Human brain atlas-based multimodal MRI analysis of volumetry, diffusimetry, relaxometry and lesion distribution in multiple sclerosis patients and healthy adult controls: implications for understanding the pathogenesis of multiple sclerosis and consolidation of quantitative MRI results in MS

Multiparametric quantitative MRI reveals progressive cortical damage over time in clinically stable relapsing-remitting MS

BACKGROUND

In relapsing-remitting multiple sclerosis (RRMS), cortical grey matter pathology relevantly contributes to long-term disability. Still, diffuse cortical inflammation cannot be detected with conventional MRI.

OBJECTIVE

We aimed to assess microstructural damage of cortical grey matter over time and the relation to clinical disability as well as relapse activity in patients with RRMS using multiparametric quantitative (q)MRI techniques.

METHODS

On 40 patients with RRMS and 33 age-matched and sex-matched healthy controls, quantitative T1, T2, T2* and proton density (PD) mapping was performed at baseline and follow-up after 2 years. Cortical qMRI parameter values were extracted with the FreeSurfer software using a surface-based approach. QMRI parameters, cortical thickness and white matter lesion (WML) load, as well as Expanded Disability Status Scale (EDSS) and relapse rate, were compared between time points.

RESULTS

Over 2 years, significant increases of T1 (p≤0.001), PD (p≤0.001) and T2 (p=0.005) values were found in the patient, but not in the control group. At decreased relapse rate over time (p=0.001), cortical thickness, WML volume and EDSS remained unchanged.

CONCLUSION

Despite clinical stability, cortical T1, T2 and PD values increased over time, indicating progressive demyelination and increasing water content. These parameters represent promising surrogate parameters of diffuse cortical inflammation in RRMS.

Three Dimensional Brain Parameters of Multiple Sclerosis (MS) Patients

BACKGROUND & OBJECTIVES

MS is not only a demyelinating disease of central nervous system, but it also affects cortical and deep gray matter (GM). Furthermore, it causes axonal damage in the brain and spinal cord through inflammation and axonal degeneration. It is mostly seen between the ages of 20 and 40 and prevalence of the disease is higher among females than males. In the present study, we measured different parameters in the brains of patients with multiple sclerosis (MS) and healthy controls in both genders to determine the amount of brain atrophy quantitatively in MS patients.

METHODS

We used T2-weighted MRI scans of 40 MS patients (25 females + 15 males) with clinically definite relapsing-remitting multiple sclerosis that was determined according to Poser criteria in multiple parts of the brain, and we compared these data with those of sex-matched healthy controls in the same numbers.

RESULTS

Wideness of the lateral and third ventricles and the volumes of cerebral sulci in MS patients were significantly increased compared to both male and female controls. Brain width, corpus callosum area and the total brain/cerebellum + brain stem volumes of MS patients were decreased considerably.

INTERPRETATION & CONCLUSIONS

The present measurements indicated that MS caused parenchymal destruction in the cortex, axonal degeneration and myelin loss in the white matter of the brain. Consequently, the current observations correlate well with worsening disability in MS patients.

Personalized maps of T1 relaxometry abnormalities provide correlates of disability in multiple sclerosis patients

OBJECTIVES AND AIMS

Quantitative MRI (qMRI) has greatly improved the sensitivity and specificity of microstructural brain pathology in multiple sclerosis (MS) when compared to conventional MRI (cMRI). More than cMRI, qMRI also provides means to assess pathology within the normal-appearing and lesion tissue. In this work, we further developed a method providing personalized quantitative T1 (qT1) abnormality maps in individual MS patients by modeling the age dependence of qT1 alterations. In addition, we assessed the relationship between qT1 abnormality maps and patients' disability, in order to evaluate the potential value of this measurement in clinical practice.

METHODS

We included 119 MS patients (64 relapsing-remitting MS (RRMS), 34 secondary progressive MS (SPMS), 21 primary progressive MS (PPMS)), and 98 Healthy Controls (HC). All individuals underwent 3T MRI examinations, including Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) for qT1 maps and High-Resolution 3D Fluid Attenuated Inversion Recovery (FLAIR) imaging. To calculate personalized qT1 abnormality maps, we compared qT1 in each brain voxel in MS patients to the average qT1 obtained in the same tissue (grey/white matter) and region of interest (ROI) in healthy controls, hereby providing individual voxel-based Z-score maps. The age dependence of qT1 in HC was modeled using linear polynomial regression. We computed the average qT1 Z-scores in white matter lesions (WMLs), normal-appearing white matter (NAWM), cortical grey matter lesions (GMcLs) and normal-appearing cortical grey matter (NAcGM). Lastly, a multiple linear regression (MLR) model with the backward selection including age, sex, disease duration, phenotype, lesion number, lesion volume and average Z-score (NAWM/NAcGM/WMLs/GMcLs) was used to assess the relationship between qT1 measures and clinical disability (evaluated with EDSS).

RESULTS

The average qT1 Z-score was higher in WMLs than in NAWM. (WMLs: 1.366 ± 0.409, NAWM: -0.133 ± 0.288, [mean ± SD], p < 0.001). The average Z-score in NAWM in RRMS patients was significantly lower than in PPMS patients (p = 0.010). The MLR model showed a strong association between average qT1 Z-scores in white matter lesions (WMLs) and EDSS (R² = 0.549, β = 0.178, 97.5 % CI = 0.030 to 0.326, p = 0.019). Specifically, we measured a 26.9 % increase in EDSS per unit of qT1 Z-score in WMLs in RRMS patients (R² = 0.099, β = 0.269, 97.5 % CI = 0.078 to 0.461, p = 0.007).

CONCLUSIONS

We showed that personalized qT1 abnormality maps in MS patients provide measures related to clinical disability, supporting the use of those maps in clinical practice.

BMSCs differentiated into neurons, astrocytes and oligodendrocytes alleviated the inflammation and demyelination of EAE mice models

Multiple sclerosis (MS) is a complex, progressive neuroinflammatory disease associated with autoimmunity. Currently, effective therapeutic strategy was poorly found in MS. Experimental autoimmune encephalomyelitis (EAE) is widely used to study the pathogenesis of MS. Cumulative research have shown that bone marrow mesenchymal stem Cells (BMSCs) transplantation could treat EAE animal models, but the mechanism was divergent. Here, we systematically evaluated whether BMSCs can differentiate into neurons, astrocytes and oligodendrocytes to alleviate the symptoms of EAE mice. We used Immunofluorescence staining to detect MAP-2, GFAP, and MBP to evaluate whether BMSCs can differentiate into neurons, astrocytes and oligodendrocytes. The effect of BMSCs transplantation on inflammatory infiltration and demyelination in EAE mice were detected by Hematoxylin-Eosin (H&E) and Luxol Fast Blue (LFB) staining, respectively. Inflammatory factors expression was detected by ELISA and RT-qPCR, respectively. Our results showed that BMSCs could be induced to differentiate into neuron cells, astrocytes and oligodendrocyte in vivo and in vitro, and BMSCs transplanted in EAE mice were easier to differentiate than normal mice. Moreover, transplanted BMSCs reduced neurological function scores and disease incidence of EAE mice. BMSCs transplantation alleviated the inflammation and demyelination of EAE mice. Finally, we found that BMSCs transplantation down-regulated the levels of pro-inflammatory factors TNF-α, IL-1β and IFN-γ, and up-regulated the levels of anti-inflammatory factors IL-10 and TGF-β. In conclusion, this study found that BMSCs could alleviate the inflammatory response and demyelination in EAE mice, which may be achieved by the differentiation of BMSCs into neurons, astrocytes and oligodendrocytes in EAE mice.

Therapeutic effects of Crocin in autoimmune diseases: A review

The immune system when acts against selfmolecules results in an imbalance in immunologic tolerance leading to the development of several autoimmune diseases (ADs) such as rheumatoid arthritis, asthma, ulcerative colitis, type 1 diabetes, and multiple sclerosis. Improved recognition of the mechanisms of ADs has led to the advancement of the management of these diseases. The principal mediators of ADs are inflammatory molecules. The herbal medicines due to their antioxidant and antiinflammatory properties have an important role in the management of ADs. Crocin is the principal chemical component extracted from saffron, which is a medicinal plant. This review focuses on the therapeutic effects of Crocin in various ADs.

Data-Driven Machine-Learning Quantifies Differences in the Voiding Initiation Network in Neurogenic Voiding Dysfunction in Women With Multiple Sclerosis

PURPOSE

To quantify the relative importance of brain regions responsible for reduced functional connectivity (FC) in their Voiding Initiation Network in female multiple sclerosis (MS) patients with neurogenic lower urinary tract dysfunction (NLUTD) and voiding dysfunction (VD). A data-driven machine-learning approach is utilized for quantification.

METHODS

Twenty-seven ambulatory female patients with MS and NLUTD (group 1: voiders, n=15 and group 2: VD, n=12) participated in a functional magnetic resonance imaging (fMRI) voiding study. Brain activity was recorded by fMRI with simultaneous urodynamic testing. The Voiding Initiation Network was identified from averaged fMRI activation maps. Four machine-learning algorithms were employed to optimize the area under curve (AUC) of the receiver-operating characteristic curve. The optimal model was used to identify the relative importance of relevant brain regions.

RESULTS

The Voiding Initiation Network exhibited stronger FC for voiders in frontal regions and stronger disassociation in cerebellar regions. Highest AUC values were obtained with 'random forests' (0.86) and 'partial least squares' algorithms (0.89). While brain regions with highest relative importance (>75%) included superior, middle, inferior frontal and cingulate regions, relative importance was larger than 60% for 186 of the 227 brain regions of the Voiding Initiation Network, indicating a global effect.

CONCLUSION

Voiders and VD patients showed distinctly different FC in their Voiding Initiation Network. Machine-learning is able to identify brain centers contributing to these observed differences. Knowledge of these centers and their connectivity may allow phenotyping patients to centrally focused treatments such as cortical modulation.

Imaging in mice and men: Pathophysiological insights into multiple sclerosis from conventional and advanced MRI techniques

Magnetic resonance imaging (MRI) is the most important tool for diagnosing multiple sclerosis (MS). However, MRI is still unable to precisely quantify the specific pathophysiological processes that underlie imaging findings in MS. Because autopsy and biopsy samples of MS patients are rare and biased towards a chronic burnt-out end or fulminant acute early stage, the only available methods to identify human disease pathology are to apply MRI techniques in combination with subsequent histopathological examination to small animal models of MS and to transfer these insights to MS patients. This review summarizes the existing combined imaging and histopathological studies performed in MS mouse models and humans with MS (in vivo and ex vivo), to promote a better understanding of the pathophysiology that underlies conventional MRI, diffusion tensor and magnetization transfer imaging findings in MS patients. Moreover, it provides a critical view on imaging capabilities and results in MS patients and mouse models and for future studies recommends how to combine those particular MR sequences and parameters whose underlying pathophysiological basis could be partly clarified. Further combined longitudinal in vivo imaging and histopathological studies on rationally selected, appropriate mouse models are required.

A Multi-Atlas Label Fusion Tool for Neonatal Brain MRI Parcellation and Quantification

Structure-by-structure analysis, in which the brain magnetic resonance imaging (MRI) is parcellated based on its anatomical units, is widely used to investigate chronological changes in morphology or signal intensity during normal development, as well as to identify the alterations seen in various diseases or conditions. The multi-atlas label fusion (MALF) method is considered a highly accurate parcellation approach, and anticipated for clinical application to quantitatively evaluate early developmental processes. However, the current MALF methods, which are designed for neonatal brain segmentations, are not widely available. In this study, we developed a T1-weighted, neonatal, multi-atlas repository and integrated it into the MALF-based brain segmentation tools in the cloud-based platform, MRICloud. The cloud platform ensures users instant access to the advanced MALF tool for neonatal brains, with no software or installation requirements for the client. The Web platform by braingps.mricloud.org will eliminate the dependence on a particular operating system (eg, Windows, Macintosh, or Linux) and the requirement for high computational performance of the user's computers. The MALF-based, fully automated, image parcellation could achieve excellent agreement with manual parcellation, and the whole and regional brain volumes quantified through this method demonstrated developmental trajectories comparable to those from a previous publication. This solution will make the latest MALF tools readily available to users, with minimum barriers, and will expedite and accelerate advancements in developmental neuroscience research, neonatology, and pediatric neuroradiology.

A Review of Herbal Therapy in Multiple Sclerosis

Multiple sclerosis is a complex autoimmune disorder which characterized by demyelination and axonal loss in the central nervous system (CNS). Several evidences indicate that some new drugs and stem cell therapy have opened a new horizon for multiple sclerosis treatment, but current therapies are partially effective or not safe in the long term. Recently, herbal therapies represent a promising therapeutic approach for multiple sclerosis disease. Here, we consider the potential benefits of some herbal compounds on different aspects of multiple sclerosis disease. The medicinal plants and their derivatives; Ginkgo biloba, Zingiber officinale, Curcuma longa, Hypericum perforatum, Valeriana officinalis, Vaccinium macrocarpon, Nigella sativa,Piper methysticum, Crocus sativus, Panax ginseng, Boswellia papyrifera, Vitis vinifera, Gastrodia elata, Camellia sinensis, Oenothera biennis, MS14 and Cannabis sativa have been informed to have several therapeutic effects in MS patients.

Personalized pathology maps to quantify diffuse and focal brain damage

Background and objectives

Quantitative MRI (qMRI) permits the quantification of brain changes compatible with inflammation, degeneration and repair in multiple sclerosis (MS) patients. In this study, we propose a new method to provide personalized maps of tissue alterations and longitudinal brain changes based on different qMRI metrics, which provide complementary information about brain pathology.

Methods

We performed baseline and two-years follow-up on (i) 13 relapsing-remitting MS patients and (ii) four healthy controls. A group consisting of up to 65 healthy controls was used to compute the reference distribution of qMRI metrics in healthy tissue. All subjects underwent 3T MRI examinations including T1, T2, T2* relaxation and Magnetization Transfer Ratio (MTR) imaging. We used a recent partial volume estimation algorithm to estimate the concentration of different brain tissue types on T1 maps; then, we computed a deviation map (z-score map) for each contrast at both time-points. Finally, we subtracted those deviation maps only for voxels showing a significant difference with healthy tissue in one of the time points, to obtain a difference map for each subject.

Results and conclusion

Control subjects did not show any significant z-score deviations or longitudinal z-score changes. On the other hand, MS patients showed brain regions with cross-sectional and longitudinal concomitant increase in T1, T2, T2* z-scores and decrease of MTR z-scores, suggesting brain tissue degeneration/loss. In the lesion periphery, we observed areas with cross-sectional and longitudinal decreased T1/T2 and slight decrease in T2* most likely related to iron accumulation. Moreover, we measured longitudinal decrease in T1, T2 - and to a lesser extent in T2* - as well as a concomitant increase in MTR, suggesting remyelination/repair.

In summary, we have developed a method that provides whole-brain personalized maps of cross-sectional and longitudinal changes in MS patients, which are computed in patient space. These maps may open new perspectives to complement and support radiological evaluation of brain damage for a given patient.

SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement

Conventional magnetic resonance images are usually evaluated using the image signal contrast between tissues and not based on their absolute signal intensities. Quantification of tissue parameters, such as relaxation rates and proton density, would provide an absolute scale; however, these methods have mainly been performed in a research setting. The development of rapid quantification, with scan times in the order of 6 minutes for full head coverage, has provided the prerequisites for clinical use. The aim of this review article was to introduce a specific quantification method and synthesis of contrast-weighted images based on the acquired absolute values, and to present automatic segmentation of brain tissues and measurement of myelin based on the quantitative values, along with application of these techniques to various brain diseases. The entire technique is referred to as “SyMRI” in this review. SyMRI has shown promising results in previous studies when used for multiple sclerosis, brain metastases, Sturge-Weber syndrome, idiopathic normal pressure hydrocephalus, meningitis, and postmortem imaging.

The Role of T1-Weighted Derived Measures of Neurodegeneration for Assessing Disability Progression in Multiple Sclerosis

Introduction

Multiple sclerosis (MS) is characterised by the accumulation of permanent neurological disability secondary to irreversible tissue loss (neurodegeneration) in the brain and spinal cord. MRI measures derived from T1-weighted image analysis (i.e., black holes and atrophy) are correlated with pathological measures of irreversible tissue loss. Quantifying the degree of neurodegeneration in vivo using MRI may offer a surrogate marker with which to predict disability progression and the effect of treatment. This review evaluates the literature examining the association between MRI measures of neurodegeneration derived from T1-weighted images and disability in MS patients.

Methods

A systematic PubMed search was conducted in January 2017 to identify MRI studies in MS patients investigating the relationship between “black holes” and/or atrophy in the brain and spinal cord, and disability. Results were limited to human studies published in English in the previous 10 years.

Results

A large number of studies have evaluated the association between the previous MRI measures and disability. These vary considerably in terms of study design, duration of follow-up, size, and phenotype of the patient population. Most, although not all, have shown that there is a significant correlation between disability and black holes in the brain, as well as atrophy of the whole brain and grey matter. The results for brain white matter atrophy are less consistently positive, whereas studies evaluating spinal cord atrophy consistently showed a significant correlation with disability. Newer ways of measuring atrophy, thanks to the development of segmentation and voxel-wise methods, have allowed us to assess the involvement of strategic regions of the CNS (e.g., thalamus) and to map the regional distribution of damage. This has resulted in better correlations between MRI measures and disability and in the identification of the critical role played by some CNS structures for MS clinical manifestations.

Conclusion

The evaluation of MRI measures of atrophy as predictive markers of disability in MS is a highly active area of research. At present, measurement of atrophy remains within the realm of clinical studies, but its utility in clinical practice has been recognized and barriers to its implementation are starting to be addressed.

Longitudinal MR spectroscopy of neurodegeneration in multiple sclerosis with diffusion of the intra-axonal constituent N-acetylaspartate

Multiple sclerosis (MS) is a pathologically complex CNS disease: inflammation, demyelination, and neuroaxonal degeneration occur concurrently and may depend on one another. Current therapies are aimed at the immune-mediated, inflammatory destruction of myelin, whereas axonal degeneration is ongoing and not specifically targeted. Diffusion-weighted magnetic resonance spectroscopy can measure the diffusivity of metabolites in vivo, such as the axonal/neuronal constituent N-acetylaspartate, allowing compartment-specific assessment of disease-related changes. Previously, we found significantly lower N-acetylaspartate diffusivity in people with MS compared to healthy controls (Wood et al., 2012) suggesting that this technique can measure axonal degeneration and could be useful in developing neuroprotective agents. In this longitudinal study, we found that N-acetylaspartate diffusivity decreased by 8.3% (p < 0.05) over 6 months in participants who were experiencing clinical or MRI evidence of inflammatory activity (n = 13), whereas there was no significant change in N-acetylaspartate diffusivity in the context of clinical and radiological stability (n = 6). As N-acetylaspartate diffusivity measurements are thought to more specifically reflect the intra-axonal space, these data suggest that N-acetylaspartate diffusivity can report on axonal health on the background of multiple pathological processes in MS, both cross-sectionally and longitudinally.

Altered Microstructural Caudate Integrity in Posttraumatic Stress Disorder but Not Traumatic Brain Injury

OBJECTIVE

Given the high prevalence and comorbidity of combat-related PTSD and TBI in Veterans, it is often difficult to disentangle the contributions of each disorder. Examining these pathologies separately may help to understand the neurobiological basis of memory impairment in PTSD and TBI independently of each other. Thus, we investigated whether a) PTSD and TBI are characterized by subcortical structural abnormalities by examining diffusion tensor imaging (DTI) metrics and volume and b) if these abnormalities were specific to PTSD versus TBI.

METHOD

We investigated whether individuals with PTSD or TBI display subcortical structural abnormalities in memory regions by examining DTI metrics and volume of the hippocampus and caudate in three groups of Veterans: Veterans with PTSD, Veterans with TBI, and Veterans with neither PTSD nor TBI (Veteran controls).

RESULTS

While our results demonstrated no macrostructural differences among the groups in these regions, there were significant alterations in microstructural DTI indices in the caudate for the PTSD group but not the TBI group compared to Veteran controls.

CONCLUSIONS

The result of increased mean, radial, and axial diffusivity, and decreased fractional anisotropy in the caudate in absence of significant volume atrophy in the PTSD group suggests the presence of subtle abnormalities evident only at a microstructural level. The caudate is thought to play a role in the physiopathology of PTSD, and the habit-like behavioral features of the disorder could be due to striatal-dependent habit learning mechanisms. Thus, DTI appears to be a vital tool to investigate subcortical pathology, greatly enhancing the ability to detect subtle brain changes in complex disorders.

Patient-specific 3D FLAIR for enhanced visualization of brain white matter lesions in multiple sclerosis

PURPOSE

To improve the conspicuity of white matter lesions (WMLs) in multiple sclerosis (MS) using patient-specific optimization of single-slab 3D fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Sixteen MS patients were enrolled in a prospective 3.0T MRI study. FLAIR inversion time and echo time were automatically optimized for each patient during the same scan session based on measurements of the relative proton density and relaxation times of the brain tissues. The optimization criterion was to maximize the contrast between gray matter (GM) and white matter (WM), while suppressing cerebrospinal fluid. This criterion also helps increase the contrast between WMLs and WM. The performance of the patient-specific 3D FLAIR protocol relative to the fixed-parameter protocol was assessed both qualitatively and quantitatively.

RESULTS

Patient-specific optimization achieved a statistically significant 41% increase in the GM-WM contrast ratio (P < 0.05) and 32% increase in the WML-WM contrast ratio (P < 0.01) compared with fixed-parameter FLAIR. The increase in WML-WM contrast ratio correlated strongly with echo time (P < 10^-11 ). Two experienced neuroradiologists indicated substantially higher lesion conspicuity on the patient-specific FLAIR images over conventional FLAIR in 3-4 cases (intrarater correlation coefficient ICC = 0.72). In no case was the image quality of patient-specific FLAIR considered inferior to conventional FLAIR by any of the raters (ICC = 0.32).

CONCLUSION

Changes in proton density and relaxation times render fixed-parameter FLAIR suboptimal in terms of lesion contrast. Patient-specific optimization of 3D FLAIR increases lesion conspicuity without scan time penalty, and has potential to enhance the detection of subtle and small lesions in MS.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:557-564.

Comparison of two quantitative proton density mapping methods in multiple sclerosis

OBJECTIVE

Proton density (PD) mapping requires correction for the receive profile (RP), which is frequently performed via bias-field correction. An alternative RP-mapping method utilizes a comparison of uncorrected PD-maps and a value ρ(T1) directly derived from T1-maps via the Fatouros equation. This may be problematic in multiple sclerosis (MS), if respective parameters are only valid for healthy brain tissue. We aimed to investigate whether the alternative method yields correct PD values in MS patients.

MATERIALS/METHODS

PD mapping was performed on 27 patients with relapsing-remitting MS and 27 healthy controls, utilizing both methods, yielding reference PD values (PD_ref, bias-field method) and PD_alt (alternative method).

RESULTS

PD_alt-values closely matched PD_ref, both for patients and controls. In contrast, ρ(T1) differed by up to 3 % from PD_ref, and the voxel-wise correlation between PD_ref and ρ(T1) was reduced in a patient subgroup with a higher degree of disability. Still, discrepancies between ρ(T1) and PD_ref were almost identical across different tissue types, thus translating into a scaling factor, which cancelled out during normalization to 100 % in CSF, yielding a good agreement between PD_alt and PD_ref.

CONCLUSION

RP correction utilizing the auxiliary parameter ρ(T1) derived via the Fatouros equation provides accurate PD results in MS patients, in spite of discrepancies between ρ(T1) and actual PD values.

Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis

Spontaneous fluctuations of neuronal activity in large-scale distributed networks are a hallmark of the resting brain. In relapsing-remitting multiple sclerosis (RRMS) several fMRI studies have suggested altered resting-state connectivity patterns. Topographical EEG analysis reveals much faster temporal fluctuations in the tens of milliseconds time range (termed “microstates”), which showed altered properties in a number of neuropsychiatric conditions.

We investigated whether these microstates were altered in patients with RRMS, and if the microstates' temporal properties reflected a link to the patients' clinical features.

We acquired 256-channel EEG in 53 patients (mean age 37.6 years, 45 females, mean disease duration 9.99 years, Expanded Disability Status Scale ≤ 4, mean 2.2) and 49 healthy controls (mean age 36.4 years, 33 females). We analyzed segments of a total of 5 min of EEG during resting wakefulness and determined for both groups the four predominant microstates using established clustering methods.

We found significant differences in the temporal dynamics of two of the four microstates between healthy controls and patients with RRMS in terms of increased appearance and prolonged duration. Using stepwise multiple linear regression models with 8-fold cross-validation, we found evidence that these electrophysiological measures predicted a patient's total disease duration, annual relapse rate, disability score, as well as depression score, and cognitive fatigue measure.

In RRMS patients, microstate analysis captured altered fluctuations of EEG topographies in the sub-second range. This measure of high temporal resolution provided potentially powerful markers of disease activity and neuropsychiatric co-morbidities in RRMS.

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EEG microstates analyses provide high resolution of temporal dynamics of brain networks.

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Temporal parameters of EEG microstates are altered in Multiple Sclerosis

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Altered microstate parameters predict several clinical characteristics in patients

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We propose an EEG microstate based marker to characterize disease evolution in patients

Assessment of cortical damage in early multiple sclerosis with quantitative T2 relaxometry

T2 relaxation time is a quantitative MRI in vivo surrogate of cerebral tissue damage in multiple sclerosis (MS) patients. Cortical T2 prolongation is a known feature in later disease stages, but has not been demonstrated in the cortical normal appearing gray matter (NAGM) in early MS. This study centers on the quantitative evaluation of the tissue parameter T2 in cortical NAGM in a collective of early MS and clinically isolated syndrome (CIS) patients, hypothesizing that T2 prolongation is already present at early disease stages and variable over space, in line with global and focal inflammatory processes in MS. Additionally, magnetization transfer ratio (MTR) mapping was performed for further characterization of the expected cortical T2 alteration. Quantitative T2 and MTR maps were acquired from 12 patients with CIS and early MS, and 12 matched healthy controls. The lesion-free part of the cortical volume was identified, and the mean T2 and MTR values and their standard deviations within the cortical volume were determined. For evaluation of spatial specificity, cortical lobar subregions were tested separately for differences of mean T2 and T2 standard deviation. We detected significantly prolonged T2 in cortical NAGM in patients. T2 prolongation was found across the whole cerebral cortex and in all individual lobar subregions. Significantly higher standard deviations across the respective region of interest were found for the whole cerebral cortex and all subregions, suggesting the occurrence of spatially inhomogeneous cortical damage in all regions studied. A trend was observed for MTR reduction and increased MTR variability across the whole cortex in the MS group, suggesting demyelination. In conclusion, our results suggest that cortical damage in early MS is evidenced by spatially inhomogeneous T2 prolongation which goes beyond demyelination. Iron deposition, which is known to decrease T2, seems less prominent.

Predictive classification of pediatric bipolar disorder using atlas-based diffusion weighted imaging and support vector machines

Previous studies have reported abnormalities of white-matter diffusivity in pediatric bipolar disorder. However, it has not been established whether these abnormalities are able to distinguish individual subjects with pediatric bipolar disorder from healthy controls with a high specificity and sensitivity. Diffusion-weighted imaging scans were acquired from 16 youths diagnosed with DSM-IV bipolar disorder and 16 demographically matched healthy controls. Regional white matter tissue microstructural measurements such as fractional anisotropy, axial diffusivity and radial diffusivity were computed using an atlas-based approach. These measurements were used to 'train' a support vector machine (SVM) algorithm to predict new or 'unseen' subjects' diagnostic labels. The SVM algorithm predicted individual subjects with specificity=87.5%, sensitivity=68.75%, accuracy=78.12%, positive predictive value=84.62%, negative predictive value=73.68%, area under receiver operating characteristic curve (AUROC)=0.7812 and chi-square p-value=0.0012. A pattern of reduced regional white matter fractional anisotropy was observed in pediatric bipolar disorder patients. These results suggest that atlas-based diffusion weighted imaging measurements can distinguish individual pediatric bipolar disorder patients from healthy controls. Notably, from a clinical perspective these findings will contribute to the pathophysiological understanding of pediatric bipolar disorder.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Quantitative MR Imaging of Brain Tissue and Brain Pathologies

Measurement of basic quantitative magnetic resonance (MR) parameters (e.g., relaxation times T1, T2*, T2 or respective rates R (1/T)) corrected for radiofrequency (RF) coil bias yields different conventional and new tissue contrasts as well as volumes for tissue segmentation. This approach also provides quantitative measures of microstructural and functional tissue changes. We herein demonstrate some prospects of quantitative MR imaging in neurological diagnostics and science.

Disconnection of the hippocampus and amygdala associated with lesion load in relapsing-remitting multiple sclerosis: a structural and functional connectivity study

BACKGROUND AND PURPOSE

Little is known about the functional and structural connectivity (FC and SC) of the hippocampus and amygdala, which are two important structures involved in cognitive processes, or their involvement in relapsing-remitting multiple sclerosis (RRMS). In this study, we aimed to examine the connectivity of white-matter (WM) tracts and the synchrony of intrinsic neuronal activity in outer regions connected with the hippocampus or amygdala in RRMS patients.

PATIENTS AND METHODS

Twenty-three RRMS patients and 23 healthy subjects participated in this study. Diffusion tensor probabilistic tractography was used to examine the SC, the FC correlation coefficient (FC-CC) and combined FC strength (FCS), which was derived from the resting-state functional magnetic resonance imaging used to examine the FC, of the connection between the hippocampus or the amygdala and other regions, and the correlations of these connections with clinical markers.

RESULTS

Compared with healthy subjects, the RRMS patients showed significantly decreased SC and increased FCS of the bilateral hippocampus, and left amygdala. Their slightly increased FC-CC was positively correlated with WM tract damage in the right hippocampus (ρ=0.57, P=0.005); an increased FCS was also positively correlated with WM tract damage in the right amygdala. A relationship was observed between the WM lesion load and SC alterations, including the lg(N tracts) of the right hippocampus (ρ=-0.68, P<0.05), lg(N tracts) (ρ=-0.69, P<0.05), and fractional anisotropy (ρ=-0.68, P<0.05) and radial diffusivity of the left hippocampus (ρ=0.45, P<0.05). A relationship between WM lesion load and FCS of the left amygdale was also observed.

CONCLUSION

The concurrent increased functional connections and demyelination-related structural disconnectivity between the hippocampus or amygdala and other regions in RRMS suggest that the functional-structural relationships require further investigation.

Transplantation of human adipose-derived stem cells enhances remyelination in lysolecithin-induced focal demyelination of rat spinal cord

Adipose-derived stem cells (ADSCs) are a desirable stem cell source in neurodegenerative diseases treatment due to their ability to differentiate into different cell lineages. In this study, we transplanted human ADSCs (hADSCs) into a lysophosphatidylcholine (lysolecithin) model of multiple sclerosis (MS) and determined the efficiency of these cells in remyelination process. Forty adult rats were randomly divided into control, lysolecithin, vehicle, and transplantation groups, and focal demyelination was induced by lysolecithin injection into spinal cord. To assess motor performance, all rats were examined weekly with a standard EAE scoring scale. Four weeks after cell transplantation, to assess the extent of demyelination and remyelination, Luxol Fast Blue staining was used. In addition, immunohistochemistry technique was used for assessment of the presence of oligodendrocyte phenotype cells in damaged spinal cord. Our results indicated that hADSCs had ability to differentiate into oligodendrocyte phenotype cells and improved remyelination process. Moreover, the evaluation of rat motor functions showed that animals which were treated with hADSC compared to other groups had significant improvement (P < 0.001). Our finding showed that hADSCs transplantation for cell-based therapies may play a proper cell source in the treatment of neurodegenerative diseases such as MS.

Multi-parametric representation of voxel-based quantitative magnetic resonance imaging

The aim of the study was to explore the possibilities of multi-parametric representations of voxel-wise quantitative MRI data to objectively discriminate pathological cerebral tissue in patients with brain disorders. For this purpose, we recruited 19 patients with Multiple Sclerosis (MS) as benchmark samples and 19 age and gender matched healthy subjects as a reference group. The subjects were examined using quantitative Magnetic Resonance Imaging (MRI) measuring the tissue structure parameters: relaxation rates, R(1) and R(2), and proton density. The resulting parameter images were normalized to a standard template. Tissue structure in MS patients was assessed by voxel-wise comparisons with the reference group and with correlation to a clinical measure, the Expanded Disability Status Scale (EDSS). The results were visualized by conventional geometric representations and also by multi-parametric representations. Data showed that MS patients had lower R(1) and R(2), and higher proton density in periventricular white matter and in wide-spread areas encompassing central and sub-cortical white matter structures. MS-related tissue abnormality was highlighted in posterior white matter whereas EDSS correlation appeared especially in the frontal cortex. The multi-parameter representation highlighted disease-specific features. In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes. Results from voxel-based statistical analysis, as exemplified in the present work, may guide radiologists where in the image to inspect for signs of disease. Future clinical studies must validate the usability of the method in clinical practice.

Visualization and unsupervised predictive clustering of high-dimensional multimodal neuroimaging data

BACKGROUND

Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data.

NEW METHOD

We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm.

COMPARISON WITH EXISTING METHODS

t-SNE was evaluated against classical principal component analysis.

CONCLUSION

Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders.

Microstructural changes in the striatum and their impact on motor and neuropsychological performance in patients with multiple sclerosis

Grey matter (GM) damage is a clinically relevant feature of multiple sclerosis (MS) that has been previously assessed with diffusion tensor imaging (DTI). Fractional anisotropy (FA) of the basal ganglia and thalamus might be increased in MS patients, and correlates with disability scores. Despite the established role of the striatum and thalamus in motor control, mood and cognition, the impact of DTI changes within these structures on motor and neuropsychological performance has not yet been specifically addressed in MS. We investigated DTI metrics of deep GM nuclei and their potential association with mobility and neuropsychological function. DTI metrics from 3T MRI were assessed in the caudate, putamen, and thalamus of 30 MS patients and 10 controls. Sixteen of the patients underwent neuropsychological testing. FA of the caudate and putamen was higher in MS patients compared to controls. Caudate FA correlated with Expanded Disability Status Scale score, Ambulation Index, and severity of depressive symptomatology. Putamen and thalamus FA correlated with deficits in memory tests. In contrast, cerebral white matter (WM) lesion burden showed no significant correlation with any of the disability, mobility and psychometric parameters. Our findings support evidence of FA changes in the basal ganglia in MS patients, as well as deep GM involvement in disabling features of MS, including mobility and cognitive impairment. Deep GM FA appears to be a more sensitive correlate of disability than WM lesion burden.

A High-resolution Atlas and Statistical Model of the Vocal Tract from Structural MRI

Magnetic resonance imaging (MRI) is an essential tool in the study of muscle anatomy and functional activity in the tongue. Objective assessment of similarities and differences in tongue structure and function has been performed using unnormalized data, but this is biased by the differences in size, shape, and orientation of the structures. To remedy this, we propose a methodology to build a 3D vocal tract atlas based on structural MRI volumes from twenty normal subjects. We first constructed high-resolution volumes from three orthogonal stacks. We then removed extraneous data so that all 3D volumes contained the same anatomy. We used an unbiased diffeomorphic groupwise registration using a cross-correlation similarity metric. Principal component analysis was applied to the deformation fields to create a statistical model from the atlas. Various evaluations and applications were carried out to show the behaviour and utility of the atlas.

Effects of gadolinium contrast agent administration on automatic brain tissue classification of patients with multiple sclerosis

BACKGROUND AND PURPOSE

The administration of gadolinium contrast agent is a common part of MR imaging examinations in patients with MS. The presence of gadolinium may affect the outcome of automated tissue classification. The purpose of this study was to investigate the effects of the presence of gadolinium on the automatic segmentation in patients with MS by using the synthetic tissue-mapping method.

MATERIALS AND METHODS

A cohort of 20 patients with clinically definite multiple sclerosis were recruited, and the T1 and T2 relaxation times and proton density were simultaneously quantified before and after the administration of gadolinium. Synthetic tissue-mapping was used to measure white matter, gray matter, CSF, brain parenchymal, and intracranial volumes. For comparison, 20 matched controls were measured twice, without gadolinium.

RESULTS

No differences were observed for the control group between the 2 measurements. For the MS group, significant changes were observed pre- and post-gadolinium in intracranial volume (-13 mL, P < .005) and cerebrospinal fluid volume (-16 mL, P < .005) and the remaining, unclassified non-WM/GM/CSF tissue volume within the intracranial volume (+8 mL, P < .05). The changes in the patient group were much smaller than the differences, compared with the controls, which were -129 mL for WM volume, -22 mL for GM volume, +91 mL for CSF volume, 24 mL for the remaining, unclassified non-WM/GM/CSF tissue volume within the intracranial volume, and -126 mL for brain parenchymal volume. No significant differences were observed for linear regression values against age and Expanded Disability Status Scale.

CONCLUSIONS

The administration of gadolinium contrast agent had a significant effect on automatic brain-tissue classification in patients with MS by using synthetic tissue-mapping. The observed differences, however, were much smaller than the group differences between MS and controls.

Reprint of "Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging"

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.

Subcortical deep gray matter pathology in patients with multiple sclerosis is associated with white matter lesion burden and atrophy but not with cortical atrophy: a diffusion tensor MRI study

BACKGROUND AND PURPOSE

The association between subcortical deep gray matter, white matter, and cortical pathology is not well understood in MS. The aim of this study was to use DTI to investigate the subcortical deep gray matter alterations and their relationship with lesion burden, white matter, and cortical atrophy in patients with MS and healthy control patients.

MATERIALS AND METHODS

A total of 210 patients with relapsing-remitting MS, 75 patients with progressive MS, and 110 healthy control patients were included in the study. DTI metrics in whole brain, normal-appearing white matter, normal-appearing gray matter, and subcortical deep gray matter structures were compared. The association between DTI metrics of the subcortical deep gray matter structures with lesion burden, normalized white matter volume, and normalized cortical volume was investigated.

RESULTS

DTI measures were significantly different in whole brain, normal-appearing white matter, and normal-appearing gray matter among the groups (P < .01). Significant differences in DTI diffusivity of total subcortical deep gray matter, caudate, thalamus, and hippocampus (P < .001) were found. DTI diffusivity of total subcortical deep gray matter was significantly associated with normalized white matter volume (P < .001) and normalized cortical volume (P = .033) in healthy control patients. In both relapsing and progressive MS groups, the DTI subcortical deep gray matter measures were associated with the lesion burden and with normalized white matter volume (P < .001), but not with normalized cortical volume.

CONCLUSIONS

These findings suggest that subcortical deep gray matter abnormalities are associated with white matter lesion burden and atrophy, whereas cortical atrophy is not associated with microstructural alterations of subcortical deep gray matter structures in patients with MS.

Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.

Brain characterization using normalized quantitative magnetic resonance imaging

Objectives

To present a method for generating reference maps of typical brain characteristics of groups of subjects using a novel combination of rapid quantitative Magnetic Resonance Imaging (qMRI) and brain normalization. The reference maps can be used to detect significant tissue differences in patients, both locally and globally.

Materials and Methods

A rapid qMRI method was used to obtain the longitudinal relaxation rate (R₁), the transverse relaxation rate (R₂) and the proton density (PD). These three tissue properties were measured in the brains of 32 healthy subjects and in one patient diagnosed with Multiple Sclerosis (MS). The maps were normalized to a standard brain template using a linear affine registration. The differences of the mean value ofR₁, R₂ and PD of 31 healthy subjects in comparison to the oldest healthy subject and in comparison to an MS patient were calculated. Larger anatomical structures were characterized using a standard atlas. The vector sum of the normalized differences was used to show significant tissue differences.

Results

The coefficient of variation of the reference maps was high at the edges of the brain and the ventricles, moderate in the cortical grey matter and low in white matter and the deep grey matter structures. The elderly subject mainly showed significantly lower R₁ and R₂ and higher PD values along all sulci. The MS patient showed significantly lower R₁ and R₂ and higher PD values at the edges of the ventricular system as well as throughout the periventricular white matter, at the internal and external capsules and at each of the MS lesions.

Conclusion

Brain normalization of rapid qMRI is a promising new method to generate reference maps of typical brain characteristics and to automatically detect deviating tissue properties in the brain.

Structural brain atlases: design, rationale, and applications in normal and pathological cohorts

Structural magnetic resonance imaging (MRI) provides anatomical information about the brain in healthy as well as in diseased conditions. On the other hand, functional MRI (fMRI) provides information on the brain activity during performance of a specific task. Analysis of fMRI data requires the registration of the data to a reference brain template in order to identify the activated brain regions. Brain templates also find application in other neuroimaging modalities, such as diffusion tensor imaging and multi-voxel spectroscopy. Further, there are certain differences (e.g., brain shape and size) in the brains of populations of different origin and during diseased conditions like in Alzheimer's disease (AD), population and disease-specific brain templates may be considered crucial for accurate registration and subsequent analysis of fMRI as well as other neuroimaging data. This manuscript provides a comprehensive review of the history, construction and application of brain atlases. A chronological outline of the development of brain template design, starting from the Talairach and Tournoux atlas to the Chinese brain template (to date), along with their respective detailed construction protocols provides the backdrop to this manuscript. The manuscript also provides the automated workflow-based protocol for designing a population-specific brain atlas from structural MRI data using LONI Pipeline graphical workflow environment. We conclude by discussing the scope of brain templates as a research tool and their application in various neuroimaging modalities.

Promotion of remyelination by adipose mesenchymal stem cell transplantation in a cuprizone model of multiple sclerosis

OBJECTIVE

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system (CNS). Stem cell transplantation is a new therapeutic approach for demyelinating diseases such as MS which may promote remyelination. In this study, we evaluate the remyelinating potential of adipose mesenchymal stem cells (ADSCs) and their effect on neural cell composition in the corpus callosum in an experimental model of MS.

MATERIALS AND METHODS

This experimental study used adult male C57BL/6 mice. Cultured ADSCs were confirmed to be CD73(+),CD90(+), CD31(-),CD45(-), and labeled by PKH26. Animals were fed with 0.2% w/w cuprizone added to ground breeder chow ad libitum for six weeks. At day 0 after cuprizone removal, mice were randomly divided into two groups: the ADSCs-transplanted group and the control vehicle group (received medium alone). Some mice of the same age were fed with their normal diet to serve as healthy control group. Homing of ADSCs in demyelinated lesions was examined by fluorescent microscope. At ten days after transplantation, the mice were euthanized and their cells analyzed by luxol fast blue staining (LFB), transmission electron microscopy and flow cytometry. Results were analyzed by one-way analysis of variance (ANOVA).

RESULTS

According to fluorescent cell labeling, transplanted ADSCs appeared to survive and exhibited homing specificity. LFB staining and transmission electron microscope evaluation revealed enhanced remyelination in the transplanted group compared to the control vehicle group. Flow cytometry analysis showedan increase in Olig2 and O4 cells and a decrease in GFAP and Iba-1 cells in the transplanted group.

CONCLUSION

Our results indicate that ADSCs may provide a feasible, practical way for remyelination in diseases such as MS.

Neuronal antigens recognized by cerebrospinal fluid IgM in multiple sclerosis

Axonal injury is the major cause of disability in patients with multiple sclerosis (MS), but the mechanisms leading to axonal damage are poorly understood. Oligoclonal IgM against lipids predicts an aggressive disease course in MS; however, the antigen that elicits the immune response has not yet been identified. We screened the CSF of 12 patients with MS, 7 patients with neuromyelitis optica (NMO), and 5 controls with non-inflammatory neurological disease (NIND) for the presence of IgM-type antibodies (IgM-Ab) against neuronal surface antigens, and analyzed the relationship between IgM-Ab level and the extent of brain atrophy. The CSF of MS patients displayed significantly higher levels of IgM-Ab compared to NIND or NMO patients. Furthermore, we document for the first time that these IgM-Ab recognize neuronal surface antigens, and that the levels of neuronal-bound IgM-Ab were independent of the IgM concentration and correlate with brain atrophy. Our findings suggest a role for the CSF IgM-Ab in the development of MS pathophysiology.

Multi-modal quantitative MRI investigation of brain tissue neurodegeneration in multiple sclerosis

PURPOSE

To investigate the utility of multimodal quantitative MRI (qMRI) and atlas-based methods to identify characteristics of lesion-driven injury and neurodegeneration in relapsing remitting multiple sclerosis (RRMS).

MATERIALS AND METHODS

This work is health insurance portability and accountability act compliant. High resolution T1-weighted, dual echo, and fluid-attenuated inversion recovery and diffusion tensor MRI images were prospectively acquired on 68 RRMS patients (range, 25-58 years) and 68 age-matched controls. The data were analyzed using standardized human brain atlas-based tissue segmentation procedures to obtain regional volumes and their corresponding T2 relaxation times and DTI maps.

RESULTS

Group-averaged brain atlas-based qMRI maps of T2, fractional anisotropy and diffusivities are visually presented and compared between controls and RRMS. The analysis shows a widespread injury in RRMS. Atrophy of the corpus callosum (CC) was substantial in RRMS. The qMRI attributes of the neocortex in combination with the CC such as T2 and diffusivities were elevated and correlated with disability.

CONCLUSION

Using a standardized multimodal qMRI acquisition and analyses that accounted for lesion distribution we demonstrate that cerebral pathology is widespread in RRMS. Our analysis of CC and neocortex qMRI metrics in relation to disability points to a neurodegenerative injury component that is independent from lesions.

Multimodal quantitative magnetic resonance imaging of thalamic development and aging across the human lifespan: implications to neurodegeneration in multiple sclerosis

The human brain thalami play essential roles in integrating cognitive, sensory, and motor functions. In multiple sclerosis (MS), quantitative magnetic resonance imaging (qMRI) measurements of the thalami provide important biomarkers of disease progression, but late development and aging confound the interpretation of data collected from patients over a wide age range. Thalamic tissue volume loss due to natural aging and its interplay with lesion-driven pathology has not been investigated previously. In this work, we used standardized thalamic volumetry combined with diffusion tensor imaging, T2 relaxometry, and lesion mapping on large cohorts of controls (N = 255, age range = 6.2-69.1 years) and MS patients (N = 109, age range = 20.8-68.5 years) to demonstrate early age- and lesion-independent thalamic neurodegeneration.