JUST-Net: Jointly unrolled cross-domain optimization based spatio-temporal reconstruction network for accelerated 3D myelin water imaging

PURPOSE

We introduced a novel reconstruction network, jointly unrolled cross-domain optimization-based spatio-temporal reconstruction network (JUST-Net), aimed at accelerating 3D multi-echo gradient-echo (mGRE) data acquisition and improving the quality of resulting myelin water imaging (MWI) maps.

METHOD

An unrolled cross-domain spatio-temporal reconstruction network was designed. The main idea is to combine frequency and spatio-temporal image feature representations and to sequentially implement convolution layers in both domains. The k-space subnetwork utilizes shared information from adjacent frames, whereas the image subnetwork applies separate convolutions in both spatial and temporal dimensions. The proposed reconstruction network was evaluated for both retrospectively and prospectively accelerated acquisition. Furthermore, it was assessed in simulation studies and real-world cases with k-space corruptions to evaluate its potential for motion artifact reduction.

RESULTS

The proposed JUST-Net enabled highly reproducible and accelerated 3D mGRE acquisition for whole-brain MWI, reducing the acquisition time from fully sampled 15:23 to 2:22 min within a 3-min reconstruction time. The normalized root mean squared error of the reconstructed mGRE images increased by less than 4.0%, and the correlation coefficients for MWI showed a value of over 0.68 when compared to the fully sampled reference. Additionally, the proposed method demonstrated a mitigating effect on both simulated and clinical motion-corrupted cases.

CONCLUSION

The proposed JUST-Net has demonstrated the capability to achieve high acceleration factors for 3D mGRE-based MWI, which is expected to facilitate widespread clinical applications of MWI.

So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging

In MRI, researchers have long endeavored to effectively visualize myelin distribution in the brain, a pursuit with significant implications for both scientific research and clinical applications. Over time, various methods such as myelin water imaging, magnetization transfer imaging, and relaxometric imaging have been developed, each carrying distinct advantages and limitations. Recently, an innovative technique named as magnetic susceptibility source separation has emerged, introducing a novel surrogate biomarker for myelin in the form of a diamagnetic susceptibility map. This paper comprehensively reviews this cutting-edge method, providing the fundamental concepts of magnetic susceptibility, susceptibility imaging, and the validation of the diamagnetic susceptibility map as a myelin biomarker that indirectly measures myelin content. Additionally, the paper explores essential aspects of data acquisition and processing, offering practical insights for readers. A comparison with established myelin imaging methods is also presented, and both current and prospective clinical and scientific applications are discussed to provide a holistic understanding of the technique. This work aims to serve as a foundational resource for newcomers entering this dynamic and rapidly expanding field.

Advanced Magnetic Resonance Imaging Biomarkers of the Injured Spinal Cord: A Comparative Study of Imaging and Histology in Human Traumatic Spinal Cord Injury

A significant problem in the diagnosis and management of traumatic spinal cord injury (tSCI) is the heterogeneity of secondary injury and the prediction of neurological outcome. Imaging biomarkers specific to myelin loss and inflammation after tSCI would enable detailed assessment of the pathophysiological processes underpinning secondary damage to the cord. Such biomarkers could be used to biologically stratify injury severity and better inform prognosis for neurological recovery. While much work has been done to establish magnetic resonance imaging (MRI) biomarkers for SCI in animal models, the relationship between imaging findings and the underlying pathology has been difficult to discern in human tSCI because of the paucity of human spinal cord tissue. We utilized post-mortem spinal cords from individuals who had a tSCI to examine this relationship by performing ex vivo MRI scans before histological analysis. We investigated the correlation between the histological distribution of myelin loss and inflammatory cells in the injured spinal cord and a number of myelin and inflammation-sensitive MRI measures: myelin water fraction (MWF), inhomogeneous magnetization transfer ratio (ihMTR), and diffusion tensor and diffusion kurtosis imaging-derived fractional anisotropy (FA) and axial, radial, and mean diffusivity (AD, RD, MD). The histological features were analyzed by staining with Luxol Fast Blue (LFB) for myelin lipids and Class II major histocompatibility complex (Class II MHC) and CD68 for microglia and macrophages. Both MWF and ihMTR were strongly correlated with LFB staining for myelin, supporting the use of both as biomarkers for myelin loss after SCI. A decrease in ihMTR was also correlated with the presence of Class II MHC positive immune cells. FA and RD correlated with both Class II MHC and CD68 and may therefore be useful biomarkers for inflammation after tSCI. Our work demonstrates the utility of advanced MRI techniques sensitive to biological tissue damage after tSCI, which is an important step toward using these MRI techniques in the clinic to aid in decision-making.

Quantifying Brain Myelin Water Fraction in a Guinea Pig Model of Spontaneous Intrauterine Growth Restriction

BACKGROUND

Intrauterine growth restriction (IUGR) is an obstetrical condition where a fetus has not achieved its genetic potential. A consequence of IUGR is a decrease in brain myelin content. Myelin water imaging (MWI) has been used to assess fetal myelin water fraction (MWF) and might potentially assess myelination changes associated with IUGR.

PURPOSE

To quantify and compare the MWF of non-IUGR and IUGR fetal guinea pigs (GPs) in late gestation.

STUDY TYPE

Prospective animal model.

ANIMAL MODEL

Dunkin-Hartley GP model of spontaneous IUGR (mean ± SD: 60 ± 1.2 days gestation; 19 IUGR, 52 control).

FIELD STRENGTH/SEQUENCE

Eight spoiled gradient-recalled (SPGR) gradient echo volumes (flip angles [α]: 2°-16°), and two sets of eight balanced steady-state free precession (bSSFP) gradient echo volumes (α: 8° - 64°), at 0° and 180° phase increments, at 3.0 T.

ASSESSMENT

MWF maps were generated for each fetal GP brain using multicomponent driven equilibrium single pulse observation of T1 /T2 (mcDESPOT). MWF was quantified in the fetal corpus callosum (CC), fornix (FOR), parasagittal white matter (PSW), and whole fetal brain.

STATISTICAL TESTS

Linear regression was performed between five fetal IUGR markers (body volume, body-to-pregnancy volume ratio, brain-to-liver volume ratio, brain-to-placenta volume ratio, and brain-to-body volume ratio) and MWF (coefficient of determination, R2 ). A t-test with a linear mixed model compared the MWF of non-IUGR and IUGR fetal GPs (significance was determined at α < 0.05).

RESULTS

The MWF of the control fetuses are (mean ± SD): 0.23 ± 0.02 (CC), 0.31 ± 0.02 (FOR), 0.28 ± 0.02 (PSW), and 0.20 ± 0.01 (whole brain). The MWF of the IUGR fetuses are (mean ± SD): 0.19 ± 0.02 (CC), 0.27 ± 0.01 (FOR), 0.24 ± 0.03 (PSW), and 0.16 ± 0.01 (whole brain). Significant differences in MWF were found between the non-IUGR and IUGR fetuses in every comparison.

DATA CONCLUSION

The mean MWF of IUGR fetal GPs is significantly lower than non-IUGR fetal GPs.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Myelin water imaging at 0.55 T using a multigradient-echo sequence

PURPOSE

To investigate the prospects of a multigradient-echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T.

METHODS

Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single-voxel fits were compared visually for 0.55 and 3 T.

RESULTS

The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi-exponential model of the NNLS algorithm more accurate.

CONCLUSION

This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields.

Cognitive decline in thrombotic thrombocytopenic purpura survivors: The role of white matter health as assessed by MRI

Immune-mediated thrombotic thrombocytopenic purpura (iTTP) is a rare condition caused by severe ADAMTS13 deficiency, leading to platelet aggregation and thrombosis. Despite treatment, patients are prone to cognitive impairment and depression. We investigated brain changes in iTTP patients during remission using advanced magnetic resonance imaging (MRI) techniques, correlating these changes with mood and neurocognitive tests. Twenty iTTP patients in remission (30 days post-haematological remission) were compared with six healthy controls. MRI scans, including standard and specialized sequences, were conducted to assess white matter health. Increased T1 relaxation times were found in the cingulate cortex (p < 0.05), and elevated T2 relaxation times were observed in the cingulate cortex, frontal, parietal and temporal lobes (p < 0.05). Pathological changes in these areas are correlated with impaired cognitive and depressive scores in concentration, short-term memory and verbal memory. This study highlights persistent white matter damage in iTTP patients, potentially contributing to depression and cognitive impairment. Key regions affected include the frontal lobe and cingulate cortex. These findings have significant implications for the acute and long-term management of iTTP, suggesting a need for re-evaluation of treatment approaches during both active phases and remission. Further research is warranted to enhance our understanding of these complexities.

Applicability of multiple quantitative magnetic resonance methods in genetic brain white matter disorders

BACKGROUND AND PURPOSE

Magnetic resonance imaging (MRI) measures of tissue microstructure are important for monitoring brain white matter (WM) disorders like leukodystrophies and multiple sclerosis. They should be sensitive to underlying pathological changes. Three whole-brain isotropic quantitative methods were applied and compared within a cohort of controls and leukodystrophy patients: two novel myelin water imaging (MWI) techniques (multi-compartment relaxometry diffusion-informed MWI: MCR-DIMWI, and multi-echo T2 relaxation imaging with compressed sensing: METRICS) and neurite orientation dispersion and density imaging (NODDI).

METHODS

For 9 patients with different leukodystrophies (age range 0.4-62.4 years) and 15 control subjects (2.3-61.3 years), T1-weighted MRI, fluid-attenuated inversion recovery, multi-echo gradient echo with variable flip angles, METRICS, and multi-shell diffusion-weighted imaging were acquired on 3 Tesla. MCR-DIMWI, METRICS, NODDI, and quality control measures were extracted to evaluate differences between patients and controls in WM and deep gray matter (GM) regions of interest (ROIs). Pearson correlations, effect size calculations, and multi-level analyses were performed.

RESULTS

MCR-DIMWI and METRICS-derived myelin water fractions (MWFs) were lower and relaxation times were higher in patients than in controls. Effect sizes of MWF values and relaxation times were large for both techniques. Differences between patients and controls were more pronounced in WM ROIs than in deep GM. MCR-DIMWI-MWFs were more homogeneous within ROIs and more bilaterally symmetrical than METRICS-MWFs. The neurite density index was more sensitive in detecting differences between patients and controls than fractional anisotropy. Most measures obtained from MCR-DIMWI, METRICS, NODDI, and diffusion tensor imaging correlated strongly with each other.

CONCLUSION

This proof-of-concept study shows that MCR-DIMWI, METRICS, and NODDI are sensitive techniques to detect changes in tissue microstructure in WM disorders.

Quantitative myelin water imaging using short TR adiabatic inversion recovery prepared echo-planar imaging (STAIR-EPI) sequence

Introduction

Numerous techniques for myelin water imaging (MWI) have been devised to specifically assess alterations in myelin. The biomarker employed to measure changes in myelin content is known as the myelin water fraction (MWF). The short TR adiabatic inversion recovery (STAIR) sequence has recently been identified as a highly effective method for calculating MWF. The purpose of this study is to develop a new clinical transitional myelin water imaging (MWI) technique that combines STAIR preparation and echo-planar imaging (EPI) (STAIR-EPI) sequence for data acquisition.

Methods

Myelin water (MW) in the brain has shorter T1 and T2 relaxation times than intracellular and extracellular water. In the proposed STAIR-EPI sequence, a short TR (e.g., ≤300 ms) together with an optimized inversion time enable robust long T1 water suppression with a wide range of T1 values [i.e., (600, 2,000) ms]. The EPI allows fast data acquisition of the remaining MW signals. Seven healthy volunteers and seven patients with multiple sclerosis (MS) were recruited and scanned in this study. The apparent myelin water fraction (aMWF), defined as the signal ratio of MW to total water, was measured in the lesions and normal-appearing white matter (NAWM) in MS patients and compared with those measured in the normal white matter (NWM) in healthy volunteers.

Results

As seen in the STAIR-EPI images acquired from MS patients, the MS lesions show lower signal intensities than NAWM do. The aMWF measurements for both MS lesions (3.6 ± 1.3%) and NAWM (8.6 ± 1.2%) in MS patients are significantly lower than NWM (10 ± 1.3%) in healthy volunteers (P < 0.001).

Discussion

The proposed STAIR-EPI technique, which can be implemented in MRI scanners from all vendors, is able to detect myelin loss in both MS lesions and NAWM in MS patients.

Myelin biomarkers in the healthy adult brain: Correlation, reproducibility, and the effect of fiber orientation

PURPOSE

We investigated the correlation, reproducibility, and effect of white matter fiber orientation for three myelin-sensitive MRI techniques: magnetization transfer ratio (MTR), inhomogeneous magnetization transfer ratio (ihMTR), and gradient and spin echo-derived myelin water fraction (MWF).

METHODS

We measured the three metrics in 17 white and three deep grey matter regions in 17 healthy adults at 3 T.

RESULTS

We found a strong correlation between ihMTR and MTR (r = 0.70, p < 0.001) and ihMTR and MWF (r = 0.79, p < 0.001), and a weaker correlation between MTR and MWF (r = 0.54, p < 0.001). The dynamic range in white matter was greatest for MWF (2.0%-27.5%), followed by MTR (14.4%-23.2%) and then ihMTR (1.2%-5.4%). The average scan-rescan coefficient of variation for white matter regions was 0.6% MTR, 0.3% ihMTR, and 0.7% MWF in metric units; however, when adjusted by the dynamic range, these became 6.3%, 6.1% and 2.8%, respectively. All three metrics varied with fiber direction: MWF and ihMTR were lower in white matter fibers perpendicular to B₀ by 6% and 1%, respectively, compared with those parallel, whereas MTR was lower by 0.5% at about 40°, with the highest values at 90°. However, separating the apparent orientation dependence by white matter region revealed large dissimilarities in the trends, suggesting that real differences in myelination between regions are confounding the apparent orientation dependence measured using this method.

CONCLUSION

The strong correlation between ihMTR and MWF suggests that these techniques are measuring the same myelination; however, the larger dynamic range of MWF may provide more power to detect small differences in myelin.

Myelin heterogeneity for assessing normal appearing white matter myelin damage in multiple sclerosis

BACKGROUND AND PURPOSE

Conventional MRI measures of multiple sclerosis (MS) disease severity, such as lesion volume and brain atrophy, do not provide information about microstructural tissue changes, which may be driving physical and cognitive progression. Myelin damage in normal-appearing white matter (NAWM) is likely an important contributor to MS disability. Myelin water fraction (MWF) provides quantitative measurements of myelin. Mean MWF reflects average myelin content, while MWF standard deviation (SD) describes variation in myelin within regions. The myelin heterogeneity index (MHI = SD/mean MWF) is a composite metric of myelin content and myelin variability. We investigated how mean MWF, SD, and MHI compare in differentiating MS from controls and their associations with physical and cognitive disability.

METHODS

Myelin water imaging data were acquired from 91 MS participants and 31 healthy controls (HC). Segmented whole-brain NAWM and corpus callosum (CC) NAWM, mean MWF, SD, and MHI were compared between groups. Associations of mean MWF, SD, and MHI with Expanded Disability Status Scale and Symbol Digit Modalities Test were assessed.

RESULTS

NAWM and CC MHI had the highest area under the curve: .78 (95% confidence interval [CI]: .69, .86) and .84 (95% CI: .76, .91), respectively, distinguishing MS from HC.

CONCLUSIONS

Mean MWF, SD, and MHI provide complementary information when assessing regional and global NAWM abnormalities in MS and associations with clinical outcome measures. Examining all three metrics (mean MWF, SD, and MHI) enables a more detailed interpretation of results, depending on whether regions of interest include areas that are more heterogeneous, earlier in the demyelination process, or uniformly injured.

Associations between myelin water imaging and measures of fall risk and functional mobility in multiple sclerosis

BACKGROUND AND PURPOSE

Myelin water fraction (MWF) deficits as measured by myelin water imaging (MWI) have been related to worse motor function in persons with multiple sclerosis (PwMS). However, it is unknown if measures from MWI metrics in motor areas relate to fall risk measures in PwMS. The objective of this study was to examine the relationship between MWI measures in motor areas to performance on clinical measures of fall risk and disability in PwMS.

METHODS

Sixteen individuals with relapsing-remitting MS participated (1 male, 15 female; age 47.1 years [12.3]; Expanded Disability Status Scale 4.0 [range 0-6.5]) and completed measures of walking and fall risk (Timed 25 Foot Walk [T25FW] and Timed Up and Go). MWF and the geometric mean of the intra-/extracellular water T₂ (geomT_2IEW ) values reflecting myelin content and contribution of large-diameter axons/density, respectively, were assessed in three motor-related regions.

RESULTS

The geomT_2IEW of the corticospinal tract (r = -.599; p = .018) and superior cerebellar peduncles (r = -.613; p = .015) demonstrated significant inverse relationships with T25FW, suggesting that decreased geomT_2IEW was related to slower walking. Though not significant, MWF in the corticospinal tract and superior cerebellar peduncles also demonstrated fair relationships with the T25FW, suggesting that worse performance on the T25FW was associated with lower MWF values.

CONCLUSIONS

MWI of key motor regions was associated with walking performance in PwMS. Further MWI studies are needed to identify relationships between pathology and clinical function in PwMS to guide targeted rehabilitation therapies aimed at preventing falls.

Multicomponent MR fingerprinting reconstruction using joint-sparsity and low-rank constraints

PURPOSE

To develop an efficient algorithm for multicomponent MR fingerprinting (MC-MRF) reconstructions directly from highly undersampled data without making prior assumptions about tissue relaxation times and expected number of tissues.

METHODS

The proposed method reconstructs MC-MRF maps from highly undersampled data by iteratively applying a joint-sparsity constraint to the estimated tissue components. Intermediate component maps are obtained by a low-rank multicomponent alternating direction method of multipliers (MC-ADMM) including the non-negativity of tissue weights as an extra regularization term. Over iterations, the used dictionary compression is adjusted. The proposed method (k-SPIJN) is compared with a two-step approach in which image reconstruction and multicomponent estimations are performed sequentially and tested in numerical simulations and in vivo by applying different undersampling factors in eight healthy volunteers. In the latter case, fully sampled data serves as the reference.

RESULTS

The proposed method shows improved precision and accuracy in simulations compared with a state-of-art sequential approach. Obtained in vivo magnetization fraction maps for different tissue types show reduced systematic errors and reduced noise-like effects. Root mean square errors in estimated magnetization fraction maps significantly reduce from 13.0% <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo></mml:mrow> <mml:annotation>$$ \pm $$</mml:annotation></mml:semantics> </mml:math> 5.8% with the conventional, two-step approach to 9.6% <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo></mml:mrow> <mml:annotation>$$ \pm $$</mml:annotation></mml:semantics> </mml:math> 3.9% and 9.6% <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>±</mml:mo></mml:mrow> <mml:annotation>$$ \pm $$</mml:annotation></mml:semantics> </mml:math> 3.2% with the proposed MC-ADMM and k-SPIJN methods, respectively. Mean standard deviation in homogeneous white matter regions reduced significantly from 8.6% to 2.9% (two step vs. k-SPIJN).

CONCLUSION

The proposed MC-ADMM and k-SPIJN reconstruction methods estimate MC-MRF maps from highly undersampled data resulting in improved image quality compared with the existing method.

Myelin Water Imaging of Nerve Recovery in Rehabilitating Stroke Patients

BACKGROUND

Myelin water imaging (MWI) using MRI has been introduced as a method to quantify the integrity of myelin in vivo. However, the investigation of its potential to probe myelin changes has been limited.

PURPOSE

To determine the myelin change using MWI in the corticospinal tract (CST) during the rehabilitation of stroke patients.

STUDY TYPE

Longitudinal.

POPULATION

A total of 24 stroke patients within 6 months from the onset (64.3 ± 16.1 years, 14 women, 10 men) and 10 healthy volunteers (27.0 ± 2.2 years, 2 women, 8 men).

FIELD STRENGTH/SEQUENCE

Three-dimensional multiecho gradient echo sequence and diffusion-weighted echoplanar imaging sequence at 3 T.

ASSESSMENT

The changes of myelin water fraction (MWF) and fractional anisotropy (FA) during rehabilitation were analyzed in the CST and other regions using tractography software and region of interest drawings by the radiologist.

STATISTICAL TESTS

A paired t-test was performed to investigate the change of MRI metrics during rehabilitation. In addition, an independent two-sample t-test was performed to investigate the effects of different rehabilitation protocols. A P-value <0.05 was considered significant.

RESULTS

In the CST, MWF significantly changed from 5.83 ± 0.91% to 6.23 ± 0.97% after rehabilitation while changes of FA (0.442 ± 0.038 to 0.443 ± 0.035) were not significant (P = 0.656). The rate of change in MWF and FA, which were 6.69% and 0.439% respectively, were significantly different. Other regions did not show significant changes (range of MWF change: -3.44% to -1.61%, range of FA change: -1.39% to 0.79%, and range of P-value: 0.144-0.761). Further analysis showed that those with additional robot-assisted rehabilitation had a significantly larger MWF change than those with conventional rehabilitation only (rate of change: 11.2% vs. 3.2%).

DATA CONCLUSION

The feasibility of using MWI to monitor myelin content was demonstrated by showing the MWF changes during rehabilitation.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Feasibility of MRI Quantification of Myelin Water Fraction in the Fetal Guinea Pig Brain

BACKGROUND

Fetal myelination assessment is important for understanding neurodevelopment and neurodegeneration. Myelin water imaging (MWI) quantifies myelin water fraction (MWF), a validated marker for myelin content, and has been used to assess brain myelin in children and neonates.

PURPOSE

To demonstrate that MWI can quantify MWF in fetal guinea pigs (GPs).

STUDY TYPE

Animal model.

ANIMAL MODEL

Nine pregnant, Dunkin-Hartley GPs with 31 fetuses (mean ± standard deviation = 60 ± 1.5 days gestation).

FIELD STRENGTH/SEQUENCE

3D spoiled gradient echo and balanced steady-state free precession sequences at 3.0 T.

ASSESSMENT

MWF maps were reconstructed for maternal and fetal GP brains using the multicomponent driven equilibrium single pulse observation of T₁ and T₂ (mcDESPOT) approach. Myelin basic protein (MBP) stain provided histological validation of the MWF. Regions of interest were placed in the maternal corpus callosum (CC), maternal fornix (FOR), fetal CC, and fetal FOR in MWF maps and MBP stains.

STATISTICAL TESTS

Linear regression between MWF and MBP stain intensity (SI) of all four regions (coefficient of determination, R² ). A paired t-test compared the MWF of maternal and mean fetal CC, MBP SI of maternal and mean fetal CC, MWF of maternal and mean fetal FOR, MBP SI of maternal and mean fetal FOR. A paired t-test with a linear mixed model compared the MWF of fetal CC and fetal FOR, and MBP SI of fetal CC and fetal FOR. A  P value < 0.0083 was considered statistically significant.

RESULTS

The mean MWF of the analyzed regions are as follows (mean ± standard deviation): 0.338 + 0.016 (maternal CC), 0.340 ± 0.017 (maternal FOR), 0.214 ± 0.016 (fetal CC), and 0.305 ± 0.025 (fetal FOR). MWF correlated with MBP SI in all regions (R²  = 0.81). Significant differences were found between MWF and MBP SI of maternal and fetal CC, and MWF and MBP SI of fetal CC and fetal FOR.

DATA CONCLUSION

This study demonstrated the feasibility of MWI in assessing fetal brain myelin content.

EVIDENCE LEVEL

2 Technical Efficacy: Stage 1.

Data-driven myelin water imaging based on T1 and T2 relaxometry

Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T₁ and T₂ relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T₁ /T₂ data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.

Accelerated 3D myelin water imaging using joint spatio-temporal reconstruction

PURPOSE

To enable acceleration in 3D multi-echo gradient echo (mGRE) acquisition for myelin water imaging (MWI) by combining joint parallel imaging (JPI) and joint deep learning (JDL).

METHODS

We implemented a multistep reconstruction process using both advanced parallel imaging and deep learning network which can utilize joint spatiotemporal components between the multi-echo images to further accelerate 3D mGRE acquisition for MWI. In the first step, JPI was performed to estimate missing k-space lines. Next, JDL was implemented to reduce residual artifacts and produce high-fidelity reconstruction by using variable splitting optimization consisting of spatiotemporal denoiser block, data consistency block, and weighted average block. The proposed method was evaluated for MWI with 2D Cartesian uniform under-sampling for each echo, enabling scan times of up to approximately 2 min for 2 mm × 2 mm × 2 mm $2\ {\rm mm} \times 2\ {\rm mm} \times 2\ {\rm mm}$ 3D coverage.

RESULTS

The proposed method showed acceptable MWI quality with improved quantitative values compared to both JPI and JDL methods individually. The improved performance of the proposed method was demonstrated by the low normalized mean-square error and high-frequency error norm values of the reconstruction with high similarity to the fully sampled MWI.

CONCLUSION

Joint spatiotemporal reconstruction approach by combining JPI and JDL can achieve high acceleration factors for 3D mGRE-based MWI.

Data-driven algorithm for myelin water imaging: Probing subvoxel compartmentation based on identification of spatially global tissue features

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.

A data-driven T2 relaxation analysis approach for myelin water imaging: Spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS)

PURPOSE

The decomposition of multi-exponential decay data into a T₂ spectrum poses substantial challenges for conventional fitting algorithms, including non-negative least squares (NNLS). Based on a combination of the resolution limit constraint and machine learning neural network algorithm, a data-driven and highly tailorable analysis method named spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS) was proposed.

THEORY AND METHODS

The theory of SAME-ECOS was derived. Then, a paradigm was presented to demonstrate the SAME-ECOS workflow, consisting of a series of calculation, simulation, and model training operations. The performance of the trained SAME-ECOS model was evaluated using simulations and six in vivo brain datasets. The code is available at https://github.com/hanwencat/SAME-ECOS.

RESULTS

Using NNLS as the baseline, SAME-ECOS achieved over 15% higher overall cosine similarity scores in producing the T₂ spectrum, and more than 10% lower mean absolute error in calculating the myelin water fraction (MWF), as well as demonstrated better robustness to noise in the simulation tests. Applying to in vivo data, MWF from SAME-ECOS and NNLS was highly correlated among all study participants. However, a distinct separation of the myelin water peak and the intra/extra-cellular water peak was only observed in the mean T₂ spectra determined using SAME-ECOS. In terms of data processing speed, SAME-ECOS is approximately 30 times faster than NNLS, achieving a whole-brain analysis in 3 min.

CONCLUSION

Compared with NNLS, the SAME-ECOS method yields much more reliable T₂ spectra in a dramatically shorter time, increasing the feasibility of multi-component T₂ decay analysis in clinical settings.

Multicomponent T2 relaxometry reveals early myelin white matter changes induced by proton radiation treatment

PURPOSE

To investigate MRI myelin water imaging (MWI) by multicomponent T₂ relaxometry as a quantitative imaging biomarker for brain radiation-induced changes and to compare it with DTI.

METHODS

Sixteen patients underwent fractionated proton therapy (PT) receiving dose to the healthy tissue because of direct or indirect (base skull tumors) irradiation. MWI was performed by a multi-echo sequence with 32 equally spaced echoes (10-320 ms). Decay data were processed to identify 3 T₂ compartments: myelin water (Mw) below 40 ms, intra-extracellular water (IEw) between 40 and 250 ms, and free water (CSFw) above 250 ms. Both MWI and DTI scans were acquired pre (pre)-treatment and immediately at the end (end) of PT. After image registration, voxel-wise difference maps, obtained by subtracting MWI and DTI pre from those acquired at the end of PT, were compared with the corresponding biological equivalent dose (BED).

RESULTS

Mw difference showed a positive correlation and IEw difference showed a negative correlation with BED considering end-pre changes (P < .01). The changes in CSFw were not significantly correlated with the delivered BED. The changes in DTI data, considering end-pre acquisitions, showed a positive correlation between fractional anisotropy and the delivered BED.

CONCLUSION

MWI might detect early white matter radiation-induced alterations, providing additional information to DTI, which might improve the understanding of the pathogenesis of the radiation damage.

Cervical cord myelin abnormality is associated with clinical disability in multiple sclerosis

BACKGROUND

Myelin water imaging (MWI) was recently optimized to provide quantitative in vivo measurement of spinal cord myelin, which is critically involved in multiple sclerosis (MS) disability.

OBJECTIVE

To assess cervical cord myelin measurements in relapsing-remitting multiple sclerosis (RRMS) and progressive multiple sclerosis (ProgMS) participants and evaluate the correlation between myelin measures and clinical disability.

METHODS

We used MWI data from 35 RRMS, 30 ProgMS, and 28 healthy control (HC) participants collected at cord level C2/C3 on a 3 T magnetic resonance imaging (MRI) scanner. Myelin heterogeneity index (MHI), a measurement of myelin variability, was calculated for whole cervical cord, global white matter, dorsal column, lateral and ventral funiculi. Correlations were assessed between MHI and Expanded Disability Status Scale (EDSS), 9-Hole Peg Test (9HPT), timed 25-foot walk, and disease duration.

RESULTS

In various regions of the cervical cord, ProgMS MHI was higher compared to HC (between 9.5% and 31%, p ⩽ 0.04) and RRMS (between 13% and 26%, p ⩽ 0.02), and ProgMS MHI was associated with EDSS (r = 0.42-0.52) and 9HPT (r = 0.45-0.52).

CONCLUSION

Myelin abnormalities within clinically eloquent areas are related to clinical disability. MWI metrics have a potential role for monitoring subclinical disease progression and adjudicating treatment efficacy for new therapies targeting ProgMS.

Quantitative Multicomponent T2 Relaxation Showed Greater Sensitivity Than Flair Imaging to Detect Subtle Alterations at the Periphery of Lower Grade Gliomas

Purpose

To demonstrate that quantitative multicomponent T2 relaxation can be more sensitive than conventional FLAIR imaging for detecting cerebral tissue abnormalities.

Methods

Six patients affected by lower-grade non-enhancing gliomas underwent T2 relaxation and FLAIR imaging before a radiation treatment by proton therapy (PT) and were examined at follow-up. The T2 decay signal obtained by a thirty-two-echo sequence was decomposed into three main components, attributing to each component a different T2 range: water trapped in the lipid bilayer membrane of myelin, intra/extracellular water and cerebrospinal fluid. The T2 quantitative map of the intra/extracellular water was compared with FLAIR images.

Results

Before PT, in five patients a mismatch was observed between the intra/extracellular water T2 map and FLAIR images, with peri-tumoral areas of high T2 that typically extended outside the area of abnormal FLAIR hyper-intensity. Such mismatch regions evolved into two different types of patterns. The first type, observed in three patients, was a reduced extension of the abnormal regions on T2 map with respect to FLAIR images (T2 decrease pattern). The second type, observed in two patients, was the appearance of new areas of abnormal hyper-intensity on FLAIR images matching the anomalous T2 map extension (FLAIR increase pattern), that was considered as asymptomatic radiation induced damage.

Conclusion

Our preliminarily results suggest that quantitative T2 mapping of the intra/extracellular water component was more sensitive than conventional FLAIR imaging to subtle cerebral tissue abnormalities, deserving to be further investigated in future clinical studies.

Exploring the Contribution of Myelin Content in Normal Appearing White Matter to Cognitive Outcomes in Cerebral Small Vessel Disease

BACKGROUND

Myelin damage is a salient feature in cerebral small vessel disease (cSVD). Of note, myelin damage extends into the normal appearing white matter (NAWM). Currently, the specific role of myelin content in cognition is poorly understood.

OBJECTIVE

The objective of this exploratory study was to investigate the association between NAWM myelin and cognitive function in older adults with cSVD.

METHODS

This exploratory study included 55 participants with cSVD. NAWM myelin was measured using myelin water imaging and was quantified as myelin water fraction (MWF). Assessment of cognitive function included processing speed (Trail Making Test Part A), set shifting (Trail Making Test Part B minus A), working memory (Verbal Digit Span Backwards Test), and inhibition (Stroop Test). Multiple linear regression analyses assessed the contribution of NAWM MWF on cognitive outcomes controlling for age, education, and total white matter hyperintensity volume. The overall alpha was set at ≤0.05.

RESULTS

After accounting for age, education, and total white matter hyperintensity volume, lower NAWM MWF was significantly associated with slower processing speed (β  = -0.29, p = 0.037) and poorer working memory (β= 0.30, p = 0.048). NAWM MWF was not significantly associated with set shifting or inhibitory control (p > 0.132).

CONCLUSION

Myelin loss in NAWM may play a role in the evolution of impaired processing speed and working memory in people with cSVD. Future studies, with a longitudinal design and larger sample sizes, are needed to fully elucidate the role of myelin as a potential biomarker for cognitive function.

Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging

Damage to the myelin sheath and the neuroaxonal unit is a cardinal feature of multiple sclerosis; however, a detailed characterization of the interaction between myelin and axon damage in vivo remains challenging. We applied myelin water and multi-shell diffusion imaging to quantify the relative damage to myelin and axons (i) among different lesion types; (ii) in normal-appearing tissue; and (iii) across multiple sclerosis clinical subtypes and healthy controls. We also assessed the relation of focal myelin/axon damage with disability and serum neurofilament light chain as a global biological measure of neuroaxonal damage. Ninety-one multiple sclerosis patients (62 relapsing-remitting, 29 progressive) and 72 healthy controls were enrolled in the study. Differences in myelin water fraction and neurite density index were substantial when lesions were compared to healthy control subjects and normal-appearing multiple sclerosis tissue: both white matter and cortical lesions exhibited a decreased myelin water fraction and neurite density index compared with healthy (P < 0.0001) and peri-plaque white matter (P < 0.0001). Periventricular lesions showed decreased myelin water fraction and neurite density index compared with lesions in the juxtacortical region (P < 0.0001 and P < 0.05). Similarly, lesions with paramagnetic rims showed decreased myelin water fraction and neurite density index relative to lesions without a rim (P < 0.0001). Also, in 75% of white matter lesions, the reduction in neurite density index was higher than the reduction in the myelin water fraction. Besides, normal-appearing white and grey matter revealed diffuse reduction of myelin water fraction and neurite density index in multiple sclerosis compared to healthy controls (P < 0.01). Further, a more extensive reduction in myelin water fraction and neurite density index in normal-appearing cortex was observed in progressive versus relapsing-remitting participants. Neurite density index in white matter lesions correlated with disability in patients with clinical deficits (P < 0.01, beta = -10.00); and neurite density index and myelin water fraction in white matter lesions were associated to serum neurofilament light chain in the entire patient cohort (P < 0.01, beta = -3.60 and P < 0.01, beta = 0.13, respectively). These findings suggest that (i) myelin and axon pathology in multiple sclerosis is extensive in both lesions and normal-appearing tissue; (ii) particular types of lesions exhibit more damage to myelin and axons than others; (iii) progressive patients differ from relapsing-remitting patients because of more extensive axon/myelin damage in the cortex; and (iv) myelin and axon pathology in lesions is related to disability in patients with clinical deficits and global measures of neuroaxonal damage.

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

Purpose

The multi‐exponential T₂ decay of the MRI signal from cerebral white matter can be separated into short T₂ components related to myelin water and long T₂ components related to intracellular and extracellular water. In this study, we investigated to what degree the apparent myelin water fraction (MWF) depends on the angle between white matter fibers and the main magnetic field.

Methods

Maps of the apparent MWF were acquired using multi‐echo Carr‐Purcell‐Meiboom‐Gill and gradient‐echo spin‐echo sequences. The Carr‐Purcell‐Meiboom‐Gill sequence was acquired with a TR of 1073 ms, 1500 ms, and 2000 ms. The fiber orientation was mapped with DTI. By angle‐wise pooling the voxels across the brain’s white matter, orientation‐dependent apparent MWF curves were generated.

Results

We found that the apparent MWF varied between 25% and 35% across different fiber orientations. Furthermore, the selection of the TR influences the apparent MWF.

Conclusion

White matter fiber orientation induces a strong systematic bias on the estimation of the apparent MWF. This finding has implications for future research and the interpretation of MWI results in previously published studies.

Probing myelin content of the human brain with MRI: A review

Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin-insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases often entail serious cognitive and physical impairments. Magnetic resonance imaging radically transformed the way these disorders are monitored, offering an irreplaceable tool to noninvasively examine the brain structure. Several advanced techniques based on MRI have been developed to provide myelin-specific contrasts and a quantitative estimation of myelin density in vivo. Here, the vast offer of acquisition strategies developed to date for this task is reviewed. Advantages and pitfalls of the different approaches are compared and discussed.

Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA

PURPOSE

Although several MRI methods have been explored to achieve in vivo myelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the acceleration of multi-echo T₂ acquisitions based on the multi-echo gradient and spin echo (GRASE) sequence using CAIPIRINHA undersampling and adapted k-space reordering patterns.

METHODS

A prototype multi-echo GRASE sequence supporting CAIPIRINHA parallel imaging was implemented. Multi-echo T₂ data were acquired from 12 volunteers using the implemented sequence (1.6 × 1.6 × 1.6 mm³ , 84 slices, acquisition time [TA] = 10:30 min) and a multi-echo spin echo (MESE) sequence as reference (1.6 × 1.6 × 3.2 mm³ , single-slice, TA = 5:41 min). Myelin water fraction (MWF) maps derived from both acquisitions were compared via correlation and Bland-Altman analyses. In addition, scan-rescan datasets were acquired to evaluate the repeatability of the derived maps.

RESULTS

Resulting maps from the MESE and multi-echo GRASE sequences were found to be correlated (r = 0.83). The Bland-Altman analysis revealed a mean bias of -0.2% (P = .24) with the limits of agreement ranging from -3.7% to 3.3%. The Pearson's correlation coefficient among MWF values obtained from the scan-rescan datasets was found to be 0.95 and the mean bias equal to 0.11% (P = .32), indicating good repeatability of the retrieved maps.

CONCLUSION

By combining a 3D multi-echo GRASE sequence with CAIPIRINHA sampling, whole-brain MWF maps were obtained in 10:30 min with 1.6 mm isotropic resolution. The good correlation with conventional MESE-based maps demonstrates that the implemented sequence may be a promising alternative to time-consuming MESE acquisitions.

Artificial neural network for multi-echo gradient echo-based myelin water fraction estimation

PURPOSE

To demonstrate robust myelin water fraction (MWF) mapping using an artificial neural network (ANN) with multi-echo gradient-echo (GRE) signal.

METHODS

Multi-echo gradient-echo signals simulated with a three-pool exponential model were used to generate the training data set for the ANN, which was designed to yield the MWF. We investigated the performance of our proposed ANN for various conditions using both numerical simulations and in vivo data. Simulations were conducted with various SNRs to investigate the performance of the ANN. In vivo data with high spatial resolutions were applied in the analyses, and results were compared with MWFs derived by the nonlinear least-squares algorithm using a complex three-pool exponential model.

RESULTS

The network results for the simulations show high accuracies against noise compared with nonlinear least-squares MWFs: RMS-error value of 5.46 for the nonlinear least-squares MWF and 3.56 for the ANN MWF at an SNR of 150 (relative gain = 34.80%). These effects were also found in the in vivo data, with reduced SDs in the region-of-interest analyses. These effects of the ANN demonstrate the feasibility of acquiring high-resolution myelin water images.

CONCLUSION

The simulation results and in vivo data suggest that the ANN facilitates more robust MWF mapping in multi-echo gradient-echo sequences compared with the conventional nonlinear least-squares method.

Learning-Challenged Youth Show an Abnormal Relationship Between Fronto-Parietal Myelination and Mathematical Ability

BACKGROUND AND PURPOSE

Differences in the microstructure of fronto-parietal white matter tracts have been associated with mathematical achievement. However, much of the supporting evidence relies on nonspecific diffusion-weighted magnetic resonance imaging, making it difficult to isolate the role of myelin in math ability.

METHODS

We used myelin water imaging to measure brain myelin. We related myelin water fraction (MWF) to Woodcock-Johnson III (WJ-III) basic math scores using region of interest (ROI) and tract-based spatial statistics (TBSS) analyses, in 14 typically developing and 36 learning challenged youth aged 9-17 years.

RESULTS

The ROI analysis found a positive relationship between fronto-parietal MWF and math in typically developing youth, but not in learning challenged youth. The relationship between fronto-parietal MWF and math observed in typically developing youth was fully mediated by age. No group differences in fronto-parietal MWF were found between typically developing and learning challenged youth. TBSS also found no group differences in MWF values. TBSS indicated math-MWF relationships extend beyond fronto-parietal tracts to descending and ascending projection tracts in typically developing youth. TBSS identified math-MWF relationships in the cerebral peduncles of learning challenged youth.

CONCLUSIONS

Our results suggest that in typically developing youth, brain myelination contributes to individual differences in basic math achievement. In contrast, youth with learning challenges appear to have less capacity to leverage myelin to improve math achievement.

Myelin water imaging and R2* mapping in neonates: Investigating R2* dependence on myelin and fibre orientation in whole brain white matter

R₂^* relaxation provides a semiquantitative method of detecting myelin, iron and white matter fibre orientation angles. Compared with standard histogram-based analyses, angle-resolved analysis of R₂^* has previously been shown to substantially improve the detection of subtle differences in the brain between healthy siblings of subjects with multiple sclerosis and unrelated healthy controls. Neonates, who are born with very little myelin and iron, and an underdeveloped connectome, provide researchers with an opportunity to investigate whether R₂^* is intimately linked with fibre-angle or myelin content as it is in adults, which may in future studies be explored as a potential white matter developmental biomarker. Five healthy adult volunteers (mean age [±SD] = 31.2 [±8.3] years; three males) were recruited from Vancouver, Canada. Eight term neonates (mean age = 38.6 ± 1.2 weeks; five males) were recruited from the Children's Hospital of Chongqing Medical University neonatal ward. All subjects were scanned on identical 3 T Philips Achieva scanners equipped with an eight-channel SENSE head coil and underwent a multiecho gradient echo scan, a 32-direction DTI scan and a myelin water imaging scan. For both neonates and adults, bin-averaged R₂^* variation across the brain's white matter was found to be best explained by fibre orientation. For adults, this represented a difference in R₂^* values of 3.5 Hz from parallel to perpendicular fibres with respect to the main magnetic field. In neonates, the fibre orientation dependency displayed a cosine wave shape, with a small R₂^* range of 0.4 Hz. This minor relationship in neonates provides further evidence for the key role myelin probably plays in creating this fibre orientation dependence later in life, but suggests limited clinical application in newborn populations. Future studies should investigate fibre-orientation dependency in infants in the first 5 years, when substantial myelin development occurs.

The Myelin Water Fraction Serves as a Marker for Age-Related Myelin Alterations in the Cerebral White Matter - A Multiparametric MRI Aging Study

Quantitative MRI modalities, such as diffusion tensor imaging (DTI) or magnetization transfer imaging (MTI) are sensitive to the neuronal effects of aging of the cerebral white matter (WM), but lack the specificity for myelin content. Myelin water imaging (MWI) is highly specific for myelin and may be more sensitive for the detection of changes in myelin content inside the cerebral WM microstructure. In this multiparametric imaging study, we evaluated the performance of myelin water fraction (MWF) estimates as a marker for myelin alterations during normal-aging. Multiparametric MRI data derived from DTI, MTI and a novel, recently-proposed MWF-map processing and reconstruction algorithm were acquired from 54 healthy subjects (aged 18-79 years) and region-based multivariate regression analysis was performed. MWFs significantly decreased with age in most WM regions (except corticospinal tract) and changes of MWFs were associated with changes of radial diffusivity, indicating either substantial alterations or preservation of myelin content in these regions. Decreases of fractional anisotropy and magnetization transfer ratio were associated with lower MWFs in commissural fiber tracts only. Mean diffusivity had no regional effects on MWF. We conclude that MWF estimates are sensitive for the assessment of age-related myelin alterations in the cerebral WM of normal-aging brains.

Multi-spin echo T2 relaxation imaging with compressed sensing (METRICS) for rapid myelin water imaging

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.

Brain Myelin Water Fraction and Diffusion Tensor Imaging Atlases for 9-10 Year-Old Children

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/.

Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination

Myelin imaging in the central nervous system is essential for monitoring pathologies involving white matter alterations. Various quantitative MRI protocols relying on the modeling of the interactions of water protons with myelinated tissues have shown sensitivities in case of myelin disruption. Some extracted model parameters are more sensitive to demyelination, such as the bound pool fraction (f) in quantitative magnetization transfer imaging (qMTI), the radial diffusivity in diffusion tensor imaging (DTI), and the myelin water fraction (MWF) in myelin water imaging (MWI). A 3D ultrashort echo time (UTE) sequence within an appropriate water suppression condition (Diff-UTE) is also considered for the direct visualization of the myelin semi-solid matrix (Diff-UTE normalized signal; rSPF). In this paper, we aimed at assessing the sensitivities and correlations of the parameters mentioned above to an immuno-histological study of the myelin basic protein (MBP) in a murine model of demyelination at 7 T. We demonstrated a high sensitivity of the MRI metrics to demyelination, and strong Spearman correlations in the corpus callosum between histology, macromolecular proton fraction (ρ>0.87) and Diff-UTE signal (ρ>0.76), but moderate ones with radial diffusivity and MWF (|ρ|<0.70).

Myelin Water Fraction and Intra/Extracellular Water Geometric Mean T2 Normative Atlases for the Cervical Spinal Cord from 3T MRI

BACKGROUND AND PURPOSE

Acquiring and interpreting quantitative myelin-specific MRI data at an individual level is challenging because of technical difficulties and natural myelin variation in the population. To overcome these challenges, we used multiecho T₂ myelin water imaging (MWI) to create T₂ metric healthy population atlases that depict the mean and variation of myelin water fraction (MWF), and intra- and extracellular water mobility as described by geometric mean T₂ (IEGMT₂ ).

METHODS

Cervical cord MWI was performed at 3T on 20 healthy individuals (10M/10F, mean age: 36 years) and 3 relapsing remitting multiple sclerosis (RRMS) participants (1M/2F, age: 39/42/37 years). Anatomical data were collected for the purpose of image segmentation and registration. Atlases were created by coregistering and averaging T₂ metrics from all controls. Voxel-wise z-score maps from 3 RRMS participants were produced to demonstrate the preliminary utility of the MWF and IEGMT₂ atlases.

RESULTS

The average MWF atlas provides a representation of myelin in the spinal cord consistent with well-known spinal cord anatomical characteristics. The IEGMT₂ atlas also depicted structural variations in the spinal cord. Z-score analysis illustrated distinct abnormalities in MWF and IEGMT₂ in the 3 RRMS cases.

CONCLUSIONS

Our findings highlight the potential for using a quantitative T₂ relaxation metric atlas to visualize and detect pathology in spinal cord. Our MWF and IEGMT₂ atlases (URL: https://sourceforge.net/projects/mwi-spinal-cord-atlases/) can serve as normative references in the cervical spinal cord for other studies.

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.

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.

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

Heterogeneous anisotropic magnetic susceptibility of the myelin-water layers causes local magnetic field perturbations in axons

One goal of MRI is to determine the myelin water fraction in neural tissue. One approach is to measure the reduction in T₂ * arising from microscopic perturbations in the magnetic field caused by heterogeneities in the magnetic susceptibility of myelin. In this paper, analytic expressions for the induced magnetic field distribution are derived within and around an axon, assuming that the myelin susceptibility is anisotropic. Previous models considered the susceptibility to be piecewise continuous, whereas this model considers a sinusoidally varying susceptibility. Many conclusions are common in both models. When the magnetic field is applied perpendicular to the axon, the magnetic field in the intraaxonal space is uniformly perturbed, the magnetic field in the myelin sheath oscillates between the lipid and water layers, and the magnetic field in the extracellular space just outside the myelin sheath is heterogeneous. These field heterogeneities cause the spins to dephase, shortening T₂ *. When the magnetic field is applied along the axon, the field is homogeneous within water-filled regions, including between lipid layers. Therefore the spins do not dephase and the magnetic susceptibility has no effect on T₂ *. Generally, the response of an axon is given as the superposition of these two contributions. The sinusoidal model uses a different set of approximations compared with the piecewise model, so their common predictions indicate that the models are not too sensitive to the details of the myelin-water distribution. Other predictions, such as the sensitivity to water diffusion between myelin and water layers, may highlight differences between the two approaches. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Normal-appearing white matter demyelination in neuromyelitis optica spectrum disorder

BACKGROUND AND PURPOSE

Increasing evidence suggests the presence of demyelination in the normal-appearing white matter (NAWM) of patients with neuromyelitis optica spectrum disorder (NMOSD). The objective was to determine the presence of subclinical demyelination in the NAWM of patients with NMOSD using myelin water imaging (MWI).

METHODS

Whole brain and regions-of-interest (ROIs) analyses, including the centrum semiovale, corona radiata, genu and splenium of the corpus callosum, and optic radiation, were conducted in the NAWM of 28 NMOSD patients and 18 healthy controls (HCs) using two MWI modalities: conventional MWI and direct visualization of short transverse relaxation time component (ViSTa) MWI.

RESULTS

Conventional myelin water fractions (MWFs) of the global NAWM and three ROIs (centrum semiovale, corona radiata, and genu of the corpus callosum) were slightly lower in NMOSD patients than in HCs, although not statistically significant. On the other hand, ViSTa MWF values of the global NAWM and all ROIs except the genu of the corpus callosum were significantly lower in NMOSD patients relative to HCs. In particular, the MWF in the optic radiation was significantly reduced in NMOSD patients relative to HCs in both MWI methods, even in patients who had no brain involvement. Additionally, patients with optic neuritis showed lower MWF than patients without optic neuritis and a negative correlation was identified between the MWF of the optic radiation and visual functional system score.

CONCLUSIONS

This study identified the presence of widespread demyelination in the NAWM of NMOSD patients and highlighted the optic radiation as a site of marked demyelination.

Probing signal phase in direct visualization of short transverse relaxation time component (ViSTa)

PURPOSE

To demonstrate the phase evolutions of direct visualization of short transverse relaxation time component (ViSTa) matches with those of myelin water.

METHOD

Myelin water imaging (MWI) measures short transverse signals and has been suggested as a biomarker for myelin. Recently, a new approach, ViSTa, has been proposed to acquire short T2* signals by suppressing long T1 signals. This method does not require any ill-conditioned data processing and therefore provides high-quality images. In this study, the phase of the ViSTa signal was compared with the phase of myelin water simulated by the magnetic susceptibility model of hollow cylinder.

RESULTS

The phase evolutions of the ViSTa signal were similar to the simulated myelin water phase evolutions. When fiber orientation was perpendicular relative to the main magnetic field, both the ViSTa and the simulated myelin water phase showed large positive frequency shifts, whereas the gradient echo phase showed a slightly negative frequency shift. Additionally, the myelin water phase map generated using diffusion tensor imaging (DTI) information revealed a good match with the ViSTa phase image.

CONCLUSION

The results of this study support the origin of ViSTa signal as myelin water. ViSTa phase may potentially provide sensitivity to demyelination.

MRI-based myelin water imaging: A technical review

Multiexponential T2 relaxation time measurement in the central nervous system shows a component that originates from water trapped between the lipid bilayers of myelin. This myelin water component is of significant interest as it provides a myelin-specific MRI signal of value in assessing myelin changes in cerebral white matter in vivo. In this article, the various acquisition and analysis strategies proposed to date for myelin water imaging are reviewed and research conducted into their validity and clinical applicability is presented. Comparisons between the imaging methods are made with a discussion regarding potential difficulties and model limitations.

Multi-slice myelin water imaging for practical clinical applications at 3.0 T

Myelin water imaging is a promising, noninvasive technique for evaluating white matter diseases such as multiple sclerosis and other leukoencephalopathies (LE), and monitoring myelination in early childhood. Unfortunately, poor image quality and a long acquisition time are major obstacles to practical clinical applications. In this study, a novel postprocessing method with an efficient multi-slice acquisition scheme, called T2 spectrum analysis using a weighted regularized non-negative least squares algorithm and nonlocal mean filter (T2SPARC), is presented to overcome these obstacles and achieve a shorter acquisition time, higher image quality, and large volume coverage. In vivo results from healthy volunteers and a patient with LE showed that the T2SPARC method can generate robust and high-quality myelin water fraction maps of 10 slices within 11 min. This method also yields some useful byproducts such as intra- and extracellular water fraction and long T2 tissue water fraction maps, which can quantify lesions in different brain diseases.