-learned features in either the myelin (83.8%, SD = 11.0%) or T1w (70.1%, SD = 13.6%) images alone, suggesting that the proposed method has strong potential for identifying image features that are more sensitive and specific to MS pathology in normal-appearing brain tissues.

Promise and pitfalls of g-ratio estimation with MRI

The fiber g-ratio is the ratio of the inner to the outer diameter of the myelin sheath of a myelinated axon. It has a limited dynamic range in healthy white matter, as it is optimized for speed of signal conduction, cellular energetics, and spatial constraints. In vivo imaging of the g-ratio in health and disease would greatly increase our knowledge of the nervous system and our ability to diagnose, monitor, and treat disease. MRI based g-ratio imaging was first conceived in 2011, and expanded to be feasible in full brain white matter with preliminary results in 2013. This manuscript reviews the growing g-ratio imaging literature and speculates on future applications. It details the methodology for imaging the g-ratio with MRI, and describes the known pitfalls and challenges in doing so.

Global loss of myelin water over 5 years in multiple sclerosis normal-appearing white matter

Background:

Reduced myelin water fraction (MWF, a marker for myelin), increased geometric mean T2 (ieGMT2, reflecting intra/extracellular water properties), and increased T1 (related to total water content) have been observed in cross-sectional studies of multiple sclerosis (MS) normal-appearing white matter (NAWM).

Objective:

To assess longitudinal changes of magnetic resonance (MR) measures in relapsing-remitting MS (RRMS) brain NAWM.

Methods:

A total of 11 subjects with RRMS and 4 controls were scanned on a 3T MRI at baseline and long-term follow-up (LTFU; 3.2–5.8 years) with a 32-echo T2 relaxation and an inversion recovery T1 sequence. For every voxel, MWF, ieGMT2, and T1 were obtained. Mean, peak height, and peak location from NAWM mask-based histograms were determined.

Results:

In MS subjects, NAWM MWF mean decreased by 8% ( p = 0.0016). No longitudinal changes were measured in T1 or ieGMT2. There was no relationship between change in any MR metric and change in EDSS. Control white matter showed no differences over time in any metric.

Conclusion:

The decreases we observed in MWF suggest that changes in myelin integrity and loss of myelin may be occurring diffusely and over long time periods in the MS brain. The timescale of these changes indicates that chronic, progressive myelin damage is an evolving process occurring over many years.

Clinical high-resolution mapping of the proteoglycan-bound water fraction in articular cartilage of the human knee joint

PURPOSE

We applied our recently introduced Bayesian analytic method to achieve clinically-feasible in-vivo mapping of the proteoglycan water fraction (PgWF) of human knee cartilage with improved spatial resolution and stability as compared to existing methods.

MATERIALS AND METHODS

Multicomponent driven equilibrium single-pulse observation of T₁ and T₂ (mcDESPOT) datasets were acquired from the knees of two healthy young subjects and one older subject with previous knee injury. Each dataset was processed using Bayesian Monte Carlo (BMC) analysis incorporating a two-component tissue model. We assessed the performance and reproducibility of BMC and of the conventional analysis of stochastic region contraction (SRC) in the estimation of PgWF. Stability of the BMC analysis of PgWF was tested by comparing independent high-resolution (HR) datasets from each of the two young subjects.

RESULTS

Unlike SRC, the BMC-derived maps from the two HR datasets were essentially identical. Furthermore, SRC maps showed substantial random variation in estimated PgWF, and mean values that differed from those obtained using BMC. In addition, PgWF maps derived from conventional low-resolution (LR) datasets exhibited partial volume and magnetic susceptibility effects. These artifacts were absent in HR PgWF images. Finally, our analysis showed regional variation in PgWF estimates, and substantially higher values in the younger subjects as compared to the older subject.

CONCLUSIONS

BMC-mcDESPOT permits HR in-vivo mapping of PgWF in human knee cartilage in a clinically-feasible acquisition time. HR mapping reduces the impact of partial volume and magnetic susceptibility artifacts compared to LR mapping. Finally, BMC-mcDESPOT demonstrated excellent reproducibility in the determination of PgWF.

Propagation of error from parameter constraints in quantitative MRI: Example application of multiple spin echo T2 mapping

PURPOSE

Quantitative MRI may require correcting for nuisance parameters which can or must be constrained to independently measured or assumed values. The noise and/or bias in these constraints propagate to fitted parameters. For example, the case of refocusing pulse flip angle constraint in multiple spin echo T₂ mapping is explored.

METHODS

An analytical expression for the mean-squared error of a parameter of interest was derived as a function of the accuracy and precision of an independent estimate of a nuisance parameter. The expression was validated by simulations and then used to evaluate the effects of flip angle (θ) constraint on the accuracy and precision of T⁁2 for a variety of multi-echo T₂ mapping protocols.

RESULTS

Constraining θ improved T⁁2 precision when the θ-map signal-to-noise ratio was greater than approximately one-half that of the first spin echo image. For many practical scenarios, constrained fitting was calculated to reduce not just the variance but the full mean-squared error of T⁁2, for bias in θ⁁≲6%.

CONCLUSION

The analytical expression derived in this work can be applied to inform experimental design in quantitative MRI. The example application to T₂ mapping provided specific cases, depending on θ⁁ accuracy and precision, in which θ⁁ measurement and constraint would be beneficial to T⁁2 variance or mean-squared error. Magn Reson Med 79:673-682, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Mechanisms of T2 * anisotropy and gradient echo myelin water imaging

In MRI, structurally aligned molecular or micro-organization (e.g. axonal fibers) can be a source of substantial signal variations that depend on the structural orientation and the applied magnetic field. This signal anisotropy gives us a unique opportunity to explore information that exists at a resolution several orders of magnitude smaller than that of typical MRI. In this review, one of the signal anisotropies, T₂ * anisotropy in white matter, and a related imaging method, gradient echo myelin water imaging (GRE-MWI), are explored. The T₂ * anisotropy has been attributed to isotropic and anisotropic magnetic susceptibility of myelin and compartmentalized microstructure of white matter fibers (i.e. axonal, myelin, and extracellular space). The susceptibility and microstructure create magnetic frequency shifts that change with the relative orientation of the fiber and the main magnetic field, generating the T₂ * anisotropy. The resulting multi-component magnitude decay and nonlinear phase evolution have been utilized for GRE-MWI, assisting in resolving the signal fraction of the multiple compartments in white matter. The GRE-MWI method has been further improved by signal compensation techniques including physiological noise compensation schemes. The T₂ * anisotropy and GRE-MWI provide microstructural information on a voxel (e.g. fiber orientation and tissue composition), and may serve as sensitive biomarkers for microstructural changes in the brain. Copyright © 2016 John Wiley & Sons, Ltd.