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Objective: To clarify the relationship between myelin water fraction (MWF) and R1⋅R2* and to develop a method to calculate MWF directly from parameters derived from QPM, i.e., MWF converted from QPM (MWFQPM). Materials and methods: Subjects were 12 healthy volunteers. On a 3 T MR scanner, dataset was acquired using spoiled gradient-echo sequence for QPM. MWF and R1⋅R2* maps were derived from the multi-gradient-echo (mGRE) dataset. Volume-of-interest (VOI) analysis using the JHU-white matter (WM) atlas was performed. All the data in the 48 WM regions measured VOI were plotted, and quadratic polynomial approximations of each region were derived from the relationship between R1·R2* and the two-pool model-MWF. The R1·R2* map was converted to MWFQPM map. MWF atlas template was generated using converted to MWF from R1·R2* per WM region. Results: The mean MWF and R1·R2* values for the 48 WM regions were 11.96 ± 6.63%, and 19.94 ± 4.59 s−2, respectively. A non-linear relationship in 48 regions of the WM between MWF and R1·R2* values was observed by quadratic polynomial approximation (R2 ≥ 0.963, P < 0.0001). Discussion: MWFQPM map improved image quality compared to the mGRE-MWF map. Myelin water atlas template derived from MWFQPM may be generated with combined multiple WM regions. [ABSTRACT FROM AUTHOR]

Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Abstract Identifying sensitive and specific measures that can quantify myelin are instrumental in characterizing microstructural changes in neurological conditions. Neuroimaging transcriptomics is emerging as a valuable technique in this regard, offering insights into the molecular basis of promising candidates for myelin quantification, such as myelin water fraction (MWF). We aimed to demonstrate the utility of neuroimaging transcriptomics by validating MWF as a myelin measure. We utilized data from a normative MWF brain atlas, comprised of 50 healthy subjects (mean age = 25 years, range = 17–42 years) scanned at 3 Tesla. Magnetic resonance imaging data included myelin water imaging to extract MWF and T1 anatomical scans for image registration and segmentation. We investigated the inter-regional distributions of gene expression data from the Allen Human Brain Atlas in conjunction with inter-regional MWF distribution patterns. Pearson correlations were used to identify genes with expression profiles mirroring MWF. The Single Cell Type Atlas from the Human Protein Atlas was leveraged to classify genes into gene sets with high cell type specificity, and a control gene set with low cell type specificity. Then, we compared the Pearson correlation coefficients for each gene set to determine if cell type-specific gene expression signatures correlate with MWF. Pearson correlation coefficients between MWF and gene expression for oligodendrocytes and adipocytes were significantly higher than for the control gene set, whereas correlations between MWF and inhibitory/excitatory neurons were significantly lower. Our approach in integrating transcriptomics with neuroimaging measures supports an emerging technique for understanding and validating MRI-derived markers such as MWF.

Identifying sensitive and specific measures that can quantify myelin are instrumental in characterizing microstructural changes in neurological conditions. Neuroimaging transcriptomics is emerging as a valuable technique in this regard, offering insights into the molecular basis of promising candidates for myelin quantification, such as myelin water fraction (MWF). We aimed to demonstrate the utility of neuroimaging transcriptomics by validating MWF as a myelin measure. We utilized data from a normative MWF brain atlas, comprised of 50 healthy subjects (mean age = 25 years, range = 17–42 years) scanned at 3 Tesla. Magnetic resonance imaging data included myelin water imaging to extract MWF and T1 anatomical scans for image registration and segmentation. We investigated the inter-regional distributions of gene expression data from the Allen Human Brain Atlas in conjunction with inter-regional MWF distribution patterns. Pearson correlations were used to identify genes with expression profiles mirroring MWF. The Single Cell Type Atlas from the Human Protein Atlas was leveraged to classify genes into gene sets with high cell type specificity, and a control gene set with low cell type specificity. Then, we compared the Pearson correlation coefficients for each gene set to determine if cell type-specific gene expression signatures correlate with MWF. Pearson correlation coefficients between MWF and gene expression for oligodendrocytes and adipocytes were significantly higher than for the control gene set, whereas correlations between MWF and inhibitory/excitatory neurons were significantly lower. Our approach in integrating transcriptomics with neuroimaging measures supports an emerging technique for understanding and validating MRI-derived markers such as MWF. [ABSTRACT FROM AUTHOR]

A quantitative biomarker for myelination, such as myelin water fraction (MWF), would boost the understanding of normative and pathological neurodevelopment, improving patients' diagnosis and follow‐up. We quantified the fraction of a rapidly relaxing pool identified as MW using multicomponent three‐dimensional (3D) magnetic resonance fingerprinting (MRF) to evaluate white matter (WM) maturation in typically developing (TD) children and alterations in leukodystrophies (LDs). We acquired DTI and 3D MRF‐based R1, R2 and MWF data of 15 TD children and 17 LD patients (9 months–12.5 years old) at 1.5 T. We computed normative maturation curves in corpus callosum and corona radiata and performed WM tract profile analysis, comparing MWF with R1, R2 and fractional anisotropy (FA). Normative maturation curves demonstrated a steep increase for all tissue parameters in the first 3 years of age, followed by slower growth for MWF while R1, R2R2 and FA reached a plateau. Unlike FA, MWF values were similar for regions of interest (ROIs) with different degrees of axonal packing, suggesting independence from fiber bundle macro‐organization and higher myelin specificity. Tract profile analysis indicated a specific spatial pattern of myelination in the major fiber bundles, consistent across subjects. LD were better distinguished from TD by MWF rather than FA, showing reduced MWF with respect to age‐matched controls in both ROI‐based and tract analysis. In conclusion, MRF‐based MWF provides myelin‐specific WM maturation curves and is sensitive to alteration due to LDs, suggesting its potential as a biomarker for WM disorders. As MRF allows fast simultaneous acquisition of relaxometry and MWF, it can represent a valuable diagnostic tool to study and follow up developmental WM disorders in children. [ABSTRACT FROM AUTHOR]

Myelin repair is an unrealized therapeutic goal in the treatment of multiple sclerosis (MS). Uncertainty remains about the optimal techniques for assessing therapeutic efficacy and imaging biomarkers are required to measure and corroborate myelin restoration. We analyzed myelin water fraction imaging from ReBUILD, a double-blind, randomized placebo-controlled (delayed treatment) remyelination trial, that showed a significant reduction in VEP latency in patients with MS. We focused on brain regions rich in myelin. Fifty MS subjects in two arms underwent 3T MRI at baseline and months 3 and 5. Half of the cohort was randomly assigned to receive treatment from baseline through 3 mo, whereas the other half received treatment from 3 mo to 5 mo post-baseline. We computed myelin water fraction changes occurring in normal-appearing white matter of corpus callosum, optic radiations, and corticospinal tracts. An increase in myelin water fraction was documented in the normal-appearing white matter of the corpus callosum, in correspondence with the administration of the remyelinating treatment clemastine. This study provides direct, biologically validated imaging-based evidence of medically induced myelin repair. Moreover, our work strongly suggests that significant myelin repair occurs outside of lesions. We therefore propose myelin water fraction within the normal-appearing white matter of the corpus callosum as a biomarker for clinical trials looking at remyelination.

A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm is proposed to correct for the T1 saturation effect and B1+/B1− inhomogeneities in the quantification of MWF. A tissue-prior-based B1+ estimation algorithm was adapted for B1 correction in the mapping of T1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R2*/T1app/M0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T1/PD/B1+/MWF/QSM/R2*, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T1/PD/B1+/MWF/R2*. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI.

Abstract Background Magnetic resonance fingerprinting (MRF) enables fast myelin quantification via the myelin water fraction (MWF), offering a noninvasive method to assess brain development and disease. However, MRF-derived MWF lacks histological evaluation and remains unexamined in relation to leukodystrophy. This study aimed to access MRF-derived MWF through histology in mice and establish links between myelin, development, and leukodystrophy in mice and children, demonstrating its potential applicability in animal and human studies. Methods 3D MRF was performed on normal C57BL/6 mice with different ages, megalencephalic leukoencephalopathy with subcortical cyst 1 wild type (MLC1 WT, control) mice, and MLC 1 knock-out (MLC1 KO, leukodystrophy) mice using a 3 T MRI. MWF values were analyzed from 3D MRF data, and histological myelin quantification was carried out using immunohistochemistry to anti-proteolipid protein (PLP) in the corpus callosum and cortex. The associations between ‘MWF and PLP’ and ‘MWF and age’ were evaluated in C57BL/6 mice. MWF values were compared between MLC1 WT and MLC1 KO mice. MWF of normal developing children were retrospectively collected and the association between MWF and age was assessed. Results In 35 C57BL/6 mice (age range; 3 weeks–48 weeks), MWF showed positive relations with PLP immunoreactivity in the corpus callosum (β = 0.0006, P = 0.04) and cortex (β = 0.0005, P = 0.006). In 12-week-old C57BL/6 mice MWF showed positive relations with PLP immunoreactivity (β = 0.0009, P = 0.003, R2 = 0.54). MWF in the corpus callosum (β = 0.0022, P

Background: Magnetic resonance fingerprinting (MRF) enables fast myelin quantification via the myelin water fraction (MWF), offering a noninvasive method to assess brain development and disease. However, MRF-derived MWF lacks histological evaluation and remains unexamined in relation to leukodystrophy. This study aimed to access MRF-derived MWF through histology in mice and establish links between myelin, development, and leukodystrophy in mice and children, demonstrating its potential applicability in animal and human studies. Methods: 3D MRF was performed on normal C57BL/6 mice with different ages, megalencephalic leukoencephalopathy with subcortical cyst 1 wild type (MLC1 WT, control) mice, and MLC 1 knock-out (MLC1 KO, leukodystrophy) mice using a 3 T MRI. MWF values were analyzed from 3D MRF data, and histological myelin quantification was carried out using immunohistochemistry to anti-proteolipid protein (PLP) in the corpus callosum and cortex. The associations between 'MWF and PLP' and 'MWF and age' were evaluated in C57BL/6 mice. MWF values were compared between MLC1 WT and MLC1 KO mice. MWF of normal developing children were retrospectively collected and the association between MWF and age was assessed. Results: In 35 C57BL/6 mice (age range; 3 weeks–48 weeks), MWF showed positive relations with PLP immunoreactivity in the corpus callosum (β = 0.0006, P = 0.04) and cortex (β = 0.0005, P = 0.006). In 12-week-old C57BL/6 mice MWF showed positive relations with PLP immunoreactivity (β = 0.0009, P = 0.003, R2 = 0.54). MWF in the corpus callosum (β = 0.0022, P < 0.001) and cortex (β = 0.0010, P < 0.001) showed positive relations with age. Seven MLC1 WT and 9 MLC1 KO mice showed different MWF values in the corpus callous (P < 0.001) and cortex (P < 0.001). A total of 81 children (median age, 126 months; range, 0–199 months) were evaluated and their MWF values according to age showed the best fit for the third-order regression model (adjusted R2 range, 0.44–0.94, P < 0.001). Conclusion: MWF demonstrated associations with histologic myelin quantity, age, and the presence of leukodystrophy, underscoring the potential of 3D MRF-derived MWF as a rapid and noninvasive quantitative indicator of brain myelin content in both mice and humans. [ABSTRACT FROM AUTHOR]

Objective: To determine if there are sex differences in myelin in Parkinson's disease, and whether these explain some of the previously-described sex differences in clinical presentation. Methods: Thirty-three subjects (23 males, 10 females) with Parkinson's disease underwent myelin water fraction (MWF) imaging, an MRI scanning technique of in vivo myelin content. MWF of 20 white matter regions of interest (ROIs) were assessed. Motor symptoms were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS). Principal component analysis, logistic and multiple linear regressions, and t-tests were used to determine which white matter ROIs differed between sexes, the clinical features associated with these myelin changes, and if overall MWF and MWF laterality differed between males and females. Results: Consistent with prior reports, tremor and bradykinesia were more likely seen in females, whereas rigidity and axial symptoms were more likely seen in males in our cohort. MWF of the thalamic radiation, cingulum, cingulum hippocampus, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate were significant in predicting sex. Overall MWF and asymmetry of MWF was greater in males. MWF differences between sexes were associated with tremor symptomatology and asymmetry of motor performance. Conclusion: Sex differences in myelin are associated with tremor and asymmetry of motor presentation. While preliminary, our results suggest that further investigation of the role of biological sex in myelin pathology and clinical presentation in Parkinson's disease is warranted. [ABSTRACT FROM AUTHOR]

BACKGROUND: It is unknown whether hypertension plays any role in cerebral myelination. To fill this knowledge gap, we studied 90 cognitively unimpaired adults, age range 40 to 94 years, who are participants in the Baltimore Longitudinal Study of Aging and the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing to look for potential associations between hypertension and cerebral myelin content across 14 white matter brain regions. METHODS: Myelin content was probed using our advanced multicomponent magnetic resonance relaxometry method of myelin water fraction, a direct and specific magnetic resonance imaging measure of myelin content, and longitudinal and transverse relaxation rates (R 1 and R 2 ), 2 highly sensitive magnetic resonance imaging metrics of myelin content. We also applied diffusion tensor imaging magnetic resonance imaging to measure fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity values, which are metrics of cerebral microstructural tissue integrity, to provide context with previous magnetic resonance imaging findings. RESULTS: After adjustment of age, sex, systolic blood pressure, smoking status, diabetes status, and cholesterol level, our results indicated that participants with hypertension exhibited lower myelin water fraction, fractional anisotropy, R 1 and R 2 values and higher mean diffusivity, radial diffusivity, and axial diffusivity values, indicating lower myelin content and higher impairment to the brain microstructure. These associations were significant across several white matter regions, particularly in the corpus callosum, fronto-occipital fasciculus, temporal lobes, internal capsules, and corona radiata. CONCLUSIONS: These original findings suggest a direct association between myelin content and hypertension and form the basis for further investigations including longitudinal assessments of this relationship. [ABSTRACT FROM AUTHOR]

Background: Cerebral tissue integrity decline and cerebral blood flow (CBF) alteration are major aspects of motor and cognitive dysfunctions and neurodegeneration. However, little is known about the association between blood flow and brain microstructural integrity, especially in normal aging. Purpose: To assess the association between CBF and cerebral microstructural integrity. Study Type: Cross sectional. Population: A total of 94 cognitively unimpaired adults (mean age 50.7 years, age range between 22 and 88 years, 56 Men). Field Strength/Sequence: A 3 T; pseudo‐continuous arterial spin labeling (pCASL), diffusion tensor imaging (DTI), Bayesian Monte Carlo analysis of multicomponent driven equilibrium steady‐state observation of T1 and T2 (BMC‐mcDESPOT). Assessment: Lobar associations between CBF derived from pCASL, and longitudinal relaxation rate (R1), transverse relaxation rate (R2) and myelin water fraction (MWF) derived from BMC‐mcDESPOT, or radial diffusivity (RD), axial diffusivity (AxD), mean diffusivity (MD) and fractional anisotropy (FA) derived from DTI were assessed. Statistical Tests: Multiple linear regression models were used using the mean region of interest (ROI) values for MWF, R1, R2, FA, MD, RD, or AxD as the dependent variable and CBF, age, age2, and sex as the independent variables. A two‐sided P value of <0.05 defined statistical significance. Results: R1, R2, MWF, FA, MD, RD, and AxD parameters were associated with CBF in most of the cerebral regions evaluated. Specifically, higher CBF values were significantly associated with higher FA, MWF, R1 and R2, or lower MD, RD and AxD values. Data Conclusion: These findings suggest that cerebral tissue microstructure may be impacted by global brain perfusion, adding further evidence to the intimate relationship between cerebral blood supply and cerebral tissue integrity. Evidence Level: 4 Technical Efficacy: Stage 4 [ABSTRACT FROM AUTHOR]

Abstract Background In Alzheimer’s disease (AD), fibrillar tau initially occurs locally and progresses preferentially between closely connected regions. However, the underlying sources of regional vulnerability to tau pathology remain unclear. Previous brain-autopsy findings suggest that the myelin levels—which differ substantially between white matter tracts in the brain—are a key modulating factor of region-specific susceptibility to tau deposition. Here, we investigated whether myelination differences between fiber tracts of the human connectome are predictive of the interregional spreading of tau pathology in AD. Methods We included two independently recruited samples consisting of amyloid-PET-positive asymptomatic and symptomatic elderly individuals, in whom tau-PET was obtained at baseline (ADNI: n = 275; BioFINDER-1: n = 102) and longitudinally in a subset (ADNI: n = 123, mean FU = 1.53 [0.69–3.95] years; BioFINDER-1: n = 39, mean FU = 1.87 [1.21–2.78] years). We constructed MRI templates of the myelin water fraction (MWF) in 200 gray matter ROIs and connecting fiber tracts obtained from adult cognitively normal participants. Using the same 200 ROI brain-parcellation atlas, we obtained tau-PET ROI values from each individual in ADNI and BioFINDER-1. In a spatial regression analysis, we first tested the association between cortical myelin and group-average tau-PET signal in the amyloid-positive and control groups. Secondly, employing a previously established approach of modeling tau-PET spreading based on functional connectivity between ROIs, we estimated in a linear regression analysis, whether the level of fiber-tract myelin modulates the association between functional connectivity and longitudinal tau-PET spreading (i.e., covariance) between ROIs. Results We found that higher myelinated cortical regions show lower tau-PET uptake (ADNI: rho = − 0.267, p

The ratio of T1-weighted/T2-weighted magnetic resonance images (T1w/T2w MRI) has been successfully applied at the cortical level since 2011 and is now one of the most used myelin mapping methods. However, no reports have explored the histological validity of T1w/T2w myelin mapping in white matter. Here we compare T1w/T2w with ex vivo postmortem histology and in vivo MRI methods, namely quantitative susceptibility mapping (QSM) and multi-echo T2 myelin water fraction (MWF) mapping techniques. We report a discrepancy between T1w/T2w myelin maps of the human corpus callosum and the histology and analyse the putative causes behind such discrepancy. T1w/T2w does not positively correlate with Luxol Fast Blue (LFB)-Optical Density but shows a weak to moderate, yet significant, negative correlation. On the contrary, MWF is strongly and positively correlated with LFB, whereas T1w/T2w and MWF maps are weakly negatively correlated. The discrepancy between T1w/T2w MRI maps, MWF and histological myelin maps suggests caution in using T1w/T2w as a white matter mapping method at the callosal level. While T1w/T2w imaging may correlate with myelin content at the cortical level, it is not a specific method to map myelin density in white matter. [ABSTRACT FROM AUTHOR]

The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects.

Background: In Alzheimer's disease (AD), fibrillar tau initially occurs locally and progresses preferentially between closely connected regions. However, the underlying sources of regional vulnerability to tau pathology remain unclear. Previous brain-autopsy findings suggest that the myelin levels—which differ substantially between white matter tracts in the brain—are a key modulating factor of region-specific susceptibility to tau deposition. Here, we investigated whether myelination differences between fiber tracts of the human connectome are predictive of the interregional spreading of tau pathology in AD. Methods: We included two independently recruited samples consisting of amyloid-PET-positive asymptomatic and symptomatic elderly individuals, in whom tau-PET was obtained at baseline (ADNI: n = 275; BioFINDER-1: n = 102) and longitudinally in a subset (ADNI: n = 123, mean FU = 1.53 [0.69–3.95] years; BioFINDER-1: n = 39, mean FU = 1.87 [1.21–2.78] years). We constructed MRI templates of the myelin water fraction (MWF) in 200 gray matter ROIs and connecting fiber tracts obtained from adult cognitively normal participants. Using the same 200 ROI brain-parcellation atlas, we obtained tau-PET ROI values from each individual in ADNI and BioFINDER-1. In a spatial regression analysis, we first tested the association between cortical myelin and group-average tau-PET signal in the amyloid-positive and control groups. Secondly, employing a previously established approach of modeling tau-PET spreading based on functional connectivity between ROIs, we estimated in a linear regression analysis, whether the level of fiber-tract myelin modulates the association between functional connectivity and longitudinal tau-PET spreading (i.e., covariance) between ROIs. Results: We found that higher myelinated cortical regions show lower tau-PET uptake (ADNI: rho = − 0.267, p < 0.001; BioFINDER-1: rho = − 0.175, p = 0.013). Fiber-tract myelin levels modulated the association between functional connectivity and tau-PET spreading, such that at higher levels of fiber-tract myelin, the association between stronger connectivity and higher covariance of tau-PET between the connected ROIs was attenuated (interaction fiber-tract myelin × functional connectivity: ADNI: β = − 0.185, p < 0.001; BioFINDER-1: β = − 0.166, p < 0.001). Conclusion: Higher levels of myelin are associated with lower susceptibility of the connected regions to accumulate fibrillar tau. These results enhance our understanding of brain substrates that explain regional variation in tau accumulation and encourage future studies to investigate potential underlying mechanisms. [ABSTRACT FROM AUTHOR]

Purpose: Myelin water fraction (MWF) is often obtained from a multiple echo spin echo (MESE) sequence using multi‐component T2 fitting with non‐negative least squares. This process fits many unknowns including B1+ to produce a T2 spectrum for each voxel. Presented is an alternative using a rapid B1+ mapping sequence to supply B1+ for the MWF fitting procedure. Methods: Effects of B1+ errors on MWF calculations were modeled for 2D and 3D MESE using Bloch and extended phase graph simulations, respectively. Variations in SNR and relative refocusing widths were tested. Human brain experiments at 3 T used 2D MESE and an independent B1+ map. MWF maps were produced with the standard approach and with the use of the independent B1+ map. Differences in B1+ and mean MWF in specific brain regions were compared. Results: For 2D MESE, MWF with the standard method was strongly affected by B1+ misestimations arising from limited SNR and response asymmetry around 180°, which decreased with increasing relative refocusing width. Using an independent B1+ map increased mean MWF and decreased coefficient of variation. Notable differences in vivo in 2D MESE were in areas of high B1+ such as thalamus and splenium where mean MWF increased by 88% and 31%, respectively (P < 0.001). Simulations also demonstrated the advantages of this approach for 3D MESE when SNR is <500. Conclusion: For 2D MESE, because of increased complexity of decay curves and limited SNR, supplying B1+ improves MWF results in peripheral and central brain regions where flip angles differ substantially from 180°. [ABSTRACT FROM AUTHOR]

Purpose Previously, an artificial neural network method was introduced to estimate quantitative myelin water fraction (MWF) using multi‐echo gradient‐echo data. However, the fiber orientation of white matter with respect to B0 could bias the quantification of MWF. Here, we developed an advanced workflow for MWF estimation that could improve the quantification of MWF. Methods: To adopt fiber orientation effects, a complex‐valued neural network with complex‐valued operation was used. In addition, to compensate for the bias from different scan parameters, a signal model incorporating the T1 value was devised for training data generation. At the testing stage, a voxel‐spread function approach was utilized for spatial B0 artifact correction. Finally, dropout‐based variational inference was implemented for uncertainty estimates on the network model to provide a confidence interpretation of the output. Results: According to simulation and in vivo analysis, the proposed method suggests improved quality of MWF estimation by correcting the bias and artifacts. The proposed complex‐valued neural network approach can alleviate the dependency of fiber orientation effects compared to previous artificial neural network method. Uncertainty estimates provides information different from fitting error that can be used as a confidence level of the resulting MWF values. Conclusion: An improved MWF mapping using complex‐valued neural network analysis has been proposed. [ABSTRACT FROM AUTHOR]

Purpose: To develop a 3D UNET convolutional neural network for rapid extraction of myelin water fraction (MWF) maps from six‐echo fast acquisition with spiral trajectory and T2‐prep data and to evaluate its accuracy in comparison with multilayer perceptron (MLP) network. Methods: The MWF maps were extracted from 138 patients with multiple sclerosis using an iterative three‐pool nonlinear least‐squares algorithm (NLLS) without and with spatial regularization (srNLLS), which were used as ground‐truth labels to train, validate, and test UNET and MLP networks as a means to accelerate data fitting. Network testing was performed in 63 patients with multiple sclerosis and a numerically simulated brain phantom at SNR of 200, 100 and 50. Results: Simulations showed that UNET reduced the MWF mean absolute error by 30.1% to 56.4% and 16.8% to 53.6% over the whole brain and by 41.2% to 54.4% and 21.4% to 49.4% over the lesions for predicting srNLLS and NLLS MWF, respectively, compared to MLP, with better performance at lower SNRs. UNET also outperformed MLP for predicting srNLLS MWF in the in vivo multiple‐sclerosis brain data, reducing mean absolute error over the whole brain by 61.9% and over the lesions by 67.5%. However, MLP yielded 41.1% and 51.7% lower mean absolute error for predicting in vivo NLLS MWF over the whole brain and the lesions, respectively, compared with UNET. The whole‐brain MWF processing time using a GPU was 0.64 seconds for UNET and 0.74 seconds for MLP. Conclusion: Subsecond whole‐brain MWF extraction from fast acquisition with spiral trajectory and T2‐prep data using UNET is feasible and provides better accuracy than MLP for predicting MWF output of srNLLS algorithm. [ABSTRACT FROM AUTHOR]

Purpose: Validation of quantitative MR measures for myelin imaging in the postmortem multiple sclerosis spinal cord. Methods: Four fixed spinal cord samples were imaged first with a 3T clinical MR scanner to identify areas of interest for scanning, and then with a 7T small bore scanner using a multicomponent‐driven equilibrium single‐pulse observation of T1 and T2 protocol to produce apparent proton density, T1, T2, myelin water, intracellular water, and free‐water fraction maps. After imaging, the cords were sectioned and stained with histological markers (hematoxylin and eosin, myelin basic protein, and neurofilament protein), which were quantitatively compared with the MR maps. Results: Excellent correspondence was found between high‐resolution MR parameter maps and histology, particularly for apparent proton density MRI and myelin basic protein staining. Conclusion: High‐resolution quantitative MRI of the spinal cord provides biologically meaningful measures, and could be beneficial to diagnose and track multiple sclerosis lesions in the spinal cord. [ABSTRACT FROM AUTHOR]

A novel lesion-mask free method based on a gamma mixture model was applied to myelin water fraction (MWF) maps to estimate the association between cortical thickness and myelin content, and how it differs between relapsing-remitting (RRMS) and secondary-progressive multiple sclerosis (SPMS) groups (135 and 23 patients, respectively). It was compared to an approach based on lesion masks. The gamma mixture distribution of whole brain, white matter (WM) MWF was characterized with three variables: the mode (most frequent value) m1 of the gamma component shown to relate to lesion, the mode m2 of the component shown to be associated with normal appearing (NA) WM, and the mixing ratio (λ) between the two distributions. The lesion-mask approach relied on the mean MWF within lesion and within NAWM. A multivariate regression analysis was carried out to find the best predictors of cortical thickness for each group and for each approach. The gamma-mixture method was shown to outperform the lesion-mask approach in terms of adjusted R2, both for the RRMS and SPMS groups. The predictors of the final gamma-mixture models were found to be m1 (β = 1.56, p < 0.005), λ (β = -0.30, p < 0.0005) and age (β = -0.0031, p < 0.005) for the RRMS group (adjusted R2 = 0.16), and m2 (β = 4.72, p < 0.0005) for the SPMS group (adjusted R2 = 0.45). Further, a DICE coefficient analysis demonstrated that the lesion mask had more overlap to an ROI associated with m1, than to an ROI associated with m2 (p < 0.00001), and vice versa for the NAWM mask (p < 0.00001). These results suggest that during the relapsing phase, focal WM damage is associated with cortical thinning, yet in SPMS patients, global WM deterioration has a much stronger influence on secondary degeneration. Through these findings, we demonstrate the potential contribution of myelin loss on neuronal degeneration at different disease stages and the usefulness of our statistical reduction technique which is not affected by the typical bias associated with approaches based on lesion masks.

• A dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory was developed to accelerate the acquisition for fast simultaneous three-dimensional (3D) multiparametric mapping of whole brain myelin water fraction (MWF), T 1 , proton density (PD), R 2 *, magnetic susceptibility (QSM), and B 1 transmit field (B 1 +). • A novel joint-sparsity-constrained multicomponent T 2 *-T 1 spectrum estimation (JMSE) algorithm was proposed to improve the quantification of MWF by correcting for the T 1 saturation effect and B 1 +/B 1 − inhomogeneities. • By integrating the DFA-mGRE SOS sequence, the JMSE algorithm, the tissue-prior-based B 1 + estimation algorithm, and the subspace-based reconstruction, our technique can provide robust multiparametric mapping of 3D whole brain MWF, T 1 , PD, R 2 *, QSM, and B 1 + with a two-minute scan. A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T 1 , proton density (PD), R 2 *, magnetic susceptibility (QSM), and B 1 transmit field (B 1 +). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T 2 *-T 1 spectrum estimation (JMSE) algorithm is proposed to correct for the T 1 saturation effect and B 1 +/B 1 − inhomogeneities in the quantification of MWF. A tissue-prior-based B 1 + estimation algorithm was adapted for B 1 correction in the mapping of T 1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R 2 */T 1app /M 0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T 1 /PD/B 1 +/MWF/QSM/R 2 *, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T 1 /PD/B 1 +/MWF/R 2 *. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI. [ABSTRACT FROM AUTHOR]

Background and Purpose: Apolipoprotein E4 (APOE4) is a major genetic risk factor for Alzheimer's disease. However, the effect of APOE4 status on myelin remains unclear. This study investigated the effect of APOE4 on myelin content in cognitively impaired individuals using T2* gradient echo (GRE)‐based myelin water fraction (MWF) imaging. Methods: Between August 2017 and January 2019, we evaluated 39 cognitively impaired patients (median age, 75 years; male:female = 8:31; Alzheimer's disease: mild cognitive impairment = 11:28). We obtained brain MWF values from white matter hyperintensities (WMHs) and normal‐appearing white matter (NAWM). Linear regression analysis was performed to investigate the relationship between the APOE4 status and MWF and cognitive function and MWF. Results: Among the 39 cognitively impaired patients, nine (23.1%) were APOE4 carriers and 30 (76.9%) were noncarriers. APOE4 carriers had a lower hippocampal volume than noncarriers (p =.045), but other brain volume parameters were not differed. After age adjustment, the APOE4 status was significantly associated with reduced MWF in NAWM (β = –0.310 per allele; p =.049) but not in WMH (β = –0.258 per allele; p =.113). After age adjustment, MWF in NAWM was significantly associated with Mini‐Mental State Examination score (β = 0.313, p =.031). Conclusions: T2* GRE‐based MWF imaging can reveal myelin loss, particularly in NAWM, in cognitively impaired patients among APOE4 carriers. In vivo MWF in NAWM might be a novel imaging marker of Alzheimer's disease, for clarifying the interactions between the white matter and cognitive dysfunction with respect to the APOE4 status. [ABSTRACT FROM AUTHOR]

Purpose: Multicomponent analysis of MRI T2 relaxation time (mcT2) is commonly used for estimating myelin content by separating the signal at each voxel into its underlying distribution of T2 values. This voxel‐based approach is challenging due to the large ambiguity in the multi‐T2 space and the low SNR of MRI signals. Herein, we present a data‐driven mcT2 analysis, which utilizes the statistical strength of identifying spatially global mcT2 motifs in white matter segments before deconvolving the local signal at each voxel. Methods: Deconvolution is done using a tailored optimization scheme, which incorporates the global mcT2 motifs without additional prior assumptions regarding the number of microscopic components. The end results of this process are voxel‐wise myelin water fraction maps. Results: Validations are shown for computer‐generated signals, uniquely designed subvoxel mcT2 phantoms, and in vivo human brain. Results demonstrated excellent fitting accuracy, both for the numerical and the physical mcT2 phantoms, exhibiting excellent agreement between calculated myelin water fraction and ground truth. Proof‐of‐concept in vivo validation is done by calculating myelin water fraction maps for white matter segments of the human brain. Interscan stability of myelin water fraction values was also estimated, showing good correlation between scans. Conclusion: We conclude that studying global tissue motifs prior to performing voxel‐wise mcT2 analysis stabilizes the optimization scheme and efficiently overcomes the ambiguity in the T2 space. This new approach can improve myelin water imaging and the investigation of microstructural compartmentation in general. [ABSTRACT FROM AUTHOR]

PurposeTo develop and measure the reproducibility of 4-min whole brain myelin water fraction (MWF) mapping using fast acquisition with spiral trajectory and T2prep (FAST-T2) sequence at 3T.MethodsExperiments were performed on phantoms, 13 volunteers, and 16 patients with multiple sclerosis. MWF maps were extracted using a spatially constrained non-linear algorithm. The proposed adiabatic modified BIR-4 (mBIR-4) T2prep was compared with the conventional composite T2prep (COMP). The effect of reducing the number of echo times (TEs) from 15 to 6 (reducing scan time from 10 to 4 min) was evaluated. Reproducibility was assessed using correlation analysis, coefficient of variation (COV), and Bland-Altman plots.ResultsCompared with COMP, mBIR-4 provided more accurate T2 in phantoms and better MWF maps in human brains. Reducing the number of TEs had a negligible effect on MWF map quality, with a regional MWF difference of

Aimsdescribe a new "profilometry" framework for the multimetric analysis of white matter tracts, and demonstrate its application to multiple sclerosis (MS) with radial diffusivity (RD) and myelin water fraction (MWF).MethodsA cohort of 15 normal controls (NC) and 141 MS patients were imaged with T1, T2 FLAIR, T2 relaxometry and diffusion MRI (dMRI) sequences. T1 and T2 FLAIR allowed for the identification of patients having lesion(s) on the tracts studied, with a special focus on the forceps minor. T2 relaxometry provided MWF maps, while dMRI data yielded RD maps and the tractography required to compute MWF and RD tract profiles. The statistical framework combined a multivariate analysis of covariance (MANCOVA) and a linear discriminant analysis (LDA) both accounting for age and gender, with multiple comparison corrections.ResultsIn the single-case case study the profilometry visualization showed a clear departure of MWF and RD from the NC normative data at the lesion location(s). Group comparison from MANCOVA demonstrated significant differences at lesion locations, and a significant age effect in several tracts. The follow-up LDA analysis suggested MWF better discriminates groups than RD.Discussion and conclusionWhile progress has been made in both tract-profiling and metrics for white matter characterization, no single framework for a joint analysis of multimodality tract profiles accounting for age and gender is known to exist. The profilometry analysis and visualization appears to be a promising method to compare groups using a single score from MANCOVA while assessing the contribution of each metric with LDA.

Background: The pathophysiology of rigidity in Parkinson's disease (PD) is poorly understood. Multi‐sequence functional and structural brain MRI may further clarify the origin of this clinical characteristic. Purpose To examine both joint and unique relationships of MRI‐based functional and structural imaging modalities to rigidity and other clinical features of PD. Study Type: Retrospective cross‐sectional study. Population 31 PD subjects (aged 68.0 ± 5.9 years, 21 males) with average disease duration 9.3 ± 5.4 years. Field Strength/Sequence: Multi‐echo GRASE, diffusion‐weighted echo planar imaging (EPI), and blood oxygen level dependent contrast EPI T2*‐weighted sequences on a 3T scanner. Assessment Myelin water fraction (MWF) and fractional anisotropy (FA) of 20 white‐matter regions of interest (ROIs), and functional connectivity derived from resting‐state fMRI among 56 ROIs were assessed. The Unified Parkinson's Disease Rating Scale—Part III, Montreal Cognitive Assessment, Beck Depression Index, and Apathy Rating Scales were used to assess motor and non‐motor symptoms. Statistical Tests: Multiset canonical correlation analysis (MCCA) and canonical correlation analysis (CCA) were utilized to examine the joint and unique relationships of multiple imaging measures with clinical symptoms of PD. A permutation test was used to determine statistical significance (P < 0.05). Results: MCCA revealed a single significant component jointly linking MWF, FA, and functional connectivity to age, bradykinesia, and leg agility, non‐motor symptoms of cognition, depression, and apathy, but not rigidity (P = 0.77), tremor (P = 0.50 and 0.67 on the left and right side), or sex (P = 0.54). After controlling for this joint component, CCA found a unique significant association between MWF and rigidity, but no other associations were detected, including with FA (P = 0.87). Data Conclusion: MWF, FA, and functional connectivity can serve as multi‐sequence imaging markers to characterize many PD symptoms. However, rigidity in PD is additionally associated with widespread myelin changes. Evidence Level 4 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Multi-echo gradient-echo (mGRE)-based myelin water fraction (MWF) mapping is a promising myelin water imaging (MWI) modality but is vulnerable to noise and artifact corruption. The linear dimensionality reduction (LDR) method has recently shown improvements with regard to these challenges. However, the magnitude value based low rank operators have been shown to misestimate the MWF for regions with $\text{T}2^\ast $ anisotropy. This paper presents a nonlinear dimensionality reduction (NLDR) method to estimate the MWF map better by encouraging nonlinear low dimensionality of mGRE signal sources. Specifically, we implemented a fully connected deep autoencoder to extract the low-dimensional features of complex-valued signals and incorporated a sparse regularization to separate the anomaly sources that do not reside in the low-dimensional manifold. Simulations and in vivo experiments were performed to evaluate the accuracy of the MWF map under various situations. The proposed NLDR-based MWF improves the accuracy of the MWF map over the conventional nonlinear least-squares method and the LDR-based MWF and maintains robustness against noise and artifact corruption. [ABSTRACT FROM AUTHOR]

Background: Magnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients. Objective: We sought to determine if MRI features have clinical discriminative power among a cohort of MS patients. Methods: Ninety‐six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA). Results: One hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337). Conclusions: These results demonstrate that individual MRI features can identify two patient clusters driven by lesion‐based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient‐specific pathophysiological processes and may guide future therapeutic approaches. [ABSTRACT FROM AUTHOR]

White matter (WM) microstructural properties change across the adult lifespan and with neuronal diseases. Understanding microstructural changes due to aging is paramount to distinguish them from neuropathological changes. Conducted on a large cohort of 147 cognitively unimpaired subjects, spanning a wide age range of 21 to 94 years, our study evaluated sex- and age-related differences in WM microstructure. Specifically, we used diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) indices, sensitive measures of myelin and axonal density in WM, and myelin water fraction (MWF), a measure of the fraction of the signal of water trapped within the myelin sheets, to probe these differences. Furthermore, we examined regional correlations between MWF and DTI indices to evaluate whether the DTI metrics provide information complementary to MWF. While sexual dimorphism was, overall, nonsignificant, we observed region-dependent differences in MWF, that is, myelin content, and axonal density with age and found that both exhibit nonlinear, but distinct, associations with age. Furthermore, DTI indices were moderately correlated with MWF, indicating their good sensitivity to myelin content as well as to other constituents of WM tissue such as axonal density. The microstructural differences captured by our MRI metrics, along with their weak to moderate associations with MWF, strongly indicate the potential value of combining these outcome measures in a multiparametric approach. Furthermore, our results support the last-in-first-out and the gain-predicts-loss hypotheses of WM maturation and degeneration. Indeed, our results indicate that the posterior WM regions are spared from neurodegeneration as compared to anterior regions, while WM myelination follows a temporally symmetric time course across the adult life span.

Multi-echo T2 magnetic resonance images contain information about the distribution of T2 relaxation times of compartmentalized water, from which we can estimate relevant brain tissue properties such as the myelin water fraction (MWF). Regularized non-negative least squares (NNLS) is the tool of choice for estimating non-parametric T2 spectra. However, the estimation is ill-conditioned, sensitive to noise, and highly affected by the employed regularization weight. The purpose of this study is threefold: first, we want to underline that the apparently innocuous use of two alternative parameterizations for solving the inverse problem, which we called the standard and alternative regularization forms, leads to different solutions; second, to assess the performance of both parameterizations; and third, to propose a new Bayesian regularized NNLS method (BayesReg). The performance of BayesReg was compared with that of two conventional approaches (L-curve and Chi-square (X2) fitting) using both regularization forms. We generated a large dataset of synthetic data, acquired in vivo human brain data in healthy participants for conducting a scan-rescan analysis, and correlated the myelin content derived from histology with the MWF estimated from ex vivo data. Results from synthetic data indicate that BayesReg provides accurate MWF estimates, comparable to those from L-curve and X2, and with better overall stability across a wider signal-to-noise range. Notably, we obtained superior results by using the alternative regularization form. The correlations reported in this study are higher than those reported in previous studies employing the same ex vivo and histological data. In human brain data, the estimated maps from L-curve and BayesReg were more reproducible. However, the T2 spectra produced by BayesReg were less affected by over-smoothing than those from L-curve. These findings suggest that BayesReg is a good alternative for estimating T2 distributions and MWF maps.

Background and Purpose: Myelin water fraction (MWF) is a histopathologically validated in vivo myelin marker. As MWF is the proportion of water with a short T2 relative to the total water, increases in water from edema and inflammation may confound MWF determination in multiple sclerosis (MS) lesions. Total water content (TWC) measurement enables calculation of absolute myelin water content (MWC) and can be used to distinguish edema/inflammation from demyelination. We assessed what influence changes in total water might have on MWF by calculating MWC values in new MS lesions. Methods: 3T 32‐echo T2 relaxation data were collected monthly for 6 months from six relapsing‐remitting MS participants. TWC was determined and multiplied with MWF images to calculate corrected MWC images. The effect of this water content correction was examined in 20 new lesions by comparing mean MWF and MWC over time. Results: On average, at lesion first appearance, lesion TWC increased by 6.4% (p =.003; range: –1% to +21%), MWF decreased by 24% (p =.006; range: –70% to +12%), and MWC decreased by 20% (p =.026; range: –68% to +21%), relative to prelesion values. Average TWC in lesions then gradually decreased, whereas MWF and MWC remained low. The shape of the MWF and MWC lesion evolution curves was nearly identical, differing only by an offset. Conclusion: MWF mirrors MWC and is able to monitor myelin in new lesions. Even after taking into account water content increases, MWC still decreased at lesion first appearance attributed to demyelination. [ABSTRACT FROM AUTHOR]

Purpose: To improve estimation of myelin water fraction (MWF) in the brain from multi‐echo gradient‐echo imaging data. Methods: A systematic sensitivity analysis was first conducted to characterize the conventional exponential models used for MWF estimation. A new estimation method was then proposed for improved estimation of MWF from practical gradient‐echo imaging data. The proposed method uses an extended signal model that includes a finite impulse response filter to compensate for practical signal variations. This new model also enables the use of prelearned parameter distributions as well as low‐rank signal structures to improve parameter estimation. The resulting parameter estimation problem was solved optimally in the Bayesian sense. Results: Our sensitivity analysis results showed that the conventional exponential models were very sensitive to measurement noise and modeling errors. Our simulation and experimental results showed that our proposed method provided a substantial improvement in reliability, reproducibility, and robustness of MWF estimates over the conventional methods. Clinical results obtained from stroke patients indicated that the proposed method, with its improved capability, could reveal the loss of myelin in lesions, demonstrating its translational potentials. Conclusion: This paper addressed the problem of robust MWF estimation from gradient‐echo imaging data. A new method was proposed to provide improved MWF estimation in the presence of significant noise and modeling errors. The performance of the proposed method has been evaluated using both simulated and experimental data, showing significantly improved robustness over the existing methods. The proposed method may prove useful for quantitative myelin imaging in clinical applications. [ABSTRACT FROM AUTHOR]

In spite of extensive work, inconsistent findings and lack of specificity in most neuroimaging techniques used to examine age- and gender-related patterns in brain tissue microstructure indicate the need for additional research. Here, we performed the largest Multi-component T 2 relaxometry cross-sectional study to date in healthy adults (N = 145, 18−60 years). Five quantitative microstructure parameters derived from various segments of the estimated T 2 spectra were evaluated, allowing a more specific interpretation of results in terms of tissue microstructure. We found similar age-related myelin water fraction (MWF) patterns in men and women but we also observed differential male related results including increased MWF content in a few white matter tracts, a faster decline with age of the intra- and extra-cellular water fraction and its T 2 relaxation time (i.e. steeper age related negative slopes) and a faster increase in the free and quasi-free water fraction, spanning the whole grey matter. Such results point to a sexual dimorphism in brain tissue microstructure and suggest a lesser vulnerability to age-related changes in women. [Display omitted] [ABSTRACT FROM AUTHOR]

ObjectivesInvestigating the potential of myelin repair strategies in multiple sclerosis (MS) requires an understanding of myelin dynamics during lesion evolution. The objective of this study is to longitudinally measure myelin water fraction (MWF), an MRI biomarker of myelin, in new MS lesions and to identify factors that influence their subsequent myelin content.MethodsTwenty-three MS patients were scanned with whole-brain Fast Acquisition with Spiral Trajectory and T2prep (FAST-T2) MWF mapping at baseline and median follow-up of 6 months. Eleven healthy controls (HC) confirmed the reproducibility of FAST-T2 in white matter regions of interests (ROIs) similar to a lesion size. A random-effect-model was implemented to determine the association between baseline clinical and lesion variables and the subsequent MWF.ResultsROI-based measurements in HCs were highly correlated between scans [mean r = 0.893 (.764-.967)]. In MS patients, 38 gadolinium enhancing (Gd+) and 25 new non-enhancing (Gd-) T2 hyperintense lesions (5.7 months, ±3.8) were identified. Significant improvement in MWF was seen in Gd+ lesions (0.035 ± 0.029, p < 0.001) as compared to Gd- lesions (0.006 ± 0.017, p = 0.065). In the model, a higher baseline MWF (p < 0.001) and the presence of Gd (p < 0.001) were associated with higher subsequent MWF.ConclusionsFAST T2 provides a clinically feasible method to quantify MWF in new MS lesions. The observed influence of baseline MWF, which represents a combined effect of both resolving edema and myelin change within acute lesions, suggests that the extent of initial inflammation impacts final myelin recovery.

The recent Deoni et al. (2013) manuscript proposed that breastfeeding was associated with increased cognitive ability and white-matter in older children (over 26 months), using ms-DESPOT MRI imaging to indirectly measure white matter in children who were either breastfed, formula fed, or combined breast+formula fed. In this response, we identify limitations in drawing causal inference among white matter, cognitive ability, and breastfeeding. We propose that the observed cognitive and neurodevelopmental differences between breastfed and formula-fed infants might actually be caused by the premature introduction of cow's milk in the second year of life, among other contributing factors. The implication of a causal relationship between intelligence and white matter metrics, especially in a developmentally young population, is premature given the recency of this field. The original analyses did not control for important covariates; when comparing both white matter and test scores, mothers were not controlled for age and socio-economic status (SES) and their children were not controlled for gender. Raw test scores, instead of age-adjusted test scores, were used even though the children were of different ages. Mothers were not controlled for reason(s) not to breastfeed, even though many prenatal factors are known to predict this such as stress, parity, obesity, and smoking habits. The observed cognitive ability and white matter benefits identified primarily within the long-term breastfed children are at least partially attributable to other factors such as age, gender, and SES. We suggest methodological approaches to removing such ambiguity, and ways to dissociate cause from effect. The formula and breastfeeding groups didn't show differences until the "formula fed" children likely had been fed cow's milk for longer than they had been fed formula, at 2.2 years. The greatest cognitive differences however were observed within the high SES breastfed infants depending on breastfeeding duration; infants who were breastfed over 15 months showed increased cognitive ability compared to those breastfed less than months. This implicates the source of dairy during the second year of life, and not other SES factors or infant formula, as the most likely nutritional factor responsible for the observed differences within the breastfed children. Given the known nutritional deficiencies of cow's milk, these findings imply infants who received cow's milk during the second year of life were at a disadvantage compared to those who were breastfed, independent of whether they were fed formula or breast milk during the first year of life. This evidence suggests that infants should receive formula in lieu of cow's milk when breast milk is unavailable as a dairy source, until roughly 2 years of age.

The diffuse and continually evolving secondary changes after mild traumatic brain injury (mTBI) make it challenging to assess alterations in brain-behaviour relationships. In this study we used myelin water imaging to evaluate changes in myelin water fraction (MWF) in individuals with chronic mTBI and persistent symptoms and measured their cognitive status using the NIH Toolbox Cognitive Battery. Fifteen adults with mTBI with persistent symptoms and twelve age, gender and education matched healthy controls took part in this study. We found a significant decrease in global white matter MWF in patients compared to the healthy controls. Significantly lower MWF was evident in most white matter region of interest (ROIs) examined including the corpus callosum (separated into genu, body and splenium), minor forceps, right anterior thalamic radiation, left inferior longitudinal fasciculus; and right and left superior longitudinal fasciculus and corticospinal tract. Although patients showed lower cognitive functioning, no significant correlations were found between MWF and cognitive measures. These results suggest that individuals with chronic mTBI who have persistent symptoms have reduced MWF.

Most magnetic resonance imaging (MRI) studies investigating the relationship between regional brain myelination or axonal density and aging have relied upon nonspecific methods to probe myelin and axonal content, including diffusion tensor imaging and relaxation time mapping. While these studies have provided pivotal insights into changes in cerebral architecture with aging and pathology, details of the underlying microstructural alterations have not been fully elucidated. In the current study, we used the BMC-mcDESPOT analysis, a direct and specific multicomponent relaxometry method for imaging of myelin water fraction (MWF), a marker of myelin content, and NODDI, an emerging multicomponent diffusion technique, for neurite density index (NDI) imaging, a proxy of axonal density. We investigated age-related differences in MWF and NDI in several white matter brain regions in a cohort of cognitively unimpaired participants over a wide age range. Our results indicate a quadratic, inverted U-shape, relationship between MWF and age in all brain regions investigated, suggesting that myelination continues until middle age followed by a decrease at older ages, in agreement with previous work. We found a similarly complex regional association between NDI and age, with several cerebral structures also exhibiting a quadratic, inverted U-shape, relationship. This novel observation suggests an increase in axonal density until the fourth decade of age followed by a rapid loss at older ages. We also observed that these age-related differences in MWF and NDI vary across different brain regions, as expected. Finally, our study indicates no significant association between MWF and NDI in most cerebral structures investigated, although this association approached significance in a limited number of brain regions, indicating the complementary nature of their information and encouraging further investigation. Overall, we find evidence of nonlinear associations between age and myelin or axonal density in a sample of well-characterized adults, using direct myelin and axonal content imaging methods.

Demyelination is the key pathological process in multiple sclerosis (MS). The extent of demyelination can be quantified with magnetic resonance imaging by assessing the myelin water fraction (MWF). However, long computation times and high noise sensitivity hinder the translation of MWF imaging to clinical practice. In this work, we introduce a more efficient and noise robust method to determine the MWF using a joint sparsity constraint and a pre-computed B1+-T2 dictionary.A single component analysis with this dictionary is used in an initial step to obtain a B1+ map. The T2 distribution is then determined from a reduced dictionary corresponding to the estimated B1+ map using a combination of a non-negativity and a joint sparsity constraint.The non-negativity constraint ensures that a feasible solution with non-negative contribution of each T2 component is obtained. The joint sparsity constraint restricts the T2 distribution to a small set of T2 relaxation times shared between all voxels and reduces the noise sensitivity.The applied Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm can be implemented efficiently, reducing the computation time by a factor of 50 compared to the commonly used regularized non-negative least squares algorithm. The proposed method was validated in simulations and in 8 healthy subjects with a 3D multi-echo gradient- and spin echo scan at 3 ​T. In simulations, the absolute error in the MWF decreased from 0.031 to 0.013 compared to the regularized NNLS algorithm for SNR ​= ​250. The in vivo results were consistent with values reported in literature and improved MWF-quantification was obtained especially in the frontal white matter. The maximum standard deviation in mean MWF in different regions of interest between subjects was smaller for the proposed method (0.0193) compared to the regularized NNLS algorithm (0.0266). In conclusion, the proposed method for MWF estimation is less computationally expensive and less susceptible to noise compared to state of the art methods. These improvements might be an important step towards clinical translation of MWF measurements.

Neurobiology underlying inter-regional variations - across the human cerebral cortex - in measures derived with multi-modal magnetic resonance imaging (MRI) is poorly understood. Here, we characterize inter-regional variations in a large number of such measures, including T1 and T2 relaxation times, myelin water fraction (MWF), T1w/T2w ratio, mean diffusivity (MD), fractional anisotropy (FA), magnetization transfer ratio (MTR) and cortical thickness. We then employ a virtual-histology approach and relate these inter-regional profiles to those in cell-specific gene expression. Virtual histology revealed that most MRI-derived measures, including T1, T2 relaxation time, MWF, T1w/T2w ratio, MTR, FA and cortical thickness, are associated with expression profiles of genes specific to CA1 pyramidal cells; these genes are enriched in biological processes related to dendritic arborisation. In addition, T2 relaxation time, MWF and T1w/T2w ratio are associated with oligodendrocyte-specific gene-expression profiles, supporting their use as measures sensitive to intra-cortical myelin. MWF contributes more variance than T1w/T2w ratio to the mean oligodendrocyte expression profile, suggesting greater sensitivity to myelin. These cell-specific MRI associations may help provide a framework for determining which MRI sequences to acquire in studies with specific neurobiological hypotheses.

Purpose: Based on a deep learning neural network (NN) algorithm, a super fast and easy to implement data analysis method was proposed for myelin water imaging (MWI) to calculate the myelin water fraction (MWF). Methods: A NN was constructed and trained on MWI data acquired by a 32-echo 3D gradient and spin echo (GRASE) sequence. Ground truth labels were created by regularized non-negative least squares (NNLS) with stimulated echo corrections. Voxel-wise GRASE data from 5 brains (4 healthy, 1 multiple sclerosis (MS)) were used for NN training. The trained NN was tested on 2 healthy brains, 1 MS brain with segmented lesions, 1 healthy spinal cord, and 1 healthy brain acquired from a different scanner. Results: Production of whole brain MWF maps in approximately 33 ​s can be achieved by a trained NN without graphics card acceleration. For all testing regions, no visual differences between NN and NNLS MWF maps were observed, and no obvious regional biases were found. Quantitatively, all voxels exhibited excellent agreement between NN and NNLS (all R2>0.98, p ​

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.

Purpose: Myelin water imaging (MWI) provides a valuable biomarker for myelin, but clinical application has been restricted by long acquisition times. Accelerating the standard multi‐echo T2 acquisition with gradient echoes (GRASE) or by 2D multi‐slice data collection results in image blurring, contrast changes, and other issues. Compressed sensing (CS) can vastly accelerate conventional MRI. In this work, we assessed the use of CS for in vivo human MWI, using a 3D multi spin‐echo sequence. Methods: We implemented multi‐echo T2 relaxation imaging with compressed sensing (METRICS) and METRICS with partial Fourier acceleration (METRICS‐PF). Scan‐rescan data were acquired from 12 healthy controls for assessment of repeatability. MWI data were acquired for METRICS in 9 m:58 s and for METRICS‐PF in 7 m:25 s, both with 1.5 × 2 × 3 mm3 voxels, 56 echoes, 7 ms ΔTE, and 240 × 240 × 170 mm3 FOV. METRICS was compared with a novel multi‐echo spin‐echo gold‐standard (MSE‐GS) MWI acquisition, acquired for a single additional subject in 2 h:2 m:40 s. Results: METRICS/METRICS‐PF myelin water fraction had mean: repeatability coefficient 1.5/1.1, coefficient of variation 6.2/4.5%, and intra‐class correlation coefficient 0.79/0.84. Repeatability metrics comparing METRICS with METRICS‐PF were similar, and both sequences agreed with reference values from literature. METRICS images and quantitative maps showed excellent qualitative agreement with those of MSE‐GS. Conclusion: METRICS and METRICS‐PF provided highly repeatable MWI data without the inherent disadvantages of GRASE or 2D multi‐slice acquisition. CS acceleration allows MWI data to be acquired rapidly with larger FOV, higher estimated SNR, more isotropic voxels and more echoes than with previous techniques. The approach introduced here generalizes to any multi‐component T2 mapping application. [ABSTRACT FROM AUTHOR]

Purpose: To model and correct the dephasing effects in the gradient‐echo signal for arbitrary RF excitation pulses with large flip angles in the presence of macroscopic field variations. Methods: The dephasing of the spoiled 2D gradient‐echo signal was modeled using a numerical solution of the Bloch equations to calculate the magnitude and phase of the transverse magnetization across the slice profile. Additionally, regional variations of the transmit RF field and slice profile scaling due to macroscopic field gradients were included. Simulations, phantom, and in vivo measurements at 3 T were conducted for R2∗ and myelin water fraction (MWF) mapping. Results: The influence of macroscopic field gradients on R2∗ and myelin water fraction estimation can be substantially reduced by applying the proposed model. Moreover, it was shown that the dephasing over time for flip angles of 60° or greater also depends on the polarity of the slice‐selection gradient because of phase variation along the slice profile. Conclusion: Substantial improvements in R2∗ accuracy and myelin water fraction mapping coverage can be achieved using the proposed model if higher flip angles are required. In this context, we demonstrated that the phase along the slice profile and the polarity of the slice‐selection gradient are essential for proper modeling of the gradient‐echo signal in the presence of macroscopic field variations. [ABSTRACT FROM AUTHOR]

Background: Myelin water fraction (MWF) can be quantified with analysis of the T2 * distribution, whereas deducing the T2 * spectrum from several echoes is an underdetermined and ill-posed problem.Purpose: To improve the quantification of myelin water content by using nonnegative jointly sparse (NNJS) optimization.Study Type: Prospective.Subjects: Nine healthy subjects.Field Strength/sequence: 3T, multiecho gradient echo.Assessment: The results of NNJS were compared with that of the nonnegative least square (NNLS)-based algorithms. Simulated models with varied MWF at different noise levels were used to evaluate the accuracy of estimations. In human data, the MWF values of different regions were compared with previous studies and the coefficient of variation (COV) was used to assess the spatial coherence.Statistical Test: Paired t-test.Results: In simulation, the relative errors of MWF obtained from synthesized data with signal-to-noise ratio (SNR) at 500, 200, 150, and 100 were 0.08, 0.09, 0.10, and 0.12 for NNJS, 0.29, 0.43, 0.48, and 0.53 for regularized NNLS (rNNLS), and 0.19, 0.24, 0.25, and 0.26 for spatially-regularized NNLS (srNNLS). In human data, the mean values of MWF produced by NNJS in different regions were consistent with previous studies. Compared with the NNLS-based algorithms, lower COVs generated by NNJS were observed in genu, forceps minor, forceps major, and internal capsule, which were 0.44 ± 0.08, 0.48 ± 0.07, 0.46 ± 0.03, and 0.48 ± 0.09 in NNJS, 0.88 ± 0.28, 0.96 ± 0.18, 0.72 ± 0.03, and 0.85 ± 0.15 in rNNLS, and 0.56 ± 0.17, 0.64 ± 0.14, 0.50 ± 0.04 and 0.58 ± 0.13 in srNNLS.Data Conclusion: Quantitative results of both simulated and human data show that NNJS provides more plausible estimation than the NNLS-based algorithms. Visual advantages of NNJS in spatial consistency can be confirmed by the comparative COV index. The proposed algorithm might improve the quantification of myelin water content.Level Of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;52:146-158. [ABSTRACT FROM AUTHOR]

In conventional gradient-echo myelin water imaging (GRE-MWI), myelin water fraction (MWF) is estimated by fitting the multi-echo gradient recalled echo (mGRE) signal to a pre-assumed numerical model (e.g., multi-component exponential curves or three component exponential curves). However, in mGRE, imaging artifacts (e.g., voxel spread function and physiological noise) and noise render the signal to deviate from the numerical model, leading to misfit of the model parameters. Here, as an alternative to the model-based GRE-MWI, a blind source separation (BSS) technique for the separation of multi-exponential mGRE signal is proposed. Among the various BSS techniques, a modified robust principal component analysis (rPCA) is presented to separate signal sources by enforcing the data-driven properties such as “low rankness” and “sparsity.” Considering the signal evolution of ${T}_{{2}}^\ast $ relaxation (i.e., non-negative exponential decay), low rankness of exponential decay was enforced by nonnegative matrix factorization (NMF) and hankelization. This method provides the separation of slow-decaying, fast-decaying exponential components and artifact components from mGRE images. After the separation, MWF map is reconstructed as the ratio of the fast-decaying component to the total decaying components. The proposed method was demonstrated in numerical simulations and in vivo scans. The method provided a robust estimation of MWF in the presence of statistical noise and imaging artifacts. [ABSTRACT FROM AUTHOR]

Background and Purpose: Myelin water imaging (MWI) and diffusion tensor imaging (DTI) provide information about myelin and axon-related brain microstructure, which can be useful for investigating normal brain development and many childhood brain disorders. While pediatric DTI atlases exist, there are no pediatric MWI atlases available for the 9-10 years old age group. As myelination and structural development occurs throughout childhood and adolescence, studies of pediatric brain pathologies must use age-specific MWI and DTI healthy control data. We created atlases of myelin water fraction (MWF) and DTI metrics for healthy children aged 9-10 years for use as normative data in pediatric neuroimaging studies.Methods: 3D-T1 , DTI, and MWI scans were acquired from 20 healthy children (mean age: 9.6 years, range: 9.2-10.3 years, 4 females). ANTs and FSL registration were used to create quantitative MWF and DTI atlases. Region of interest (ROI) analysis in nine white matter regions was used to compare pediatric MWF with adult MWF values from a recent study and to investigate the correlation between pediatric MWF and DTI metrics.Results: Adults had significantly higher MWF than the pediatric cohort in seven of the nine white matter ROIs, but not in the genu of the corpus callosum or the cingulum. In the pediatric data, MWF correlated significantly with mean diffusivity, but not with axial diffusivity, radial diffusivity, or fractional anisotropy.Conclusions: Normative MWF and DTI metrics from a group of 9-10 year old healthy children provide a resource for comparison to pathologies. The age-specific atlases are ready for use in pediatric neuroimaging research and can be accessed: https://sourceforge.net/projects/pediatric-mri-myelin-diffusion/. [ABSTRACT FROM AUTHOR]