Magnetic resonance techniques to quantify tissue damage, tissue repair, and functional cortical reorganization in multiple sclerosis

Motor function in multiple sclerosis assessed by navigated transcranial magnetic stimulation mapping

INTRODUCTION

Impaired motor function is a major cause of disability in multiple sclerosis (MS), involving various neuroplasticity processes typically assessed by neuroimaging. This study aimed to determine whether navigated transcranial magnetic stimulation (nTMS) could also provide biomarkers of motor cortex plasticity in patients with MS (pwMS).

METHODS

nTMS motor mapping was performed for hand and leg muscles bilaterally. nTMS variables included the amplitude and latency of motor evoked potentials (MEPs), corticospinal excitability measures, and the size of cortical motor maps (CMMs). Clinical assessment included disability (Expanded Disability Status Scale, EDSS), strength (MRC scale, pinch and grip), and dexterity (9-hole Pegboard Test).

RESULTS

nTMS motor mapping was performed in 68 pwMS. PwMS with high disability (EDSS ≥ 3) had enlarged CMMs with less dense distribution of MEPs and various MEP parameter changes compared to pwMS with low disability (EDSS < 3). Patients with progressive MS had also various MEP parameter changes compared to pwMS with relapsing remitting form. MRC score correlated positively with MEP amplitude and negatively with MEP latency, pinch strength correlated negatively with CMM volume and dexterity with MEP latency.

CONCLUSIONS

This is the first study to perform 4-limb cortical motor mapping in pwMS using a dedicated nTMS procedure. By quantifying the cortical surface representation of a given muscle and the variability of MEP within this representation, nTMS can provide new biomarkers of motor function impairment in pwMS. Our study opens perspectives for the use of nTMS as an objective method for assessing pwMS disability in clinical practice.

Brain functional connectivity analysis in patients with relapsing-remitting multiple sclerosis: A graph theory approach of EEG resting state

Multiple sclerosis (MS) is an autoimmune disease related to the central nervous system (CNS). This study aims to investigate the effects of MS on the brain's functional connectivity network using the electroencephalogram (EEG) resting-state signals and graph theory approach. Resting-state eyes-closed EEG signals were recorded from 20 patients with relapsing-remitting MS (RRMS) and 18 healthy cases. In this study, the prime objective is to calculate the connectivity between EEG channels to assess the differences in brain functional network global features. The results demonstrated lower cortical activity in the alpha frequency bands and higher activity for the gamma frequency bands in patients with RRMS compared to the healthy group. In this study, graph metric calculations revealed a significant difference in the diameter of the functional brain network based on the directed transfer function (DTF) measure between the two groups, indicating a higher diameter in RRMS cases for the alpha frequency band. A higher diameter for the functional brain network in MS cases can result from anatomical damage. In addition, considerable differences between the networks' global efficiency and transitivity based on the imaginary part of the coherence (iCoh) measure were observed, indicating higher global efficiency and transitivity in the delta, theta, and beta frequency bands for RRMS cases, which can be related to the compensatory functional reaction from the brain. This study indicated that in RRMS cases, some of the global characteristics of the brain's functional network, such as diameter and global efficiency, change and can be illustrated even in the resting-state condition when the brain is not under cognitive load.

Tracking oxidation-induced alterations in fibrin clot formation by NMR-based methods

Plasma fibrinogen is an important coagulation factor and susceptible to post-translational modification by oxidants. We have reported impairment of fibrin polymerization after exposure to hypochlorous acid (HOCl) and increased methionine oxidation of fibrinogen in severely injured trauma patients. Molecular dynamics suggests that methionine oxidation poses a mechanistic link between oxidative stress and coagulation through protofibril lateral aggregation by disruption of AαC domain structures. However, experimental evidence explaining how HOCl oxidation impairs fibrinogen structure and function has not been demonstrated. We utilized polymerization studies and two dimensional-nuclear magnetic resonance spectrometry (2D-NMR) to investigate the hypothesis that HOCl oxidation alters fibrinogen conformation and T₂ relaxation time of water protons in the fibrin gels. We have demonstrated that both HOCl oxidation of purified fibrinogen and addition of HOCl-oxidized fibrinogen to plasma fibrinogen solution disrupted lateral aggregation of protofibrils similarly to competitive inhibition of fibrin polymerization using a recombinant AαC fragment (AαC 419–502). DOSY NMR measurement of fibrinogen protons demonstrated that the diffusion coefficient of fibrinogen increased by 17.4%, suggesting the oxidized fibrinogen was more compact and fast motion in the prefibrillar state. 2D-NMR analysis reflected that water protons existed as bulk water (T₂) and intermediate water (T_2i) in the control plasma fibrin. Bulk water T₂ relaxation time was increased twofold and correlated positively with the level of HOCl oxidation. However, T₂ relaxation of the oxidized plasma fibrin gels was dominated by intermediate water. Oxidation induced thinner fibers, in which less water is released into the bulk and water fraction in the hydration shell was increased. We have confirmed that T₂ relaxation is affected by the self-assembly of fibers and stiffness of the plasma fibrin gel. We propose that water protons can serve as an NMR signature to probe oxidative rearrangement of the fibrin clot.

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture. Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls. Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies. Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity. Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture. Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls. Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies. Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity. Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.

How changes in brain activity and connectivity are associated with motor performance in people with MS

People with multiple sclerosis (MS) exhibit pronounced changes in brain structure, activity, and connectivity. While considerable work has begun to elucidate how these neural changes contribute to behavior, the heterogeneity of symptoms and diagnoses makes interpretation of findings and application to clinical practice challenging. In particular, whether MS related changes in brain activity or brain connectivity protect against or contribute to worsening motor symptoms is unclear. With the recent emergence of neuromodulatory techniques that can alter neural activity in specific brain regions, it is critical to establish whether localized brain activation patterns are contributing to (i.e. maladaptive) or protecting against (i.e. adaptive) progression of motor symptoms. In this manuscript, we consolidate recent findings regarding changes in supraspinal structure and activity in people with MS and how these changes may contribute to motor performance. Furthermore, we discuss a hypothesis suggesting that increased neural activity during movement may be either adaptive or maladaptive depending on where in the brain this increase is observed. Specifically, we outline preliminary evidence suggesting sensorimotor cortex activity in the ipsilateral cortices may be maladaptive in people with MS. We also discuss future work that could supply data to support or refute this hypothesis, thus improving our understanding of this important topic.

Longitudinal changes of cerebral glutathione (GSH) levels associated with the clinical course of disease progression in patients with secondary progressive multiple sclerosis

BACKGROUND

Increased oxidative stress leads to loss of glutathione (GSH). We have reported lower cerebral GSH in patients with secondary progressive multiple sclerosis (SPMS), indicating the involvement of oxidative stress in multiple sclerosis (MS) pathophysiology.

OBJECTIVE

This study expanded upon our earlier work by examining longitudinal changes in cerebral GSH in patients with SPMS in relation to their clinical status.

METHODS

A total of 13 patients with SPMS (Expanded Disability Status Scale (EDSS) = 4.0-6.5; MS duration = 21.2 ± 8.7 years) and 12 controls were studied over 3-5 years. GSH mapping was acquired from frontal and parietal regions using a multiple quantum chemical shift imaging technique at 3 T. Clinical assessments of the patient's disability included EDSS, gait, motor strength, ataxia, tremor, brainstem function and vision changes.

RESULTS

Brain GSH concentrations in patients were lower than those in controls for both baseline and 3- to 5-year follow-ups. Longitudinal GSH changes of patients were associated with their neurologist's blinded appraisal of their clinical progression. Patients judged to have worsening clinical status had significantly greater declines in frontal GSH concentrations than those with stable clinical status.

CONCLUSION

GSH provides a distinct measure associated with the disease progression in SPMS, possibly due to its dynamic alignment with pathogenic processes of MS related to oxidative stress.

Quantification and reproducibility assessment of the regional brain T2 relaxation in naïve rats at 7T

PURPOSE

To measure the reproducibility of T₂ relaxation and to determine the statistical power of T₂ mapping in the rat brain as a characteristic of the baseline performance of the T₂ relaxation as a potential biomarker of neurotoxicity.

MATERIALS AND METHODS

Multislice multiecho spin-echo imaging was utilized to obtain the quantitative T₂ maps in 138 naïve rats at 7T. Images were skull-stripped and coregistered to the common anatomical reference. A full anatomical segmentation mask, which included all major brain structures, was created using the same reference T₂ map. The overall variability map was also calculated from all T₂ maps and the areas with arbitrarily high variability (coefficient of variation >25%) were excluded from the full segmentation mask to produce a trimmed mask. T₂ maps were segmented using both these masks and statistical power analysis was conducted in all segmented areas.

RESULTS

The coefficient of variation of T₂ relaxation in different brain areas varied from 5.4% (cerebrospinal fluid) to 1.2% (cortex) when using a full segmentation mask. The use of a trimmed segmentation mask decreased the coefficient of variation in many areas, which ranged between 3.2% (inferior colliculi) and 1.2% (cortex) in this case. As revealed by statistical power analysis to detect 5% change with power of 0.8, the minimum number of observations needed for different areas ranged from 3 (cortex) to 8 (inferior colliculi) in the case of use of a trimmed segmentation mask.

CONCLUSION

T₂ relaxation is a very reproducible MRI parameter of the rat brain with high statistical power, which allows detecting very small changes in groups consisting of a minimal number of experimental animals.

LEVEL OF EVIDENCE

1 J. Magn. Reson. Imaging 2017;45:700-709.

Validation of network communicability metrics for the analysis of brain structural networks

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Diffusion tensor imaging based network analysis detects alterations of neuroconnectivity in patients with clinically early relapsing-remitting multiple sclerosis

Although it is inarguable that conventional MRI (cMRI) has greatly contributed to the diagnosis and assessment of multiple sclerosis (MS), cMRI does not show close correlation with clinical findings or pathologic features, and is unable to predict prognosis or stratify disease severity. To this end, diffusion tensor imaging (DTI) with tractography and neuroconnectivity analysis may assist disease assessment in MS. We, therefore, attempted this pilot study for initial assessment of early relapsing-remitting MS (RRMS). Neuroconnectivity analysis was used for evaluation of 24 early RRMS patients within 2 years of presentation, and compared to the network measures of a group of 30 age-and-gender-matched normal control subjects. To account for the situation that the connections between two adjacent regions may be disrupted by an MS lesion, a new metric, network communicability, was adopted to measure both direct and indirect connections. For each anatomical area, the brain network communicability and average path length were computed and compared to characterize the network changes in efficiencies. Statistically significant (P < 0.05) loss of communicability was revealed in our RRMS cohort, particularly in the frontal and hippocampal/parahippocampal regions as well as the motor strip and occipital lobes. Correlation with the 25-foot Walk test with communicability measures in the left superior frontal (r = -0.71) as well as the left superior temporal gyrus (r = -0.43) and left postcentral gyrus (r = -0.41) were identified. Additionally identified were increased communicability between the deep gray matter structures (left thalamus and putamen) with the major interhemispheric and intrahemispheric white matter tracts, the corpus callosum, and cingulum, respectively. These foci of increased communicability are thought to represent compensatory changes. The proposed DTI-based neuroconnectivity analysis demonstrated quantifiable, structurally relevant alterations of fiber tract connections in early RRMS and paves the way for longitudinal studies in larger patient groups.

Diffusion kurtosis imaging discriminates patients with white matter lesions from healthy subjects

This work illustrates that DKI reveals white matter lesions and also discriminates healthy subjects from patients with white matter lesions. To show this capability, we have investigated DKI images of a healthy subject and a patient with white matter lesions. The analysis was performed both between and within subjects. Regions of Interest (ROIs) for lesion and normal white matter in the patient images are selected manually (for within subject study) and also the corresponding ROIs in the healthy subject are defined (for between subject study). The results of comparing the estimated values for apparent diffusion and kurtosis parameters show that both D(app) and K(app) can distinguish normal and abnormal tissues. K(app) (D(app)) of the normal regions is greater (lower) than that of the abnormal regions. Another investigation over all voxels in the brain shows an important feature of kurtosis in determining white matter lesions.

Magnetization transfer imaging in premanifest and manifest Huntington disease

BACKGROUND AND PURPOSE

MTI has the potential to detect abnormalities in normal-appearing white and gray matter on conventional MR imaging. Early detection methods and disease progression markers are needed in HD research. Therefore, we investigated MTI parameters and their clinical correlates in premanifest and manifest HD.

MATERIALS AND METHODS

From the Leiden TRACK-HD study, 78 participants (28 controls, 25 PMGC, 25 MHD) were included. Brain segmentation of cortical gray matter, white matter, caudate nucleus, putamen, pallidum, thalamus, amygdala, and hippocampus was performed using FSL's automated tools FAST and FIRST. Individual MTR values were calculated from these regions and MTR histograms constructed. Regression analysis of MTR measures from all gene carriers with clinical measures was performed.

RESULTS

MTR peak height was reduced in both cortical gray (P = .01) and white matter (P = .006) in manifest HD compared with controls. Mean MTR was also reduced in cortical gray matter (P = .01) and showed a trend in white matter (P = .052). Deep gray matter structures showed a uniform pattern of reduced MTR values (P < .05). No differences between premanifest gene carriers and controls were found. MTR values correlated with disease burden and motor and cognitive impairment.

CONCLUSIONS

Throughout the brain, disturbances in MTI parameters are apparent in early HD and are homogeneous across white and gray matter. The correlation of MTI with clinical measures indicates the potential to act as a disease monitor in clinical trials. However, our study does not provide evidence for MTI as a marker in premanifest HD.

MRI signature in a novel mouse model of genetically induced adult oligodendrocyte cell death

Two general pathological processes contribute to multiple sclerosis (MS): acute inflammation and degeneration. While magnetic resonance imaging (MRI) is highly sensitive in detecting abnormalities related to acute inflammation both clinically and in animal models of experimental autoimmune encephalomyelitis (EAE), the correlation of these readouts with acute and future disabilities has been found rather weak. This illustrates the need for imaging techniques addressing neurodegenerative processes associated with MS. In the present work we evaluated the sensitivity of different MRI techniques (T(2) mapping, macrophage tracking based on labeling cells in vivo by ultrasmall particles of iron oxide (USPIO), diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI)) to detect histopathological changes in a novel animal model making use of intrinsic, temporally and spatially controlled triggering of oligodendrocyte cell death. This mouse model allows studying the MRI signature associated to neurodegenerative processes of MS in the absence of adaptive inflammatory components that appear to be foremost in the EAE models. Our results revealed pronounced T(2) hyperintensities in brain stem and cerebellar structures, which we attribute to structural alteration of white matter by pronounced vacuolation. Brain areas were found devoid of significant macrophage infiltration in line with the absence of a peripheral inflammatory response. The significant decrease in diffusion anisotropy derived from DTI measures in these structures is mainly caused by a pronounced decrease in diffusivity parallel to the fiber indicative of axonal damage. Triggering of oligodendrocyte ablation did not translate into a significant increase in radial diffusivity. Only minor decreases in MT ratio have been observed, which is attributed to inefficient removal of myelin debris.

[Neuroimaging of multiple sclerosis in children]

There is an increasing appreciation that multiple sclerosis (MS) can affect children. Up to 10% of MS patients experience their first symptoms before the age of 16. The natural history and magnetic resonance imaging of MS in child-hood differ from those observed in adult patients. The differential diagnosis of MS in children should also encompass some paediatric diseases. Recently, the diagnostic criteria for MS in children were published. Due to the high frequency of relapses and the risk of disability at a young age, early diagnosis and treatment of MS in children is very important. This work presents recent data regarding epidemiology, pathogenesis and diagnosis of MS in children, including the role of neuroimaging in the diagnosis of childhood multiple sclerosis.

Analysis of the mitochondrial proteome in multiple sclerosis cortex

Mitochondrial dysfunction has been proposed to play a role in the neuropathology of multiple sclerosis (MS). Previously, we reported significant alterations in the transcription of nuclear-encoded electron transport chain genes in MS and confirmed translational alterations for components of Complexes I and III that resulted in reductions in their activity. To more thoroughly and efficiently elucidate potential alterations in the expression of mitochondrial and related proteins, we have characterized the mitochondrial proteome in postmortem MS and control cortex using Surface-Enhanced Laser Desorption Ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS). Using principal component analysis (PCA) and hierarchical clustering techniques we were able to analyze the differential patterns of SELDI-TOF spectra to reveal clusters of peaks which distinguished MS from control samples. Four proteins in particular were responsible for distinguishing disease from control. Peptide fingerprint mapping unambiguously identified these differentially expressed proteins. Three proteins identified are involved in respiration including cytochrome c oxidase subunit 5b (COX5b), the brain specific isozyme of creatine kinase, and hemoglobin β-chain. The fourth protein identified was myelin basic protein (MBP). We then investigated whether these alterations were consistent in the experimental autoimmune encephalomyelitis (EAE) mouse model of MS. We found that MBP was similarly altered in EAE but the respiratory proteins were not. These data indicate that while the EAE mouse model may mimic aspects of MS neuropathology which result from inflammatory demyelinating events, there is another distinct mechanism involved in mitochondrial dysfunction in gray matter in MS which is not modeled in EAE.

Longitudinal whole-brain N-acetylaspartate concentration in healthy adults

BACKGROUND AND PURPOSE

Although NAA is often used as a marker of neural integrity and health in different neurologic disorders, the temporal behavior of WBNAA is not well characterized. Our goal therefore was to establish its normal variations in a cohort of healthy adults over typical clinical trial periods.

MATERIALS AND METHODS

Baseline amount of brain NAA, Q(NAA), was obtained with nonlocalizing proton MR spectroscopy from 9 subjects (7 women, 2 men; 31.2 ± 5.6 years old). Q(NAA) was converted into absolute millimole amount by using phantom-replacement. The WBNAA concentration was derived by dividing Q(NAA) with the brain parenchyma volume, V(B), segmented from MR imaging. Temporal variations were determined with 4 annual scans of each participant.

RESULTS

The distribution of WBNAA levels was not different among time points with respect to the mean, 12.1 ± 1.5 mmol/L (P > .6), nor was its intrasubject change (coefficient of variation = 8.6%) significant between any 2 scans (P > .5). There was a small (0.2 mL) but significant (P = .05) annual V(B) decline.

CONCLUSIONS

WBNAA is stable over a 3-year period in healthy adults. It qualifies therefore as a biomarker for global neuronal loss and dysfunction in diffuse neurologic disorders that may be well worth considering as a secondary outcome measure candidate for clinical trials.

Anatomical distribution of central nervous system plaques in multiple sclerosis: an Iranian experience

Multiple Sclerosis (MS) begins most commonly in young adults and is characterized by multiple areas of Central Nervous System (CNS) white matter inflammation, demyelination and glial scarring. The most valuable laboratory aid for diagnosing MS is Magnetic Resonance Imaging (MRI). An advanced type of MRI that exploits molecular diffusion can detect acute and active lesions. Early diagnosis and onset of treatment help to hinder disease progression. The aim of this study was to compare the findings of conventional and Diffusion-Weighted (DW) MRI in assessing the cerebral lesions of MS patients. Thirty patients with clinically definite MS (mean age 32.76 +/- 8.79 years) and an age- and sex-matched control group of 30 healthy volunteers (mean age 32.75 +/- 9.23 years) were enrolled in this 12 month descriptive-prospective survey. Both groups were subjected to conventional and DW MRI and were compared in respect of the total number, morphology, location and the mean size of the intra-cerebral MS plaques. The sensitivities and specificities of both imaging methods in detecting these plaques were determined. The conventional method revealed significantly more plaques within the brain (p < 0.05) and showed more ovoid lesions. More lesions were detected by the conventional method in the periventricular area, centrum semiovale and corpus callosum. The minimum plaque size was significantly lower in the conventional method group. The sensitivity of both methods was 100%. The specificities of conventional and DW MRI were 86.6 and 96.6%, respectively, so DW MRI may detect lesions that are not obvious by routine methods.

Visualization of cytoplasmic diffusion within living myelin sheaths of CNS white matter axons using microinjection of the fluorescent dye Lucifer Yellow

The compactness of myelin allows for efficient insulation defining rapid propagation of action potentials, but also raises questions about how cytoplasmic access to its membranes is achieved, which is critical for physiological activity. Understanding the organization of cytoplasmic ('water') spaces of myelin is also important for diffusion MRI studies of CNS white matter. Using longitudinal slices of mature rat spinal cord, we monitored the diffusion of the water-soluble fluorescent dye Lucifer Yellow injected into individual oligodendrocytes or internodal myelin. We show that living myelin sheaths on CNS axons are fenestrated by a network of diffusionally interconnected cytoplasmic 'pockets' (1.9 ± 0.2 pockets per 10μm sheath length, n=58) that included Schmidt-Lanterman clefts (SLCs) and numerous smaller compartments. 3-D reconstructions of these cytoplasmic networks show that the outer cytoplasmic layer of CNS myelin is cylindrically 'encuffing', which differs from EM studies using fixed tissue. SLCs were found in different 'open states' and remained stable within a 1-2hour observation period. Unlike the peripheral nervous system, where similarly small (<500Da) molecules diffuse along the whole myelin segment within a few minutes, in mature CNS this takes more than one hour. The slower cytoplasmic diffusion in CNS myelin possibly contributes to its known vulnerability to injury and limited capacity for repair. Our findings point to an elaborate cytoplasmic access to compact CNS myelin. These results could be of relevance to MRI studies of CNS white matter and to CNS repair/regeneration strategies.