Untangling the R2* contrast in multiple sclerosis: A combined MRI-histology study at 7.0 Tesla

Correlations between postmortem quantitative MRI parameters and demyelination, axonal loss and gliosis in multiple sclerosis: A systematic review and meta-analysis

Magnetic resonance imaging (MRI) is frequently used to monitor disease progression in multiple sclerosis (MS). This study aims to systematically evaluate the correlation between MRI measures and histopathological changes, including demyelination, axonal loss, and gliosis, in the central nervous system of MS patients. We systematically reviewed post-mortem histological studies evaluating myelin density, axonal loss, and gliosis using quantitative imaging in MS. Relevant studies were identified through searches in PubMed, EMBASE, and Web of Science. A total of 38 studies involving 1782 regions of interest from 229 subjects were included. Pooled random-effects models were used to calculate the correlation between demyelination, axonal loss, gliosis, and various MRI parameters, including magnetization transfer ratio (MTR), T1 and T2 relaxation times, myelin water fraction (MWF), proton density (PD), and diffusivities. Pair-wise analyses compared results between lesioned and non-lesioned tissues. Our results demonstrated moderate to strong correlations between MRI parameters and myelin density in MS, with correlation coefficients: T1 (0.72), T2 (0.72), MTR (-0.73), FA (-0.73), RD (0.70), MD (0.70), MWF (-0.82), and PD (0.73). Interestingly, stronger correlations were found in lesioned tissues compared to non-lesioned tissues (P < 0.001). Moderate correlations were found between MRI parameters and axonal loss and gliosis. Our study reveals significant correlations between MRI techniques and histological assessments of myelin, axonal damage, and gliosis in MS. MRI metrics exhibited a more robust association with demyelination in lesioned areas than in non-lesioned brain tissue, highlighting the pronounced degree of myelin degradation in MS lesions. Further investigation is warranted to corroborate these results and refine MRI-based monitoring of MS pathology.

Chronic active lesions in multiple sclerosis: classification, terminology, and clinical significance

In multiple sclerosis (MS), increasing disability is considered to occur due to persistent, chronic inflammation trapped within the central nervous system (CNS). This condition, known as smoldering neuroinflammation, is present across the clinical spectrum of MS and is currently understood to be relatively resistant to treatment with existing disease-modifying therapies. Chronic active white matter lesions represent a key component of smoldering neuroinflammation. Initially characterized in autopsy specimens, multiple approaches to visualize chronic active lesions (CALs) in vivo using advanced neuroimaging techniques and postprocessing methods are rapidly emerging. Among these in vivo imaging correlates of CALs, paramagnetic rim lesions (PRLs) are defined by the presence of a perilesional rim formed by iron-laden microglia and macrophages, whereas slowly expanding lesions are identified based on linear, concentric lesion expansion over time. In recent years, several longitudinal studies have linked the occurrence of in vivo detected CALs to a more aggressive disease course. PRLs are highly specific to MS and therefore have recently been incorporated into the MS diagnostic criteria. They also have prognostic potential as biomarkers to identify patients at risk of early and severe disease progression. These developments could significantly affect MS care and the evaluation of new treatments. This review describes the latest knowledge on CAL biology and imaging and the relevance of CALs to the natural history of MS. In addition, we outline considerations for current and future in vivo biomarkers of CALs, emphasizing the need for validation, standardization, and automation in their assessment.

Longitudinal Multiparametric Quantitative MRI Evaluation of Acute and Chronic Multiple Sclerosis Paramagnetic Rim Lesions

BACKGROUND

Multiple sclerosis (MS) paramagnetic rim lesions (PRLs) are markers of chronic active biology and exhibit complex iron and myelin changes that may complicate quantification when using conventional MRI approaches.

PURPOSE

To conduct a multiparametric MRI analysis of PRLs.

STUDY TYPE

Retrospective/longitudinal.

SUBJECTS

Ninety-five progressive MS subjects with at least one persistent PRL who were enrolled in the CONSONANCE trial.

FIELD STRENGTH/SEQUENCE

3-T/Susceptibility-weighted, T1-weighted, T2-weighted, and fluid-attenuated inversion recovery.

ASSESSMENT

Acute/chronic PRLs and non-PRLs were measured at screening, 24, 48, and 96 weeks using quantitative magnetic susceptibility (QS), R2*, and standardized T1w/T2w ratio (sT1w/T2w). PRL analyses were performed for whole lesion, core, and rim. The correlations between PRL core and rim sT1w/T2w, QS, and R2* were assessed.

STATISTICAL TESTS

Linear mixed models. A P-value <0.05 was considered significant.

RESULTS

There was a significant decrease in sT1w/T2w (-0.24 ± -5.3 × 10-3) and R2* (-3.6 ± 2.2 Hz) but a significant increase in QS (+21 ± 1.3 ppb) using whole-lesion analysis of chronic PRLs compared to non-PRLs at screening. Tissue damage accumulated at the 96-week time point was more evident in acute/chronic PRLs compared to acute/chronic non-PRLs (ΔsT1w/T2w = -0.21/-0.24 ± 0.033/0.0053; ΔR2* = -4.4/-3.6 ± 1.4/2.2 Hz). New, acute PRL sT1w/T2w significantly increased in lesion core (+4.3 × 10-3 ± 1.2 × 10-4) and rim (+5.6 × 10-3 ± 1.2 × 10-4) 24 weeks post lesion inception, suggestive of partial recovery. Chronic PRLs, contrastingly, showed significant decreases in sT1w/T2w over the initial 24 weeks for both core (-2.1 × 10-4 ± 2.0 × 10-5) and rim (-2.4 × 10-4 ± 2.0 × 10-5), indicative of irreversible tissue damage. Significant positive correlations between PRL core and rim sT1w/T2w (R2 = 0.53), R2* (R2 = 0.69) and QS (R2 = 0.52) were observed.

DATA CONCLUSION

Multiparametric assessment of PRLs has the potential to be a valuable tool for assessing complex iron and myelin changes in chronic active PRLs of progressive MS patients.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 3.

An Improved Postprocessing Method to Mitigate the Macroscopic Cross-Slice B0 Field Effect on R2* Measurements in the Mouse Brain at 7T

The MR transverse relaxation rate, R2*, has been widely used to detect iron and myelin content in tissue. However, it is also sensitive to macroscopic B0 inhomogeneities. One approach to correct for the B0 effect is to fit gradient-echo signals with the three-parameter model, a sinc function-weighted monoexponential decay. However, such three-parameter models are subject to increased noise sensitivity. To address this issue, this study presents a two-stage fitting procedure based on the three-parameter model to mitigate the B0 effect and reduce the noise sensitivity of R2* measurement in the mouse brain at 7T. MRI scans were performed on eight healthy mice. The gradient-echo signals were fitted with the two-stage fitting procedure to generate R2corr_t*. The signals were also fitted with the monoexponential and three-parameter models to generate R2nocorr* and R2corr*, respectively. Regions of interest (ROIs), including the corpus callosum, internal capsule, somatosensory cortex, caudo-putamen, thalamus, and lateral ventricle, were selected to evaluate the within-ROI mean and standard deviation (SD) of the R2* measurements. The results showed that the Akaike information criterion of the monoexponential model was significantly reduced by using the three-parameter model in the selected ROIs (p = 0.0039-0.0078). However, the within-ROI SD of R2corr* using the three-parameter model was significantly higher than that of the R2nocorr* in the internal capsule, caudo-putamen, and thalamus regions (p = 0.0039), a consequence partially due to the increased noise sensitivity of the three-parameter model. With the two-stage fitting procedure, the within-ROI SD of R2corr* was significantly reduced by 7.7-30.2% in all ROIs, except for the somatosensory cortex region with a fast in-plane variation of the B0 gradient field (p = 0.0039-0.0078). These results support the utilization of the two-stage fitting procedure to mitigate the B0 effect and reduce noise sensitivity for R2* measurement in the mouse brain.

Cerebrospinal Fluid-In Gradient of Cortical and Deep Gray Matter Damage in Multiple Sclerosis

BACKGROUND AND OBJECTIVES

A CSF-in gradient in cortical and thalamic gray matter (GM) damage has been found in multiple sclerosis (MS). We concomitantly explored the patterns of cortical, thalamic, and caudate microstructural abnormalities at progressive distances from CSF using a multiparametric MRI approach.

METHODS

For this cross-sectional study, from 3T 3D T1-weighted scans, we sampled cortical layers at 25%-50%-75% depths from pial surface and thalamic and caudate bands at 2-3-4 voxels from the ventricular-GM interface. Using linear mixed models, we tested between-group comparisons of magnetization transfer ratio (MTR) and R2* layer-specific z-scores, CSF-in across-layer z-score changes, and their correlations with clinical (disease duration and disability) and structural (focal lesions, brain, and choroid plexus volume) MRI measures.

RESULTS

We enrolled 52 patients with MS (33 relapsing-remitting [RRMS], 19 progressive [PMS], mean age: 46.4 years, median disease duration: 15.1 years, median: EDSS 2.0) and 70 controls (mean age 41.5 ± 12.8). Compared with controls, RRMS showed lower MTR values in the outer and middle cortical layers (false-discovery rate [FDR]-p ≤ 0.025) and lower R2* values in all 3 cortical layers (FDR-p ≤ 0.016). PMS had lower MTR values in the outer and middle cortical (FDR-p ≤ 0.016) and thalamic (FDR-p ≤ 0.048) layers, and in the outer caudate layer (FDR-p = 0.024). They showed lower R2* values in the outer cortical layer (FDR-p = 0.003) and in the outer thalamic layer (FDR-p = 0.046) and higher R2* values in all 3 caudate layers (FDR-p ≤ 0.031). Both RRMS and PMS had a gradient of damage, with lower values closer to the CSF, for cortical (FDR-p ≤ 0.002) and thalamic (FDR-p ≤ 0.042) MTR. PMS showed a gradient of damage for cortical R2* (FDR-p = 0.005), thalamic R2* (FDR-p = 0.004), and caudate MTR (FDR-p ≤ 0.013). Lower MTR and R2* of outer cortical, thalamic, and caudate layers and steeper gradient of damage toward the CSF were significantly associated with older age, higher T2-hyperintense white matter lesion volume, higher thalamic lesion volume, and lower brain volume (β ≥ 0.08, all FDR-p ≤ 0.040). Lower MTR of outer caudate layer was associated with more severe disability (β = -0.26, FDR-p = 0.040). No correlations with choroid plexus volume were found.

DISCUSSION

CSF-in damage gradients are heterogeneous among different GM regions and through MS course, possibly reflecting different dynamics of demyelination and iron loss/accumulation.

Brain microstructure is linked to cognitive fatigue in early multiple sclerosis

Cognitive fatigue is a major symptom of Multiple Sclerosis (MS), from the early stages of the disease. This study aims to detect if brain microstructure is altered early in the disease course and is associated with cognitive fatigue in people with MS (pwMS) compared to matched healthy controls (HC). Recently diagnosed pwMS (N = 18, age < 45 years old) with either a Relapsing-Remitting or a Clinically Isolated Syndrome course of the disease, and HC (N = 19) matched for sex, age and education were analyzed. Quantitative multiparameter maps (MTsat, PD, R1 and R2*) of pwMS and HC were calculated. Parameters were extracted within the normal appearing white matter, cortical grey matter and deep grey matter (NAWM, NACGM and NADGM, respectively). Bayesian T-test for independent samples assessed between-group differences in brain microstructure while associations between score at a cognitive fatigue scale and each parameter in each tissue class were investigated with Generalized Linear Mixed Models. Patients exhibited lower MTsat and R1 values within NAWM and NACGM, and higher R1 values in NADGM compared to HC. Cognitive fatigue was associated with PD measured in every tissue class and to MTsat in NAWM, regardless of group. Disease-specific negative correlations were found in pwMS in NAWM (R1, R2*) and NACGM (R1). These findings suggest that brain microstructure within normal appearing tissues is already altered in the very early stages of the disease. Moreover, additional microstructure alterations (e.g. diffuse and widespread demyelination or axonal degeneration) in pwMS may lead to disease-specific complaint of cognitive fatigue.

Evaluation of the Blood-Brain Barrier, Demyelination, and Neurodegeneration in Paramagnetic Rim Lesions in Multiple Sclerosis on 7 Tesla MRI

BACKGROUND

Paramagnetic rim lesions (PRLs) are associated with chronic inflammation in multiple sclerosis (MS). 7-Tesla (7T) magnetic resonance imaging (MRI) can evaluate the integrity of the blood-brain barrier (BBB) in addition to the tissue myelination status and cell loss.

PURPOSE

To use MRI metrics to investigate underlying physiology and clinical importance of PRLs.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-six participants (mean-age 47, 23 females, 13 males) of mixed MS subtypes.

FIELD STRENGTH/SEQUENCE

7T, MP2RAGE, MULTI-ECHO 3D-GRE, FLAIR.

ASSESSMENT

Lesion heterogeneity; longitudinal changes in lesion counts; comparison of T1, R2*, and χ; association between baseline lesion types and disease progression (2-3 annual MRI visits with additional years of annual clinical follow-up).

STATISTICAL TESTS

Two-sample t-test, Wilcoxon Rank-Sum test, Pearson's chi-square test, two-group comparison with linear-mixed-effect model, mixed-effect ANOVA, logistic regression. P-values <0.05 were considered significant.

RESULTS

A total of 58.3% of participants had at least one PRL at baseline. Higher male proportion in PRL+ group was found. Average change in PRL count was 0.20 (SD = 2.82) for PRLs and 0.00 (SD = 0.82) for mottled lesions. Mean and median pre-/post-contrast T1 were longer in PRL+ than in PRL-. No differences in mean χ were seen for lesions grouped by PRL (P = 0.310, pre-contrast; 0.086, post-contrast) or PRL/M presence (P = 0.234, pre-contrast; 0.163, post-contrast). Median χ were less negative in PRL+ and PRL/M+ than in PRL- and PRL/M-. Mean and median pre-/post-contrast R2* were slower in PRL+ compared to PRL-. Mean and median pre-/post-contrast R2* were slower in PRL/M+ than in PRL/M-. PRL presence at baseline was associated with confirmed EDSS Plus progression (OR 3.75 [1.22-7.59]) and PRL/M+ at baseline with confirmed EDSS Plus progression (OR 3.63 [1.14-7.43]).

DATA CONCLUSION

Evidence of BBB breakdown in PRLs was not seen. Quantitative metrics confirmed prior results suggesting greater demyelination, cell loss, and possibly disruption of tissue anisotropy in PRLs.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

MR myelin imaging in multiple sclerosis: A scoping review

The inability of disease-modifying therapies to stop the progression of multiple sclerosis (MS), has led to the development of a new therapeutic strategy focussing on myelin repair. While conventional MRI lacks sensitivity for quantifying myelin damage, advanced MRI techniques are proving effective. The development of targeted therapeutics requires histological validation of myelin imaging results, alongside the crucial task of establishing correlations between myelin imaging results and clinical assessments, so that the effectiveness of therapeutic interventions can be evaluated. The aims of this scoping review were to identify myelin imaging methods - some of which have been histologically validated, and to determine how these approaches correlate with clinical assessments of people with MS (pwMS), thus allowing for effective therapeutic evaluation. A search of two databases was undertaken for publications relating to studies on adults MS using either MRI/MR-histology of the MS brain in the range 1990-to-2022. The myelin imaging methods specified were relaxometry, magnetization transfer, and quantitative susceptibility. Relaxometry was used most frequently, with myelin water fraction (MWF) being the primary metric. Studies conducted on tissue from various regions of the brain showed that MWF was significantly lower in pwMS than in healthy controls. Magnetization transfer ratio indicated that the macromolecular content of lesions was lower than that of normal-appearing tissue. Higher magnetic susceptibility of lesions were indicative of myelin breakdown and iron accumulation. Several myelin imaging metrics were correlated with disability, disease severity and duration. Many studies showed a good correlation between myelin measured histologically and by MR myelin imaging techniques.

Quantitative magnetic resonance imaging reflects different levels of histologically determined myelin densities in multiple sclerosis, including remyelination in inactive multiple sclerosis lesions

Magnetic resonance imaging (MRI) of focal or diffuse myelin damage or remyelination may provide important insights into disease progression and potential treatment efficacy in multiple sclerosis (MS). We performed post-mortem MRI and histopathological myelin measurements in seven progressive MS cases to evaluate the ability of three myelin-sensitive MRI scans to distinguish different stages of MS pathology, particularly chronic demyelinated and remyelinated lesions. At 3 Tesla, we acquired two different myelin water imaging (MWI) scans and magnetisation transfer ratio (MTR) data. Histopathology included histochemical stainings for myelin phospholipids (LFB) and iron as well as immunohistochemistry for myelin proteolipid protein (PLP), CD68 (phagocytosing microglia/macrophages) and BCAS1 (remyelinating oligodendrocytes). Mixed-effects modelling determined which histopathological metric best predicted MWF and MTR in normal-appearing and diffusely abnormal white matter, active/inactive, inactive, remyelinated and ischemic lesions. Both MWI measures correlated well with each other and histology across regions, reflecting the different stages of MS pathology. MTR data showed a considerable influence of components other than myelin and a strong dependency on tissue storage duration. Both MRI and histology revealed increased myelin densities in inactive compared with active/inactive lesions. Chronic inactive lesions harboured single scattered myelin fibres indicative of low-level remyelination. Mixed-effects modelling showed that smaller differences between white matter areas were linked to PLP densities and only to a small extent confounded by iron. MWI reflects differences in myelin lipids and proteins across various levels of myelin densities encountered in MS, including low-level remyelination in chronic inactive lesions.

Statistical analyses of motion-corrupted MRI relaxometry data computed from multiple scans

BACKGROUND

Consistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses.

NEW METHOD

The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2 * , which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2 * , and MTsat, computed from multiple sets of images.

RESULTS

QUIQI restores homoscedasticity in analyses of quantitative MRI data computed from multiple scans. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy.

COMPARISON WITH EXISTING METHODS

QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis.

CONCLUSION

QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.

Higher hippocampal diffusivity values in welders are associated with greater R2* in the red nucleus and lower psychomotor performance

INTRODUCTION

Chronic excessive welding exposure may be related to higher metal accumulation and structural differences in different subcortical structures. We examined how welding affected brain structures and their associations with metal exposure and neurobehavioral consequences.

METHODS

Study includes 42 welders and 31 controls without a welding history. Welding-related structural differences were assessed by volume and diffusion tensor imaging (DTI) metrics in basal ganglia, red nucleus (RN), and hippocampus. Metal exposure was estimated by both exposure questionnaires and whole blood metal levels. Brain metal accumulations were estimated by R1 (for Mn) and R2* (for Fe). Neurobehavioral status was assessed by standard neuropsychological tests.

RESULTS

Compared to controls, welders displayed higher hippocampal mean (MD), axial (AD), and radial diffusivity (RD) (p's < 0.036), but similar DTI or volume in other ROIs (p's > 0.117). Welders had higher blood metal levels (p's < 0.004), higher caudate and RN R2* (p's < 0.014), and lower performance on processing/psychomotor speed, executive function, and visuospatial processing tasks (p's < 0.046). Higher caudate and RN R2* were associated with higher blood Fe and Pb (p's < 0.043), respectively. RN R2* was a significant predictor of all hippocampal diffusivity metrics (p's < 0.006). Higher hippocampal MD and RD values were associated with lower Trail Making Test-A scores (p's < 0.025). A mediation analysis of both groups revealed blood Pb indirectly affected hippocampal diffusivity via RN R2* (p's < 0.041).

DISCUSSION

Welding-related higher hippocampal diffusivity metrics may be associated with higher RN R2* and lower psychomotor speed performance. Future studies are warranted to test the role of Pb exposure in these findings.

Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study

The in-vivo profiling of iron and myelin across cortical depths and underlying white matter has important implications for advancing knowledge about their roles in brain development and degeneration. Here, we utilize χ-separation, a recently-proposed advanced susceptibility mapping that creates positive (χ_pos) and negative (χ_neg) susceptibility maps, to generate the depth-wise profiles of χ_pos and χ_neg as surrogate biomarkers for iron and myelin, respectively. Two regional sulcal fundi of precentral and middle frontal areas are profiled and compared with findings from previous studies. The results show that the χ_pos profiles peak at superificial white matter (SWM), which is an area beneath cortical gray matter known to have the highest accumulation of iron within the cortex and white matter. On the other hand, the χ_neg profiles increase in SWM toward deeper white matter. These characteristics in the two profiles are in agreement with histological findings of iron and myelin. Furthermore, the χ_neg profiles report regional differences that agree with well-known distributions of myelin concentration. When the two profiles are compared with those of QSM and R₂*, different shapes and peak locations are observed. This preliminary study offers an insight into one of the possible applications of χ-separation for exploring microstructural information of the human brain, as well as clinical applications in monitoring changes of iron and myelin in related diseases.

Both noise-floor and tissue compartment difference in diffusivity contribute to FA dependence on b-value in diffusion MRI

Noninvasive diffusion magnetic resonance imaging (dMRI) has been widely employed in both clinical and research settings to investigate brain tissue microstructure. Despite the evidence that dMRI-derived fractional anisotropy (FA) correlates with white matter properties, the metric is not specific. Recent studies have reported that FA is dependent on the b-value, and its origin has primarily been attributed to either the influence of microstructure or the noise-floor effect. A systematic investigation into the inter-relationship of these two effects is however still lacking. This study aims to quantify contributions of the reported differences in intra- and extra-neurite diffusivity to the observed changes in FA, in addition to the noise in measurements. We used in-vivo and post-mortem human brain imaging, as well as numerical simulations and histological validation, for this purpose. Our investigations reveal that the percentage difference of FA between b-values (pdFA) has significant positive associations with neurite density index (NDI), which is derived from in-vivo neurite orientation dispersion and density imaging (NODDI), or Bielschowsky's silver impregnation (BIEL) staining sections of fixed post-mortem human brain samples. Furthermore, such an association is found to be varied with Signal-to-Noise Ratio (SNR) level, indicating a nonlinear interaction effect between tissue microstructure and noise. Finally, a multicompartment model simulation revealed that these findings can be driven by differing diffusivities of intra- and extra-neurite compartments in tissue, with the noise-floor further amplifying the effect. In conclusion, both the differences in intra- and extra-neurite diffusivity and noise-floor effects significantly contribute to the FA difference associated with the b-value.

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.

Tensor image registration library: Deformable registration of stand-alone histology images to whole-brain post-mortem MRI data

BACKGROUND

Accurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data.

METHODS

Our pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slab photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline.

RESULTS

All 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks.

CONCLUSIONS

Our open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.

Quantitative MRI in Multiple Sclerosis: From Theory to Application

Quantitative MR imaging techniques allow evaluating different aspects of brain microstructure, providing meaningful information about the pathophysiology of damage in CNS disorders. In the study of patients with MS, quantitative MR imaging techniques represent an invaluable tool for studying changes in myelin and iron content occurring in the context of inflammatory and neurodegenerative processes. In the first section of this review, we summarize the physics behind quantitative MR imaging, here defined as relaxometry and quantitative susceptibility mapping, and describe the neurobiological correlates of quantitative MR imaging findings. In the second section, we focus on quantitative MR imaging application in MS, reporting the main findings in both the gray and white matter compartments, separately addressing macroscopically damaged and normal-appearing parenchyma.

An automated pipeline for extracting histological stain area fraction for voxelwise quantitative MRI-histology comparisons

The acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction, SAF) from multiple immunohistochemical (IHC) stains. The pipeline is designed to directly address key IHC artefacts related to tissue staining and slide digitisation. Here, the pipeline was applied to post-mortem human brain data from multiple subjects, relating MRI parameters (FA, MD, RD, AD, R2*, R1) to IHC slides stained for myelin, neurofilaments, microglia and activated microglia. Utilising high-quality MRI-histology co-registrations, we then performed whole-slide voxelwise comparisons (simple correlations, partial correlations and multiple regression analyses) between multimodal MRI- and IHC-derived parameters. The pipeline was found to be reproducible, robust to artefacts and generalisable across multiple IHC stains. Our partial correlation results suggest that some simple MRI-SAF correlations should be interpreted with caution, due to the co-localisation of other tissue features (e.g., myelin and neurofilaments). Further, we find activated microglia-a generic biomarker of inflammation-to consistently be the strongest predictor of high DTI FA and low RD, which may suggest sensitivity of diffusion MRI to aspects of neuroinflammation related to microglial activation, even after accounting for other microstructural changes (demyelination, axonal loss and general microglia infiltration). Together, these results show the utility of this approach in carefully curating IHC data and performing multimodal analyses to better understand microstructural relationships with MRI.

Quantitative susceptibility mapping (QSM) of the cardiovascular system: challenges and perspectives

Quantitative susceptibility mapping (QSM) is a powerful, non-invasive, magnetic resonance imaging (MRI) technique that relies on measurement of magnetic susceptibility. So far, QSM has been employed mostly to study neurological disorders characterized by iron accumulation, such as Parkinson's and Alzheimer's diseases. Nonetheless, QSM allows mapping key indicators of cardiac disease such as blood oxygenation and myocardial iron content. For this reason, the application of QSM offers an unprecedented opportunity to gain a better understanding of the pathophysiological changes associated with cardiovascular disease and to monitor their evolution and response to treatment. Recent studies on cardiovascular QSM have shown the feasibility of a non-invasive assessment of blood oxygenation, myocardial iron content and myocardial fibre orientation, as well as carotid plaque composition. Significant technical challenges remain, the most evident of which are related to cardiac and respiratory motion, blood flow, chemical shift effects and susceptibility artefacts. Significant work is ongoing to overcome these challenges and integrate the QSM technique into clinical practice in the cardiovascular field.

Heritability of R2* iron in the basal ganglia and cortex

BACKGROUND

While iron is essential for normal brain functioning, elevated concentrations are commonly found in neurodegenerative diseases and are associated with impaired cognition and neurological deficits. Currently, only little is known about genetic and environmental factors that influence brain iron concentrations.

METHODS

Heritability and bivariate heritability of regional brain iron concentrations, assessed by R2* relaxometry at 3 Tesla MRI, were estimated with variance components models in 130 middle-aged to elderly participants of the Austrian Stroke Prevention Family Study.

RESULTS

Heritability of R2* iron ranged from 0.46 to 0.82 in basal ganglia and from 0.65 to 0.76 in cortical lobes. Age and BMI explained up to 12% and 9% of the variance of R2* iron, while APOE ε4 carrier status, hypertension, diabetes, hypercholesterolemia, sex and smoking explained 5% or less. The genetic correlation of R2* iron among basal ganglionic nuclei and among cortical lobes ranged from 0.78 to 0.87 and from 0.65 to 0.97, respectively. R2* rates in basal ganglia and cortex were not genetically correlated.

CONCLUSIONS

Regional brain iron concentrations are mainly driven by genetic factors while environmental factors contribute to a certain extent. Brain iron levels in the basal ganglia and cortex are controlled by distinct sets of genes.

Microstructural changes in prodromal dementia with Lewy bodies compared to normal aging: multiparametric quantitative MRI evidences

Dementia with Lewy bodies (DLB) patients show few significant macroscopic structural changes, especially at the early stages of the disease, making quantitative MRI especially interesting to explore more subtle changes that are not detectable by conventional volumetric techniques. Microstructural alterations have been reported in DLB at the dementia stage, but no study to date was conducted in prodromal patients. Here, quantitative MRI data were collected from 46 DLB prodromal patients and 20 healthy elderly subjects, who also underwent a detailed clinical examination including the Mayo Clinic Fluctuation Scale. We conducted voxel-wise between-group comparisons in diffusion tensor imaging (DTI) metrics and in R2* mapping, along with a multivariate analysis combining the two modalities. We highlighted multiple grey matter and white matter microstructural changes in DLB patients at the prodromal stage, compared to control subjects. Our multivariate analysis identified three distinct regional patterns of DTI and R2* changes (anterior, anteromedial, posterior) in DLB patients, that could reflect different neuropathological processes across brain regions. We also observed an association between R2* alterations in the thalamus, and the severity of fluctuations, in the DLB group. These preliminary findings are promising and require future investigations to better understand the biological underpinnings of microstructural alterations.

On the separation of susceptibility sources in quantitative susceptibility mapping: Theory and phantom validation with an in vivo application to multiple sclerosis lesions of different age

PURPOSE

In biological tissue, phase contrast is determined by multiple substances such as iron, myelin or calcifications. Often, these substances occur co-located within the same measurement volume. However, quantitative susceptibility mapping can solely measure the average susceptibility per voxel. To provide new insight in disease progression and mechanisms in neurological diseases, where multiple processes such as demyelination and iron accumulation occur simultaneously in the same location, a separation of susceptibility sources is desirable to disentangle the underlying susceptibility proportions.

METHODS

The basic concept of separating the susceptibility effects from sources with different sign within one voxel is to include information on relaxation rate ΔR₂^∗ in the quantitative susceptibility mapping reconstruction pipeline. The presented reconstruction algorithm is implemented as a constrained minimization problem and solved using conjugate gradients. The algorithm is evaluated using a software phantom and validated in MRI measurements with a phantom containing mixtures of microscopic positive and negative susceptibility sources. Data from three multiple sclerosis patients are used to show in vivo feasibility.

RESULTS

In numerical simulations, the feasibility of disentangling susceptibility sources within the same voxel was confirmed provided the critera of the static dephasing regime were fulfilled. In phantom experiments, the magnitude decay kernel, which is an essential reconstruction parameter of the algorithm, was determined to be D_m=194.5T^-1s^-1ppm^-1, and susceptibility sources could be separated in MRI measurement data.

CONCLUSIONS

In conclusion, in this study a detailed description of the implementation of an algorithm for the separation of positive and negative susceptibility sources within the same volume element as well as its limitations is presented and validated quantitatively in both simulation and phantom experiments for the first time. An application to multiple sclerosis lesions shows promising results for in vivo usability.

Decompose quantitative susceptibility mapping (QSM) to sub-voxel diamagnetic and paramagnetic components based on gradient-echo MRI data

PURPOSE

A method named DECOMPOSE-QSM is developed to decompose bulk susceptibility measured with QSM into sub-voxel paramagnetic and diamagnetic components based on a three-pool complex signal model.

METHODS

Multi-echo gradient echo signal is modeled as a summation of three weighted exponentials corresponding to three types of susceptibility sources: reference susceptibility, diamagnetic and paramagnetic susceptibility relative to the reference. Paramagnetic component susceptibility (PCS) and diamagnetic component susceptibility (DCS) maps are constructed to represent the sub-voxel compartments by solving for linear and nonlinear parameters in the model.

RESULTS

Numerical forward simulation and phantom validation confirmed the ability of DECOMPOSE-QSM to separate the mixture of paramagnetic and diamagnetic components. The PCS obtained from temperature-variant brainstem imaging follows the Curie's Law, which further validated the model and the solver. Initial in vivo investigation of human brain images showed the ability to extract sub-voxel PCS and DCS sources that produce visually enhanced contrast between brain structures comparing to threshold QSM.

Parkinson's disease multimodal imaging: F-DOPA PET, neuromelanin-sensitive and quantitative iron-sensitive MRI

Parkinson's disease (PD) is a neurodegenerative synucleinopathy characterized by the degeneration of neuromelanin (NM)-containing dopaminergic neurons and deposition of iron in the substantia nigra (SN). How regional NM loss and iron accumulation within specific areas of SN relate to nigro-striatal dysfunction needs to be clarified. We measured dopaminergic function in pre- and postcommissural putamen by [¹⁸F]DOPA PET in 23 Parkinson's disease patients and 23 healthy control (HC) participants in whom NM content and iron load were assessed in medial and lateral SN, respectively, by NM-sensitive and quantitative R2* MRI. Data analysis consisted of voxelwise regressions testing the group effect and its interaction with NM or iron signals. In PD patients, R2* was selectively increased in left lateral SN as compared to healthy participants, suggesting a local accumulation of iron in Parkinson's disease. By contrast, NM signal differed between PD and HC, without specific regional specificity within SN. Dopaminergic function in posterior putamen decreased as R2* increased in lateral SN, indicating that dopaminergic function impairment progresses with iron accumulation in the SN. Dopaminergic function was also positively correlated with NM signal in lateral SN, indicating that dopaminergic function impairment progresses with depigmentation in the SN. A complex relationship was detected between R2* in the lateral SN and NM signal in the medial SN. In conclusion, multimodal imaging reveals regionally specific relationships between iron accumulation and depigmentation within the SN of Parkinson's disease and provides in vivo insights in its neuropathology.

Simultaneous T2 and T 2 ∗ mapping of multiple sclerosis lesions with radial RARE-EPI

PURPOSE

The characteristic MRI features of multiple sclerosis (MS) lesions make it conceptually appealing to pursue parametric mapping techniques that support simultaneous generation of quantitative maps of 2 or more MR contrast mechanisms. We present a modular rapid acquisition with relaxation enhancement (RARE)-EPI hybrid that facilitates simultaneous T₂ and T 2 ∗ mapping (2in1-RARE-EPI).

METHODS

In 2in1-RARE-EPI the first echoes in the echo train are acquired with a RARE module, later echoes are acquired with an EPI module. To define the fraction of echoes covered by the RARE and EPI module, an error analysis of T₂ and T 2 ∗ was conducted with Monte Carlo simulations. Radial k-space (under)sampling was implemented for acceleration (R = 2). The feasibility of 2in1-RARE-EPI for simultaneous T₂ and T 2 ∗ mapping was examined in a phantom study mimicking T₂ and T 2 ∗ relaxation times of the brain. For validation, 2in1-RARE-EPI was benchmarked versus multi spin-echo (MSE) and multi gradient-echo (MGRE) techniques. The clinical applicability of 2in1-RARE-EPI was demonstrated in healthy subjects and MS patients.

RESULTS

There was a good agreement between T₂ / T 2 ∗ values derived from 2in1-RARE-EPI and T₂ / T 2 ∗ reference values obtained from MSE and MGRE in both phantoms and healthy subjects. In patients, MS lesions in T₂ and T 2 ∗ maps deduced from 2in1-RARE-EPI could be just as clearly delineated as in reference maps calculated from MSE/MGRE.

CONCLUSION

This work demonstrates the feasibility of radially (under)sampled 2in1-RARE-EPI for simultaneous T₂ and T 2 ∗ mapping in MS patients.

Can MRI measure myelin? Systematic review, qualitative assessment, and meta-analysis of studies validating microstructural imaging with myelin histology

Recent years have seen an increased understanding of the importance of myelination in healthy brain function and neuropsychiatric diseases. Non-invasive microstructural magnetic resonance imaging (MRI) holds the potential to expand and translate these insights to basic and clinical human research, but the sensitivity and specificity of different MR markers to myelination is a subject of debate. To consolidate current knowledge on the topic, we perform a systematic review and meta-analysis of studies that validate microstructural imaging by combining it with myelin histology. We find meta-analytic evidence for correlations between various myelin histology metrics and markers from different MRI modalities, including fractional anisotropy, radial diffusivity, macromolecular pool, magnetization transfer ratio, susceptibility and longitudinal relaxation rate, but not mean diffusivity. Meta-analytic correlation effect sizes range widely, between R2 = 0.26 and R2 = 0.82. However, formal comparisons between MRI-based myelin markers are limited by methodological variability, inconsistent reporting and potential for publication bias, thus preventing the establishment of a single most sensitive strategy to measure myelin with MRI. To facilitate further progress, we provide a detailed characterisation of the evaluated studies as an online resource. We also share a set of 12 recommendations for future studies validating putative MR-based myelin markers and deploying them in vivo in humans.

Altered iron and myelin in premanifest Huntington's Disease more than 20 years before clinical onset: Evidence from the cross-sectional HD Young Adult Study

BACKGROUND

Pathological processes in Huntington's disease (HD) begin many years prior to symptom onset. Recently we demonstrated that in a premanifest cohort approximately 24 years from predicted disease onset, despite intact function, there was evidence of subtle neurodegeneration. Here, we use novel imaging techniques to determine whether macro- and micro-structural changes can be detected across the whole-brain in the same cohort.

METHODS

62 premanifest HD (PreHD) and 61 controls from the HD Young Adult Study (HD-YAS) were included. Grey and white matter volume, diffusion weighted imaging (DWI) measures of white matter microstructure, multiparametric maps (MPM) estimating myelin and iron content from magnetization transfer (MT), proton density (PD), longitudinal relaxation (R1) and effective transverse relaxation (R2*), and myelin g-ratio were examined. Group differences between PreHD and controls were assessed; associations between all imaging metrics and disease burden and CSF neurofilament light (NfL) were also performed. Volumetric and MPM results were corrected at a cluster-wise value of familywise error (FWE) 0.05. Diffusion and g-ratio results were corrected via threshold-free cluster enhancement at FWE 0.05.

FINDINGS

We showed significantly increased R1 and R2*, suggestive of increased iron, in the putamen, globus pallidum and external capsule of PreHD participants. There was also a significant association between lower cortical R2*, suggestive of reduced myelin or iron, and higher CSF NfL in the frontal lobe and the parieto-occipital cortices. No other results were significant at corrected levels.

INTERPRETATION

Increased iron in subcortical structures and the surrounding white matter is a feature of very early PreHD. Furthermore, increases in CSF NfL were linked to microstructural changes in the posterior parietal-occipital cortex, a region previously shown to undergo some of the earliest cortical changes in HD. These findings suggest that disease related process are occurring in both subcortical and cortical regions more than 20 years from predicted disease onset.

Iron Heterogeneity in Early Active Multiple Sclerosis Lesions

OBJECTIVE

Multiple sclerosis (MS) is a heterogeneous inflammatory demyelinating disease. Iron distribution is altered in MS patients' brains, suggesting iron liberation within active lesions amplifies demyelination and neurodegeneration. Whether the amount and distribution of iron are similar or different among different MS immunopatterns is currently unknown.

METHODS

We used synchrotron X-ray fluorescence imaging, histology, and immunohistochemistry to compare the iron quantity and distribution between immunopattern II and III early active MS lesions. We analyzed archival autopsy and biopsy tissue from 21 MS patients.

RESULTS

Immunopattern II early active lesions contain 64% more iron (95% confidence interval [CI] = 17-127%, p = 0.004) than immunopattern III lesions, and 30% more iron than the surrounding periplaque white matter (95% CI = 3-64%, p = 0.03). Iron in immunopattern III lesions is 28% lower than in the periplaque white matter (95% CI = -40 to -14%, p < 0.001). When normalizing the iron content of early active lesions to that of surrounding periplaque white matter, the ratio is significantly higher in immunopattern II (p < 0.001). Microfocused X-ray fluorescence imaging shows that iron in immunopattern II lesions localizes to macrophages, whereas macrophages in immunopattern III lesions contain little iron.

INTERPRETATION

Iron distribution and content are heterogeneous in early active MS lesions. Iron accumulates in macrophages in immunopattern II, but not immunopattern III lesions. This heterogeneity in the two most common MS immunopatterns may be explained by different macrophage polarization, origin, or different demyelination mechanisms, and paves the way for developing new or using existing iron-sensitive magnetic resonance imaging techniques to differentiate among immunopatterns in the general nonbiopsied MS patient population. ANN NEUROL 2021;89:498-510.

Myelin quantification with MRI: A systematic review of accuracy and reproducibility

OBJECTIVES

Currently, multiple sclerosis is treated with anti-inflammatory therapies, but these treatments lack efficacy in progressive disease. New treatment strategies aim to repair myelin damage and efficacy evaluation of such new therapies would benefit from validated myelin imaging techniques. Several MRI methods for quantification of myelin density are available now. This systematic review aims to analyse the performance of these MRI methods.

METHODS

Studies comparing myelin quantification by MRI with histology, the current gold standard, or assessing reproducibility were retrieved from PubMed/MEDLINE and Embase (until December 2019). Included studies assessed both myelin histology and MRI quantitatively. Correlation or variance measurements were extracted from the studies. Non-parametric tests were used to analyse differences in study methodologies.

RESULTS

The search yielded 1348 unique articles. Twenty-two animal studies and 13 human studies correlated myelin MRI with histology. Eighteen clinical studies analysed the reproducibility. Overall bias risk was low or unclear. All MRI methods performed comparably, with a mean correlation between MRI and histology of R²=0.54 (SD=0.30) for animal studies, and R²=0.54 (SD=0.18) for human studies. Reproducibility for the MRI methods was good (ICC=0.75-0.93, R²=0.90-0.98, COV=1.3-27%), except for MTR (ICC=0.05-0.51).

CONCLUSIONS

Overall, MRI-based myelin imaging methods show a fairly good correlation with histology and a good reproducibility. However, the amount of validation data is too limited and the variability in performance between studies is too large to select the optimal MRI method for myelin quantification yet.

Mapping Human Laryngeal Motor Cortex during Vocalization

The representations of the articulators involved in human speech production are organized somatotopically in primary motor cortex. The neural representation of the larynx, however, remains debated. Both a dorsal and a ventral larynx representation have been previously described. It is unknown, however, whether both representations are located in primary motor cortex. Here, we mapped the motor representations of the human larynx using functional magnetic resonance imaging and characterized the cortical microstructure underlying the activated regions. We isolated brain activity related to laryngeal activity during vocalization while controlling for breathing. We also mapped the articulators (the lips and tongue) and the hand area. We found two separate activations during vocalization-a dorsal and a ventral larynx representation. Structural and quantitative neuroimaging revealed that myelin content and cortical thickness underlying the dorsal, but not the ventral larynx representation, are similar to those of other primary motor representations. This finding confirms that the dorsal larynx representation is located in primary motor cortex and that the ventral one is not. We further speculate that the location of the ventral larynx representation is in premotor cortex, as seen in other primates. It remains unclear, however, whether and how these two representations differentially contribute to laryngeal motor control.

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.

Multiparameter quantitative histological MRI values in high-grade gliomas: a potential biomarker of tumor progression

Background

Conventional MRI poorly distinguishes brain parenchyma microscopically invaded by high-grade gliomas (HGGs) from the normal brain. By contrast, quantitative histological MRI (hMRI) measures brain microstructure in terms of physical MR parameters influenced by histochemical tissue composition. We aimed to determine the relationship between hMRI parameters in the area surrounding the surgical cavity and the presence of HGG recurrence.

Methods

Patients were scanned after surgery with an hMRI multiparameter protocol that allowed for estimations of longitudinal relaxation rate (R1) = 1/T1, effective transverse relaxation rate (R2)*=1/T2*, magnetization transfer saturation (MT_sat), and proton density. The initial perioperative zone (IPZ) was segmented on the postoperative MRI. Once recurrence appeared on conventional MRI, the area of relapsing disease was delineated (extension zone, EZ). Conventional MRI showing recurrence and hMRI were coregistered, allowing for the extraction of parameters R1, R2*, MT_sat, and PD in 3 areas: the overlap area between the IPZ and EZ (OZ), the peritumoral brain zone, PBZ (PBZ = IPZ - OZ), and the area of recurrence (RZ = EZ - OZ).

Results

Thirty-one patients with HGG who underwent gross-total resection were enrolled. MT_sat and R1 were the most strongly associated with tumor progression. MT_sat was significantly lower in the OZ and RZ, compared to PBZ. R1 was significantly lower in RZ compared to PBZ. PD was significantly higher in OZ compared to PBZ, and R2* was higher in OZ compared to PBZ or RZ. These changes were detected 4 to 120 weeks before recurrence recognition on conventional MRI.

Conclusions

HGG recurrence was associated with hMRI parameters' variation after initial surgery, weeks to months before overt recurrence.

Selective inversion recovery quantitative magnetization transfer imaging: Toward a 3 T clinical application in multiple sclerosis

BACKGROUND

Assessing the degree of myelin injury in patients with multiple sclerosis (MS) is challenging due to the lack of magnetic resonance imaging (MRI) methods specific to myelin quantity. By measuring distinct tissue parameters from a two-pool model of the magnetization transfer (MT) effect, quantitative magnetization transfer (qMT) may yield these indices. However, due to long scan times, qMT has not been translated clinically.

OBJECTIVES

We aim to assess the clinical feasibility of a recently optimized selective inversion recovery (SIR) qMT and to test the hypothesis that SIR-qMT-derived metrics are informative of radiological and clinical disease-related changes in MS.

METHODS

A total of 18 MS patients and 9 age- and sex-matched healthy controls (HCs) underwent a 3.0 Tesla (3 T) brain MRI, including clinical scans and an optimized SIR-qMT protocol. Four subjects were re-scanned at a 2-week interval to determine inter-scan variability.

RESULTS

SIR-qMT measures differed between lesional and non-lesional tissue (p < 0.0001) and between normal-appearing white matter (NAWM) of patients with more advanced disability and normal white matter (WM) of HCs (p < 0.05). SIR-qMT measures were associated with lesion volumes, disease duration, and disability scores (p ⩽ 0.002).

CONCLUSION

SIR-qMT at 3 T is clinically feasible and predicts both radiological and clinical disease severity in MS.

Targeting Iron Dyshomeostasis for Treatment of Neurodegenerative Disorders

While iron has an important role in the normal functioning of the brain owing to its involvement in several physiological processes, dyshomeostasis has been found in many neurodegenerative disorders, as evidenced by both histopathological and imaging studies. Although the exact causes have remained elusive, the fact that altered iron levels have been found in disparate diseases suggests that iron may contribute to their development and/or progression. As such, the processes involved in iron dyshomeostasis may represent novel therapeutic targets. There are, however, many questions about the exact interplay between neurodegeneration and altered iron homeostasis. Some insight can be gained by considering the parallels with respect to what occurs in healthy aging, which is also characterized by increased iron throughout many regions in the brain along with progressive neurodegeneration. Nevertheless, the exact mechanisms of iron-mediated damage are likely disease specific to a certain degree, given that iron plays a crucial role in many disparate biological processes, which are not always affected in the same way across different neurodegenerative disorders. Moreover, it is not even entirely clear yet whether iron actually has a causative role in all of the diseases where altered iron levels have been noted. For example, there is strong evidence of iron dyshomeostasis leading to neurodegeneration in Parkinson's disease, but there is still some question as to whether changes in iron levels are merely an epiphenomenon in multiple sclerosis. Recent advances in neuroimaging now offer the possibility to detect and monitor iron levels in vivo, which allows for an improved understanding of both the temporal and spatial dynamics of iron changes and associated neurodegeneration compared to post-mortem studies. In this regard, iron-based imaging will likely play an important role in the development of therapeutic approaches aimed at addressing altered iron dynamics in neurodegenerative diseases. Currently, the bulk of such therapies have focused on chelating excess iron. Although there is some evidence that these treatment options may yield some benefit, they are not without their own limitations. They are generally effective at reducing brain iron levels, as assessed by imaging, but clinical benefits are more modest. New drugs that specifically target iron-related pathological processes may offer the possibility to prevent, or at the least, slow down irreversible neurodegeneration, which represents an unmet therapeutic target.

Probing axons using multi-compartmental diffusion in multiple sclerosis

Objects

The diffusion‐based spherical mean technique (SMT) provides a novel model to relate multi‐b‐value diffusion magnetic resonance imaging (MRI) data to features of tissue microstructure. We propose the first clinical application of SMT to image the brain of patients with multiple sclerosis (MS) and investigate clinical feasibility and translation.

Methods

Eighteen MS patients and nine age‐ and sex‐matched healthy controls (HCs) underwent a 3.0 Tesla scan inclusive of clinical sequences and SMT images (isotropic resolution of 2 mm). Axial diffusivity (AD), apparent axonal volume fraction (V_ax), and effective neural diffusivity (D_ax) parametric maps were fitted. Differences in AD, V_ax, and D_ax between anatomically matched regions reflecting different tissues types were estimated using generalized linear mixed models for binary outcomes.

Results

Differences were seen in all SMT‐derived parameters between chronic black holes (cBHs) and T2‐lesions (P ≤ 0.0016), in V_ax and AD between T2‐lesions and normal appearing white matter (NAWM) (P < 0.0001), but not between the NAWM and normal WM in HCs. Inverse correlations were seen between V_ax and AD in cBHs (r = −0.750, P = 0.02); in T2‐lesions D_ax values were associated with V_ax (r = 0.824, P < 0.0001) and AD (r = 0.570, P = 0.014).

Interpretations

SMT‐derived metrics are sensitive to pathological changes and hold potential for clinical application in MS patients.

Matching ex vivo MRI With Iron Histology: Pearls and Pitfalls

Iron levels in the brain can be estimated using newly developed specific magnetic resonance imaging (MRI) sequences. This technique has several applications, especially in neurodegenerative disorders like Alzheimer's disease or Parkinson's disease. Coupling ex vivo MRI with histology allows neuroscientists to better understand what they see in the images. Iron is one of the most extensively studied elements, both by MRI and using histological or physical techniques. Researchers were initially only able to make visual comparisons between MRI images and different types of iron staining, but the emergence of specific MRI sequences like R2* or quantitative susceptibility mapping meant that quantification became possible, requiring correlations with physical techniques. Today, with advances in MRI and image post-processing, it is possible to look for MRI/histology correlations by matching the two sorts of images. For the result to be acceptable, the choice of methodology is crucial, as there are hidden pitfalls every step of the way. In order to review the advantages and limitations of ex vivo MRI correlation with iron-based histology, we reviewed all the relevant articles dealing with the topic in humans. We provide separate assessments of qualitative and quantitative studies, and after summarizing the significant results, we emphasize all the pitfalls that may be encountered.

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.

Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis

Objectives

Conventional MRI is not sensitive to many pathological processes underpinning multiple sclerosis (MS) ongoing in normal appearing brain tissue (NABT). Quantitative MRI (qMRI) and a multiparameter mapping (MPM) protocol are used to simultaneously quantify magnetization transfer (MT) saturation, transverse relaxation rate R2* (1/T2*) and longitudinal relaxation rate R1 (1/T1), and assess differences in NABT microstructure between MS patients and healthy controls (HC).

Methods

This prospective cross-sectional study involves 36 MS patients (21 females, 15 males; age range 22–63 years; 15 relapsing-remitting MS - RRMS; 21 primary or secondary progressive MS - PMS) and 36 age-matched HC (20 females, 16 males); age range 21–61 years). The qMRI maps are computed and segmented in lesions and 3 normal appearing cerebral tissue classes: normal appearing cortical grey matter (NACGM), normal appearing deep grey matter (NADGM), normal appearing white matter (NAWM). Individual median values are extracted for each tissue class and MR parameter. MANOVAs and stepwise regressions assess differences between patients and HC.

Results

MS patients are characterized by a decrease in MT, R2* and R1 within NACGM (p < .0001) and NAWM (p < .0001). In NADGM, MT decreases (p < .0001) but R2* and R1 remain normal. These observations tend to be more pronounced in PMS. Quantitative MRI parameters are independent predictors of clinical status: EDSS is significantly related to R1 in NACGM and R2* in NADGM; the latter also predicts motor score. Cognitive score is best predicted by MT parameter within lesions.

Conclusions

Multiparametric data of brain microstructure concord with the literature, predict clinical performance and suggest a diffuse reduction in myelin and/or iron content within NABT of MS patients.

•

We revisit microstructural alterations of NABT in MS patients by simultaneously quantifying three MRI parameters.

•

Data suggest reduction of MT/R2*/R1 in NABT of MS patients, suggesting a reduction in myelin and/or iron content.

•

Quantitative MRI parameters in NABT are independent predictors of clinical status.

The influence of brain iron on myelin water imaging

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