Progression of regional grey matter atrophy in multiple sclerosis

The role of 7 T MRI to assess atrophy of the subcortical deep gray matter in relapsing-remitting multiple sclerosis

BACKGROUND

Deep gray matter (DGM) atrophy and lesions are found in multiple sclerosis (MS).

OBJECTIVE

To optimize automated segmentation for 7 T DGM volumetrics and assess sensitivity to atrophy and relationship to DGM lesions and disability in relapsing-remitting (RR) MS.

METHODS

30 RRMS subjects [mean age 44.0 years, median Expanded Disability Status Scale (EDSS) score 2] and 14 healthy controls underwent 7 T MRI with 3D magnetization-prepared 2 rapid gradient-echoes (MP2RAGE) and fluid-attenuated inversion recovery. Customizing an automated pipeline to assess DGM structure volumes required pre-processing combining two MP2RAGE inversion times and uniform T1 images, and noise-suppressed reconstruction. DGM volumes were normalized. Brain DGM lesions and white matter T2 lesion volume (T2LV) were expert-quantified. Spearman correlations and Wilcoxon rank-sum tests were assessed.

RESULTS

DGM lesions were found in 77% (n = 23) of MS subjects and no controls, with thalamic lesions most prevalent (73%). An average of 3.6 DGM lesions was found per person with MS. Total DGM volumes were lower in MS vs. controls (p = 0.034), varying by region, most pronounced in the caudate (p = 0.008). DGM volumes inversely correlated with EDSS (total DGM: r = - 0.45, p = 0.014; globus pallidus: r =  - 0.42, p = 0.023; putamen: r = - 0.44, p = 0.016; caudate: r = - 0.37, p = 0.047) and T2LV (total DGM: r = - 0.53, p = 0.003; putamen: r = - 0.40, p = 0.030; thalamus: r = - 0.63, p < 0.001). DGM atrophy was most closely linked to disability among all MRI measures. Thalamic lesion volume correlated inversely with thalamic volume (r = - 0.38, p = 0.045).

CONCLUSION

7 T MRI shows a link between DGM atrophy and both white matter lesions and physical disability in RRMS. Thalamic lesions are associated with thalamic atrophy.

Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms

From Alzheimer's disease to amyotrophic lateral sclerosis, the molecular cascades underlying neurodegenerative disorders remain poorly understood. The clinical view of neurodegeneration is confounded by symptomatic heterogeneity and mixed pathology in almost every patient. While the underlying physiological alterations originate, proliferate, and propagate potentially decades before symptomatic onset, the complexity and inaccessibility of the living brain limit direct observation over a patient's lifespan. Consequently, there is a critical need for robust computational methods to support the search for causal mechanisms of neurodegeneration by distinguishing pathogenic processes from consequential alterations, and inter-individual variability from intra-individual progression. Recently, promising advances have been made by data-driven spatiotemporal modeling of the brain, based on in vivo neuroimaging and biospecimen markers. These methods include disease progression models comparing the temporal evolution of various biomarkers, causal models linking interacting biological processes, network propagation models reproducing the spatial spreading of pathology, and biophysical models spanning cellular- to network-scale phenomena. In this review, we discuss various computational approaches for integrating cross-sectional, longitudinal, and multi-modal data, primarily from large observational neuroimaging studies, to understand (i) the temporal ordering of physiological alterations, i(i) their spatial relationships to the brain's molecular and cellular architecture, (iii) mechanistic interactions between biological processes, and (iv) the macroscopic effects of microscopic factors. We consider the extents to which computational models can evaluate mechanistic hypotheses, explore applications such as improving treatment selection, and discuss how model-informed insights can lay the groundwork for a pathobiological redefinition of neurodegenerative disorders.

Causal relationships of grey matter structures in multiple sclerosis and neuromyelitis optica spectrum disorder: insights from Mendelian randomization

Multiple sclerosis and neuromyelitis optica spectrum disorder are two debilitating inflammatory demyelinating diseases of the CNS. Although grey matter alterations have been linked to both multiple sclerosis and neuromyelitis optica spectrum disorder in observational studies, it is unclear whether these associations indicate causal relationships between these diseases and grey matter changes. Therefore, we conducted a bidirectional two-sample Mendelian randomization analysis to investigate the causal relationships between 202 grey matter imaging-derived phenotypes (33 224 individuals) and multiple sclerosis (47 429 cases and 68 374 controls) as well as neuromyelitis optica spectrum disorder (215 cases and 1244 controls). Our results suggested that genetically predicted multiple sclerosis was positively associated with the surface area of the left parahippocampal gyrus (β = 0.018, P = 2.383 × 10-4) and negatively associated with the volumes of the bilateral caudate (left: β = -0.020, P = 7.203 × 10-5; right: β = -0.021, P = 3.274 × 10-5) and putamen nuclei (left: β = -0.030, P = 2.175 × 10-8; right: β = -0.024, P = 1.047 × 10-5). In addition, increased neuromyelitis optica spectrum disorder risk was associated with an increased surface area of the left paracentral gyrus (β = 0.023, P = 1.025 × 10-4). Conversely, no evidence was found for the causal impact of grey matter imaging-derived phenotypes on disease risk in the opposite direction. We provide suggestive evidence that genetically predicted multiple sclerosis and neuromyelitis optica spectrum disorder are associated with increased cortical surface area and decreased subcortical volume in specific regions. Our findings shed light on the associations of grey matter alterations with the risk of multiple sclerosis and neuromyelitis optica spectrum disorder.

Brain atrophy assessment in multiple sclerosis: technical- and subject-related barriers for translation to real-world application in individual subjects

INTRODUCTION

Brain atrophy is a well-established MRI outcome for predicting clinical progression and monitoring treatment response in persons with multiple sclerosis (pwMS) at the group level. Despite the important progress made, the translation of brain atrophy assessment into clinical practice faces several challenges.

AREAS COVERED

In this review, the authors discuss technical- and subject-related barriers for implementing brain atrophy assessment as part of the clinical routine at the individual level. Substantial progress has been made to understand and mitigate technical barriers behind MRI acquisition. Numerous research and commercial segmentation techniques for volume estimation are available and technically validated, but their clinical value has not been fully established. A systematic assessment of subject-related barriers, which include genetic, environmental, biological, lifestyle, comorbidity, and aging confounders, is critical for the interpretation of brain atrophy measures at the individual subject level. Educating both medical providers and pwMS will help better clarify the benefits and limitations of assessing brain atrophy for disease monitoring and prognosis.

EXPERT OPINION

Integrating brain atrophy assessment into clinical practice for pwMS requires overcoming technical and subject-related challenges. Advances in MRI standardization, artificial intelligence, and clinician education will facilitate this process, improving disease management and potentially reducing long-term healthcare costs.

Multimodal magnetic resonance longitudinal study on the deep gray matter in multiple sclerosis patients with teriflunomide

Disease-modifying therapies (DMTs) are used in an increasing number of patients with multiple sclerosis (MS). However, whether DMTs have intrinsic effects on deep gray matter (DGM) microstructure and atrophy is still poorly understood. In this study, we described the quantitative susceptibility values (QSV) and diffusion kurtosis imaging (DKI) metrics of DGM in relapsing-remitting MS (RRMS) patients and their association with cognitive deficits. We recruited 62 patients with RRMS receiving DMTs and 30 patients with RRMS not receiving DMTs underwent MRI on a 3T scanner. Fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), mean diffusivity (MD), mean kurtosis (MK), QSV and volumes of bilateral caudate nucleus (CAU), amygdala (AMYG), putamen (PUT), hippocampus (Hipp), globus pallidus (GP) and thalamus (THA) were measured. Correlation analysis was performed between those image indexes with longitudinal significant changes and clinical neurological scores, including Expanded Disability Status Scale (EDSS), Digit Span Testand (DST), Symbol Digit Modalities Test (SDMT), Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Significant longitudinal increases in FA, KFA and MK values were found in both groups in bilateral CAU, AMYG, PUT, Hipp, GP and THA (all p < 0.005). MD values of the right of CAU in the two groups were significant longitudinal increase (p = 0.009, p = 0.047); MD values of the right of GP (p = 0.042), the left of THA (p = 0.003), the right of THA (p = 0.001) in treated MS were significant longitudinal decrease; There were no significant longitudinal changes between treated and untreated groups in normalized deep gray matter volume. For QSV, longitudinal increase in the right of PUT (p = 0.022) in the treated MS group and in the left of Hipp (p = 0.045) in the untreated MS group. The QSV and DKI measures were highly correlated with cognitive and disability tests. The treated RRMS patients showed different longitudinal changes of MD value and QSV with untreated in several DGM regions, and these differences were correlated with cognitive and microstructural integrity.

Integrated elemental analysis supports targeting copper perturbations as a therapeutic strategy in multiple sclerosis

Multiple sclerosis (MS) is a debilitating affliction of the central nervous system (CNS) that involves demyelination of neuronal axons and neurodegeneration resulting in disability that becomes more pronounced in progressive forms of the disease. The involvement of neurodegeneration in MS underscores the need for effective neuroprotective approaches necessitating identification of new therapeutic targets. Herein, we applied an integrated elemental analysis workflow to human MS-affected spinal cord tissue utilising multiple inductively coupled plasma-mass spectrometry methodologies. These analyses revealed shifts in atomic copper as a notable aspect of disease. Complementary gene expression and biochemical analyses demonstrated that changes in copper levels coincided with altered expression of copper handling genes and downstream functionality of cuproenzymes. Copper-related problems observed in the human MS spinal cord were largely reproduced in the experimental autoimmune encephalomyelitis (EAE) mouse model during the acute phase of disease characterised by axonal demyelination, lesion formation, and motor neuron loss. Treatment of EAE mice with the CNS-permeant copper modulating compound CuII(atsm) resulted in recovery of cuproenzyme function, improved myelination and lesion volume, and neuroprotection. These findings support targeting copper perturbations as a therapeutic strategy for MS with CuII(atsm) showing initial promise.

Dimethyl fumarate preserves brainstem and cervical spinal cord integrity in radiologically isolated syndrome

BACKGROUND AND PURPOSE

The first randomized placebo-controlled therapeutic trial in radiologically isolated syndrome (RIS), ARISE, demonstrated that treatment with dimethyl fumarate (DMF) delayed the onset of a first clinical event related to CNS demyelination and was associated with a significant reduction in new and/or newly enlarging T2-weighted hyperintense lesions. The purpose of this study was to explore the effect of DMF on volumetric measures, including whole brain, thalamic, and subcortical gray matter volumes, brainstem and upper cervical spine three-dimensional (3D) volumes, and brainstem and upper cervical spine surface characteristics.

METHODS

Standardized 3T MRIs including 3D isotropic T1-weighted gradient echo images were acquired at baseline and end-of-study according to the ARISE study protocol. The acquired data were analyzed using Structural Image Evaluation Using Normalization of Atrophy (SIENA), FreeSurfer v7.3, and an in-house pipeline for 3D conformational metrics. Multivariate mixed models for repeated measures were used to analyze rates of change in whole brain, thalamic, subcortical gray matter, as well as change in the 3D surface curvature of the dorsal pons and dorsal medulla and 3D volume change at the medulla-upper cervical spinal cord.

RESULTS

The study population consisted of 64 RIS subjects (DMF:30, placebo:34). No significant difference was seen in whole brain, thalamic, or subcortical gray matter volumes in treated vs. untreated RIS patients. A significant difference was observed in dorsal pons curvature with the DMF group having a lower least squares mean change of - 4.46 (standard estimate (SE): 3.77) when compared to placebo [6.94 (3.71)] (p = 0.036). In individuals that experienced a first clinical event, a greater reduction in medulla-upper cervical spinal cord volume (p = 0.044) and a decrease in surface curvature was observed at the dorsal medulla (p = 0.009) but not at the dorsal pons (p = 0.443).

CONCLUSIONS

The benefit of disease-modifying therapy in RIS may extend to CNS structures impacted by neurodegeneration that is below the resolution of conventional volumetric measures.

Digital outcome measures are associated with brain atrophy in patients with multiple sclerosis

BACKGROUND

Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression.

OBJECTIVE

To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS.

METHODS

In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates.

RESULTS

In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12.

CONCLUSION

Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.

Phonemic processing is below expectations and linked to word-finding difficulty in multiple sclerosis

BACKGROUND

Word-finding difficulty is prevalent but poorly understood in persons with relapsing-remitting multiple sclerosis (RRMS).

OBJECTIVE

The objective was to investigate our hypothesis that phonological processing ability is below expectations and related to word-finding difficulty in patients with RRMS.

METHOD

Data were analyzed from patients with RRMS (n = 50) on patient-reported word-finding difficulty (PR-WFD) and objective performance on Wechsler Individual Achievement Test, Fourth Edition (WIAT-4) Phonemic Proficiency (PP; analysis of phonemes within words), Word Reading (WR; proxy of premorbid literacy and verbal ability), and Sentence Repetition (SR; auditory processing of word-level information).

RESULTS

Performance (mean (95% confidence interval)) was reliably lower than normative expectations for PP (-0.41 (-0.69, -0.13)) but not for WR (0.02 (-0.21, 0.25)) or SR (0.08 (-0.15, 0.31). Within-subjects performance was worse on PP than on both WR (t(49) = 4.00, p < 0.001, d = 0.47) and SR (t(49) =3.76, p < 0.001, d = 0.54). Worse PR-WFD was specifically related to lower PP (F2,47 = 6.24, p = 0.004, η2 = 0.21); worse PP performance at PR-WFD Often (n = 13; -1.16 (-1.49, -0.83)) than Sometimes (n = 17; -0.14 (-0.68, 0.41)) or Rarely (n = 20; -0.16 (-0.58, 0.27). PR-WFD was unrelated to WR or SR (ps > 0.25).

CONCLUSION

Phonological processing was below expectations and specifically linked to word-finding difficulty in RRMS. Findings are consistent with early disease-related cortical changes within the posterior superior temporal/supramarginal region. Results inform our developing model of multiple sclerosis-related word-finding difficulty.

Disability independent of cerebral white matter demyelination in progressive multiple sclerosis

The pathogenic mechanisms contributing to neurological disability in progressive multiple sclerosis (PMS) are poorly understood. Cortical neuronal loss independent of cerebral white matter (WM) demyelination in myelocortical MS (MCMS) and identification of MS patients with widespread cortical atrophy and disability progression independent of relapse activity (PIRA) support pathogenic mechanisms other than cerebral WM demyelination. The three-dimensional distribution and underlying pathology of myelinated T2 lesions were investigated in postmortem MCMS brains. Postmortem brain slices from previously characterized MCMS (10 cases) and typical MS (TMS) cases (12 cases) were co-registered with in situ postmortem T2 hyperintensities and T1 hypointensities. T1 intensity thresholds were used to establish a classifier that differentiates MCMS from TMS. The classifier was validated in 36 uncharacterized postmortem brains and applied to baseline MRIs from 255 living PMS participants enrolled in SPRINT-MS. Myelinated T2 hyperintensities in postmortem MCMS brains have a contiguous periventricular distribution that expands at the occipital poles of the lateral ventricles where a surface-in gradient of myelinated axonal degeneration was observed. The MRI classifier distinguished pathologically confirmed postmortem MCMS and TMS cases with an accuracy of 94%. For SPRINT-MS patients, the MRI classifier identified 78% as TMS, 10% as MCMS, and 12% with a paucity of cerebral T1 and T2 intensities. In SPRINT-MS, expanded disability status scale and brain atrophy measures were similar in MCMS and TMS cohorts. A paucity of cerebral WM demyelination in 22% of living PMS patients raises questions regarding a primary role for cerebral WM demyelination in disability progression in all MS patients and has implications for clinical management of MS patients and clinical trial outcomes in PMS. Periventricular myelinated fiber degeneration provides additional support for surface-in gradients of neurodegeneration in MS.

White matter disease derived from vascular and demyelinating origins

Damage or microstructural alterations of the white matter can cause dysfunction of the intrinsic neural networks in a condition termed as white matter disease (WMD). Frequently detected on brain computed tomography and magnetic resonance imaging scans, WMD is commonly presented in inflammatory demyelinating diseases like multiple sclerosis (MS) and vascular diseases such as cerebral small vessel disease (CSVD). Prevention of MS and CSVD progression requires early treatments with drastically different medications and approaches, as such, early and accurate diagnosis of WMD, derived from vascular or demyelinating etiologies, is of paramount importance. However, the clinical and imaging similarities between MS, especially during the early stage, and CSVD, pose a significant dilemma in differentiating these two conditions. In this review, we attempt to summarize and contrast the distinguishing features of MS and CSVD for aiding accurate diagnosis to ensure timely corresponding management in the early stages of MS and CSVD.

Very-long T2-weighted imaging of the non-lesional brain tissue in multiple sclerosis patients

The purpose of this study is to demonstrate that T2-weighted imaging with very long echo time (TE > 300 ms) can provide relevant information in neurodegenerative/inflammatory disorder. Twenty patients affected by relapsing-remitting multiple sclerosis with stable disease course underwent 1.5 T 3D FLAIR, 3D T1-weighted, and a multi-echo sequence with 32 echoes (TE = 10-320 ms). Focal lesions (FL) were identified on FLAIR. T1-images were processed to segment deep gray matter (dGM), white matter (WM), FL sub-volumes with T1 hypo-intensity (T1FL), and dGM volumes (atrophy). Clinical-radiological parameters included Expanded Disability Status Scale (EDSS), disease duration, patient age, T1FL, and dGM atrophy. Correlation analysis was performed between the mean signal intensity (SI) computed on the non-lesional dGM and WM at different TE versus the clinical-radiological parameters. Multivariable linear regressions were fitted to the data to assess the association between the dependent variable EDSS and the independent variables obtained by T1FL lesion load and the mean SI of dGM and WM at the different TE. A clear trend is observed, with a systematic strengthening of the significance of the correlation at longer TE for all the relationships with the clinical-radiological parameters, becoming significant (p < 0.05) for EDSS, T1FL volumes, and dGM atrophy. Multivariable linear regressions show that at shorter TE, the SI of the T2-weighted sequences is not relevant for describing the EDSS variability while the T1FL volumes are relevant, and vice versa, at very-long TEs (around 300 ms); the SI of the T2-weighted sequences significantly (p < 0.05) describes the EDSS variability. By very long TE, the SI primarily originates from water with a T2 longer than 250 ms and/or free water, which may be arising from the perivascular space (PVS). Very-long T2-weighting might detect dilated PVS and represent an unexplored MR approach in neurofluid imaging of neurodegenerative/inflammatory diseases.

Atrophy-Independent and Dependent Iron and Myelin Changes in Deep Gray Matter of Multiple Sclerosis: A Longitudinal Study Using χ-Separation Imaging

RATIONALE AND OBJECTIVES

To investigate iron and myelin changes in deep gray matter (DGM) of relapsing-remitting multiple sclerosis (RRMS) patients and their relationship to atrophy by χ-separation imaging.

MATERIALS AND METHODS

33 RRMS patients and 34 healthy controls (HC) were included in this study. The χ-separation map reconstructed from a 3D multi-echo gradient echo scan was used to measure the positive susceptibility (χpos) and negative susceptibility (χneg) of DGM. To take into account the effect of atrophy, susceptibility mass of DGM was calculated by multiplying volume by the mean bulk susceptibility. Differences in MRI metrics between baseline patients, follow-up patients, and HC were compared respectively.

RESULTS

Compared to HC, χpos of basal ganglia were significantly increased in follow-up patients (P < 0.05). The χpos of pallidum was significantly higher in follow-up patients than that in baseline patients (P = 0.006). The χneg of caudate, pallidum and hippocampus in baseline and follow-up patients was significantly higher than that in HC (P < 0.05). When taking into account the effect of atrophy, there was a significant decrease in χpos mass and a significant increase in χneg mass of thalamus, accumbens and amygdala in follow-up patients compared to HC (P < 0.05). The χpos mass of the thalamus was further decreased in follow-up patients compared to baseline patients (P = 0.006).

CONCLUSION

χ-separation imaging could generate independent information on iron and myelin changes in RRMS patients, showing atrophy-dependent iron increase in basal ganglia and atrophy-independent iron and myelin decrease in thalamus.

Structural and functional brain correlates of socioeconomic status across the life span: A systematic review

It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.

The neural substrates of social cognition deficits in newly diagnosed multiple sclerosis patients

OBJECTIVE

Cognitive and affective symptoms in multiple sclerosis (MS) can be independently impaired and have different pathways of progression. Cognitive alterations have been described since the earliest MS stages; by contrast, the social cognition (SC) domain has never been investigated in the first year from MS diagnosis. We aimed to evaluate SC and unravel its neural bases in newly diagnosed MS patients.

METHODS

Seventy MS patients underwent at diagnosis a 3 T-MRI and a neuropsychological/SC assessment (median time between diagnosis and MRI/cognitive evaluation = 0 months). We tested two matched reference samples: 31 relapsing-remitting MS patients with longer course (mean ± SD disease duration = 7.0 ± 4.5 years) and 38 healthy controls (HCs). Cortical thicknesses (CTh) and volumes of brain regions were calculated.

RESULTS

Newly diagnosed MS patients performed significantly lower than HCs in facial emotion recognition (global: p < 0.001; happiness: p = 0.041, anger: p = 0.007; fear: p < 0.001; disgust: p = 0.004) and theory of mind (p = 0.005), while no difference was found between newly diagnosed and longer MS patients. Compared to lower performers, higher performers in facial emotion recognition showed greater volume of amygdala (p = 0.032) and caudate (p = 0.036); higher performers in theory of mind showed greater CTh in lingual gyrus (p = 0.006), cuneus (p = 0.024), isthmus cingulate (p = 0.038), greater volumes of putamen (p = 0.016), pallidum (p = 0.029), and amygdala (p = 0.032); patients with higher empathy showed lower cuneus CTh (p = 0.042) and putamen volume (p = 0.007).

INTERPRETATIONS

SC deficits are present in MS patients since the time of diagnosis and remain persistent along the disease course. Specific basal, limbic, and occipital areas play a significant role in the pathogenesis of these alterations.

Global and Regional Deep Learning Models for Multiple Sclerosis Stratification From MRI

BACKGROUND

The combination of anatomical MRI and deep learning-based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. However, studies assessing the effect of different input strategies on model's performance are lacking.

PURPOSE

To compare whole-brain input sampling strategies and regional/specific-tissue strategies, which focus on a priori known relevant areas for disability accrual, to stratify MS patients based on their disability level.

STUDY TYPE

Retrospective.

SUBJECTS

Three hundred nineteen MS patients (382 brain MRI scans) with clinical assessment of disability level performed within the following 6 months (~70% training/~15% validation/~15% inference in-house dataset) and 440 MS patients from multiple centers (independent external validation cohort).

FIELD STRENGTH/SEQUENCE

Single vendor 1.5 T or 3.0 T. Magnetization-Prepared Rapid Gradient-Echo and Fluid-Attenuated Inversion Recovery sequences.

ASSESSMENT

A 7-fold patient cross validation strategy was used to train a 3D-CNN to classify patients into two groups, Expanded Disability Status Scale score (EDSS) ≥ 3.0 or EDSS < 3.0. Two strategies were investigated: 1) a global approach, taking the whole brain volume as input and 2) regional approaches using five different regions-of-interest: white matter, gray matter, subcortical gray matter, ventricles, and brainstem structures. The performance of the models was assessed in the in-house and the independent external cohorts.

STATISTICAL TESTS

Balanced accuracy, sensitivity, specificity, area under receiver operating characteristic (ROC) curve (AUC).

RESULTS

With the in-house dataset, the gray matter regional model showed the highest stratification accuracy (81%), followed by the global approach (79%). In the external dataset, without any further retraining, an accuracy of 72% was achieved for the white matter model and 71% for the global approach.

DATA CONCLUSION

The global approach offered the best trade-off between internal performance and external validation to stratify MS patients based on accumulated disability.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Real-World Effectiveness and Safety of Cladribine in Multiple Sclerosis: Longitudinal Data From the Nationwide Registry in Argentina

OBJECTIVE

The aim was to evaluate patient profiles, effectiveness and safety of cladribine (CLAD) in patients with relapsing-remitting multiple sclerosis in Argentina.

METHODS

This was a substudy included in RelevarEM (MS and neuromyelitis optica registry in Argentina, NCT03375177). Patients with MS who received CLAD tablets and were followed up for at least 24 months were included. Clinical evaluations every 3 months collect information about: a) clinical relapses; b) progression of physical disability, evaluated through Expanded Disability Status Scale, and c) new lesions found in the magnetic resonance imaging. Lymphopenia was evaluated during the follow-up and defined as grade 1: absolute lymphocyte count (ALC) 800-999/μL; grade 2: ALC 500-799/μL; grade 3: ALC 200-499/μL and grade 4: ALC <200/μL.

RESULTS

A total of 240 patients were included from 19 centers from Argentina. The mean annualized relapse rate during the 12-month pre-CLAD initiation was 1.19 ± 0.56 versus 0.22 ± 0.18 at month 12 and 0.19 ± 0.15 at month 24 ( P < 0.001). A total of 142 (59.2%) fulfilled the criteria of disease activity during the 12 months before treatment initiation, whereas 27 (11.3%) fulfilled it at month 12 and 38 (15.8%) at month 24, P < 0.001. Regarding no evidence of disease activity (NEDA), 202 (84.2%) patients achieved NEDA status at month 12 and 185 (77%) at month 24. The most frequent incidence density of lymphopenia for course 2 observed was also for grade 1, 6.1 (95% confidence interval [CI] = 5.5-7.1). The overall incidence density of lymphopenia grade 4 was 0.1 (95% CI = 0.06-0.19).

CONCLUSION

This information will help when choosing the best treatment option for Argentinean patients.

Mapping brain volume change across time in primary-progressive multiple sclerosis

PURPOSE

Detection and prediction of the rate of brain volume loss with age is a significant unmet need in patients with primary progressive multiple sclerosis (PPMS). In this study we construct detailed brain volume maps for PPMS patients. These maps compare age-related changes in both cortical and sub-cortical regions with those in healthy individuals.

METHODS

We conducted retrospective analyses of brain volume using T1-weighted Magnetic Resonance Imaging (MRI) scans of a large cohort of PPMS patients and healthy subjects. The volume of brain parenchyma (BP), cortex, white matter (WM), deep gray matter, thalamus, and cerebellum were measured using the robust SynthSeg segmentation tool. Age- and gender-related regression curves were constructed based on data from healthy subjects, with the 95% prediction interval adopted as the normality threshold for each brain region.

RESULTS

We analyzed 495 MRI scans from 169 PPMS patients, aged 20-79 years, alongside 563 exams from healthy subjects aged 20-86. Compared to healthy subjects, a higher proportion of PPMS patients showed lower than expected brain volumes in all regions except the cerebellum. The most affected areas were BP, WM, and thalamus. Lower brain volumes correlated with longer disease duration for BP and WM, and higher disability for BP, WM, cortex, and thalamus.

CONCLUSIONS

Constructing age- and gender-related brain volume maps enabled identifying PPMS patients at a higher risk of brain volume loss. Monitoring these high-risk patients may lead to better treatment decisions and improve patient outcomes.

The NR4A2/VGF pathway fuels inflammation-induced neurodegeneration via promoting neuronal glycolysis

A disturbed balance between excitation and inhibition (E/I balance) is increasingly recognized as a key driver of neurodegeneration in multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system. To understand how chronic hyperexcitability contributes to neuronal loss in MS, we transcriptionally profiled neurons from mice lacking inhibitory metabotropic glutamate signaling with shifted E/I balance and increased vulnerability to inflammation-induced neurodegeneration. This revealed a prominent induction of the nuclear receptor NR4A2 in neurons. Mechanistically, NR4A2 increased susceptibility to excitotoxicity by stimulating continuous VGF secretion leading to glycolysis-dependent neuronal cell death. Extending these findings to people with MS (pwMS), we observed increased VGF levels in serum and brain biopsies. Notably, neuron-specific deletion of Vgf in a mouse model of MS ameliorated neurodegeneration. These findings underscore the detrimental effect of a persistent metabolic shift driven by excitatory activity as a fundamental mechanism in inflammation-induced neurodegeneration.

Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is an immune-mediated neurological disorder, and up to 50% of patients experience depression. We investigated how white matter network disruption is related to depression in MS.

METHODS

Using electronic health records, 380 participants with MS were identified. Depressed individuals (MS+Depression group; n = 232) included persons who had an ICD-10 depression diagnosis, had a prescription for antidepressant medication, or screened positive via Patient Health Questionnaire (PHQ)-2 or PHQ-9. Age- and sex-matched nondepressed individuals with MS (MS-Depression group; n = 148) included persons who had no prior depression diagnosis, had no psychiatric medication prescriptions, and were asymptomatic on PHQ-2 or PHQ-9. Research-quality 3T structural magnetic resonance imaging was obtained as part of routine care. We first evaluated whether lesions were preferentially located within the depression network compared with other brain regions. Next, we examined if MS+Depression patients had greater lesion burden and if this was driven by lesions in the depression network. Primary outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain.

RESULTS

MS lesions preferentially affected fascicles within versus outside the depression network (β = 0.09, 95% CI = 0.08 to 0.10, p < .001). MS+Depression patients had more lesion burden (β = 0.06, 95% CI = 0.01 to 0.10, p = .015); this was driven by lesions within the depression network (β = 0.02, 95% CI = 0.003 to 0.040, p = .020).

CONCLUSIONS

We demonstrated that lesion location and burden may contribute to depression comorbidity in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression patients had more disease than MS-Depression patients, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Spatial correspondence among regional gene expressions and gray matter volume loss in multiple sclerosis

In multiple sclerosis (MS), a non-random and clinically relevant pattern of gray matter (GM) volume loss has been described. Whether differences in regional gene expression might underlay distinctive pathological processes contributing to this regional variability has not been explored yet. Two hundred eighty-six MS patients and 172 healthy controls (HC) underwent a brain 3T MRI, a complete neurological evaluation and a neuropsychological assessment. Using Allen Human Brain Atlas, voxel-based morphometry and MENGA platform, we integrated brain transcriptome and neuroimaging data to explore the spatial cross-correlations between regional GM volume loss and expressions of 2710 genes involved in MS (p < 0.05, family-wise error-corrected). Enrichment analyses were performed to evaluate overrepresented molecular functions, biological processes and cellular components involving genes significantly associated with voxel-based morphometry-derived GM maps (p < 0.05, Bonferroni-corrected). A diffuse GM volume loss was found in MS patients compared to HC and it was spatially correlated with 74 genes involved in GABA neurotransmission and mitochondrial oxidoreductase activity mainly expressed in neurons and astrocytes. A more severe GM volume loss was spatially associated, in more disabled MS patients, with 44 genes involved in mitochondrial integrity of all resident cells of the central nervous system (CNS) and, in cognitively impaired MS patients, with 64 genes involved in mitochondrial protein heterodimerization and oxidoreductase activities expressed also in microglia and endothelial cells. Specific differences in the expressions of genes involved in synaptic GABA receptor activities and mitochondrial functions in resident CNS cells may influence regional susceptibility to MS-related excitatory/inhibitory imbalance and oxidative stress, and subsequently, to GM volume loss.

Vulnerability of Thalamic Nuclei at CSF Interface During the Entire Course of Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Thalamic atrophy can be used as a proxy for neurodegeneration in multiple sclerosis (MS). Some data point toward thalamic nuclei that could be affected more than others. However, the dynamic of their changes during MS evolution and the mechanisms driving their differential alterations are still uncertain.

METHODS

We paired a large cohort of 1,123 patients with MS with the same number of healthy controls, all scanned with conventional 3D-T1 MRI. To highlight the main atrophic regions at the thalamic nuclei level, we validated a segmentation strategy consisting of deep learning-based synthesis of sequences, which were used for automatic multiatlas segmentation. Then, through a lifespan-based approach, we could model the dynamics of the 4 main thalamic nuclei groups.

RESULTS

All analyses converged toward a higher rate of atrophy for the posterior and medial groups compared with the anterior and lateral groups. We also demonstrated that focal MS white matter lesions were associated with atrophy of groups of nuclei when specifically located within the associated thalamocortical projections. The volumes of the most affected posterior group, but also of the anterior group, were better associated with clinical disability than the volume of the whole thalamus.

DISCUSSION

These findings point toward the thalamic nuclei adjacent to the third ventricle as more susceptible to neurodegeneration during the entire course of MS through potentiation of disconnection effects by regional factors. Because this information can be obtained even from standard T1-weighted MRI, this paves the way toward such an approach for future monitoring of patients with MS.

Enlarged choroid plexus in relapsing-remitting multiple sclerosis may lead to brain structural changes through the glymphatic impairment

OBJECTIVES

To investigate the potential link among choroid plexus (CP) volume, glymphatic clearance and brain structural change in relapsing-remitting multiple sclerosis (RRMS) patients.

MATERIALS AND METHODS

Sixty-five RRMS patients and 48 healthy controls (HC) underwent MRI examination. The diffusion tensor image analysis along the perivascular space (DTI-ALPS) was calculated to reflect glymphatic system function. The brain structure volume and DTI-ALPS index were compared between RRMS and HC. The mediating effect of the DTI-ALPS index between CP volume and brain structural changes was further investigated. The longitudinal changes of brain structure and DTI-ALPS index were compared in 20 RRMS patients.

RESULTS

Compared to HC, CP volume in RRMS was significantly increased (P < 0.001), and DTI-ALPS index was significantly decreased (P = 0.001). The volumes of white matter, thalamus, putamen and pallidum were significantly decreased in RRMS, and the volumes of lateral ventricle and third ventricle were increased. Mediation analysis showed DTI-ALPS index partially mediated the association between CP enlargement and deep gray matter (DGM) atrophy in RRMS, and between CP enlargement and ventricle enlargement. CP volume and DTI-ALPS index were also significantly correlated with Expanded Disability Status Scale (EDSS) (P = 0.006, P = 0.043). Notably, the variation of DTI_ALPS index during the follow-up period were significantly and negatively correlated with the variation of EDSS (P = 0.045).

CONCLUSION

Enlarged CP volume and decreased DTI_ALPS index may be closely related to DGM atrophy and ventricular enlargement in RRMS, and may be potential imaging markers of clinical disability.

Low-frequency MR elastography reveals altered deep gray matter viscoelasticity in multiple sclerosis

INTRODUCTION

Brain viscoelasticity as assessed by magnetic resonance elastography (MRE) has been discussed as a promising surrogate of microstructural alterations due to neurodegenerative processes. Existing studies indicate that multiple sclerosis (MS) is associated with a global reduction in brain stiffness. However, no study to date systematically investigated the MS-related characteristics of brain viscoelasticity separately in normal-appearing white matter (NAWM), deep gray matter (DGM) and T2-hyperintense white matter (WM) lesions.

METHODS

70 MS patients and 42 healthy volunteers underwent whole-cerebral MRE using a stimulated echo sequence (DENSE) with a low-frequency mechanical excitation at 20 Hertz. The magnitude |G∗| (Pa) and phase angle φ (rad) of the complex shear modulus G∗ were reconstructed by multifrequency dual elasto-visco (MDEV) inversion and related to structural imaging and clinical parameters.

RESULTS

We observed φ in the thalamus to be higher by 4.3 % in patients relative to healthy controls (1.11 ± 0.07 vs. 1.06 ± 0.07, p < 0.0001). Higher Expanded Disability Status Scale (EDSS) scores were negatively associated with φ in the basal ganglia (p = 0.01). We measured φ to be lower in MS lesions compared to surrounding NAWM (p = 0.001), which was most prominent for lesions in the temporal lobe (1.01 ± 0.22 vs. 1.06 ± 0.19, p = 0.003). Age was associated with lower values of |G∗| (p = 0.04) and φ (p = 0.004) in the thalamus of patients. No alteration in NAWM stiffness relative to WM in healthy controls was observed.

CONCLUSION

Low-frequency elastography in MS patients reveals age-independent alterations in the viscoelasticity of deep gray matter at early stages of disease.

Cognitive phenotypes in multiple sclerosis: mapping the spectrum of impairment

BACKGROUND

Available criteria for cognitive phenotypes in multiple sclerosis (MS) do not consider the severity of impairment.

OBJECTIVES

To identify cognitive phenotypes with varying degrees of impairment in MS patients and describe their demographic, clinical and MRI characteristics.

METHODS

Two hundred and forty-three MS patients and 158 healthy controls underwent neuropsychological tests to assess memory, attention, and executive function. For each domain, mild impairment was defined as performing 1.5 standard deviations below the normative mean on two tests, while the threshold for significant impairment was 2 standard deviations. Patients were classified into cognitive phenotypes based on severity of the impairment (mild/significant) and number of domains affected (one/more).

RESULTS

Five cognitive phenotypes emerged: Preserved cognition (PC; 56%), Mild Single-Domain Impairment (MSD; 15%), Mild Multi-Domain Impairment (MMD; 9%), Significant Single-Domain Impairment (SSD; 12%), Significant Multi-Domain Impairment (SMD; 8%). Compared with PC, MSD patients were older, had longer disease duration (DD) and higher T2-hyperintense lesion volume (LV; all p ≤ 0.02); MMD patients were older, had longer DD, higher disability, higher T2 LV and lower thalamic volume (all p ≤ 0.01); SSD patients had longer DD and lower gray matter cortical volume, thalamic, caudate, putamen and accumbens volumes (all p ≤ 0.04); and SMD patients were older, had longer DD, higher disability and more extensive structural damage in all brain regions explored (all p ≤ 0.03), except white matter and amygdala volumes.

CONCLUSIONS

We identified five cognitive phenotypes with graded levels of impairment. These phenotypes were characterized by distinct demographic, clinical and MRI features, indicating potential variations in the neural substrates of dysfunction throughout disease stages.

B cell depletion with anti-CD20 promotes neuroprotection in a BAFF-dependent manner in mice and humans

Anti-CD20 therapy to deplete B cells is highly efficacious in preventing new white matter lesions in patients with relapsing-remitting multiple sclerosis (RRMS), but its protective capacity against gray matter injury and axonal damage is unclear. In a passive experimental autoimmune encephalomyelitis (EAE) model whereby TH17 cells promote brain leptomeningeal immune cell aggregates, we found that anti-CD20 treatment effectively spared myelin content and prevented myeloid cell activation, oxidative damage, and mitochondrial stress in the subpial gray matter. Anti-CD20 treatment increased B cell survival factor (BAFF) in the serum, cerebrospinal fluid, and leptomeninges of mice with EAE. Although anti-CD20 prevented gray matter demyelination, axonal loss, and neuronal atrophy, co-treatment with anti-BAFF abrogated these benefits. Consistent with the murine studies, we observed that elevated BAFF concentrations after anti-CD20 treatment in patients with RRMS were associated with better clinical outcomes. Moreover, BAFF promoted survival of human neurons in vitro. Together, our data demonstrate that BAFF exerts beneficial functions in MS and EAE in the context of anti-CD20 treatment.

Clinical trials for progressive multiple sclerosis: progress, new lessons learned, and remaining challenges

Despite the success of disease-modifying treatments in relapsing multiple sclerosis, for many individuals living with multiple sclerosis, progressive disability continues to accrue. How to interrupt the complex pathological processes underlying progression remains a daunting and ongoing challenge. Since 2014, several immunomodulatory approaches that have modest but clinically meaningful effects have been approved for the management of progressive multiple sclerosis, primarily for people who have active inflammatory disease. The approval of these drugs required large phase 3 trials that were sufficiently powered to detect meaningful effects on disability. New classes of drug, such as Bruton tyrosine-kinase inhibitors, are coming to the end of their trial stages, several candidate neuroprotective compounds have been successful in phase 2 trials, and innovative approaches to remyelination are now also being explored in clinical trials. Work continues to define intermediate outcomes that can provide results in phase 2 trials more quickly than disability measures, and more efficient trial designs, such as multi-arm multi-stage and futility approaches, are increasingly being used. Collaborations between patient organisations, pharmaceutical companies, and academic researchers will be crucial to ensure that future trials maintain this momentum and generate results that are relevant for people living with progressive multiple sclerosis.

Associations Between Cognitive Impairment and Neuroimaging in Patients with Multiple Sclerosis

OBJECTIVE

Multiple sclerosis (MS) is a debilitating inflammatory and neurodegenerative disease which commonly involves cognitive dysfunction. Magnetic resonance imaging (MRI) studies have shown that patients with MS (pwMS) have diffuse patterns of brain atrophy, however, the relationship between the presentation of cognitive dysfunction and brain tissue loss remains understudied. Given the integral function of thalamus as a central nervous system relay center and its involvement in various brain circuits, thalamic atrophy may play a key role in the development and progression of cognitive dysfunction. The purpose of this study is to examine the relationship between cognitive impairment in pwMS and thalamic atrophy.

METHODS

A total of 121 pwMS who had neuropsychological testing and quantitative MRI within 1 year of each were retrospectively identified. Grouped LASSO linear regression with 10-fold cross validation was used to estimate each neuropsychological test score with thalamic volume as the focal predictor and all other demographic and MRI metrics as covariates.

RESULTS

Rates of impairment ranged from 19% to 44%. Results showed notable associations between thalamic volume and Symbol Digit Modalities Test (β = 0.11), Brief Visuospatial Memory Test, delayed (β = 0.12), California Verbal Learning Test, delayed and total (β = 0.24 and β = 0.15 respectively), and Trail Making Test Part A (β = -0.01), after adjusting for covariates.

CONCLUSIONS

These findings demonstrate an independent association between thalamic volumes and processing speed and memory performance, after accounting for demographic, clinical, and other MRI variables, among pwMS.

Early-stage volume losses in the corpus callosum and thalamus predict the progression of brain atrophy in patients with multiple sclerosis

BACKGROUND

A method that can be used in the early stage of multiple sclerosis (MS) to predict the progression of brain volume loss (BVL) has not been fully established.

METHODS

To develop a method of predicting progressive BVL in patients with MS (pwMS), eighty-two consecutive Japanese pwMS-with either relapsing-remitting MS (86%) or secondary progressive MS (14%)-and 41 healthy controls were included in this longitudinal retrospective analysis over an observational period of approximately 3.5 years. Using a hierarchical cluster analysis with multivariate imaging data obtained by FreeSurfer analysis, we classified the pwMS into clusters.

RESULTS

At baseline and follow-up, pwMS were cross-sectionally classified into three major clusters (Clusters 1, 2, and 3) in ascending order by disability and BVL. Among the patients included in Cluster 1 at baseline, approximately one-third of patients (12/52) transitioned into Cluster 2 at follow-up. The volumes of the corpus callosum, the thalamus, and the whole brain excluding the ventricles were significantly decreased in the transition group compared with the nontransition group and were found to be the most important predictors of transition.

CONCLUSION

Decreased volumes of the corpus callosum and thalamus in the relatively early stage of MS may predict the development of BVL.

MRI features and disability in multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

In this systematic review and meta-analysis, we aimed to investigate the correlation between disability in patients with Multiple sclerosis (MS) measured by the Expanded Disability Status Scale (EDSS) and brain Magnetic Resonance Imaging (MRI) features to provide reliable results on which characteristics in the MRI can predict disability and prognosis of the disease.

METHODS

A systematic literature search was performed using three databases including PubMed, Scopus, and Web of Science. The selected peer-reviewed studies must report a correlation between EDSS scores and MRI features. The correlation coefficients of included studies were converted to the Fisher's z scale, and the results were pooled.

RESULTS

Overall, 105 studies A total of 16,613 patients with MS entered our study. We found no significant correlation between total brain volume and EDSS assessment (95 % CI: -0.37 to 0.08; z-score: -0.15). We examined the potential correlation between the volume of T1 and T2 lesions and the level of disability. A positive significant correlation was found (95 % CI: 0.19 to 0.43; z-score: 0.31), (95 % CI: 0.17 to 0.33; z-score: 0.25). We observed a significant correlation between white matter volume and EDSS score in patients with MS (95 % CI: -0.37 to -0.03; z-score: -0.21). Moreover, there was a significant negative correlation between gray matter volume and disability (95 % CI: -0.025 to -0.07; z-score: -0.16).

CONCLUSION

In conclusion, this systematic review and meta-analysis revealed that disability in patients with MS is linked to extensive changes in different brain regions, encompassing gray and white matter, as well as T1 and T2 weighted MRI lesions.

Data-driven modelling of neurodegenerative disease progression: thinking outside the black box

Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.

Enlarged choroid plexus in multiple sclerosis is associated with increased lesion load and atrophy in white matter but not gray matter atrophy

BACKGROUND

Enlargement of the choroid plexus (CP) is reported to associate with inflammatory activity and contribute to brain atrophy in patients with multiple sclerosis (pwMS). However, a recent study in healthy volunteers (HVTs) has suggested that CP enlargement can be attributed to ventriculomegaly.

OBJECTIVES

To clarify the pathological significance of the enlargement of CP in multiple sclerosis (MS).

METHODS

A total of 102 pwMS (89 with relapsing-remitting MS and 13 with secondary progressive MS) and 41 HVTs were cross-sectionally evaluated using brain volumetry. The CP volume was compared between disease groups and investigated for the relationships with other brain regional volumes.

RESULTS

CP volume was significantly larger in pwMS than in HVTs in the univariate analysis, but not in multivariable analysis. Meanwhile, the CP and lateral ventricle (LV) volumes were significantly correlated. CP enlargement was significantly associated with increased lesion load and cerebral white matter (WM) atrophy, even after adjusting for LV volume. In contrast, multivariable analyses revealed that LV enlargement, but not CP enlargement, was associated with total gray matter (GM) atrophy.

CONCLUSION

CP enlargement was closely associated with LV enlargement. After adjusting for LV volume, CP enlargement in pwMS was associated with increased lesion load and WM atrophy but not GM atrophy.

Longitudinal fibre-specific white matter damage predicts cognitive decline in multiple sclerosis

During the course of multiple sclerosis, many patients experience cognitive deficits which are not simply driven by lesion number or location. By considering the full complexity of white matter structure at macro- and microstructural levels, our understanding of cognitive impairment in multiple sclerosis may increase substantially. Accordingly, this study aimed to investigate specific patterns of white matter degeneration, the evolution over time, the manifestation across different stages of the disease and their role in cognitive impairment using a novel fixel-based approach. Neuropsychological test scores and MRI scans including 30-direction diffusion-weighted images were collected from 327 multiple sclerosis patients (mean age = 48.34 years, 221 female) and 95 healthy controls (mean age = 45.70 years, 55 female). Of those, 233 patients and 61 healthy controls had similar follow-up assessments 5 years after. Patients scoring 1.5 or 2 standard deviations below healthy controls on at least two out of seven cognitive domains (from the Brief Repeatable Battery of Neuropsychological Tests, BRB-N) were classified as mildly cognitively impaired or cognitively impaired, respectively, or otherwise cognitively preserved. Fixel-based analysis of diffusion data was used to calculate fibre-specific measures (fibre density, reflecting microstructural diffuse axonal damage; fibre cross-section, reflecting macrostructural tract atrophy) within atlas-based white matter tracts at each visit. At baseline, all fixel-based measures were significantly worse in multiple sclerosis compared with healthy controls (P < 0.05). For both fibre density and fibre cross-section, a similar pattern was observed, with secondary progressive multiple sclerosis patients having the most severe damage, followed by primary progressive and relapsing-remitting multiple sclerosis. Similarly, damage was least severe in cognitively preserved (n = 177), more severe in mildly cognitively impaired (n = 63) and worst in cognitively impaired (n = 87; P < 0.05). Microstructural damage was most pronounced in the cingulum, while macrostructural alterations were most pronounced in the corticospinal tract, cingulum and superior longitudinal fasciculus. Over time, white matter alterations worsened most severely in progressive multiple sclerosis (P < 0.05), with white matter atrophy progression mainly seen in the corticospinal tract and microstructural axonal damage worsening in cingulum and superior longitudinal fasciculus. Cognitive decline at follow-up could be predicted by baseline fixel-based measures (R2 = 0.45, P < 0.001). Fixel-based approaches are sensitive to white matter degeneration patterns in multiple sclerosis and can have strong predictive value for cognitive impairment. Longitudinal deterioration was most marked in progressive multiple sclerosis, indicating that degeneration in white matter remains important to characterize further in this phenotype.

Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study

BACKGROUND

Observational studies have suggested an association between multiple sclerosis (MS) and cortical structure, but the results have been inconsistent.

OBJECTIVE

We used two-sample Mendelian randomization (MR) to assess the causal relationship between MS and cortical structure.

METHODS

MS data as the exposure trait, including 14,498 cases and 24,091 controls, were obtained from the International Multiple Sclerosis Genetics Consortium. Genome-wide association study (GWAS) data for cortical surface area (SAw/nw) and thickness (THw/nw) in 51,665 individuals of European ancestry were obtained from the ENIGMA Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Enrichment analysis was performed on MR analyses filtered by sensitivity analysis.

RESULTS

After IVW and sensitivity analysis filtering, only six surviving MR results provided suggestive evidence supporting a causal relationship between MS and cortical structure, including lingual SAw (p = .0342, beta (se) = 5.7127 (2.6969)), parahippocampal SAw (p = .0224, beta (se) = 1.5577 (0.6822)), rostral middle frontal SAw (p = .0154, beta (se) = - 9.0301 (3.7281)), cuneus THw (p = .0418, beta (se) =  - 0.0020 (0.0010)), lateral orbitofrontal THw (p = .0281, beta (se) = 0.0025 (0.0010)), and lateral orbitofrontal THnw (p = .0417, beta (se) = 0.0029 (0.0014)). Enrichment analysis suggested that leukocyte cell-related pathways, JAK-STAT signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and prolactin signaling pathway may be involved in the effect of MS on cortical morphology.

CONCLUSION

Our results provide evidence supporting a causal relationship between MS and cortical structure. Enrichment analysis suggests that the pathways mediating brain morphology abnormalities in MS patients are mainly related to immune and inflammation-driven pathways.

Multiple sclerosis clinical forms classification with graph convolutional networks based on brain morphological connectivity

Multiple Sclerosis (MS) is an autoimmune disease that combines chronic inflammatory and neurodegenerative processes underlying different clinical forms of evolution, such as relapsing-remitting, secondary progressive, or primary progressive MS. This identification is usually performed by clinical evaluation at the diagnosis or during the course of the disease for the secondary progressive phase. In parallel, magnetic resonance imaging (MRI) analysis is a mandatory diagnostic complement. Identifying the clinical form from MR images is therefore a helpful and challenging task. Here, we propose a new approach for the automatic classification of MS forms based on conventional MRI (i.e., T1-weighted images) that are commonly used in clinical context. For this purpose, we investigated the morphological connectome features using graph based convolutional neural network. Our results obtained from the longitudinal study of 91 MS patients highlight the performance (F1-score) of this approach that is better than state-of-the-art as 3D convolutional neural networks. These results open the way for clinical applications such as disability correlation only using T1-weighted images.

Prognostic value of single-subject grey matter networks in early multiple sclerosis

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.

Adult inflammatory leukoencephalopathies

Inflammatory white matter disorders may commonly mimic genetic leukoencephalopathies. These include atypical presentations of common conditions, such as multiple sclerosis, together with rare inflammatory disorders. A structured approach to such cases is essential, together with judicious use of the many available diagnostic biomarkers. The potential for such conditions to respond to immunotherapy emphasizes the importance of an accurate and prompt diagnosis in improving patient outcomes.

Pediatric inflammatory leukoencephalopathies

Acquired demyelinating syndromes (ADS) represent acute neurologic illnesses characterized by deficits persisting for at least 24hours and involving the optic nerve, brain, or spinal cord, associated with regional areas of increased signal on T2-weighted images. In children, ADS may occur as a monophasic illness or as a relapsing condition, such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Almost all young people with MS have a relapsing-remitting course with clinical relapses. Important strides have been made in delineating MS from other ADS subtypes. Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) and aquaporin 4-antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD) were once considered variants of MS; however, studies in the last decade have established that these are in fact distinct entities. Although there are clinical phenotypic overlaps between MOGAD, AQP4-NMOSD, and MS, cumulative biologic, clinical, and pathologic evidence allows discrimination between these conditions. There has been a rapid increase in the number of available disease-modifying therapies for MS and novel treatment strategies are starting to appear for both MOGAD and AQP4-NMOSD. Importantly, there are a number of both inflammatory and noninflammatory mimics of ADS in children with implications of management for these patients in terms of treatment.

Novel data-driven subtypes and stages of brain atrophy in the ALS-FTD spectrum

BACKGROUND

TDP-43 proteinopathies represent a spectrum of neurological disorders, anchored clinically on either end by amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The ALS-FTD spectrum exhibits a diverse range of clinical presentations with overlapping phenotypes, highlighting its heterogeneity. This study was aimed to use disease progression modeling to identify novel data-driven spatial and temporal subtypes of brain atrophy and its progression in the ALS-FTD spectrum.

METHODS

We used a data-driven procedure to identify 13 anatomic clusters of brain volume for 57 behavioral variant FTD (bvFTD; with either autopsy-confirmed TDP-43 or TDP-43 proteinopathy-associated genetic variants), 103 ALS, and 47 ALS-FTD patients with likely TDP-43. A Subtype and Stage Inference (SuStaIn) model was trained to identify subtypes of individuals along the ALS-FTD spectrum with distinct brain atrophy patterns, and we related subtypes and stages to clinical, genetic, and neuropathological features of disease.

RESULTS

SuStaIn identified three novel subtypes: two disease subtypes with predominant brain atrophy in either prefrontal/somatomotor regions or limbic-related regions, and a normal-appearing group without obvious brain atrophy. The limbic-predominant subtype tended to present with more impaired cognition, higher frequencies of pathogenic variants in TBK1 and TARDBP genes, and a higher proportion of TDP-43 types B, E and C. In contrast, the prefrontal/somatomotor-predominant subtype had higher frequencies of pathogenic variants in C9orf72 and GRN genes and higher proportion of TDP-43 type A. The normal-appearing brain group showed higher frequency of ALS relative to ALS-FTD and bvFTD patients, higher cognitive capacity, higher proportion of lower motor neuron onset, milder motor symptoms, and lower frequencies of genetic pathogenic variants. The overall SuStaIn stages also correlated with evidence for clinical progression including longer disease duration, higher King's stage, and cognitive decline. Additionally, SuStaIn stages differed across clinical phenotypes, genotypes and types of TDP-43 pathology.

CONCLUSIONS

Our findings suggest distinct neurodegenerative subtypes of disease along the ALS-FTD spectrum that can be identified in vivo, each with distinct brain atrophy, clinical, genetic and pathological patterns.

The sequence of regional structural disconnectivity due to multiple sclerosis lesions

Prediction of disease progression is challenging in multiple sclerosis as the sequence of lesion development and retention of inflammation within a subset of chronic lesions is heterogeneous among patients. We investigated the sequence of lesion-related regional structural disconnectivity across the spectrum of disability and cognitive impairment in multiple sclerosis. In a full cohort of 482 multiple sclerosis patients (age: 41.83 ± 11.63 years, 71.57% females), the Expanded Disability Status Scale was used to classify patients into (i) no or mild (Expanded Disability Status Scale <3) versus (ii) moderate or severe disability groups (Expanded Disability Status Scale ≥3). In 363 out of 482 patients, quantitative susceptibility mapping was used to identify paramagnetic rim lesions, which are maintained by a rim of iron-laden innate immune cells. In 171 out of 482 patients, Brief International Cognitive Assessment was used to identify subjects as being cognitively preserved or impaired. Network Modification Tool was used to estimate the regional structural disconnectivity due to multiple sclerosis lesions. Discriminative event-based modelling was applied to investigate the sequence of regional structural disconnectivity due to (i) all representative T2 fluid-attenuated inversion recovery lesions, (ii) paramagnetic rim lesions versus non-paramagnetic rim lesions separately across disability groups ('no to mild disability' to 'moderate to severe disability'), (iii) all representative T2 fluid-attenuated inversion recovery lesions and (iv) paramagnetic rim lesions versus non-paramagnetic rim lesions separately across cognitive status ('cognitively preserved' to 'cognitively impaired'). In the full cohort, structural disconnection in the ventral attention and subcortical networks, particularly in the supramarginal and putamen regions, was an early biomarker of moderate or severe disability. The earliest biomarkers of disability progression were structural disconnections due to paramagnetic rim lesions in the motor-related regions. Subcortical structural disconnection, particularly in the ventral diencephalon and thalamus regions, was an early biomarker of cognitive impairment. Our data-driven model revealed that the structural disconnection in the subcortical regions, particularly in the thalamus, is an early biomarker for both disability and cognitive impairment in multiple sclerosis. Paramagnetic rim lesions-related structural disconnection in the motor cortex may identify the patients at risk for moderate or severe disability in multiple sclerosis. Such information might be used to identify people with multiple sclerosis who have an increased risk of disability progression or cognitive decline in order to provide personalized treatment plans.

Lifespan neurodegeneration of the human brain in multiple sclerosis

Atrophy related to multiple sclerosis (MS) has been found at the early stages of the disease. However, the archetype dynamic trajectories of the neurodegenerative process, even prior to clinical diagnosis, remain unknown. We modeled the volumetric trajectories of brain structures across the entire lifespan using 40,944 subjects (38,295 healthy controls and 2649 MS patients). Then, we estimated the chronological progression of MS by assessing the divergence of lifespan trajectories between normal brain charts and MS brain charts. Chronologically, the first affected structure was the thalamus, then the putamen and the pallidum (around 4 years later), followed by the ventral diencephalon (around 7 years after thalamus) and finally the brainstem (around 9 years after thalamus). To a lesser extent, the anterior cingulate gyrus, insular cortex, occipital pole, caudate and hippocampus were impacted. Finally, the precuneus and accumbens nuclei exhibited a limited atrophy pattern. Subcortical atrophy was more pronounced than cortical atrophy. The thalamus was the most impacted structure with a very early divergence in life. Our experiments showed that lifespan models of most impacted structures could be an important tool for future preclinical/prodromal prognosis and monitoring of MS.

Benefits of a mosaic approach for assessing cortical atrophy in individual multiple sclerosis patients

OBJECTIVE

Cortical gray matter (GM) atrophy plays a central role in multiple sclerosis (MS) pathology. However, it is not commonly assessed in clinical routine partly because a number of methodological problems hamper the development of a robust biomarker to quantify GM atrophy. In previous work, we have demonstrated the clinical utility of the "mosaic approach" (MAP) to assess individual GM atrophy in the motor neuron disease spectrum and frontotemporal dementia. In this study, we investigated the clinical utility of MAP in MS, comparing this novel biomarker to existing methods for computing GM atrophy in single patients. We contrasted the strategies based on correlations with established biomarkers reflecting MS disease burden.

METHODS

We analyzed T1-weighted MPRAGE magnetic resonance imaging data from 465 relapsing-remitting MS patients and 89 healthy controls. We inspected how variations of existing strategies to estimate individual GM atrophy ("standard approaches") as well as variations of MAP (i.e., different parcellation schemes) impact downstream analysis results, both on a group and an individual level. We interpreted individual cortical disease burden as single metric reflecting the fraction of significantly atrophic data points with respect to the control group. In addition, we evaluated the correlations to lesion volume (LV) and Expanded Disability Status Scale (EDSS).

RESULTS

We found that the MAP method yielded highest correlations with both LV and EDSS as compared to all other strategies. Although the parcellation resolution played a minor role in terms of absolute correlations with clinical variables, higher resolutions provided more clearly defined statistical brain maps which may facilitate clinical interpretability.

CONCLUSION

This study provides evidence that MAP yields high potential for a clinically relevant biomarker in MS, outperforming existing methods to compute cortical disease burden in single patients. Of note, MAP outputs brain maps illustrating individual cortical disease burden which can be directly interpreted in daily clinical routine.

Optical coherence tomography (OCT) measurements and disability in multiple sclerosis (MS): A systematic review and meta-analysis

BACKGROUND

Studies have demonstrated that people with multiple sclerosis (pwMS) experience visual impairments and neurodegenerative retinal processes. The disability progression in pwMS may be associated with retinal changes assessed with optical coherence tomography (OCT). This meta-analysis aims at synthesizing the correlations between OCT measurements of disability in pwMS.

METHODS

We systematically searched four databases (PubMed/MEDLINE, Embase, Scopus, and Web of Science) from inception to November 2022, then conducted a meta-analysis using a random effects model to determine the pooled correlation coefficient(r) between OCT measurements and disability scales by R version 4.2.3 with the meta version 6.2-1 package.

RESULTS

From 3129 studies, 100 studies were included. Among 9051 pwMS, the female-to-male ratio was 3.15:1, with a mean age of 39.57 ± 6.07 years. The mean disease duration and Expanded Disability Status Scale (EDSS) were 8.5 ± 3.7 and 2.7 ± 1.1, respectively. Among the pooled subgroup analyses, macular ganglion cell inner plexiform layer (mGCIPL) in patients with relapsing-remitting (pwRRMS) and peripapillary retinal nerve fiber layer (pRNFL) in patients with progressive MS (pwPMS) had strong correlations with EDSS, r = -0.33 (95% CI: -0.45 to -0.20, I2 = 45%, z-score = -4.86, p < 0.001) and r = -0.20 (95% CI:-0.58 to 0.26, I2 = 76%, z-score = -0.85, p = 0.395), respectively. According to subgroup analysis on pwMS without optic neuritis (ON) history, the largest correlation was seen between EDSS and macular ganglion cell complex (mGCC): r = -0.39 (95% CI: -0.70 to 0.04, I2 = 79%, z-score = -1.79, p = 0.073).

CONCLUSION

OCT measurements are correlated with disability in pwMS, and they can complement the comprehensive neurological visit as an additional paraclinical test.

Sex differences in the neuronal transcriptome and synaptic mitochondrial function in the cerebral cortex of a multiple sclerosis model

Introduction

Multiple sclerosis (MS) affects the cerebral cortex, inducing cortical atrophy and neuronal and synaptic pathology. Despite the fact that women are more susceptible to getting MS, men with MS have worse disability progression. Here, sex differences in neurodegenerative mechanisms are determined in the cerebral cortex using the MS model, chronic experimental autoimmune encephalomyelitis (EAE).

Methods

Neurons from cerebral cortex tissues of chronic EAE, as well as age-matched healthy control, male and female mice underwent RNA sequencing and gene expression analyses using RiboTag technology. The morphology of mitochondria in neurons of cerebral cortex was assessed using Thy1-CFP-MitoS mice. Oxygen consumption rates were determined using mitochondrial respirometry assays from intact as well as permeabilized synaptosomes.

Results

RNA sequencing of neurons in cerebral cortex during chronic EAE in C57BL/6 mice showed robust differential gene expression in male EAE compared to male healthy controls. In contrast, there were few differences in female EAE compared to female healthy controls. The most enriched differential gene expression pathways in male mice during EAE were mitochondrial dysfunction and oxidative phosphorylation. Mitochondrial morphology in neurons showed significant abnormalities in the cerebral cortex of EAE males, but not EAE females. Regarding function, synaptosomes isolated from cerebral cortex of male, but not female, EAE mice demonstrated significantly decreased oxygen consumption rates during respirometry assays.

Discussion

Cortical neuronal transcriptomics, mitochondrial morphology, and functional respirometry assays in synaptosomes revealed worse neurodegeneration in male EAE mice. This is consistent with worse neurodegeneration in MS men and reveals a model and a target to develop treatments to prevent cortical neurodegeneration and mitigate disability progression in MS men.

Brain MRI Volumetric Assessment of Patients With Multiple Sclerosis: The Volume of Basal Ganglia, Thalamus, and Posterior Fossa

Introduction

Multiple sclerosis (MS) is an inflammatory demyelinating and neurodegenerative disorder of the central nervous system, which is associated with brain atrophy and volume changes in some brain structures. This study aimed to compare the volume of the basal ganglia, thalamus, cerebellum, and brainstem in patients with relapsing-remitting MS with that of the control group using magnetic resonance imaging (MRI).

Methods

In this cross-sectional study, MRI brain scans were obtained from 25 patients with relapsing-remitting MS and 25 healthy control subjects. Volumetric analyses were performed using Brain Suite software.

Results

The mean age of the MS and the control groups was 33.96±8.75 and 40.40±8.72, respectively. No statistically significant difference was found in gender (P=0.747). The bilateral putamen and caudate nuclei volumes were significantly higher in the case group than in the control group (P<0.001). Moreover, lower the volume of the brainstem, cerebellum, bilateral thalamus, and globus pallidus were identified in the MS patients compared to the control group (P<0.001). There was an inverse correlation between the disease and treatment duration with the thalamus and cerebellum volume in MS patients (P=0.001). Treatment duration also had an inverse correlation with brainstem volume (P=0.047).

Conclusion

The volume of some structures of the brain, including globus pallidus, thalamus, cerebellum, and brainstem is lower in MS and can be one of the markers of disease progression and disability among MS patients.

Highlights

Due to the degenerative process in multiple sclerosis, some cerebral structures may face volume change.The present study demonstrated that the volume of globus pallidus, thalamus, cerebellum, and brainstem is lower in MS patients compared to the controls.

Plain Language Summary

Multiple sclerosis (MS) is defined as an inflammatory disease involving the white matter of the brain, but experience has shown that many non-white matter structures also change in MS. In this study, we aimed to examine some parts of the brain, such as the thalamus, basal ganglia, brainstem, and cerebellum, for volume changes. The results showed that all these structures can have a smaller volume in MS patients than in healthy people. Especially in the case of the thalamus and cerebellum, this difference increases with increasing the disease duration. Changes in the size of these structures can be the result of degeneration of the neurons in these areas. These changes can cause significant disability in patients; however, there may not be significant changes in the number of plaques in patients. Attention to these changes can be essential in interpreting patients' clinical changes, including motor and cognitive disabilities.

Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR

BACKGROUND AND OBJECTIVES

Disability and cognitive impairment are known to be related to brain atrophy in multiple sclerosis (MS), but 3D-T1 imaging required for brain volumetrics is often unavailable in clinical protocols, unlike 3D-FLAIR. Here our aim was to investigate whether brain volumes derived from 3D-FLAIR images result in similar associations with disability and cognition in MS as do those derived from 3D-T1 images.

METHODS

3T-MRI scans of 329 MS patients and 76 healthy controls were included in this cross-sectional study. Brain volumes were derived using FreeSurfer on 3D-T1 and compared with brain volumes derived with SynthSeg and SAMSEG on 3D-FLAIR. Relative agreement was evaluated by calculating the intraclass correlation coefficient (ICC) of the 3D-T1 and 3D-FLAIR volumes. Consistency of relations with disability and average cognition was assessed using linear regression, while correcting for age and sex. The findings were corroborated in an independent validation cohort of 125 MS patients.

RESULTS

The ICC between volume measured with FreeSurfer and those measured on 3D-FLAIR for brain, ventricle, cortex, total deep gray matter and thalamus was above 0.74 for SAMSEG and above 0.91 for SynthSeg. Worse disability and lower average cognition were similarly associated with brain (adj. R2 = 0.24-0.27, p < 0.01; adj. R2 = 0.26-0.29, p < 0.001) ventricle (adj. R2 = 0.27-0.28, p < 0.001; adj. R2 = 0.19-0.20, p < 0.001) and deep gray matter volumes (adj. R2 = 0.24-0.28, p < 0.001; adj. R2 = 0.27-0.28, p < 0.001) determined with all methods, except for cortical volumes derived from 3D-FLAIR.

DISCUSSION

In this cross-sectional study, brain volumes derived from 3D-FLAIR and 3D-T1 show similar relationships to disability and cognitive dysfunction in MS, highlighting the potential of these techniques in clinical datasets.

Multimodal Investigation of Deep Gray Matter Nucleus in Patients with Multiple Sclerosis and Their Clinical Correlations: A Multivariate Pattern Analysis Study

Deep gray matter (DGM) nucleus are involved in patients with multiple sclerosis (MS) and are strongly associated with clinical symptoms. We used machine learning approach to further explore microstructural alterations in DGM of MS patients. One hundred and fifteen MS patients and seventy-one healthy controls (HC) underwent brain MRI. The fractional anisotropy (FA), mean diffusivity (MD), quantitative susceptibility value (QSV) and volumes of the caudate nucleus (CN), putamen (PT), globus pallidus (GP), and thalamus (TH) were measured. Multivariate pattern analysis, based on a machine-learning algorithm, was applied to investigate the most damaged regions. Partial correlation analysis was used to investigate the correlation between MRI quantitative metrics and clinical neurological scores. The area under the curve of FA-based classification model was 0.83, while they were 0.93 for MD and 0.81 for QSV. The Montreal cognitive assessment scores were correlated with the volume of the DGM and the expanded disability status scale scores were correlated with the MD of the GP and PT. The study results indicated that MS patients had involvement of DGM with the CN being the most affected. The atrophy of DGM in MS patients mainly affected cognitive function and the microstructural damage of DGM was mainly correlated with clinical disability.

Reliability of brain atrophy measurements in multiple sclerosis using MRI: an assessment of six freely available software packages for cross-sectional analyses

PURPOSE

Volume measurement using MRI is important to assess brain atrophy in multiple sclerosis (MS). However, differences between scanners, acquisition protocols, and analysis software introduce unwanted variability of volumes. To quantify theses effects, we compared within-scanner repeatability and between-scanner reproducibility of three different MR scanners for six brain segmentation methods.

METHODS

Twenty-one people with MS underwent scanning and rescanning on three 3 T MR scanners (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) to obtain 3D T1-weighted images. FreeSurfer, FSL, SAMSEG, FastSurfer, CAT-12, and SynthSeg were used to quantify brain, white matter and (deep) gray matter volumes both from lesion-filled and non-lesion-filled 3D T1-weighted images. We used intra-class correlation coefficient (ICC) to quantify agreement; repeated-measures ANOVA to analyze systematic differences; and variance component analysis to quantify the standard error of measurement (SEM) and smallest detectable change (SDC).

RESULTS

For all six software, both between-scanner agreement (ICCs ranging 0.4-1) and within-scanner agreement (ICC range: 0.6-1) were typically good, and good to excellent (ICC > 0.7) for large structures. No clear differences were found between filled and non-filled images. However, gray and white matter volumes did differ systematically between scanners for all software (p < 0.05). Variance component analysis yielded within-scanner SDC ranging from 1.02% (SAMSEG, whole-brain) to 14.55% (FreeSurfer, CSF); and between-scanner SDC ranging from 4.83% (SynthSeg, thalamus) to 29.25% (CAT12, thalamus).

CONCLUSION

Volume measurements of brain, GM and WM showed high repeatability, and high reproducibility despite substantial differences between scanners. Smallest detectable change was high, especially between different scanners, which hampers the clinical implementation of atrophy measurements.

Multiparametric magnetic resonance imaging for detection of pathological changes in the central nervous system of a mouse model of multiple sclerosis in vivo

Multiple sclerosis (MS) is an autoimmune disease involving demyelination and axonal damage in the central nervous system (CNS). In this study, we investigated pathological changes in the lumbar spinal cord of C57BL/6 mice induced with progressive experimental autoimmune encephalomyelitis (EAE) disease using 9.4-T magnetic resonance imaging (MRI). Multiparametric MRI measurements including MR spectroscopy, diffusion tensor imaging (DTI) and volumetric analyses were applied to detect metabolic changes in the CNS of EAE mice. Compared with healthy mice, EAE mice showed a significant reduction in N-acetyl aspartate and increases in choline, glycine, taurine and lactate. DTI revealed a significant reduction in fractional anisotropy and axial diffusivity and an increase in radial diffusivity in the lumbar spinal cord white matter (WM), while in the grey matter (GM), fractional anisotropy increased. High-resolution structural imaging also revealed lumbar spinal cord WM hypertrophy and GM atrophy. Importantly, these MRI changes were strongly correlated with EAE disease scoring and pathological changes in the lumbar (L2-L6), particularly WM demyelination lesions and aggregation of immune cells (microglia/macrophages and astrocytes) in this region. This study identified changes in MRI biomarker signatures that can be useful for evaluating the efficacy of novel drugs using EAE models in vivo.

Caudate volume and symptoms of apathy in older adults with multiple sclerosis

BACKGROUND

Apathy is common in multiple sclerosis (MS) and neurological disease, but its presence and underlying brain mechanisms in older adults with MS (OAMS) have not been evaluated.

OBJECTIVE

Examine apathy and its association with caudate nuclei volume in OAMS and controls. We hypothesized that compared to controls, OAMS would demonstrate: a) greater apathy; b) stronger associations between apathy and caudate nuclei volumes.

METHODS

OAMS (n = 67, mean age = 64.55 ± 3.89) and controls (n = 74, mean age = 69.04 ± 6.32) underwent brain MRI, cognitive assessment, psychological, and motoric testing. Apathy was assessed through the apathy subscale of the 30-item Geriatric Depression Scale.

RESULTS

OAMS reported greater apathy compared to controls (β = 0.281, p = 0.004). Adjusted moderation analyses revealed a significantly stronger association between caudate volume and apathy (left: B = -1.156, p = 0.039, right: B = -1.163, p = 0.040) among OAMS compared to controls. Conditional effects revealed that in adjusted models, lower volume of both the left (b = -0.882, p = 0.037) and right (b = -0.891, p = 0.038) caudate nuclei was significantly associated with greater apathy only among OAMS.

CONCLUSION

Caudate nuclei, which are susceptible to adverse MS effects and implicated in mediating cognitive and motor function, may influence the presence and severity of apathy in OAMS.