Effect of intercompartmental water exchange on the apparent myelin water fraction in multiexponential T2 measurements of rat spinal cord

Empirical relationship between TEM-derived myelin volume fraction and MRI-R2 values in aging ex vivo rat corpus callosum

Ex vivo ratiometric measurements of short- and long-T2 components using the multiple spin echo sequence of MRI are often employed to evaluate alterations in myelin content in the white matter (WM) of the brain. However, the relationship between absolute MRI-T2 values (long-T2 component) and myelin volumetric information in aged ex vivo rodent WM appears to be influenced by factors such as animal species, field strength, and fixation durations/washing. Here, multiple spin echo sequence-based MRI-R2 (the reciprocal of T2) values were measured in the corpus callosum (CC) region in the post-mortem rat brains (n = 9) of different age groups with common fixation techniques without washing at 7 T. Transmission electron microscopy (TEM)-based quantification of myelin volume fraction (MVF) and corresponding Monte-Carlo simulation to estimate relaxation rates (R2,IE) due to diffusion in the presence of inhomogeneous magnetic field perturbation in intra- and extra-cellular (IE) spaces were respectively performed. To determine whether the short-T2 components originating from myelin water were mixed with long-T2 components from IE water or were undetectable, the MVF values obtained from TEM results were respectively compared with MRI-R2 and R2,IE values. A significant correlation (Pearson's correlation coefficient r = 0.8763; p < 0.01) of average MRI-R2 and MVF values was observed. Estimated R2,IE values from Monte-Carlo simulations in IE water signals were also positively correlated (r = 0.8281; p < 0.01) with MVF values. However, the magnitudes of R2,IE values were much smaller than those observed for MRI-R2 values, indicating that changes in R2 related MVF are likely dominated by myelin water components. Such comparisons between independent parameters from MRI, TEM, and simulations support the suggestion that myelin water signals were indistinguishably mixed to exhibit mono-exponential T2 relaxation, and multiple spin echo sequence-based MRI-R2 values in aging ex vivo rat CC without prolonged washing still reflect the volumetric information of myelin, likely due to enhanced water exchange across the myelin.

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.

Measuring water exchange on a preclinical MRI system using filter exchange and diffusion time dependent kurtosis imaging

PURPOSE

Filter exchange imaging (FEXI) and diffusion time (t)-dependent diffusion kurtosis imaging (DKI(t)) are both sensitive to water exchange between tissue compartments. The restrictive effects of tissue microstructure, however, introduce bias to the exchange rate obtained by these two methods, as their interpretation conventionally rely on the Kärger model of barrier limited exchange between Gaussian compartments. Here, we investigated whether FEXI and DKI(t) can provide comparable exchange rates in ex vivo mouse brains.

THEORY AND METHODS

FEXI and DKI(t) data were acquired from ex vivo mouse brains on a preclinical MRI system. Phase cycling and negative slice prewinder gradients were used to minimize the interferences from imaging gradients.

RESULTS

In the corpus callosum, apparent exchange rate (AXR) from FEXI correlated with the exchange rate (the inverse of exchange time, 1/τex ) from DKI(t) along the radial direction. In comparison, discrepancies between FEXI and DKI(t) were found in the cortex due to low filter efficiency and confounding effects from tissue microstructure.

CONCLUSION

The results suggest that FEXI and DKI(t) are sensitive to the same exchange processes in white matter when separated from restrictive effects of microstructure. The complex microstructure in gray matter, with potential exchange among multiple compartments and confounding effects of microstructure, still pose a challenge for FEXI and DKI(t).

Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling

PURPOSE

The effective transverse relaxation rate (R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (θ $$ \uptheta $$ ) complicate interpretation. The α- andθ $$ \uptheta $$ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

METHODS

We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 2 * $$ {\mathrm{R}}_2^{\ast } $$ into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically.

RESULTS

R 2 * $$ {\mathrm{R}}_2^{\ast } $$ increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity.

CONCLUSION

We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

A pilot study comparing myelin measurements from myelin water imaging and 11C-PIB PET in multiple sclerosis

MRI-based myelin water fraction (MWF) and PET-based Pittsburgh compound B (PiB) imaging both have potential to measure myelin in multiple sclerosis (MS). We characterised the differences in MWF and PiB binding in MS lesions relative to normal-appearing white matter and assessed the correlation between MWF and PiB binding in 11 MS participants and 3 healthy controls within 14 white matter regions of interest. Both PiB binding and MWF were reduced in MS lesions relative to NAWM, and a modest within subject correlation between MWF and PiB binding was found. This pilot study shows that MWF and PET-PiB provide different information about myelin loss in MS.

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.

Data-driven separation of MRI signal components for tissue characterization

PURPOSE

MRI can be utilized for quantitative characterization of tissue. To assess e.g. water fractions or diffusion coefficients for compartments in the brain, a decomposition of the signal is necessary. Imposing standard models carries the risk of estimating biased parameters if model assumptions are violated. This work introduces a data-driven multicomponent analysis, the monotonous slope non-negative matrix factorization (msNMF), tailored to extract data features expected in MR signals.

METHODS

The msNMF was implemented by extending the standard NMF with monotonicity constraints on the signal profiles and their first derivatives. The method was validated using simulated data, and subsequently applied to both ex vivo DWI data and in vivo relaxometry data. Reproducibility of the method was tested using the latter.

RESULTS

The msNMF recovered the multi-exponential signals in the simulated data and showed superiority to standard NMF (based on the explained variance, area under the ROC curve, and coefficient of variation). Diffusion components extracted from the DWI data reflected the cell density of the underlying tissue. The relaxometry analysis resulted in estimates of edema water fractions (EWF) highly correlated with published results, and demonstrated acceptable reproducibility.

CONCLUSION

The msNMF can robustly separate MR signals into components with relation to the underlying tissue composition, and may potentially be useful for e.g. tumor tissue characterization.

Impact of the acquisition protocol on the sensitivity to demyelination and axonal loss of clinically feasible DWI techniques: a simulation study

OBJECTIVE

To evaluate: (a) the specific effect that the demyelination and axonal loss have on the DW signal, and (b) the impact of the sequence parameters on the sensitivity to damage of two clinically feasible DWI techniques, i.e. DKI and NODDI.

METHODS

We performed a Monte Carlo simulation of water diffusion inside a novel synthetic model of white matter in the presence of axonal loss and demyelination, with three compartments with permeable boundaries between them. We compared DKI and NODDI in their ability to detect and assess the damage, using several acquisition protocols. We used the F test statistic as an index of the sensitivity for each DWI parameter to axonal loss and demyelination, respectively.

RESULTS

DKI parameters significantly changed with increasing axonal loss, but, in most cases, not with demyelination; all the NODDI parameters showed sensitivity to both the damage processes (at p < 0.01). However, the acquisition protocol strongly affected the sensitivity to damage of both the DKI and NODDI parameters and, especially for NODDI, the parameter absolute values also.

DISCUSSION

This work is expected to impact future choices for investigating white matter microstructure in focusing on specific stages of the disease, and for selecting the appropriate experimental framework to obtain optimal data quality given the purpose of the experiment.

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.

Temperature dependence and histological correlation of inhomogeneous magnetization transfer and myelin water imaging in ex vivo brain

PURPOSE

The promise of inhomogeneous magnetization transfer (ihMT) as a new myelin imaging method was studied in ex vivo human brain tissue and in relation to myelin water fraction (MWF). The temperature dependence of both methods was characterized, as well as their correspondence with a histological measure of myelin content. Unfiltered and filtered ihMT protocols were studied by adjusting the saturation scheme to preserve or attenuate signal from tissue with short dipolar relaxation time T_1D.

METHODS

ihMT ratio (ihMTR) and MWF maps were acquired at 7 T from formalin-fixed human brain samples at 22.5 °C, 30 °C and 37 °C. The impact of temperature on unfiltered ihMTR, filtered ihMTR and MWF was investigated and compared to myelin basic protein staining.

RESULTS

Unfiltered ihMTR exhibited no temperature dependence, whereas filtered ihMTR increased with increasing temperature. MWF decreased at higher temperature, with an increasing prevalence of areas where the myelin water signal was unreliably determined, likely related to a reduction in T₂ peak separability at higher temperatures ex vivo. MWF and ihMTR showed similar per-sample correlation with myelin staining at room temperature. At 37 ^°C, filtered ihMTR was more strongly correlated with myelin staining and had increased dynamic range compared to unfiltered ihMTR.

CONCLUSIONS

Given the temperature dependence of filtered ihMT, increased dynamic range, and strong myelin specificity that persists at higher temperatures, we recommend carefully controlled temperatures close to 37 °C for filtered ihMT acquisitions. Unfiltered ihMT may also be useful, due to its independence from temperature, higher amplitude values, and sensitivity to short T_1D components. Ex vivo myelin water imaging should be performed at room temperature, to avoid fitting issues found at higher temperatures.

Identification of water compartments in spinal cords by 2 H double quantum filtered NMR

In ² H double quantum filtered (DQF) NMR, the various water compartments are characterized by their different residual quadrupolar interactions. The spectral separation between the different signals enables the measurement of the relaxation of each compartment and the magnetization transfer (MT) between them. In the current study, five water compartments were identified in the ² H DQF spectra of porcine spinal cord. The most prominent signal was the pair of satellites with a quadrupolar splitting of about 550 Hz. ² H DQF MRI optimized for the 550 Hz quadrupolar splitting indicated that this signal originated mainly from the white matter and it was assigned to the myelin water. This splitting does not change upon changing the orientation of the spinal cord relative to the magnetic field, indicating a liquid crystalline nature. Another site exhibiting splitting of about 1500 Hz was assigned to collagenous connective tissue. The narrow central peak was assigned to a combination of intra- and inter-axonal water. The assignment of the other two sites is not certain and requires further study. The rates of MT between the various sites were recorded.

Understanding aqueous and non-aqueous proton T1 relaxation in brain

A full picture of longitudinal relaxation in complex heterogeneous environments like white matter brain tissue remains elusive. In tissue, successive approximations, from the solvation layer model to the two pool model, have highlighted how longitudinal magnetization evolution depends on both inter-compartmental exchange and spin-lattice relaxation. In white matter, however, these models fail to capture the behaviour of the two distinct aqueous pools, myelin water and intra/extra-cellular water. A challenge with testing more comprehensive multi-pool models lies in directly observing all pools, both aqueous and non-aqueous. In this work, we advance these efforts by integrating three main experimental and analytical elements: direct observation of the longitudinal relaxation of both the aqueous and the non-aqueous protons in white matter, a wide range of different initial conditions, and application of an analysis pipeline which includes lineshape, CPMG, and fitting of a four pool model. An eigenvector interpretation of the four pool model highlights how longitudinal relaxation in white matter depends on initial conditions. We find that a single set of model parameters is able to describe the entire range of relaxation behaviour observed in all the separable aqueous and non-aqueous pools in experiments involving six different initial conditions. Understanding of the nature and connectedness of the tissue components is crucial in the design and interpretation of many MRI measurements, especially those based on magnetization transfer and longitudinal relaxation. In particular, the dependency of relaxation behaviour on initial conditions is likely the basis for understanding method-dependent discrepancies in in vivo T₁.

Myelin development in visual scene-network tracts beyond late childhood: A multimethod neuroimaging study

The visual scene-network-comprising the parahippocampal place area (PPA), retrosplenial cortex (RSC), and occipital place area (OPA)-shows a prolonged functional development. Structural development of white matter that underlies the scene-network has not been investigated despite its potential influence on scene-network function. The key factor for white matter maturation is myelination. However, research on myelination using the gold standard method of post-mortem histology is scarce. In vivo alternatives diffusion-weighted imaging (DWI) and myelin water imaging (MWI) so far report broad-scale findings that prohibit inferences concerning the scene-network. Here, we combine MWI, DWI tractography, and fMRI to investigate myelination in scene-network tracts in middle childhood, late childhood, and adulthood. We report increasing myelin from middle childhood to adulthood in right PPA-OPA, and trends towards increases in the left and right RSC-OPA tracts. Investigating tracts to regions highly connected with the scene-network, such as early visual cortex and the hippocampus, did not yield any significant age group differences. Our findings indicate that structural development coincides with functional development in the scene-network, possibly enabling structure-function interactions.

Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging

BACKGROUND

The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease.

NEW METHOD

This is the second review on the topic of g-ratio mapping using MRI.

RESULTS

This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches.

COMPARISON WITH EXISTING METHODS

Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology.

CONCLUSIONS

We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.

An atlas for human brain myelin content throughout the adult life span

Myelin water imaging is a quantitative neuroimaging technique that provides the myelin water fraction (MWF), a metric highly specific to myelin content, and the intra-/extra-cellular T₂ (IET2), which is related to water and iron content. We coupled high-resolution data from 100 adults with gold-standard methodology to create an optimized anatomical brain template and accompanying MWF and IET2 atlases. We then used the MWF atlas to characterize how myelin content relates to demographic factors. In most brain regions, myelin content followed a quadratic pattern of increase during the third decade of life, plateau at a maximum around the fifth decade, then decrease during later decades. The ranking of mean myelin content between brain regions remained consistent across age groups. These openly available normative atlases can facilitate evaluation of myelin imaging results on an individual basis and elucidate the distribution of myelin content between brain regions and in the context of aging.

A simple estimate of axon size with diffusion MRI

Noninvasive estimation of mean axon diameter presents a new opportunity to explore white matter plasticity, development, and pathology. Several diffusion-weighted MRI (DW-MRI) methods have been proposed to measure the average axon diameter in white matter, but they typically require many diffusion encoding measurements and complicated mathematical models to fit the signal to multiple tissue compartments, including intra- and extra-axonal spaces. Here, Monte Carlo simulations uncovered a straightforward DW-MRI metric of axon diameter: the change in radial apparent diffusion coefficient estimated at different effective diffusion times, ΔD_⊥. Simulations indicated that this metric increases monotonically within a relevant range of effective mean axon diameter while being insensitive to changes in extra-axonal volume fraction, axon diameter distribution, g-ratio, and influence of myelin water. Also, a monotonic relationship was found to exist for signals coming from both intra- and extra-axonal compartments. The slope in ΔD_⊥ with effective axon diameter increased with the difference in diffusion time of both oscillating and pulsed gradient diffusion sequences.

Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T2 decay data

Multi-compartment T₂ mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T₂ data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B₁⁺ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T₂ and MWF maps. We generated multi-echo spin-echo T₂ decay curves following the Carr-Purcell-Meiboom-Gill approach for various myelin concentrations and myelin T₂ scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean T₂ (gmT₂ ). MWF estimates were more stable than myelin water gmT₂ time across different settings of the T₂ analysis. We observed that the lower limit of the T₂ distribution grid should be slightly shorter than TE₁ . Both TE₁ and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T₂ signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT₂ differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B₁⁺ inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow us to better characterize the T₂ distribution, including the myelin water, in vivo.

An interactive meta-analysis of MRI biomarkers of myelin

Several MRI measures have been proposed as in vivo biomarkers of myelin, each with applications ranging from plasticity to pathology. Despite the availability of these myelin-sensitive modalities, specificity and sensitivity have been a matter of discussion. Debate about which MRI measure is the most suitable for quantifying myelin is still ongoing. In this study, we performed a systematic review of published quantitative validation studies to clarify how different these measures are when compared to the underlying histology. We analyzed the results from 43 studies applying meta-analysis tools, controlling for study sample size and using interactive visualization (https://neurolibre.github.io/myelin-meta-analysis). We report the overall estimates and the prediction intervals for the coefficient of determination and find that MT and relaxometry-based measures exhibit the highest correlations with myelin content. We also show which measures are, and which measures are not statistically different regarding their relationship with histology.

Myelin water fraction estimation using small-tip fast recovery MRI

PURPOSE

To demonstrate the feasibility of an optimized set of small-tip fast recovery (STFR) MRI scans for rapidly estimating myelin water fraction (MWF) in the brain.

METHODS

We optimized a set of STFR scans to minimize the Cramér-Rao Lower Bound of MWF estimates. We evaluated the RMSE of MWF estimates from the optimized scans in simulation. We compared STFR-based MWF estimates (both modeling exchange and not modeling exchange) to multi-echo spin echo (MESE)-based estimates. We used the optimized scans to acquire in vivo data from which a MWF map was estimated. We computed the STFR-based MWF estimates using PERK, a recently developed kernel regression technique, and the MESE-based MWF estimates using both regularized non-negative least squares (NNLS) and PERK.

RESULTS

In simulation, the optimized STFR scans led to estimates of MWF with low RMSE across a range of tissue parameters and across white matter and gray matter. The STFR-based MWF estimates that modeled exchange compared well to MESE-based MWF estimates in simulation. When the optimized scans were tested in vivo, the MWF map that was estimated using a 3-compartment model with exchange was closer to the MESE-based MWF map.

CONCLUSIONS

The optimized STFR scans appear to be well suited for estimating MWF in simulation and in vivo when we model exchange in training. In this case, the STFR-based MWF estimates are close to the MESE-based estimates.

Evaluation of the diffusion MRI white matter tract integrity model using myelin histology and Monte-Carlo simulations

Quantitative evaluation of brain myelination has drawn considerable attention. Conventional diffusion-based magnetic resonance imaging models, including diffusion tensor imaging and diffusion kurtosis imaging (DKI),¹ have been used to infer the microstructure and its changes in neurological diseases. White matter tract integrity (WMTI) was proposed as a biophysical model to relate the DKI-derived metrics to the underlying microstructure. Although the model has been validated on ex vivo animal brains, it was not well evaluated with ex vivo human brains. In this study, histological samples (namely corpus callosum) from postmortem human brains have been investigated based on WMTI analyses on a clinical 3T scanner and comparisons with gold standard myelin staining in proteolipid protein and Luxol fast blue. In addition, Monte Carlo simulations were conducted to link changes from ex vivo to in vivo conditions based on the microscale parameters of water diffusivity and permeability. The results show that WMTI metrics, including axonal water fraction AWF, radial extra-axonal diffusivity D_e^⊥, and intra-axonal diffusivity D_awere needed to characterize myelin content alterations. Thus, WMTI model metrics are shown to be promising candidates as sensitive biomarkers of demyelination.

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/.

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.

Estimation of cellular-interstitial water exchange in dynamic contrast enhanced MRI using two flip angles

PURPOSE

To investigate the feasibility of using multiple flip angles in dynamic contrast enhanced (DCE) MRI to reduce the uncertainty in estimation of intracellular water lifetime (τ_i ).

METHODS

Numerical simulation studies were conducted to assess the uncertainty in estimation of τ_i using dynamic contrast enhanced MRI with one or two flip angles. In vivo experiments with a murine brain tumor model were conducted at 7T using two flip angles. The in vivo data were used to compare τ_i estimation using the single-flip-angle (SFA) protocol with that using the double-flip-angle (DFA) protocol. Data analysis was conducted using the two-compartment exchange model combined with the three-site-two-exchange model for water exchange.

RESULTS

In the numerical simulation studies with a range of contrast kinetic parameters and signal-to-noise ratio = 20, the median bias of τ_i estimation decreased from 72 ms with SFA to 65 ms with DFA, and the corresponding median inter-quartile range reduced from 523 ms to 156 ms. In the in vivo studies, τ_i estimation with SFA was not successful in most voxels in the tumors, as the estimated τ_i values reached the upper limit of the parameter range (2 s). In contrast, the estimated τ_i values with DFA were mostly between 0.2 and 1.5 s and homogeneously distributed spatially across the tumor. The τ_i estimation with DFA was less sensitive to arterial input function scaling but more sensitive to pre-contrast T₁ than the other contrast kinetic parameters.

CONCLUSION

This study results demonstrate the feasibility of using multiple flip angles to encode the post-contrast time-intensity curve with different weighting of water exchange effect to reduce the uncertainty in τ_i estimation.

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

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

Adult brain aging investigated using BMC-mcDESPOT-based myelin water fraction imaging

The relationship between regional brain myelination and aging has been the subject of intense study, with magnetic resonance imaging perhaps the most effective modality for elucidating this. However, most of these studies have used nonspecific methods to probe myelin content, including diffusion tensor imaging, magnetization transfer ratio, and relaxation times. In the present study, we used the BMC-mcDESPOT analysis, a direct and specific method for imaging of myelin water fraction (MWF), a surrogate of myelin content. We investigated age-related differences in MWF in several brain regions in a large cohort of cognitively unimpaired participants, spanning a wide age range. Our results indicate a quadratic, inverted U-shape, relationship between MWF and age in all brain regions investigated, suggesting that myelination continues until middle age followed by decreases at older ages. We also observed that these age-related differences vary across different brain regions, as expected. Our results provide evidence for nonlinear associations between age and myelin in a large sample of well-characterized adults, using a direct myelin content imaging method.

Diffusion MRI microstructural models in the cervical spinal cord - Application, normative values, and correlations with histological analysis

Multi-compartment tissue modeling using diffusion magnetic resonance imaging has proven valuable in the brain, offering novel indices sensitive to the tissue microstructural environment in vivo on clinical MRI scanners. However, application, characterization, and validation of these models in the spinal cord remain relatively under-studied. In this study, we apply a diffusion "signal" model (diffusion tensor imaging, DTI) and two commonly implemented "microstructural" models (neurite orientation dispersion and density imaging, NODDI; spherical mean technique, SMT) in the human cervical spinal cord of twenty-one healthy controls. We first provide normative values of DTI, SMT, and NODDI indices in a number of white matter ascending and descending pathways, as well as various gray matter regions. We then aim to validate the sensitivity and specificity of these diffusion-derived contrasts by relating these measures to indices of the tissue microenvironment provided by a histological template. We find that DTI indices are sensitive to a number of microstructural features, but lack specificity. The microstructural models also show sensitivity to a number of microstructure features; however, they do not capture the specific microstructural features explicitly modelled. Although often regarded as a simple extension of the brain in the central nervous system, it may be necessary to re-envision, or specifically adapt, diffusion microstructural models for application to the human spinal cord with clinically feasible acquisitions - specifically, adjusting, adapting, and re-validating the modeling as it relates to both theory (i.e. relevant biology, assumptions, and signal regimes) and parameter estimation (for example challenges of acquisition, artifacts, and processing).

Monte Carlo Simulations of Water Exchange Through Myelin Wraps: Implications for Diffusion MRI

Diffusion magnetic resonance imaging (dMRI) yields parameters sensitive to brain tissue microstructure. A structurally important aspect of this microstructure is the myelin wrapping around the axons. This paper investigated the forward problem concerning whether water exchange via the spiraling structure of the myelin can meaningfully contribute to the signal in dMRI. Monte Carlo simulations were performed in a system with intra-axonal, myelin, and extra-axonal compartments. Diffusion in the myelin was simulated as a spiral wrapping the axon, with a custom number of wraps. Exchange (or intra-axonal residence) times were analyzed for various number of wraps and axon diameters. Pulsed gradient sequences were employed to simulate the dMRI signal, which was analyzed using different methods. Diffusional kurtosis imaging analysis yielded the radial diffusivity (RD) and radial kurtosis (RK), while the two-compartment Kärger model yielded estimates the intra-axonal volume fraction ( ν _ic ) and exchange time ( τ ). Results showed that τ was on the sub-second level for geometries with axon diameters below 1.0 μ m and less than eight wraps. Otherwise, exchange was negligible compared to typical experimental durations, with τ of seconds or longer. In situations where exchange influenced the signal, estimates of RK and ν _ic increased with the number of wraps, while RD decreased. τ estimates from simulated signals were in agreement with predicted ones. In conclusion, exchange through spiraling myelin permits sub-second τ for small diameters and low number of wraps. Such conditions may arise in the developing brain or in neurodegenerative disease, and thus the results could aid the interpretation of dMRI studies.

Formalin tissue fixation biases myelin-sensitive MRI

PURPOSE

Chemical fixatives such as formalin form cross-links between proteins and affect the relaxation times and diffusion properties of tissue. These fixation-induced changes likely also affect myelin density measurements produced by quantitative magnetization transfer and myelin water imaging. In this work, we evaluate these myelin-sensitive MRI methods for fixation-induced biases.

METHODS

We perform quantitative magnetization transfer, myelin water imaging, and deuterium oxide-exchanged zero TE imaging on unfixed human spinal cord tissue at 9.4 Tesla and repeat these measurements after 1 day and 31 days of formalin fixation.

RESULTS

The quantitative magnetization-transfer bound pool fraction increased by 30.7% ± 21.1% after 1 day of fixation and by 42.6% ± 33.9% after 31 days of fixation. Myelin water fraction increased by 39.7% ± 15.5% and 37.0% ± 15.9% at these same time points, and mean T₂ of the myelin water pool nearly doubled. Reference-normalized deuterium oxide-exchanged zero TE signal intensity increased by 8.17% ± 6.03% after 31 days of fixation but did not change significantly after 1 day of fixation. After fixation, specimen cross-sectional area decreased by approximately 5%; after correction for shrinkage, changes in deuterium oxide-exchanged zero TE intensity were nearly eliminated.

CONCLUSION

Bound pool fraction and myelin water fraction are significantly increased by formalin fixation, whereas deuterium oxide-exchanged zero TE intensity is minimally affected. Changes in quantitative magnetization transfer and myelin water imaging may be due in part to delamination and formation of vacuoles in the myelin sheath. Deuterium oxide-exchanged signal intensity may be altered by fixation-induced changes in myelin lipid solid-state ¹ H T₁ . We urge caution in the comparison of these measurements across subjects or specimens in different states, especially unfixed versus fixed tissue.

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.

Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation

Multicomponent driven equilibrium steady-state observation of T₁ and T₂ (mcDESPOT) aims to quantify the Myelin Water Fraction (MWF) using a two-pool microstructural model. The MWF has been used to track neurodevelopment and neurodegeneration and has been histologically correlated to myelin content. mcDESPOT has a clinically feasible acquisition time and high signal-to-noise ratio (SNR) relative to other MWF techniques. However, disagreement exists in the literature between experimental studies that show MWF maps with plausible grey matter-white matter (GM-WM) contrast and theoretical work that questions the accuracy and precision of mcDESPOT. We demonstrate that mcDESPOT parameter estimation is inaccurate and imprecise if intercompartmental exchange is included in the microstructural model, but that significant bias results if exchange is neglected. The source of apparent MWF contrast is likely due to the complex convergence behaviour of the Stochastic Region Contraction (SRC) method commonly used to fit the mcDESPOT model. mcDESPOT-derived parameter estimates are hence not directly relatable to the underlying microstructural model and are only comparable to others using similar acquisition schemes and fitting constraints.

Measuring intra-axonal T2 in white matter with direction-averaged diffusion MRI

PURPOSE

To demonstrate how the T₂ relaxation time of intra-axonal water (T_2a ) in white matter can be measured with direction-averaged diffusion MRI.

METHODS

For b-values larger than about 4000 s/mm² , the direction-averaged diffusion MRI signal from white matter is dominated by the contribution from water within axons, which enables T_2a to be estimated by acquiring data for multiple TE values and fitting a mono-exponential decay curve. If given a value of the intra-axonal diffusivity, an extension of the method allows the extra-axonal relaxation time (T_2e ) to be calculated also. This approach was applied to estimate T_2a in white matter for 3 healthy subjects at 3 T, as well as T_2e for a selected set of assumed intra-axonal diffusivities.

RESULTS

The estimated T_2a values ranged from about 50 ms to 110 ms, with considerable variation among white matter regions. For white matter tracts with primarily collinear fibers, T_2a was found to depend on the angle of the tract relative to the main magnetic field, which is consistent with T_2a being affected by magnetic field inhomogeneities arising from spatial differences in magnetic susceptibility. The T_2e values were significantly smaller than the T_2a values across white matter regions for several plausible choices of the intra-axonal diffusivity.

CONCLUSION

The relaxation time for intra-axonal water in white matter can be determined in a straightforward manner by measuring the direction-averaged diffusion MRI signal with a large b-value for multiple TEs. In healthy brain, T_2a is greater than T_2e and varies considerably with anatomical region.

Two-dimensional magnetization-transfer - CPMG MRI reveals tract-specific signatures in fixed rat spinal cord

Multiexponential T₂ (MET₂) Relaxometry and Magnetization Transfer (MT) are among the most promising MRI-derived techniques for white matter (WM) characterization. Both techniques are shown to have histologically correlated sensitivity to myelin, but these correlations are not fully understood. Furthermore, MET₂ and MT report on different WM features, thus they can be considered specific to different (patho)physiological states. Two-dimensional studies potentially resolving interactions, such as those commonly used in NMR, have been rarely performed in this context. Here, we investigated how off-resonance irradiation affects different MET₂ components in fixed rat spinal cord white matter at 16.4 T. These 2D MT-MET₂ experiments reveal that MT affects both short and long T₂ components in a tract-specific fashion. The spatially distinct signal modulations enhanced contrast between microstructurally-distinct spinal cord tracts. Two hypotheses to explain these findings were proposed: either selective elimination of a short T₂ component through pre-saturation combines with intercompartmental water exchange effects occurring on the irradiation timescale; or, other macromolecular species that exist within the tissue - other than myelin - such as neurofilaments, may be involved in the apparent microstructural segregation of the spinal cord (SC) from MET₂. Though further investigation is required to elucidate the underlying mechanism, this phenomenon adds a new dimension for WM characterization.

Myelin volume fraction imaging with MRI

MRI is a valuable tool to assess myelin during development and demyelinating disease processes. While multiexponential T2 and quantitative magnetization transfer measures correlate with myelin content, neither provides the total myelin volume fraction. In many cases correlative measures are adequate; but to assess microstructure of myelin, (e.g. calculate the g-ratio using MRI), an accurate measure of myelin volume fraction is imperative. Using a volumetric model of white matter, we relate MRI measures of myelin to absolute measures of myelin volume fraction and compare them to quantitative histology. We assess our approach in control mice along with two models of hypomyelination and one model of hypermyelination and find strong agreement between MRI and histology amongst models. This work investigates the sensitivities of MRI myelin measures to changes in axon geometry and displays promise for estimating g-ratio from MRI.

White matter intercompartmental water exchange rates determined from detailed modeling of the myelin sheath

PURPOSE

Magnetization exchange (ME) between hydrogen protons of water and large molecules (semisolids [SS]) in lipid bilayers is an important factor in MRI signal generation and can be exploited to study white matter pathology. Current models used to quantify ME in white matter generally consider water to reside in 1 or 2 distinct compartments, ignoring the complexities of the myelin sheath's multicompartment structure of alternating myelin SS and myelin water (MW) layers. Here, we investigated the effect of this by fitting ME data obtained from human brain at 7 T with a multilayer model of myelin.

METHODS

A multi-echo acquisition for a T₂ ^* -based separation of MW from other water signals was combined with various preparation pulses to change the (relative) state of the SS and water pools and analyzed by fitting with a multilayer exchange model.

RESULTS

The estimated lifetime within a single MW layer was 260 µs, corresponding to a lipid bilayer permeability of 6.7 µm/s. The magnetization lifetime of the aggregate of all MW was estimated at 13 ms, shorter than previously reported values in the range of 40 to 140 ms.

CONCLUSION

Contrary to expectations and previous reports, ME between protons in myelin SS and water is not limited by the myelin sheath but rather by the exchange between SS and water protons. The analysis of ME contrast should account for the relatively short MW lifetime and affects the interpretation of tissue compartmentalization from MRI contrasts such as T₁ - and diffusion-weighting.

Inferring brain tissue composition and microstructure via MR relaxometry

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

Extended phase graph formalism for systems with magnetization transfer and exchange

Purpose

An extended phase graph framework (EPG‐X) for modeling systems with exchange or magnetization transfer (MT) is proposed.

Theory

EPG‐X models coupled two‐compartment systems by describing each compartment with separate phase graphs that exchange during evolution periods. There are two variants: EPG‐X(BM) for systems governed by the Bloch‐McConnell equations, and EPG‐X(MT) for the pulsed MT formalism. For the MT case, the “bound” protons have no transverse components, so their phase graph consists of only longitudinal states.

Methods

The EPG‐X model was validated against steady‐state solutions and isochromat‐based simulation of gradient‐echo sequences. Three additional test cases were investigated: (i) MT effects in multislice turbo spin‐echo; (ii) variable flip angle gradient‐echo imaging of the type used for MR fingerprinting; and (iii) water exchange in multi‐echo spin‐echo T₂ relaxometry.

Results

EPG‐X was validated successfully against isochromat based transient simulations and known steady‐state solutions. EPG‐X(MT) simulations matched in‐vivo measurements of signal attenuation in white matter in multislice turbo spin‐echo images. Magnetic resonance fingerprinting–style experiments with a bovine serum albumin (MT) phantom showed that the data were not consistent with a single‐pool model, but EPG‐X(MT) could be used to fit the data well. The EPG‐X(BM) simulations of multi‐echo spin‐echo T₂ relaxometry suggest that exchange could lead to an underestimation of the myelin‐water fraction.

Conclusions

The EPG‐X framework can be used for modeling both steady‐state and transient signal response of systems exhibiting exchange or MT. This may be particularly beneficial for relaxometry approaches that rely on characterizing transient rather than steady‐state sequences. Magn Reson Med 80:767–779, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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

Promise and pitfalls of g-ratio estimation with MRI

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

Effect of myelin water exchange on DTI-derived parameters in diffusion MRI: Elucidation of TE dependence

PURPOSE

Water exchange exists between different neuronal compartments of brain tissue but is often ignored in most diffusion models. The goal of the current study was to demonstrate the dependence of diffusion measurements on echo time (TE) in the human brain and to investigate the underlying effects of myelin water exchange.

METHODS

Five healthy subjects were examined with single-shot pulsed-gradient spin-echo echo-planar imaging with fixed duration (δ) and separation (Δ) of diffusion gradient pulses and a set of varying TEs. The effects of water exchange and intrinsic T₂ difference in cellular environments were investigated with Monte Carlo simulations.

RESULTS

Both in vivo measurements and simulations showed that fractional anisotropy (FA) and axial diffusivity (AD) had positive correlations with TE, while radial diffusivity (RD) showed a negative correlation, which is consistent with a previous study. The simulation results further indicated the sensitivity of TE dependence to the change of g-ratio.

CONCLUSION

The exchange between myelin and intra/extra-axonal water pools often plays a non-negligible role in the observed TE dependence of diffusion parameters, which may accompany or alter the effect of intrinsic T₂ in causing such dependence. The TE dependence may potentially serve as a biomarker for demyelination processes (e.g., in multiple sclerosis and Alzheimer's disease). Magn Reson Med 79:1650-1660, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Impact of transcytolemmal water exchange on estimates of tissue microstructural properties derived from diffusion MRI

PURPOSE

To investigate the influence of transcytolemmal water exchange on estimates of tissue microstructural parameters derived from diffusion MRI using conventional PGSE and IMPULSED methods.

METHODS

Computer simulations were performed to incorporate a broad range of intracellular water life times τin (50-∞ ms), cell diameters d (5-15 μm), and intrinsic diffusion coefficient Din (0.6-2 μm2 /ms) for different values of signal-to-noise ratio (SNR) (10 to 50). For experiments, murine erythroleukemia (MEL) cancer cells were cultured and treated with saponin to selectively change cell membrane permeability. All fitted microstructural parameters from simulations and experiments in vitro were compared with ground-truth values.

RESULTS

Simulations showed that, for both PGSE and IMPULSED methods, cell diameter d can be reliably fit with sufficient SNR (≥ 50), whereas intracellular volume fraction fin is intrinsically underestimated due to transcytolemmal water exchange. Din can be reliably fit only with sufficient SNR and using the IMPULSED method with short diffusion times. These results were confirmed with those obtained in the cell culture experiments in vitro.

CONCLUSION

For the sequences and models considered in this study, transcytolemmal water exchange has minor effects on the fittings of d and Din with physiologically relevant membrane permeabilities if the SNR is sufficient (> 50), but fin is intrinsically underestimated. Magn Reson Med 77:2239-2249, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

The effect of realistic geometries on the susceptibility-weighted MR signal in white matter

PURPOSE

To investigate the effect of realistic microstructural geometry on the susceptibility-weighted MR signal in white matter (WM), with application to demyelination.

METHODS

Previous work has modeled susceptibility-weighted signals under the assumption that axons are cylindrical. In this study, we explored the implications of this assumption by considering the effect of more realistic geometries. A three-compartment WM model incorporating relevant properties based on the literature was used to predict the MR signal. Myelinated axons were modeled with several cross-sectional geometries of increasing realism: nested circles, warped/elliptical circles, and measured axonal geometries from electron micrographs. Signal simulations from the different microstructural geometries were compared with measured signals from a cuprizone mouse model with varying degrees of demyelination.

RESULTS

Simulation results suggest that axonal geometry affects the MR signal. Predictions with realistic models were significantly different compared with circular models under the same microstructural tissue properties, for simulations with and without diffusion.

CONCLUSION

The geometry of axons affects the MR signal significantly. Literature estimates of myelin susceptibility, which are based on fitting biophysical models to the MR signal, are likely to be biased by the assumed geometry, as will any derived microstructural properties. Magn Reson Med 79:489-500, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Validating myelin water imaging with transmission electron microscopy in a rat spinal cord injury model

Myelin content is an important marker for neuropathology and MRI generated myelin water fraction (MWF) has been shown to correlate well with myelin content. However, because MWF is based on the amount of signal from myelin water, that is, the water trapped between the myelin lipid bilayers, the reading may depend heavily on myelin morphology. This is of special concern when there is a mix of intact myelin and myelin debris, as in the case of injury. To investigate what MWF measures in the presence of debris, we compared MWF to transmission electron microscopy (TEM) derived myelin fraction that measures the amount of compact appearing myelin. A rat spinal cord injury model was used with time points at normal (normal myelin), 3 weeks post-injury (myelin debris), and 8 weeks post-injury (myelin debris, partially cleared). The myelin period between normal and 3 or 8 weeks post-injury cords did not differ significantly, suggesting that as long as the bilayer structure is intact, myelin debris has the same water content as intact myelin. The MWF also correlated strongly with the TEM-derived myelin fraction, suggesting that MWF measures the amount of compact appearing myelin in both intact myelin and myelin debris. From the TEM images, it appears that as myelin degenerates, it tends to form large watery spaces within the myelin sheaths that are not classified as myelin water. The results presented in this study improve our understanding and allows for better interpretation of MWF in the presence of myelin debris.

New rapid, accurate T2 quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients

Introduction

Quantitative T₂ mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T₂ changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38).

Methods

The EMC algorithm uses Bloch simulations to model T₂ decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings. T₂ values were extracted from normal-appearing white and gray matter brain regions using both expert manual regions-of-interest and user-independent FreeSurfer segmentation.

Results

Compared to conventional exponential T₂ modeling, EMC fitting provided more accurate estimations of T₂ with less variance across scans, MRI systems, and healthy individuals. Thalamic T₂ was increased 8.5% in RRMS subjects (p < 0.001) and could be used to discriminate RRMS from healthy controls well (AUC = 0.913). Manual segmentation detected both statistically significant increases (corpus callosum & temporal stem) and decreases (posterior limb internal capsule) in T₂ associated with RRMS diagnosis (all p < 0.05). In healthy controls, we also observed statistically significant T₂ differences for different white and gray matter structures.

Conclusions

The EMC algorithm precisely characterizes T₂ values, and is able to detect subtle T₂ changes in normal-appearing brain regions of RRMS patients. These presumably capture both axon and myelin changes from inflammation and neurodegeneration. Further, T₂ variations between different brain regions of healthy controls may correlate with distinct nervous tissue environments that differ from one another at a mesoscopic length-scale.

•

EMC technique provides accurate and scanner-invariant T₂ mapping in MS subjects.

•

Thalamus T₂ differences distinguish relapsing-remitting MS subjects from controls.

•

Normal-appearing brain regions demonstrate T₂ changes in MS patients compared to controls.

•

T₂ values reflect anatomic and function-specific differences in healthy controls.

Magnetic Resonance of Myelin Water: An in vivo Marker for Myelin

Myelin is critical for healthy brain function. An accurate in vivo measure of myelin content has important implications for understanding brain plasticity and neurodegenerative diseases. Myelin water imaging is a magnetic resonance imaging method which can be used to visualize myelination in the brain and spinal cord in vivo. This review presents an overview of myelin water imaging data acquisition and analysis, post-mortem validation work, findings in both animal and human studies and a brief discussion about other MR techniques purported to provide in vivo myelin content. Multi-echo T₂ relaxation approaches continue to undergo development and whole-brain imaging time now takes less than 10 minutes; the standard analysis method for this type of data acquisition is a non-negative least squares approach. Alternate methods including the multi-flip angle gradient echo mcDESPOT are also being used for myelin water imaging. Histological validation studies in animal and human brain and spinal cord tissue demonstrate high specificity of myelin water imaging for myelin. Potential confounding factors for in vivo myelin water fraction measurement include the presence of myelin debris and magnetization exchange processes. Myelin water imaging has successfully been used to study animal models of injury, applied in healthy human controls and can be used to assess damage and injury in conditions such as multiple sclerosis, neuromyelitis optica, schizophrenia, phenylketonuria, neurofibromatosis, niemann pick’s disease, stroke and concussion. Other quantitative magnetic resonance approaches that are sensitive to, but not specific for, myelin exist including magnetization transfer, diffusion tensor imaging and T₁ weighted imaging.

Fast, accurate 2D-MR relaxation exchange spectroscopy (REXSY): Beyond compressed sensing

Previously, we showed that compressive or compressed sensing (CS) can be used to reduce significantly the data required to obtain 2D-NMR relaxation and diffusion spectra when they are sparse or well localized. In some cases, an order of magnitude fewer uniformly sampled data were required to reconstruct 2D-MR spectra of comparable quality. Nonetheless, this acceleration may still not be sufficient to make 2D-MR spectroscopy practicable for many important applications, such as studying time-varying exchange processes in swelling gels or drying paints, in living tissue in response to various biological or biochemical challenges, and particularly for in vivo MRI applications. A recently introduced framework, marginal distributions constrained optimization (MADCO), tremendously accelerates such 2D acquisitions by using a priori obtained 1D marginal distribution as powerful constraints when 2D spectra are reconstructed. Here we exploit one important intrinsic property of the 2D-MR relaxation exchange spectra: the fact that the 1D marginal distributions of each 2D-MR relaxation exchange spectrum in both dimensions are equal and can be rapidly estimated from a single Carr-Purcell-Meiboom-Gill (CPMG) or inversion recovery prepared CPMG measurement. We extend the MADCO framework by further proposing to use the 1D marginal distributions to inform the subsequent 2D data-sampling scheme, concentrating measurements where spectral peaks are present and reducing them where they are not. In this way we achieve compression or acceleration that is an order of magnitude greater than that in our previous CS method while providing data in reconstructed 2D-MR spectral maps of comparable quality, demonstrated using several simulated and real 2D T2 - T2 experimental data. This method, which can be called "informed compressed sensing," is extendable to other 2D- and even ND-MR exchange spectroscopy.

Simulations on the influence of myelin water in diffusion-weighted imaging

While myelinated axons present an important barrier to water diffusion, many models used to interpret DWI signal neglect other potential influences of myelin. In this work, Monte Carlo simulations were used to test the sensitivity of DWI results to the diffusive properties of water within myelin. Within these simulations, the apparent diffusion coefficient (D app) varied slowly over several orders of magnitude of the coefficient of myelin water diffusion (D m), but exhibited important differences compared to D app values simulated that neglect D m (=0). Compared to D app, the apparent diffusion kurtosis (K app) was generally more sensitive to D m. Simulations also tested the sensitivity of D app and K app to the amount of myelin present. Unique variations in D app and K app caused by differences in the myelin volume fraction were diminished when myelin water diffusion was included. Also, expected trends in D app and K app with experimental echo time were reduced or inverted when accounting for myelin water diffusion, and these reduced/inverted trends were seen experimentally in ex vivo rat brain DWI experiments. In general, myelin water has the potential to subtly influence DWI results and bias models of DWI that neglect these components of white matter.