Simultaneous measurement of total water content and myelin water fraction in brain at 3 T using a T 2 relaxation based method

Magnetic resonance fingerprinting-based myelin water fraction mapping for the assessment of white matter maturation and integrity in typical development and leukodystrophies

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.

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

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.

The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity

Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) framework in the context of myelin water imaging (MWI); a quantitative MRI technique generally regarded as the most rigorous approach for noninvasive, in vivo measurement of myelin content. The CALIPR framework exploits data redundancy to recover high-quality images from a small fraction of an imaging dataset, which allowed MWI to be acquired with a previously unattainable sequence (fully sampled acquisition 2 hours:57 min:20 s) in 7 min:26 s (4.2% of the dataset, acceleration factor 23.9). CALIPR quantitative metrics had excellent precision (myelin water fraction mean coefficient of variation 3.2% for the brain and 3.0% for the spinal cord) and markedly increased sensitivity to demyelinating disease pathology compared to a current, widely used technique. The CALIPR framework facilitates drastically improved MWI and could be similarly transformative for other quantitative MRI applications.

Microstructure-Informed Myelin Mapping (MIMM) from Gradient Echo MRI using Stochastic Matching Pursuit

Quantification of the myelin content of the white matter is important for studying demyelination in neurodegenerative diseases such as Multiple Sclerosis (MS), particularly for longitudinal monitoring. A novel noninvasive MRI method, called Microstructure-Informed Myelin Mapping (MIMM), is developed to quantify the myelin volume fraction (MVF) by utilizing a multi gradient echo sequence (mGRE) and a detailed biophysical model of tissue microstructure. Myelin is modeled as anisotropic negative susceptibility source based on the Hollow Cylindrical Fiber Model (HCFM), and iron as isotropic positive susceptibility source in the extracellular region. Voxels with a range of biophysical parameters are simulated to create a dictionary of MR echo time magnitude signals and total susceptibility values. MRI signals measured using a mGRE sequence are then matched voxel-by-voxel to the created dictionary to obtain the spatial distributions of myelin and iron. Three different MIMM versions are presented to deal with the fiber orientation dependent susceptibility effects of the myelin sheaths: a basic variation, which assumes fiber orientation is an unknown to fit, two orientation informed variations, which assume the fiber orientation distribution is available either from a separate diffusion tensor imaging (DTI) acquisition or from a DTI atlas based fiber orientation map. While all showed a significant linear correlation with the reference method based on T2-relaxometry (p < 0.0001), DTI orientation informed and atlas orientation informed variations reduced overestimation at white matter tracts compared to the basic variation. Finally, the implications and usefulness of attaining an additional iron susceptibility distribution map are discussed.

Highlights

novel stochastic matching pursuit algorithm called microstructure-informed myelin mapping (MIMM) is developed to quantify Myelin Volume Fraction (MVF) using Magnetic Resonance Imaging (MRI) and microstructural modeling.utilizes a detailed biophysical model to capture the susceptibility effects on both magnitude and phase to quantify myelin and iron.matter fiber orientation effects are considered for the improved MVF quantification in the major fiber tracts.acquired myelin and iron maps may be utilized to monitor longitudinal disease progress.

Association of brain tissue cerebrospinal fluid fraction with age in healthy cognitively normal adults

Background and purpose

Our objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal CSF fraction (CSFF), a potential measure of the subvoxel CSF space.

Materials and methods

A total of 60 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analyses were performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. ROIs include the cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM). In each model, a quadratic term for age was tested using an ANOVA test. A Spearman's correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed.

Results

Regression analyses showed that there was a statistically significant quadratic relationship with age for CSFF in the cortex (p = 0.018), MWF in the cerebral WM (p = 0.033), deep GM (p = 0.017) and cortex (p = 0.029); and IEWF in the deep GM (p = 0.033). There was a statistically highly significant positive linear relationship between age and regional CSFF in the cerebral WM (p < 0.001) and deep GM (p < 0.001). In addition, there was a statistically significant negative linear association between IEWF and age in the cerebral WM (p = 0.017) and cortex (p < 0.001). In the univariate correlation analysis, the normalized lateral ventricle volume correlated with the regional CSFF measurement in the cerebral WM (ρ = 0.64, p < 0.001), cortex (ρ = 0.62, p < 0.001), and deep GM (ρ = 0.66, p < 0.001).

Conclusion

Our cross-sectional data demonstrate that brain tissue water in different compartments shows complex age-dependent patterns. Parenchymal CSFF, a measure of subvoxel CSF-like water in the brain tissue, is quadratically associated with age in the cerebral cortex and linearly associated with age in the cerebral deep GM and WM.

Serum neurofilament light chain correlates with myelin and axonal magnetic resonance imaging markers in multiple sclerosis

BACKGROUND

Neurofilaments are cytoskeletal proteins that are detectable in the blood after neuroaxonal injury. Multiple sclerosis (MS) disease progression, greater lesion volume, and brain atrophy are associated with higher levels of serum neurofilament light chain (NfL), but few studies have examined the relationship between NfL and advanced magnetic resonance imaging (MRI) measures related to myelin and axons. We assessed the relationship between serum NfL and brain MRI measures in a diverse group of MS participants.

METHODS AND MATERIALS

103 participants (20 clinically isolated syndrome, 33 relapsing-remitting, 30 secondary progressive, 20 primary progressive) underwent 3T MRI to obtain myelin water fraction (MWF), geometric mean T₂ (GMT₂), water content, T_1; high angular resolution diffusion imaging (HARDI)-derived axial diffusivity (AD), radial diffusivity (RD), fractional anisotropy (FA); diffusion basis spectrum imaging (DBSI)-derived AD, RD, FA; restricted, hindered, water and fiber fractions; and volume measurements of normalized brain, lesion, thalamic, deep gray matter (GM), and cortical thickness. Multiple linear regressions assessed the strength of association between serum NfL (dependent variable) and each MRI measure in whole brain (WB), normal appearing white matter (NAWM) and T₂ lesions (independent variables), while controlling for age, expanded disability status scale, and disease duration.

RESULTS

Serum NfL levels were significantly associated with metrics of axonal damage (FA: R²_WB-HARDI = 0.29, R²_NAWM-HARDI = 0.31, R²_NAWM-DBSI = 0.30, R²_Lesion-DBSI = 0.31; AD: R²_WB-HARDI=0.31), myelin damage (MWF: R²_WB = 0.29, R²_NAWM = 0.30, RD: R²_WB-HARDI = 0.32, R²_NAWM-HARDI = 0.34, R²_Lesion-DBSI = 0.30), edema and inflammation (T₁: R²_Lesion = 0.32; GMT₂: R²_WB = 0.31, R²_Lesion = 0.31), and cellularity (restricted fraction R²_WB = 0.30, R²_NAWM = 0.32) across the entire MS cohort. Higher serum NfL levels were associated with significantly higher T₂ lesion volume (R² = 0.35), lower brain structure volumes (thalamus R² = 0.31; deep GM R² = 0.33; normalized brain R² = 0.31), and smaller cortical thickness R² = 0.31).

CONCLUSION

The association between NfL and myelin MRI markers suggest that elevated serum NfL is a useful biomarker that reflects not only acute axonal damage, but also damage to myelin and inflammation, likely due to the known synergistic myelin-axon coupling relationship.

Revisiting the T2 spectrum imaging inverse problem: Bayesian regularized non-negative least squares

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.

Water content changes in new multiple sclerosis lesions have a minimal effect on the determination of myelin water fraction values

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.

Characterization of multiple sclerosis neuroinflammation and neurodegeneration with relaxation and diffusion basis spectrum imaging

BACKGROUND

Advanced magnetic resonance imaging (MRI) methods can provide more specific information about various microstructural tissue changes in multiple sclerosis (MS) brain. Quantitative measurement of T₁ and T₂ relaxation, and diffusion basis spectrum imaging (DBSI) yield metrics related to the pathology of neuroinflammation and neurodegeneration that occurs across the spectrum of MS.

OBJECTIVE

To use relaxation and DBSI MRI metrics to describe measures of neuroinflammation, myelin and axons in different MS subtypes.

METHODS

103 participants (20 clinically isolated syndrome (CIS), 33 relapsing-remitting MS (RRMS), 30 secondary progressive MS and 20 primary progressive MS) underwent quantitative T₁, T₂, DBSI and conventional 3T MRI. Whole brain, normal-appearing white matter, lesion and corpus callosum MRI metrics were compared across MS subtypes.

RESULTS

A gradation of MRI metric values was seen from CIS to RRMS to progressive MS. RRMS demonstrated large oedema-related differences, while progressive MS had the most extensive abnormalities in myelin and axonal measures.

CONCLUSION

Relaxation and DBSI-derived MRI measures show differences between MS subtypes related to the severity and composition of underlying tissue damage. RRMS showed oedema, demyelination and axonal loss compared with CIS. Progressive MS had even more evidence of increased oedema, demyelination and axonal loss compared with CIS and RRMS.

Age- and gender-related differences in brain tissue microstructure revealed by multi-component T2 relaxometry

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 T₂ 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 T₂ 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 T₂ 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.

Comparison of non-parametric T2 relaxometry methods for myelin water quantification

Multi-component T₂ relaxometry allows probing tissue microstructure by assessing compartment-specific T₂ relaxation times and water fractions, including the myelin water fraction. Non-negative least squares (NNLS) with zero-order Tikhonov regularization is the conventional method for estimating smooth T₂ distributions. Despite the improved estimation provided by this method compared to non-regularized NNLS, the solution is still sensitive to the underlying noise and the regularization weight. This is especially relevant for clinically achievable signal-to-noise ratios. In the literature of inverse problems, various well-established approaches to promote smooth solutions, including first-order and second-order Tikhonov regularization, and different criteria for estimating the regularization weight have been proposed, such as L-curve, Generalized Cross-Validation, and Chi-square residual fitting. However, quantitative comparisons between the available reconstruction methods for computing the T₂ distribution, and between different approaches for selecting the optimal regularization weight, are lacking. In this study, we implemented and evaluated ten reconstruction algorithms, resulting from the individual combinations of three penalty terms with three criteria to estimate the regularization weight, plus non-regularized NNLS. Their performance was evaluated both in simulated data and real brain MRI data acquired from healthy volunteers through a scan-rescan repeatability analysis. Our findings demonstrate the need for regularization. As a result of this work, we provide a list of recommendations for selecting the optimal reconstruction algorithms based on the acquired data. Moreover, the implemented methods were packaged in a freely distributed toolbox to promote reproducible research, and to facilitate further research and the use of this promising quantitative technique in clinical practice.

Quantification of Myelinated Nerve Fraction and Degeneration in Spinal Cord Neuropil by SHIFT MRI

BACKGROUND

Neurodegeneration is a complex cellular process linked to prompt changes in myelin integrity and gradual neuron loss. Current imaging techniques offer estimations of myelin volumes in lesions/remyelinated areas but are limited to detect subtle injury.

PURPOSE

To investigate whether measurements detected by a signal hierarchically isolated as a function of time-to-echo (SHIFT) MRI technique can determine changes in myelin integrity and fiber axolemma.

STUDY TYPE

Prospective animal model.

ANIMAL MODEL

Surgically demyelinated spinal cord (SC) injury model in rodents (n = 6).

FIELD STRENGTH/SEQUENCE

Gradient-echo spin-echo at 3T.

ASSESSMENT

Multicompartment T₂ relaxations were computed by SHIFT MRI in 75-microns-resolution images of the SC injury penumbra region 2 weeks post-trauma. G-ratio and axolemma delamination were assessed by transmission electron microscopy (TEM) in intact and injured samples. SC myelinated nerve fraction was computed by SHIFT MRI prospectively and assessed histologically.

STATISTICAL TESTS

Relations between SHIFT-isolated T₂ -components and TEM measurements were studied using linear regression and t-tests. Pearson's correlation and significance were computed to determine the SHIFT's sensitivity to detect myelinated fibers ratio in gray matter. Regularized least-squares-based ranking analysis was employed to determine SHIFT MRI's ability to discern intact and injured myelinated nerves.

RESULTS

Biexponential signals isolated by SHIFT MRI for intact vs. lesion penumbra exhibited changes in T₂ , shifting from intermediate components (25 ± 2 msec) to long (43 ± 11 msec) in white matter, and similarly in gray matter regions-of-interest (31 ± 2 to 46 ± 16 msec). These changes correlated highly with TEM g-ratio and axon delamination measurements (P < 0.05). Changes in short T₂ components were observed but not statistically significant (8.5 ± 0.5 to 7 ± 3 msec, P = 0.445, and 4.0 ± 0.9 to 7 ± 3 msec, P = 0.075, respectively). SHIFT MRI's ability to detect myelinated fibers within gray matter was confirmed (P < 0.001).

DATA CONCLUSION

Changes detected by SHIFT MRI are associated with abnormal intermembrane spaces formed upon mild injury, directly correlated with early neuro integrity loss. Level of Evidence 1 Technical Efficacy Stage 2.

Effects of Alzheimer's disease and formalin fixation on the different mineralised-iron forms in the human brain

Iron accumulation in the brain is a phenomenon common to many neurodegenerative diseases, perhaps most notably Alzheimer’s disease (AD). We present here magnetic analyses of post-mortem brain tissue of patients who had severe Alzheimer’s disease, and compare the results with those from healthy controls. Isothermal remanent magnetization experiments were performed to assess the extent to which different magnetic carriers are affected by AD pathology and formalin fixation. While Alzheimer’s brain material did not show higher levels of magnetite/maghemite nanoparticles than corresponding controls, the ferrihydrite mineral, known to be found within the core of ferritin proteins and hemosiderin aggregates, almost doubled in concentration in patients with Alzheimer’s pathology, strengthening the conclusions of our previous studies. As part of this study, we also investigated the effects of sample preparation, by performing experiments on frozen tissue as well as tissue which had been fixed in formalin for a period of 5 months. Our results showed that the two different preparations did not critically affect the concentration of magnetic carriers in brain tissue, as observable by SQUID magnetometry.

Conduction delays in the visual pathways of progressive multiple sclerosis patients covary with brain structure

In developed countries, multiple sclerosis (MS) is the leading cause of non-traumatic neurological disability in young adults. MS is a chronic demyelinating disease of the central nervous system, in which myelin is attacked, changing white matter structure and leaving lesions. The demyelination has a direct effect on white matter conductivity. This effect can be examined in the visual system, where damage is highly prevalent in MS, leading to substantial delays in conduction, commonly measured with visual evoked potentials (VEPs). The structural damage to the visual system in MS is often estimated with MRI measurements in the white matter. Recent developments in quantitative MRI (qMRI) provide improved sensitivity to myelin content and new structural methods allow better modeling of the axonal structure, leading researchers to link white matter microstructure to conduction properties of action potentials along fiber tracts. This study attempts to explain the variance in conduction latencies down the visual pathway using structural measurements of both the retina and the optic radiation (OR). Forty-eight progressive MS patients, participants in a longitudinal stem-cell therapy clinical trial, were included in this study, three and six months post final treatment. Twenty-seven patients had no history of optic neuritis, and were the main focus of this study. All participants underwent conventional MRI scans, as well as diffusion MRI and qMRI sequences to account for white matter microstructure. Optical coherence tomography scans were also obtained, and peripapillary retinal nerve fiber layer (pRNFL) thickness and macular volume measurements were extracted. Finally, latencies of recorded VEPs were estimated. Our results show that in non-optic neuritis progressive MS patients there is a relationship between the VEP latency and both retinal damage and OR lesion load. In addition, we find that qMRI values, sampled along the OR, are also correlated with VEP latency. Finally, we show that combining these parameters using PCA we can explain more than 40% of the inter-subject variance in VEP latency. In conclusion, this study contributes to understanding the relationship between the structural properties and conduction in the visual system in disease. We focus on the visual system, where the conduction latencies can be estimated, but the conclusions could be generalized to other brain systems where the white matter structure can be measured. It also highlights the importance of having multiple parameters when assessing the clinical stages of MS patients, which could have major implications for future studies of other white matter diseases.

T2 mapping in orbital masses: preliminary study on differential diagnostic ability of T2 relaxation time

Background

T2 mapping has been proven to be useful in tumor characterization. As to orbital masses, its diagnostic value needs to be investigated.

Purpose

To evaluate the usefulness of T2 mapping in orbital masses and the ability of T2 relaxation time in differentiating malignant from benign orbital masses.

Material and Methods

Forty-seven patients with solid orbital masses (33 benign and 14 malignant) who underwent T2 mapping examination for preoperative assessment were enrolled in the current study. T2 mapping was acquired using 16 TE values (range 12–192 ms; delta TE 12 ms). Mean T2 relaxation time was calculated based on the whole mass region of interest and compared between the malignant and benign groups using the unpaired t-test. Receiver operating characteristic curve analysis was adopted to calculate its diagnostic value.

Results

Malignant orbital masses showed significantly lower T2 relaxation time than benign masses (76.4 ± 13.0 ms vs. 119.1 ± 20.4 ms; P < 0.001). If setting a T2 relaxation time of 89.5 ms as the threshold value, optimal differentiating performance could be achieved (area under the curve 0.936; sensitivity 100.0%; specificity 87.9%; accuracy 91.5%; positive predictive value 77.8%; negative predictive value 100%).

Conclusion

T2 mapping and its derived T2 relaxation time could provide quantitative information and serve as a supplementary imaging marker for differentiating malignant from benign orbital masses.

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.

So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging

Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T₂ -, T₂ *-, T₁ -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.

In Vivo Magnetic Resonance Imaging of the Rat Vocal Folds After Systemic Dehydration and Rehydration

Objective Consuming less water (systemic dehydration) has long been thought to dehydrate the vocal folds. An in vivo, repeated measures study tested the assumption that systemic dehydration causes vocal fold dehydration. Proton density (PD)-weighted magnetic resonance imaging (MRI) of rat vocal folds was employed to investigate (a) whether varying magnitudes of systemic dehydration would dehydrate the vocal folds and (b) whether systemic rehydration would rehydrate the vocal folds. Method Male (n = 25) and female (n = 14) Sprague Dawley rats were imaged with 7T MRI, and normalized PD-weighted signal intensities were obtained at predehydration, following dehydration, and following rehydration. Animals were dehydrated to 1 of 3 levels by water withholding to induce body weight loss: mild (< 6% body weight loss), moderate (6%-10% body weight loss), and marked (> 10% body weight loss). Results There was a significant decrease in vocal fold signal intensities after moderate and marked dehydration (p < .0167). Rehydration increased the normalized signal intensity to predehydration levels for only the moderate group (p < .0167). Normalized signal intensity did not significantly change after mild dehydration or when the mildly dehydrated animals were rehydrated. Additionally, there were no significant differences in PD-weighted MRI normalized signal intensity between male and female rats (p > .05). Conclusion This study provides evidence supporting clinical voice recommendations for rehydration by increasing water intake after an acute, moderate systemic dehydration event. However, acute systemic dehydration of mild levels did not dehydrate the vocal folds as observed by PD-weighted MRI. Future programmatic research will focus on chronic, recurring systemic dehydration.

Evidence That Cannabis Exposure, Abuse, and Dependence Are Related to Glutamate Metabolism and Glial Function in the Anterior Cingulate Cortex: A 1H-Magnetic Resonance Spectroscopy Study

There is evidence that long-term cannabis use is associated with alterations to glutamate neurotransmission and glial function. In this study, 26 long-term cannabis users (males=65.4%) and 47 non-cannabis using healthy controls (males=44.6%) underwent proton magnetic resonance spectroscopy (¹H-MRS) of the anterior cingulate cortex (ACC) in order to characterize neurometabolite alterations in cannabis users and to examine associations between neurometabolites, cannabis exposure, and cannabis use behaviors. Myo-inositol, a marker of glial function, and glutamate metabolites did not differ between healthy controls and cannabis users or cannabis users who met criteria for DSM5 cannabis use disorder (n=17). Lower myo-inositol, a putative marker of glial function, was related to greater problematic drug use (F_1,22 = 11.95, p=.002; Cohen's f=0.59, large effect; Drug Abuse Screening Test) and severity of cannabis dependence (F_1,22 = 6.61, p=.17; Cohen's f=0.44, large effect). Further, past-year cannabis exposure exerted different effects on glutamate and glutamate+glutamine in males and females (glutamate: F_1,21 = 6.31, p=.02; glutamate+glutamine: F_1,21 = 7.20, p=.014), such that greater past-year cannabis exposure was related to higher concentrations of glutamate metabolites in male cannabis users (glutamate: F_1,14 = 25.94, p=.00016; Cohen's f=1.32, large effect; glutamate+glutamine: F_1,14 = 23.24, p=.00027, Cohen's f=1.24, large effect) but not in female cannabis users (glutamate: F_1,6 = 1.37, p=0.78; glutamate+glutamine: F_1,6 = 0.001, p=.97). The present results extend existing evidence of altered glial function and glutamate metabolism with cannabis use by providing evidence linking problematic drug use behaviors with glial function as measured with myo-inositol and recent chronic cannabis exposure to alterations in glutamate metabolism. This provides novel directions for the interrogation of the impact of cannabis use on brain neurochemistry.

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.

Differential levels of prefrontal cortex glutamate+glutamine in adults with antisocial personality disorder and bipolar disorder: A proton magnetic resonance spectroscopy study

As the main excitatory neurotransmitter in the central nervous system, glutamate, as measured in combination with glutamine (Glx), is implicated in several psychopathologies when levels are aberrant. One illness that shows heightened Glx levels is bipolar disorder (BD), an illness characterized by high impulsivity. In addition, although animal studies have reported elevated levels of Glx in aggressive and impulsive phenotypes, no study, to our knowledge, has reported Glx in the human cortex in relation to aggression. Here, we addressed the question of whether elevated levels of Glx would be present in patients with BD and antisocial personality disorder (ASPD), a condition associated with aggression and, like BD, also presents high impulsivity. We recruited individuals with ASPD (n = 18), individuals with BD (n = 16), and a healthy control group (n = 24). We used proton magnetic resonance spectroscopy to measure relative neurometabolite concentrations in the left dorsolateral prefrontal cortex (dlPFC) and supra-genual anterior cingulate cortex (ACC), two brain regions associated with impulsivity and behavior control. We found significantly elevated levels of Glx in the ASPD group relative to the BD and healthy control groups in the dlPFC (p = .014), and a positive correlation between Glx levels and aggression in the dlPFC in the ASPD group alone (r = .59, p = .026). These findings suggest a link between aggression in ASPD and Glx levels.

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

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

Iron, Myelin, and the Brain: Neuroimaging Meets Neurobiology

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

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

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

Ultra-short echo time imaging with multiple echo refocusing for porous media T2 mapping

T₂ relaxation time measurement is a powerful tool to distinguish signal components in porous media. As T₂ weighting is generally achieved by spin-echo based methods, it is very challenging to capture very short T₂ relaxation time components, approximately 1 ms, with high resolution spatial encoding. It is especially challenging when T₂ relaxation times of the other signal components are not known a priori. We propose a method, combining ultrashort echo time (UTE) imaging with multiple spin echo refocusing, to generate a series of images with T₂ weighting. The T₂ decay curves for each image voxel were extracted, and multiple T₂ relaxation components were quantitatively evaluated. The method has been applied to a fast relaxation system, namely, moisture content in wood samples to differentiate cell wall (bound) water and cell cavity (lumen) water.

Proton density-weighted laryngeal magnetic resonance imaging in systemically dehydrated rats

OBJECTIVES/HYPOTHESIS

Dehydrated vocal folds are inefficient sound generators. Although systemic dehydration of the body is believed to induce vocal fold dehydration, this causative relationship has not been demonstrated in vivo. Here we investigate the feasibility of using in vivo proton density (PD)-weighted magnetic resonance imaging (MRI) to demonstrate hydration changes in vocal fold tissue following systemic dehydration in rats.

STUDY DESIGN

Animal study.

METHODS

Sprague-Dawley rats (n = 10) were imaged at baseline and following a 10% reduction in body weight secondary to withholding water. In vivo, high-field (7 T), PD-weighted MRI was used to successfully resolve vocal fold and salivary gland tissue structures.

RESULTS

Normalized signal intensities within the vocal fold decreased postdehydration by an average of 11.38% ± 3.95% (mean ± standard error of the mean [SEM], P = .0098) as compared to predehydration levels. The salivary glands experienced a similar decrease in normalized signal intensity by an average of 10.74% ± 4.14% (mean ± SEM, P = .0195) following dehydration. The correlation coefficient (percent change from dehydration) between vocal folds and salivary glands was 0.7145 (P = .0202).

CONCLUSIONS

Ten percent systemic dehydration induced vocal fold dehydration as assessed by PD-weighted MRI. Changes in the hydration state of vocal fold tissue were highly correlated with that of the salivary glands in dehydrated rats in vivo. These preliminary findings demonstrate the feasibility of using PD-weighted MRI to quantify hydration states of the vocal folds and lay the foundation for further studies that explore more routine and realistic magnitudes of systemic dehydration and rehydration.

LEVEL OF EVIDENCE

NA. Laryngoscope, 128:E222-E227, 2018.

Evaluating g-ratio weighted changes in the corpus callosum as a function of age and sex

Recent years have seen a growing interest in relating MRI measurements to the structural-biophysical properties of white matter fibers. The fiber g-ratio, defined as the ratio between the inner and outer radii of the axon myelin sheath, is an important structural property of white matter, affecting signal conduction. Recently proposed modeling methods that use a combination of quantitative-MRI signals, enable a measurement of the fiber g-ratio in vivo. Here we use an MRI-based g-ratio estimation to observe the variance of the g-ratio within the corpus callosum, and evaluate sex and age related differences. To estimate the g-ratio we used a model (Stikov et al., 2011; Duval et al., 2017) based on two different WM microstructure parameters: the relative amounts of myelin (myelin volume fraction, MVF) and fibers (fiber volume fraction, FVF) in a voxel. We derived the FVF from the fractional anisotropy (FA), and estimated the MVF by using the lipid and macromolecular tissue volume (MTV), calculated from the proton density (Mezer et al., 2013). In comparison to other methods of estimating the MVF, MTV represents a stable parameter with a straightforward route of acquisition. To establish our model, we first compared histological MVF measurements (West et al., 2016) with the MRI derived MTV. We then implemented our model on a large database of 92 subjects (44 males), aged 7 to 81, in order to evaluate age and sex related changes within the corpus callosum. Our results show that the MTV provides a good estimation of MVF for calculating g-ratio, and produced values from the corpus callosum that correspond to those found in animals ex vivo and are close to the theoretical optimum, as well as to published in vivo data. Our results demonstrate that the MTV derived g-ratio provides a simple and reliable in vivo g-ratio-weighted (GR*) measurement in humans. In agreement with theoretical predictions, and unlike other tissue parameters measured with MRI, the g-ratio estimations were found to be relatively stable with age, and we found no support for a significant sexual dimorphism with age.