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Background: Cognitive training elicits mild-to-moderate improvements in cognitive functioning in people with multiple sclerosis (PwMS), although response heterogeneity limits overall effectiveness. Objective: To identify patient characteristics associated with response and non-response to cognitive training. Methods: Eighty-two PwMS were randomized into a 7-week attention training ( n = 58, age = 48.4 ± 10.2 years) or a waiting-list control group ( n = 24, age = 48.5 ± 9.4 years). Structural and functional magnetic resonance imaging (MRI) was obtained at baseline and post-intervention. Twenty-one healthy controls (HCs, age = 50.27 ± 10.15 years) were included at baseline. Responders were defined with a reliable change index of 1.64 on at least 2/6 cognitive domains. General linear models and logistic regression were applied. Results: Responders ( n = 36) and non-responders ( n = 22) did not differ on demographics, clinical variables and baseline cognition and structural MRI. However, non-responders exhibited a higher baseline functional connectivity (FC) between the default-mode network (DMN) and the ventral attention network (VAN), compared with responders ( p = 0.018) and HCs ( p = 0.001). Conversely, responders exhibited no significant baseline differences in FC compared with HCs. Response to cognitive training was predicted by lower DMN-VAN FC ( p = 0.004) and DMN-frontoparietal FC ( p = 0.029) (Nagelkerke R2 = 0.25). Conclusion: An intact pre-intervention FC is associated with cognitive training responsivity in pwMS, suggesting a window of opportunity for successful cognitive interventions.

Background: Neuroaxonal degeneration is one of the hallmarks of clinical deterioration in progressive multiple sclerosis (PMS). Objective: To elucidate the association between neuroaxonal degeneration and both local cortical and connected white matter (WM) tract pathology in PMS. Methods: Post-mortem in situ 3T magnetic resonance imaging (MRI) and cortical tissue blocks were collected from 16 PMS donors and 10 controls. Cortical neuroaxonal, myelin, and microglia densities were quantified histopathologically. From diffusion tensor MRI, fractional anisotropy, axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were quantified in normal-appearing white matter (NAWM) and white matter lesions (WML) of WM tracts connected to dissected cortical regions. Between-group differences and within-group associations were investigated through linear mixed models. Results: The PMS donors displayed significant axonal loss in both demyelinated and normal-appearing (NA) cortices ( p Conclusion: Reduced integrity of connected WM tracts and cortical demyelination both contribute to cortical axonal loss in PMS.

The severity and effects of damage to short- and long-range structural connections in multiple sclerosis are unknown. Meijer et al. report that long-range connections are more severely damaged than short-range connections. Damage to long-range connections is more strongly associated with reduced structural network efficiency, abnormal functional connectivity, and impaired cognition., An efficient network such as the human brain features a combination of global integration of information, driven by long-range connections, and local processing involving short-range connections. Whether these connections are equally damaged in multiple sclerosis is unknown, as is their relevance for cognitive impairment and brain function. Therefore, we cross-sectionally investigated the association between damage to short- and long-range connections with structural network efficiency, the functional connectome and cognition. From the Amsterdam multiple sclerosis cohort, 133 patients (age = 54.2 ± 9.6) with long-standing multiple sclerosis and 48 healthy controls (age = 50.8 ± 7.0) with neuropsychological testing and MRI were included. Structural connectivity was estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of brain regions. Structural connections were divided into short- (length < quartile 1) and long-range (length > quartile 3) connections, based on the mean distribution of tract lengths in healthy controls. To determine the severity of damage within these connections, (i) fractional anisotropy as a measure for integrity; (ii) total number of fibres; and (iii) percentage of tract affected by lesions were computed for each connecting tract and averaged for short- and long-range connections separately. To investigate the impact of damage in these connections for structural network efficiency, global efficiency was computed. Additionally, resting-state functional connectivity was computed between each pair of brain regions, after artefact removal with FMRIB’s ICA-based X-noiseifier. The functional connectivity similarity index was computed by correlating individual functional connectivity matrices with an average healthy control connectivity matrix. Our results showed that the structural network had a reduced efficiency and integrity in multiple sclerosis relative to healthy controls (both P < 0.05). The long-range connections showed the largest reduction in fractional anisotropy (z = −1.03, P < 0.001) and total number of fibres (z = −0.44, P < 0.01), whereas in the short-range connections only fractional anisotropy was affected (z = −0.34, P = 0.03). Long-range connections also demonstrated a higher percentage of tract affected by lesions than short-range connections, independent of tract length (P < 0.001). Damage to long-range connections was more strongly related to structural network efficiency and cognition (fractional anisotropy: r = 0.329 and r = 0.447. number of fibres r = 0.321 and r = 0.278. and percentage of lesions: r = −0.219; r = −0.426, respectively) than damage to short-range connections. Only damage to long-distance connections correlated with a more abnormal functional network (fractional anisotropy: r = 0.226). Our findings indicate that long-range connections are more severely affected by multiple sclerosis-specific damage than short-range connections. Moreover compared to short-range connections, damage to long-range connections better explains network efficiency and cognition.

Background: Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS). Objective: To investigate whether single-subject gray matter network properties are related to impaired cognition in MS. Methods: We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level. Results: Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p Conclusion: Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS.

Background: Cortical lesions are highly inconspicuous on magnetic resonance imaging (MRI). Double inversion recovery (DIR) has a higher sensitivity than conventional clinical sequences (i.e. T1, T2, FLAIR) but is difficult to acquire, leading to overseen cortical lesions in clinical care and clinical trials. Objective: To evaluate the usability of artificially generated DIR (aDIR) images for cortical lesion detection compared to conventionally acquired DIR (cDIR). Methods: The dataset consisted of 3D-T1 and 2D-proton density (PD) T2 images of 73 patients (49RR, 20SP, 4PP) at 1.5 T. Using a 4:1 train:test-ratio, a fully convolutional neural network was trained to predict 3D-aDIR from 3D-T1 and 2D-PD/T2 images. Randomized blind scoring of the test set was used to determine detection reliability, precision and recall. Results: A total of 626 vs 696 cortical lesions were detected on 15 aDIR vs cDIR images (intraclass correlation coefficient (ICC) = 0.92). Compared to cDIR, precision and recall were 0.84 ± 0.06 and 0.76 ± 0.09, respectively. The frontal and temporal lobes showed the largest differences in discernibility. Conclusion: Cortical lesions can be detected with good reliability on artificial DIR. The technique has potential to broaden the availability of DIR in clinical care and provides the opportunity of ex post facto implementation of cortical lesions imaging in existing clinical trial data.

Cortical lesions are important in multiple sclerosis, but notoriously hard to detect with MRI. Bouman et al. compare all hitherto suggested sequences to histopathology, and report that double inversion recovery and phase-sensitive inversion recovery outperform conventional clinical sequences, but complement each other., Cortical demyelinating lesions are clinically important in multiple sclerosis, but notoriously difficult to visualize with MRI. At clinical field strengths, double inversion recovery MRI is most sensitive, but still only detects 18% of all histopathologically validated cortical lesions. More recently, phase-sensitive inversion recovery was suggested to have a higher sensitivity than double inversion recovery, although this claim was not histopathologically validated. Therefore, this retrospective study aimed to provide clarity on this matter by identifying which MRI sequence best detects histopathologically-validated cortical lesions at clinical field strength, by comparing sensitivity and specificity of the thus far most commonly used MRI sequences, which are T2, fluid-attenuated inversion recovery (FLAIR), double inversion recovery and phase-sensitive inversion recovery. Post-mortem MRI was performed on non-fixed coronal hemispheric brain slices of 23 patients with progressive multiple sclerosis directly after autopsy, at 3 T, using T1 and proton-density/T2-weighted, as well as FLAIR, double inversion recovery and phase-sensitive inversion recovery sequences. A total of 93 cortical tissue blocks were sampled from these slices. Blinded to histopathology, all MRI sequences were consensus scored for cortical lesions. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesion types I–IV (mixed grey matter/white matter, intracortical, subpial and cortex-spanning lesions, respectively). MRI scores were compared to histopathological scores to calculate sensitivity and specificity per sequence. Next, a retrospective (unblinded) scoring was performed to explore maximum scoring potential per sequence. Histopathologically, 224 cortical lesions were detected, of which the majority were subpial. In a mixed model, sensitivity of T1, proton-density/T2, FLAIR, double inversion recovery and phase-sensitive inversion recovery was 8.9%, 5.4%, 5.4%, 22.8% and 23.7%, respectively (20, 12, 12, 51 and 53 cortical lesions). Specificity of the prospective scoring was 80.0%, 75.0%, 80.0%, 91.1% and 88.3%. Sensitivity and specificity did not significantly differ between double inversion recovery and phase-sensitive inversion recovery, while phase-sensitive inversion recovery identified more lesions than double inversion recovery upon retrospective analysis (126 versus 95; P

The ratio between T1-weighted (T1w) and T2-weighted (T2w) sequences (T1w/T2w-ratio) has been proposed to enhance myelin sensitivity and specificity.1 However, studies assessing its histopathological substrates in multiple sclerosis (MS) found contradictory results. One study reported lower T1w/T2w-ratio in demyelinated versus normal-appearing cortex, but neurite density was not investigated.2 In another study, T1w/T2w-ratio correlated with dendrite but not myelin density; however, only normal-appearing cortex was evaluated.3 Both myelin and neurite density could influence T1w/T2w-ratio.4 Since T1w/T2w-ratio is derived from commonly acquired sequences and seems sensitive to cortical damage, its pathological validation is strongly needed before its wider application. In this post-mortem MRI/histopathology study, we evaluated normal-appearing and demyelinated cortices from non-neurological controls (nNC) and patients with MS (PwMS) to define whether myelin and/or neurite density were associated with T1w/T2w-ratio. ### Donors PwMS were collected by the Netherlands Brain Bank (http://www.brainbank.nl/), while nNC by the Normal Aging Brain Collection Amsterdam (http://nabca.eu/). ### MRI The following sequences were acquired during a 3T whole-brain in situ MRI scan: sagittal three-dimensional FLAIR; sagittal three-dimensional T1w fast spoiled gradient echo; axial T2w spin echo. See online supplemental methods for scan geometry. ### Supplementary data [jnnp-2020-324391supp001.pdf] White matter (WM) lesion volume (LV) was automatically quantified on FLAIR.5 T1w/T2w-ratio was obtained with an in-house pipeline adapted from Ganzetti et al 1 (online supplemental figure). Native three-dimensional T1w and T2w sequences underwent bias field correction (SPM12). Unbiased images were calibrated adjusting the intensity histograms using the lowest and highest intensity peaks derived from eye and temporal muscle masks on T1w and T2w images. T2w sequences were coregistered on T1w images and the T1w/T2w-ratio was calculated. From three-dimensional T1w images, grey matter (GM) and WM maps were created (SPM12). GM maps were thresholded at 0.5 to limit partial voluming and masked to include the cortex and remove cerebellum and basal ganglia. ### Histopathology After …

To understand the heterogeneity of functional connectivity results reported in the literature, we analyzed the separate effects of grey and white matter damage on functional connectivity and networks in multiple sclerosis. For this, we employed a biophysical thalamo‐cortical model consisting of interconnected cortical and thalamic neuronal populations, informed and amended by empirical diffusion MRI tractography data, to simulate functional data that mimic neurophysiological signals. Grey matter degeneration was simulated by decreasing within population connections and white matter degeneration by lowering between population connections, based on lesion predilection sites in multiple sclerosis. For all simulations, functional connectivity and functional network organization are quantified by phase synchronization and network integration, respectively. Modeling results showed that both cortical and thalamic grey matter damage induced a global increase in functional connectivity, whereas white matter damage induced an initially increased connectivity followed by a global decrease. Both white and especially grey matter damage, however, induced a decrease in network integration. These empirically informed simulations show that specific topology and timing of structural damage are nontrivial aspects in explaining functional abnormalities in MS. Insufficient attention to these aspects likely explains contradictory findings in multiple sclerosis functional imaging studies so far.

[Background] Mitochondrial dysfunction is increasingly recognized as an important feature of multiple sclerosis (MS) pathology and may be relevant for clinical disease progression. However, it is unknown whether mitochondrial DNA (mtDNA) levels in the cerebrospinal fluid (CSF) associate with disease progression and therapeutic response. [Objectives] To evaluate whether CSF concentrations of mtDNA in MS patients can serve as a marker of ongoing neuropathology and may be helpful to differentiate between MS disease subtypes. To explore the effect of disease-modifying therapies on mtDNA levels in the CSF. [Methods] CSF mtDNA was measured using a digital polymerase chain reaction (PCR) CSF mtDNA in two independent MS cohorts. The cohorts included 92 relapsing-remitting multiple sclerosis (RRMS) patients, 40 progressive multiple sclerosis (PMS) patients (27 secondary progressive and 13 primary progressive), 50 various neurologic disease controls, and 5 healthy controls. [Results] Patients with PMS showed a significant increase in CSF mtDNA compared to non-inflammatory neurologic disease controls. Patients with higher T2 lesion volumes and lower normalized brain volumes showed increased concentration of mtDNA. Patients treated with fingolimod had significantly lower mtDNA copy levels at follow-up compared to baseline. [Conclusion] Our results showed a non-specific elevation of concentration of mtDNA in PMS patients. mtDNA concentrations respond to fingolimod and may be used to monitor biological effect of this treatment, This work has been funded, in part, by the Ministerio de Economia y Competitividad of Spain (SAF2014-56644) and by CIBERNED grants to R.T. and P.P.

Objective To explore the added value of dynamic functional connectivity (dFC) of the default mode network (DMN) during resting-state (RS), during an information processing speed (IPS) task, and the within-subject difference between these conditions, on top of conventional brain measures in explaining IPS in people with multiple sclerosis (pwMS). Methods In 29 pwMS and 18 healthy controls, IPS was assessed with the Letter Digit Substitution Test and Stroop Card I and combined into an IPS-composite score. White matter (WM), grey matter (GM) and lesion volume were measured using 3 T MRI. WM integrity was assessed with diffusion tensor imaging. During RS and task-state fMRI (i.e. symbol digit modalities task, IPS), stationary functional connectivity (sFC; average connectivity over the entire time series) and dFC (variation in connectivity using a sliding window approach) of the DMN was calculated, as well as the difference between both conditions (i.e. task-state minus RS; ΔsFC-DMN and ΔdFC-DMN). Regression analysis was performed to determine the most important predictors for IPS. Results Compared to controls, pwMS performed worse on IPS-composite (p = 0.022), had lower GM volume (p, Highlights • Problems with information processing speed occur often in multiple sclerosis (MS) • Dynamics in brain communication can reflect information transfer within the brain • With fMRI, dynamic communication can be measured, which increases upon task demands • This increase in dynamics explains information processing speed in MS

Background: We conducted a multi-modal optical coherence tomography (OCT) and magnetoencephalography (MEG) study to test whether there is a relationship between retinal layer integrity and electrophysiological activity and connectivity (FC) in the visual network influenced by optic neuritis (ON) in patients with multiple sclerosis (MS). Methods: One hundred and two MS patients were included in this MEG/OCT study. Retinal OCT data were collected from the optic discs, macular region, and segmented. Neuronal activity and FC in the visual cortex was estimated from source-reconstructed resting-state MEG data by computing relative power and the phase lag index (PLI). Generalized estimating equations (GEE) were used to account for intereye within-patient dependencies. Results: There was a significant relationship for both relative power and FC in the visual cortex with retinal layer thicknesses. The findings were influenced by the presence of MSON, particularly for connectivity in the alpha bands and the outer macular layers. In the absence of MSON, this relationship was dominated by the lower frequency bands (theta, delta) and inner and outer retinal layers. Conclusion: These results suggest that visual cortex FC more than activity alters in the presence of MSON, which may guide the understanding of FC plasticity effects following MSON.

ObjectiveTo determine which pathologic process could be responsible for the acceleration of cognitive decline during the course of multiple sclerosis (MS), using longitudinal structural MRI, which was related to cognitive decline in relapsing-remitting MS (RRMS) and progressive MS (PMS).MethodsA prospective cohort of 230 patients with MS (179 RRMS and 51 PMS) and 59 healthy controls was evaluated twice with 5-year (mean 4.9, SD 0.94) interval during which 22 patients with RRMS converted to PMS. Annual rates of cortical and deep gray matter atrophy as well as lesion volume increase were computed on longitudinal (3T) MRI data and correlated to the annual rate of cognitive decline as measured using an extensive cognitive evaluation at both time points.ResultsThe deep gray matter atrophy rate did not differ between PMS and RRMS (−0.82%/year vs −0.71%/year, p = 0.11), while faster cortical atrophy was observed in PMS (−0.87%/year vs −0.48%/year, p < 0.01). Similarly, faster cognitive decline was observed in PMS compared to RRMS (p < 0.01). Annual cognitive decline was related to the rate of annual lesion volume increase in stable RRMS (r = −0.17, p = 0.03) to the rate of annual deep gray matter atrophy in converting RRMS (r = 0.50, p = 0.02) and annual cortical atrophy in PMS (r = 0.35, p = 0.01).ConclusionsThese results indicate that cortical atrophy and cognitive decline accelerate together during the course of MS. Substrates of cognitive decline shifted from worsening lesional pathology in stable RRMS to deep gray matter atrophy in converting RRMS and to accelerated cortical atrophy in PMS only.

Background The pathophysiology of multiple sclerosis disease progression remains undetermined. The aim of this study was to identify differences in plasma proteome during different stages of MS disease progression. Methods We used a multiplex aptamer proteomics platform (Somalogic) for sensitive detection of 1129 proteins in plasma. MS patients were selected and categorized based on baseline and a 4-year follow-up EDSS (delta EDSS) scores; relapse-onset (RO) slow progression (n = 31), RO with rapid progression (n = 29), primary progressive (n = 30), and healthy controls (n = 20). The relation of baseline plasma protein levels with delta EDSS and different MRI progression parameters were assessed using linear regression models. Results Regression analyses of plasma proteins with delta EDSS showed six significant associations. Strong associations were found for the proteins LGLAS8 (P = 7.64 × 10-5 , q = 0.06), CCL3 (P = 0.0001, q = 0.06), and RGMA (P = 0.0005, q = 0.09). In addition, associations of plasma proteins were found with percentage brain volume for C3 (P = 2,08 × 10-9 , q = 1,70 × 10-6 ), FGF9 (P = 3,42 × 10-9 , q = 1,70 × 10-6 ), and EHMT2 (P = 0.0007, q = 0.01). Most of the significant markers were associated with cell-cell and cell-extracellular matrix adhesion, immune system communication, immune system activation, and complement pathways. Conclusions Our results revealed eight novel biomarkers related to clinical and radiological progression in MS. These results indicate that changes in immune system, complement pathway and ECM remodeling proteins contribute to MS progression and may therefore be further explored for use in prognosis of MS.

Cortical microstructural abnormalities are associated with clinical and cognitive deterioration in multiple sclerosis. Using diffusion tensor MRI, a higher fractional anisotropy has been found in cortical lesions versus normal-appearing cortex in multiple sclerosis. The pathological substrates of this finding have yet to be definitively elucidated. By performing a combined post-mortem diffusion tensor MRI and histopathology study, we aimed to define the histopathological substrates of diffusivity abnormalities in multiple sclerosis cortex. Sixteen subjects with multiple sclerosis and 10 age- and sex-matched non-neurological control donors underwent post-mortem in situ at 3 T MRI, followed by brain dissection. One hundred and ten paraffin-embedded tissue blocks (54 from multiple sclerosis patients, 56 from non-neurological controls) were matched to the diffusion tensor sequence to obtain regional diffusivity measures. Using immunohistochemistry and silver staining, cortical density of myelin, microglia, astrocytes and axons, and density and volume of neurons and glial cells were evaluated. Correlates of diffusivity abnormalities with histological markers were assessed through linear mixed-effects models. Cortical lesions (77% subpial) were found in 27/54 (50%) multiple sclerosis cortical regions. Multiple sclerosis normal-appearing cortex had a significantly lower fractional anisotropy compared to cortex from non-neurological controls (P = 0.047), whereas fractional anisotropy in demyelinated cortex was significantly higher than in multiple sclerosis normal-appearing cortex (P = 0.012) but not different from non-neurological control cortex (P = 0.420). Compared to non-neurological control cortex, both multiple sclerosis normal-appearing and demyelinated cortices showed a lower density of axons perpendicular to the cortical surface (P = 0.012 for both) and of total axons (parallel and perpendicular to cortical surface) (P = 0.028 and 0.012). In multiple sclerosis, demyelinated cortex had a lower density of myelin (P = 0.004), parallel (P = 0.018) and total axons (P = 0.029) versus normal-appearing cortex. Regarding the pathological substrate, in non-neurological controls, cortical fractional anisotropy was positively associated with density of perpendicular, parallel, and total axons (P = 0.031 for all). In multiple sclerosis, normal-appearing cortex fractional anisotropy was positively associated with perpendicular and total axon density (P = 0.031 for both), while associations with myelin, glial and total cells and parallel axons did not survive multiple comparison correction. Demyelinated cortex fractional anisotropy was positively associated with density of neurons, and total cells and negatively with microglia density, without surviving multiple comparison correction. Our results suggest that a reduction of perpendicular axons in normal-appearing cortex and of both perpendicular and parallel axons in demyelinated cortex may underlie the substrate influencing cortical microstructural coherence and being responsible for the different patterns of fractional anisotropy changes occurring in multiple sclerosis cortex.

Introduction Atrophy of the spinal cord is known to occur in multiple sclerosis (MS). The mean upper cervical cord area (MUCCA) can be used to measure this atrophy. Currently, several (semi-)automated methods for MUCCA measurement exist, but validation in clinical magnetic resonance (MR) images is lacking. Methods Five methods to measure MUCCA (SCT-PropSeg, SCT-DeepSeg, NeuroQLab, Xinapse JIM and ITK-SNAP) were investigated in a predefined upper cervical cord region. First, within-scanner reproducibility and between-scanner robustness were assessed using intra-class correlation coefficient (ICC) and Dice's similarity index (SI) in scan-rescan 3DT1-weighted images (brain, including cervical spine using a head coil) performed on three 3 T MR machines (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) in 21 subjects with MS and 6 healthy controls (dataset A). Second, sensitivity of MUCCA measurement to lesions in the upper cervical cord was assessed with cervical 3D T1-weighted images (3 T GE HDxT using a head-neck-spine coil) in 7 subjects with MS without and 14 subjects with MS with cervical lesions (dataset B), using ICC and SI with manual reference segmentations. Results In dataset A, MUCCA differed between MR machines (p 0.176). However, there was an effect of method for both volumetric and voxel wise agreement of the segmentations (both p, Highlights • Mean upper cervical cord area (MUCCA) was obtained with five different methods. • MUCCA was determined in a unique scan-rescan multi-vendor MR study. • Reproducibility: MUCCA did not differ between scan-rescan images for any method. • Robustness: MUCCA differed between methods and between scanners. • Performance of MUCCA methods was not affected by the presence of lesions.

ObjectiveThe clinical course of multiple sclerosis (MS) is variable and largely unpredictable pointing to an urgent need for markers to monitor disease activity and progression. Recent evidence revealed that tissue transglutaminase (TG2) is altered in patient-derived monocytes. We hypothesize that blood cell–derived TG2 messenger RNA (mRNA) can potentially be used as biomarker in patients with MS.MethodsIn peripheral blood mononuclear cells (PBMCs) from 151 healthy controls and 161 patients with MS, TG2 mRNA was measured and correlated with clinical and MRI parameters of disease activity (annualized relapse rate, gadolinium-enhanced lesions, and T2 lesion volume) and disease progression (Expanded Disability Status Scale [EDSS], normalized brain volume, and hypointense T1 lesion volume).ResultsPBMC-derived TG2 mRNA levels were significantly associated with disease progression, i.e., worsening of the EDSS over 2 years of follow-up, normalized brain volume, and normalized gray and white matter volume in the total MS patient group at baseline. Of these, in patients with relapsing-remitting MS, TG2 expression was significantly associated with worsening of the EDSS scores over 2 years of follow-up. In the patients with primary progressive (PP) MS, TG2 mRNA levels were significantly associated with EDSS, normalized brain volume, and normalized gray and white matter volume at baseline. In addition, TG2 mRNA associated with T1 hypointense lesion volume in the patients with PP MS at baseline.ConclusionPBMC-derived TG2 mRNA levels hold promise as biomarker for disease progression in patients with MS.Classification of EvidenceThis study provides Class II evidence that in patients with MS, PBMC-derived TG2 mRNA levels are associated with disease progression.

Introduction Despite the recognized importance of atrophy in multiple sclerosis (MS), methods for its quantification have been mostly restricted to the research domain. Recently, a CE labelled and FDA approved MS-specific atrophy quantification method, MSmetrix, has become commercially available. Here we perform a validation of MSmetrix against established methods in simulated and in vivo MRI data. Methods Whole-brain and gray matter (GM) volume were measured with the cross-sectional pipeline of MSmetrix and compared to the outcomes of FreeSurfer (cross-sectional pipeline), SIENAX and SPM. For this comparison we investigated 20 simulated brain images, as well as in vivo data from 100 MS patients and 20 matched healthy controls. In fifty of the MS patients a second time point was available. In this subgroup, we additionally analyzed the whole-brain and GM volume change using the longitudinal pipeline of MSmetrix and compared the results with those of FreeSurfer (longitudinal pipeline) and SIENA. Results In the simulated data, SIENAX displayed the smallest average deviation compared with the reference whole-brain volume (+ 19.56 ± 10.34 mL), followed by MSmetrix (− 38.15 ± 17.77 mL), SPM (− 42.99 ± 17.12 mL) and FreeSurfer (− 78.51 ± 12.68 mL). A similar pattern was seen in vivo. Among the cross-sectional methods, Deming regression analyses revealed proportional errors particularly in MSmetrix and SPM. The mean difference percentage brain volume change (PBVC) was lowest between longitudinal MSmetrix and SIENA (+ 0.16 ± 0.91%). A strong proportional error was present between longitudinal percentage gray matter volume change (PGVC) measures of MSmetrix and FreeSurfer (slope = 2.48). All longitudinal methods were sensitive to the MRI hardware upgrade that occurred during the time of the study. Conclusion MSmetrix, FreeSurfer, FSL and SPM show differences in atrophy measurements, even at the whole-brain level, that are large compared to typical atrophy rates observed in MS. Especially striking are the proportional errors between methods. Cross-sectional MSmetrix behaved similarly to SPM, both in terms of mean volume difference as well as proportional error. Longitudinal MSmetrix behaved most similar to SIENA. Our results indicate that brain volume measurement and normalization from T1-weighted images remains an unsolved problem that requires much more attention., Highlights • MSmetrix is validated against established atrophy quantification methods. • MSmetrix, FreeSurfer, SIENA(x) and SPM provide different results. • Most striking are the proportional errors between methods. • Cross-sectional MSmetrix behaves most similar to SPM. • Longitudinal MSmetrix behaves most similar to SIENA.

Background: Body fluid and structural imaging biomarkers give information on neurodegeneration. The relationship over time is not known in multiple sclerosis. Objective: To investigate the temporal relationship of elevated cerebrospinal fluid (CSF) neurofilament (Nf) protein levels, a biomarker for axonal loss, with magnetic resonance imaging (MRI) atrophy measures. Methods: In patients with multiple sclerosis, CSF Nf heavy chain (NfH) phosphoform levels were quantified at baseline and dichotomised into ‘normal’ and ‘high’. Atrophy was assessed by MRI at baseline and 15-year follow-up using SIENAX and FreeSurfer software. Results: High baseline CSF NfH SMI35 levels predicted pronounced atrophy at 15-year follow-up (odds ratio (OR): 36, p 80% is reached with 14–50 patients. Conclusion: These data suggest that high CSF NfH levels are an early predictor of later brain and spinal cord atrophy using structural imaging biomarkers and can be investigated in reasonably sized patient cohorts.

Background: Cortical gray matter (GM) demyelination is frequent and clinically relevant in multiple sclerosis (MS). Quantitative magnetic resonance imaging (qMRI) sequences such as magnetization transfer ratio (MTR) and quantitative R2* (qR2*) can capture pathological subtleties missed by conventional magnetic resonance imaging (MRI) sequences. Although differences in MTR and qR2* have been reported between lesional and non-lesional tissue, differences between lesion types or lesion types and myelin density matched normal-appearing gray matter (NAGM) have not been found or investigated. Objective: Identify quantitative differences in histopathologically verified GM lesion types and matched NAGM at ultra-high field strength. Methods: Using 7T post-mortem MRI, MRI lesions were marked on T2 images and co-registered to the calculated MTR and qR2* maps for further evaluation. In all, 15 brain slices were collected, containing a total of 74 cortical GM lesions and 45 areas of NAGM. Results: Intracortical lesions had lower MTR and qR2* values compared to NAGM. Type I lesions showed lower MTR than type III lesions. Type III lesions showed lower MTR than matched NAGM, and type I and IV lesions showed lower qR2* than matched NAGM. Conclusion: qMRI at 7T can provide additional information on extent of cortical pathology, especially concerning subpial lesions. This may be relevant for monitoring disease progression and potential treatment effects.

BACKGROUND AND PURPOSE: Natalizumab treatment strongly affects relapsing-remitting multiple sclerosis, possibly by restraining white matter damage. This study investigated changes in white matter diffusivity in patients with relapsing-remitting multiple sclerosis during their first year of natalizumab treatment by using diffusion tensor imaging. MATERIALS AND METHODS: The study included patients with relapsing-remitting multiple sclerosis initiating natalizumab at baseline ( n = 22), patients with relapsing-remitting multiple sclerosis continuing interferon-β or glatiramer acetate ( n = 17), and healthy controls ( n = 12). Diffusion tensor imaging parameters were analyzed at baseline and month 12. We measured the extent and severity of white matter damage with diffusion tensor imaging parameters such as fractional anisotropy, comparing the patient groups with healthy controls at both time points. RESULTS: The extent and severity of white matter damage were reduced significantly in the natalizumab group with time (fractional anisotropy–based extent, 56.8% to 47.2%; severity, z = −0.67 to −0.59; P = .02); this reduction was not observed in the interferon-β/glatiramer acetate group (extent, 41.4% to 39.1%, and severity, z = −0.64 to −0.67; P = .94). Cognitive performance did not change with time in the patient groups but did correlate with the severity of damage ( r = 0.53, P = CONCLUSIONS: In patients with relapsing-remitting multiple sclerosis starting natalizumab treatment, the extent and severity of white matter damage were reduced significantly in the first year of treatment. These findings may aid in explaining the large observed clinical effect of natalizumab in relapsing-remitting multiple sclerosis.

Objective Abnormalities in segregative and integrative properties of brain networks have been observed in multiple sclerosis (MS) and are related to clinical functioning. This study aims to investigate the micro-scale correlates of macro-scale network measures of segregation and integration in MS. Methods Eight MS patients underwent post-mortem in situ whole-brain diffusion tensor (DT) imaging and subsequent brain dissection. Macro-scale structural network topology was derived from DT data using graph theory. Clustering coefficient and mean white matter (WM) fiber length were measures of nodal segregation and integration. Thirty-three tissue blocks were collected from five cortical brain regions. Using immunohistochemistry micro-scale tissue properties were evaluated, including, neuronal size, neuronal density, axonal density and total cell density. Nodal network properties and tissue properties were correlated. Results A negative correlation between clustering coefficient and WM fiber length was found. Higher clustering coefficient was associated with smaller neuronal size and lower axonal density, and vice versa for fiber length. Higher whole-brain WM lesion load was associated with higher whole-brain clustering, shorter whole-brain fiber length, lower neuronal size and axonal density. Conclusion Structural network properties on MRI associate with neuronal size and axonal density, suggesting that macro-scale network measures may grasp cortical neuroaxonal degeneration in MS. Electronic supplementary material The online version of this article (10.1007/s00415-018-9130-2) contains supplementary material, which is available to authorized users.

Background/objective: Endurance exercise can improve memory function in persons with multiple sclerosis (pwMS), but the effects on hippocampal functioning are currently unknown. We investigated the effects of a running intervention on memory and hippocampal functional connectivity in pwMS. Methods/results: Memory and resting-state functional magnetic resonance imaging (fMRI) data were collected in a running intervention (n = 15) and waitlist group (n = 14). Visuospatial memory improvement was correlated to increased connectivity between the hippocampus and the default-mode network (DMN) in the intervention group only. Conclusion: As a result of endurance exercise, improvements in visuospatial memory may be mediated by a stronger functional embedding of the hippocampus in the DMN. The non-for-profit organization Move to Sport (www.movetosport.be) initiated the study. The authors acknowledge Prof. Dr P. Parizel (UZA Antwerp) for facilitation of neuroimaging at UZA Wilrijk and Novartis and the MS Network Limburg for funding related operational costs.

Background: The biological mechanism of depression in multiple sclerosis (MS) is not well understood. Based on work in major depressive disorder, fronto-limbic disconnection might be important. Objective: To investigate structural and functional fronto-limbic changes in depressed MS (DMS) and non-depressed MS (nDMS) patients. Methods: In this retrospective study, 22 moderate-to-severe DMS patients (disease duration 8.2 ± 7.7 years), 21 nDMS patients (disease duration 15.3 ± 8.3 years), and 12 healthy controls underwent neuropsychological testing and magnetic resonance imaging (MRI; 1.5 T). Brain volumes (white matter (WM), gray matter, amygdala, hippocampus, thalamus), lesion load, fractional anisotropy (FA) of fronto-limbic tracts, and resting-state functional connectivity (FC) between limbic and frontal areas were measured and compared between groups. Regression analysis was performed to relate MRI measures to the severity of depression. Results: Compared to nDMS patients, DMS patients (shorter disease duration) had lower WM volume ( p Conclusion: DMS patients showed more pronounced (MS) damage, that is, structural and functional changes in temporo-frontal regions, compared to nDMS patients, suggestive of fronto-limbic disconnection.

Grey matter atrophy is common in multiple sclerosis. However, in contrast with other neurodegenerative diseases, it is unclear whether grey matter atrophy in multiple sclerosis is a diffuse ‘global’ process or develops, instead, according to distinct anatomical patterns. Using source-based morphometry we searched for anatomical patterns of co-varying cortical thickness and assessed their relationships with white matter pathology, physical disability and cognitive functioning. Magnetic resonance imaging was performed at 3 T in 208 patients with long-standing multiple sclerosis (141 females; age = 53.7 ± 9.6 years; disease duration = 20.2 ± 7.1 years) and 60 age- and sex-matched healthy controls. Spatial independent component analysis was performed on cortical thickness maps derived from 3D T 1 -weighted images across all subjects to identify co-varying patterns. The loadings, which reflect the presence of each cortical thickness pattern in a subject, were compared between patients with multiple sclerosis and healthy controls with generalized linear models. Stepwise linear regression analyses were used to assess whether white matter pathology was associated with these loadings and to identify the cortical thickness patterns that predict measures of physical and cognitive dysfunction. Ten cortical thickness patterns were identified, of which six had significantly lower loadings in patients with multiple sclerosis than in controls: the largest loading differences corresponded to the pattern predominantly involving the bilateral temporal pole and entorhinal cortex, and the pattern involving the bilateral posterior cingulate cortex. In patients with multiple sclerosis, overall white matter lesion load was negatively associated with the loadings of these two patterns. The final model for physical dysfunction as measured with Expanded Disability Status Scale score (adjusted R 2 = 0.297; P < 0.001) included the predictors age, overall white matter lesion load, the loadings of two cortical thickness patterns (bilateral sensorimotor cortex and bilateral insula), and global cortical thickness. The final model predicting average cognition (adjusted R 2 = 0.469; P < 0.001) consisted of age, the loadings of two cortical thickness patterns (bilateral posterior cingulate cortex and bilateral temporal pole), overall white matter lesion load and normal-appearing white matter integrity. Although white matter pathology measures were part of the final clinical regression models, they explained limited incremental variance (to a maximum of 4%). Several cortical atrophy patterns relevant for multiple sclerosis were found. This suggests that cortical atrophy in multiple sclerosis occurs largely in a non-random manner and develops (at least partly) according to distinct anatomical patterns. In addition, these cortical atrophy patterns showed stronger associations with clinical (especially cognitive) dysfunction than global cortical atrophy.

BACKGROUND AND PURPOSE: The considerable clinical effect of natalizumab in patients with relapsing-remitting multiple sclerosis might be explained by its possible beneficial effect on axonal functioning. In this longitudinal study, the effect of natalizumab on absolute concentrations of total N-acetylaspartate, a marker for neuronal integrity, and other brain metabolites is investigated in patients with relapsing-remitting multiple sclerosis by using MR spectroscopic imaging. MATERIALS AND METHODS: In this explorative observational study, 25 patients with relapsing-remitting multiple sclerosis initiating natalizumab treatment were included and scanned every 6 months for 18 months. Additionally 18 matched patients with relapsing-remitting multiple sclerosis continuing treatment with interferon-β or glatiramer acetate were included along with 12 healthy controls. Imaging included short TE 2D-MR spectroscopic imaging with absolute metabolite quantification of total N-acetylaspartate, creatine and phosphocreatine, choline-containing compounds, myo-inositol, and glutamate. Concentrations were determined for lesional white matter, normal-appearing white matter, and gray matter. RESULTS: At baseline in both patient groups, lower concentrations of total N-acetylaspartate and creatine and phosphocreatine were found in lesional white matter compared with normal-appearing white matter and additionally lower glutamate in lesional white matter of patients receiving natalizumab. In those patients, a significant yearly metabolite increase was found for lesional white matter total N-acetylaspartate (7%, P < .001), creatine and phosphocreatine (6%, P = .042), and glutamate (10%, P = .028), while lesion volumes did not change. In patients receiving interferon-β/glatiramer acetate, no significant change was measured in lesional white matter for any metabolite, while whole-brain normalized lesion volumes increased. CONCLUSIONS: Patients treated with natalizumab showed an increase in total N-acetylaspartate, creatine and phosphocreatine, and glutamate in lesional white matter. These increasing metabolite concentrations might be a sign of enhanced axonal metabolism.

Purpose: The purpose of this study was to present an effective algorithm for computing the discrete polar Stockwell transform (PST), investigate its unique multiscale and multi-orientation features, and explore potentially new applications including denoising and tissue segmentation. Theory and Methods: We investigated PST responses using both synthetic and MR images. Moreover, we compared the features of PST with both Gabor and Morlet wavelet transforms, and compared the PST with two wavelet approaches for denoising using MRI. Using a synthetic image, we also tested the edge effect of PST through signal-padding. Then, we constructed a partially supervised classifier using radial, marginal PST spectra of T2-weighted MRI, acquired from postmortem brains with multiple sclerosis. The classification involved three histology-verified tissue types: normal appearing white matter (NAWM), lesion, or other, along with 5-fold cross-validation. Results: The PST generated a series of images with varying orientations or rotation-invariant scales. Radial frequencies highlighted image structures of different size, and angular frequencies enhanced structures by orientation. Signal-padding helped suppress boundary artifacts but required attention to incidental artifacts. In comparison, the Gabor transform produced more redundant images and the wavelet spectra appeared less spatially smooth than the PST. In addition, the PST demonstrated lower root-mean-square errors than other transforms in denoising and achieved a 93% accuracy for NAWM pixels (296/317), and 88% accuracy for lesion pixels (165/188) in MRI segmentation. Conclusions: The PST is a unique local spectral density-assessing tool which is sensitive to both structure orientations and scales. This may facilitate multiple new applications including advanced characterization of tissue structure in standard MRI.

Cognitive decline is common in multiple sclerosis and strongly affects overall quality of life. Despite the identification of cross-sectional MRI correlates of cognitive impairment, predictors of future cognitive decline remain unclear. The objective of this study was to identify which MRI measures of structural damage, demographic and/or clinical measures at baseline best predict cognitive decline, during a 5-year follow-up period. A total of 234 patients with clinically definite multiple sclerosis and 60 healthy control subjects were examined twice, with a 5-year interval (mean = 4.9 years, standard deviation = 0.9). An extensive neuropsychological evaluation was performed at both time points and the reliable change index was computed to evaluate cognitive decline. Both whole-brain and regional MRI (3 T) measures were assessed at baseline, including white matter lesion volume, diffusion-based white matter integrity, cortical and deep grey matter volume. Logistic regression analyses were performed to determine which baseline measures best predicted cognitive decline in the entire sample as well as in early relapsing-remitting (symptom duration

Introduction Gray matter (GM) atrophy is common in multiple sclerosis (MS), but the relationship with white matter (WM) pathology is largely unknown. Some studies found a co-occurrence in specific systems, but a regional analysis across the brain in different clinical phenotypes is necessary to further understand the disease mechanism underlying GM atrophy in MS. Therefore, we investigated the association between regional GM atrophy and pathology in anatomically connected WM tracts. Methods Conventional and diffusion tensor imaging was performed at 3T in 208 patients with long-standing MS and 60 healthy controls. Deep and cortical GM regions were segmented and quantified, and both lesion volumes and average normal appearing WM fractional anisotropy of their associated tracts were derived using an atlas obtained by probabilistic tractography in the controls. Linear regression was then performed to quantify the amount of regional GM atrophy that can be explained by WM pathology in the connected tract. Results MS patients showed extensive deep and cortical GM atrophy. Cortical atrophy was particularly present in frontal and temporal regions. Pathology in connected WM tracts statistically explained both regional deep and cortical GM atrophy in relapsing-remitting (RR) patients, but only deep GM atrophy in secondary-progressive (SP) patients. Conclusion In RRMS patients, both deep and cortical GM atrophy were associated with pathology in connected WM tracts. In SPMS patients, only regional deep GM atrophy could be explained by pathology in connected WM tracts. This suggests that in SPMS patients cortical GM atrophy and WM damage are (at least partly) independent disease processes. Hum Brain Mapp, 36:1796–1807, 2015. © 2015 Wiley Periodicals, Inc.

Objective To investigate the coexistence of anterograde and retrograde trans-synaptic axonal degeneration, and to explore the relationship between selective visual pathway damage and global brain involvement in longstanding multiple sclerosis (MS). Methods In this single-centre, cross-sectional study, patients with longstanding MS (N=222) and healthy controls (HC, N=62) were included. We analysed thickness of retinal layers (optical coherence tomography), damage within optic radiations (OR) (lesion volume and fractional anisotropy and mean diffusivity by diffusion tensor imaging) and atrophy of the visual cortex and that of grey and white matter of the whole-brain (structural MRI). Linear regression analyses were used to assess associations between the different components and for comparing patients with and without optic neuritis and HC. Results In patients with MS, an episode of optic neuritis (MSON) was significantly associated with decreased integrity of the ORs and thinning of the peripapillary retinal nerve fibre layer (pRNFL) and macular ganglion cell complex (GCC). Lesion volume in the OR was negatively associated with pRNFL and GCC thickness in patients without optic neuritis (MSNON). The pRNFL and GCC showed associations with integrity of the OR, thickness of the primary visual cortex (only in patients with MSON), and also with global white and grey matter atrophy. In HCs, no such relationships were demonstrated. Interpretation This study provides evidence for presence of bidirectional (both anterograde and retrograde) trans-synaptic axonal degeneration in the visual pathway of patients with MS. Additionally, thinning of the retinal pRNFL and GCC are related to global white and grey matter atrophy in addition to pathology of the visual pathway. © 2014 by the BMJ Publishing Group Ltd.

Background and Purpose In vivo identification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset. Methods 70 MS patients (median EDSS of 2.0 [range 0.0–6.5]) were included from a six-center dataset of the MAGNIMS Study Group ( www.magnims.eu ) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on ‘unseen’ center. Results Compared to the reference mean lesion volume (4.85 ± 7.29 mL), the methods displayed a mean difference of 1.60 ± 4.83 (Cascade), 2.31 ± 7.66 (LGA), 0.44 ± 4.68 (LPA), 1.76 ± 4.17 (Lesion-TOADS) and −1.39 ± 4.10 mL (kNN-TTP). The ICCs were 0.755, 0.713, 0.851, 0.806 and 0.723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0.37 ± 0.23), Lesion-TOADS (SI = 0.35 ± 0.18) and kNN-TTP (SI = 0.44 ± 0.14) than for Cascade (SI = 0.26 ± 0.17) or LGA (SI = 0.31 ± 0.23). All methods showed highly similar results when used on data from a center not used in software parameter optimization. Conclusion The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods.

Objective:To investigate how changes in functional network hierarchy determine cognitive impairment in multiple sclerosis (MS).Methods:A cohort consisting of 332 patients with MS (age 48.1 ± 11.0 years, symptom duration 14.6 ± 8.4 years) and 96 healthy controls (HCs; age 45.9 ± 10.4 years) underwent structural MRI, fMRI, and extensive neuropsychological testing. Patients were divided into 3 groups: cognitively impaired (CI; n = 87), mildly cognitively impaired (MCI; n = 65), and cognitively preserved (CP; n = 180). The functional importance of brain regions was quantified with degree centrality, the average strength of the functional connections of a brain region with the rest of the brain, and eigenvector centrality, which adds to this concept by adding additional weight to connections with brain hubs because these are known to be especially important. Centrality values were calculated for each gray matter voxel based on resting-state fMRI data, registered to standard space. Group differences were assessed with a cluster-wise permutation-based method corrected for age, sex, and education.Results:CI patients demonstrated widespread centrality increases compared to both HCs and CP patients, mainly in regions making up the default-mode network. Centrality decreases were similar in all patient groups compared to HCs, mainly in occipital and sensorimotor areas. Results were robust across centrality measures.Conclusions:Patients with MS with cognitive impairment show hallmark alterations in functional network hierarchy with increased relative importance (centrality) of the default-mode network.

Both gray matter atrophy and disruption of functional networks are important predictors for physical disability and cognitive impairment in multiple sclerosis (MS), yet their relationship is poorly understood. Graph theory provides a modality invariant framework to analyze patterns of gray matter morphology and functional coactivation. We investigated, how gray matter and functional networks were affected within the same MS sample and examined their interrelationship. Magnetic resonance imaging and magnetoencephalography (MEG) were performed in 102 MS patients and 42 healthy controls. Gray matter networks were computed at the group-level based on cortical thickness correlations between 78 regions across subjects. MEG functional networks were computed at the subject level based on the phase-lag index between time-series of regions in source-space. In MS patients, we found a more regular network organization for structural covariance networks and for functional networks in the theta band, whereas we found a more random network organization for functional networks in the alpha2 band. Correlation analysis revealed a positive association between covariation in thickness and functional connectivity in especially the theta band in MS patients, and these results could not be explained by simple regional gray matter thickness measurements. This study is a first multimodal graph analysis in a sample of MS patients, and our results suggest that a disruption of gray matter network topology is important to understand alterations in functional connectivity in MS as regional gray matter fails to take into account the inherent connectivity structure of the brain.

Objective Trans-synaptic axonal degeneration is a mechanism by which neurodegeneration can spread from a sick to a healthy neuron in the central nervous system. This study investigated to what extent trans-synaptic axonal degeneration takes place within the visual pathway in multiple sclerosis (MS). Methods A single-centre study, including patients with long-standing MS and healthy controls. Structural imaging of the brain (MRI) and retina (spectral-domain optical coherence tomography) were used to quantify the extent of atrophy of individual retinal layers and the primary and secondary visual cortex. Generalised estimation equations and multivariable regression analyses were used for comparisons. Results Following rigorous quality control (OSCAR-IB), data from 549 eyes of 293 subjects (230 MS, 63 healthy controls) were included. Compared with control data, there was a significant amount of atrophy of the inner retinal layers in MS following optic neuritis (ON) and also in absence of ON. For both scenarios, atrophy stopped at the level of the inner nuclear layer. In contrast, there was significant localised atrophy of the primary visual cortex and secondary visual cortex in MS following ON, but not in MS in absence of ON. Interpretation These data suggest that retrograde (trans-synaptic) axonal degeneration stops at the inner nuclear layer, a neuronal network capable of plasticity. In contrast, there seems to be no neuroplasticity of the primary visual cortex, rendering the structure vulnerable to anterograde (trans-synaptic) degeneration.

Background: The majority of patients with multiple sclerosis (MS) present with spinal cord pathology. Spinal cord atrophy is thought to be a marker of disease severity, but in long-disease duration its relation to brain pathology and clinical disability is largely unknown. Objective: Our aim was to investigate mean upper cervical cord area (MUCCA) in patients with long-standing MS and assess its relation to brain magnetic resonance imaging (MRI) measures and clinical disability. Methods: MUCCA was measured in 196 MS patients and 55 healthy controls using 3DT1-weighted cervical images obtained at 3T MRI. Clinical disability was measured using the Expanded Disability Status Scale (EDSS), Nine-Hole-Peg test (9-HPT), and 25 feet Timed Walk Test (TWT). Stepwise linear regression was performed to assess the association between MUCCA and MRI measures, and between MUCCA and clinical disability. Results: MUCCA was smaller (mean 11.7%) in MS patients compared with healthy controls (72.56±9.82 and 82.24±7.80 mm2 respectively; pConclusion: MUCCA was reduced in MS patients compared with healthy controls. It provides a relevant marker for clinical disability in long-standing disease, independent of other MRI measures.

Purpose: Fatigue is a frequent and difficult to treat symptom affecting patients with multiple sclerosis (MS) with a profound negative impact on quality of life. Fatigue has been associated with functional and structural abnormalities of the frontal cortex, including frontal hypo-activation. The aim of this exploratory study was to assess whether fatigue symptoms can be reduced by excitability-enhancing anodal transcranial direct current stimulation (tDCS). Methods: In this sham-controlled, double-blind intervention study, tDCS was applied over the left prefrontal cortex of MS patients with fatigue for five consecutive days. Symptoms were tracked for 1 month via questionnaires. Lesion load at baseline was calculated for each patient and correlated with fatigue levels and responsiveness to stimulation. Results: In the whole group analysis the scores of the fatigue scales were not altered by tDCS. However, in an exploratory analysis we found a correlation between response to the stimulation regarding subjectively perceived fatigue and lesion load in the left frontal cortex: patients responding positively to anodal tDCS had higher lesion load, compared to non-responding patients. Conclusion: We conclude that in patient subgroups discernible by specific morphological alterations, tDCS may be a tool for MS fatigue management.

Objective: To investigate whether extent and severity of white matter (WM) damage, as measured with diffusion tensor imaging (DTI), can distinguish cognitively preserved (CP) from cognitively impaired (CI) multiple sclerosis (MS) patients. Methods: Conventional MRI and DTI data were acquired from 55 MS patients (35 CP, 20 CI) and 30 healthy controls (HC). Voxelwise analyses were used to investigate fractional anisotropy (FA), mean diffusivity, radial diffusivity, and axial diffusivity of a WM skeleton. Regional gray matter volume was quantified and lesion probability maps were generated. Results: Compared to HCs, decreased FA was found in 49% of the investigated WM skeleton in CP patients and in 76% of the investigated WM in CI patients. Several brain areas that showed reduced FA in both patient groups were significantly worse in CI patients, i.e, corpus callosum, superior and inferior longitudinal fasciculus, corticospinal tracts, forceps major, cingulum, and fornices. In CI patients, WM integrity damage was additionally seen in cortical brain areas, thalamus, uncinate fasciculus, brainstem, and cerebellum. These findings were independent of lesion location and regional gray matter volume, since no differences were found between the groups. Conclusion: CI patients diverged from CP patients only on DTI metrics. WM integrity changes were found in areas that are highly relevant for cognition in the CI patients but not in the CP patients. These WM changes are therefore thought to be related to the cognitive deficits and suggest that DTI might be a powerful tool when monitoring cognitive impairment in MS.

Background: Gray matter (GM) pathology has high clinical relevance in multiple sclerosis (MS), but conventional magnetic resonance imaging (MRI) is insufficiently sensitive to visualize the rather subtle damage. Objective: To investigate whether high spatial resolution T1-relaxation time (T1-RT) measurements can detect changes in the normal-appearing GM of patients with long-standing MS and whether these changes are associated with physical and cognitive impairment. Methods: High spatial resolution (1.05 × 1.05 × 1.2 mm3) T1-RT measurements were performed at 3 T in 156 long-standing MS patients and 54 healthy controls. T1-RT histogram parameters in several regions were analyzed to investigate group differences. Stepwise linear regression analyses were used to assess the relation of T1-RT with physical and cognitive impairment. Results: In both thalamus and cortex, T1-RT histogram skewness was higher in patients than controls. In the cortex, this was driven by the frontal and temporal lobes. No differences were found in other GM histogram parameters. Cortical skewness, thalamus volume, and average white matter (WM) lesion T1-RT emerged as the strongest predictors for cognitive performance (adjusted R2 = 0.39). Conclusion: Subtle GM damage was present in the cortex and thalamus of MS patients, as indicated by increased T1-RT skewness. Increased cortical skewness emerged as an independent predictor of cognitive dysfunction.

Background: Cognitive deficits are common in multiple sclerosis. Most previous studies investigating the imaging substrate of cognitive deficits in multiple sclerosis included patients with relatively short disease durations and were limited to one modality/brain region. Objective: To identify the strongest neuroimaging predictors for cognitive dysfunction in a large cohort of patients with long-standing multiple sclerosis. Methods: Extensive neuropsychological testing and multimodal 3.0T MRI was performed in 202 patients with multiple sclerosis and 52 controls. Cognitive scores were compared between groups using Z-scores. Whole-brain, white matter, grey matter, deep grey matter and lesion volumes; cortical thickness, (juxta)cortical and cerebellar lesions; and extent and severity of diffuse white matter damage were measured. Stepwise linear regression was used to identify the strongest predictors for cognitive dysfunction. Results: All cognitive domains were affected in patients. Patients showed extensive atrophy, focal pathology and damage in up to 75% of the investigated white matter. Associations between imaging markers and average cognition were two times stronger in cognitively impaired patients than in cognitively preserved patients. The final model for average cognition consisted of deep grey matter DGMV volume and fractional anisotropy severity (adjusted R²=0.490; pConclusion: From all imaging markers, deep grey matter atrophy and diffuse white matter damage emerged as the strongest predictors for cognitive dysfunction in long-standing multiple sclerosis.

BACKGROUND AND PURPOSE: Spinal cord atrophy is a common and clinically relevant characteristic in multiple sclerosis. We aimed to perform a multicenter validation study of mean upper cervical cord area measurements in patients with multiple sclerosis and healthy controls from head MR images and to explore the effect of gadolinium administration on mean upper cervical cord area measurements.MATERIALS AND METHODS: We recruited 97 subjects from 3 centers, including 60 patients with multiple sclerosis of different disease types and 37 healthy controls. Both cervical cord and head 3D T1-weighted images were acquired. In 11 additional patients from 1 center, head images before and after gadolinium administration and cervical cord images after gadolinium administration were acquired. The mean upper cervical cord area was compared between cervical cord and head images by using intraclass correlation coefficients (ICC) for both consistency (ICCconsist) and absolute (ICCabs) agreement.RESULTS: There was excellent agreement of mean upper cervical cord area measurements from head and cervical cord images in the entire group (ICCabs = 0.987) and across centers and disease subtypes. The mean absolute difference between the mean upper cervical cord area measured from head and cervical cord images was 2 mm2 (2.3%). Additionally, excellent agreement was found between the mean upper cervical cord area measured from head images with and without gadolinium administration (ICCabs = 0.991) and between the cervical cord and head images with gadolinium administration (ICCabs = 0.992).CONCLUSIONS: Excellent agreement between mean upper cervical cord area measurements on head and cervical cord images was observed in this multicenter study, implying that upper cervical cord atrophy can be reliably measured from head images. Postgadolinium head or cervical cord images may also be suitable for measuring mean upper cervical cord area.

Magnetic resonance imaging (MRI) is the most powerful tool for the early (differential) diagnosis of multiple sclerosis (MS) and has been part of the International Panel criteria (2001, 2005, 2010) for more than 10 years. The role of brain and spinal cord MRI in the diagnosis of MS is well established. New MR techniques and markers will further improve the diagnostic value in a research and clinical routine setting. In addition to diagnosis, MRI is widely used for prognostic evaluation as well as treatment efficacy and safety monitoring. This field has gained importance with the introduction of new MS therapeutics. Therefore, the scope of MRI-guided MS disease monitoring has been widened to include rigorous treatment monitoring aiming at "no evidence of disease activity (NEDA)". Next, safety monitoring of treated MS patients has become major concern to enable early detection of opportunistic infections such as progressive multifocal leukoencephalopathy (PML). Driven by these new developments, recently published expert panel guidelines stressed the need for standardized imaging protocols and targeted specialized imaging markers for MS diagnosis and disease monitoring. This review article aims to give an update on the role of MRI in the diagnosis and monitoring of MS with particular emphasis to treatment efficacy and safety, both in clinical practice and in research.

Objective: To find the strongest neuroimaging predictors for motor dysfunction using conventional and quantitative imaging measures focusing on the corticospinal tract (CST) in a large cohort of patients with long-standing multiple sclerosis (MS). Methods: In this cross-sectional study, a wide spectrum of neuroimaging measures at the whole-brain, cervical, and CST level were analyzed in 195 patients with MS and 54 healthy controls. Motor function was assessed using the Expanded Disability Status Scale (EDSS), 9-Hole Peg Test, Timed 25-Foot Walk Test, and Multiple Sclerosis Walking Scale. Associations between damage in different parts of the motor system and motor functioning were assessed using stepwise linear regression. Results: Patients had an average disease duration of 19.98 (±6.99) years and a median EDSS score of 4 (range: 1.0–8.0). EDSS score was associated with number of infratentorial and cervical cord lesions, lesion volume in the CST, and mean upper cervical cord area (adjusted R 2 = 0.403). Timed 25-Foot Walk Test score was associated with number of infratentorial lesions and cerebellar volume (adjusted R 2 = 0.150), 9-Hole Peg Test score with number of infratentorial lesions and thickness of the cortex connected to the CST (adjusted R 2 = 0.245), and Multiple Sclerosis Walking Scale with number of infratentorial and cervical lesions, thickness of the cortex connected to the CST, and mean upper cervical cord area (adjusted R 2 = 0.354). Conclusions: Motor dysfunction in MS has a complex substrate that cannot be ascribed to a single neuroimaging finding, but is the consequence of infratentorial and spinal cord damage, as well as damage in the CST.

Both gray matter atrophy and disruption of functional networks are important predictors for physical disability and cognitive impairment in multiple sclerosis (MS), yet their relationship is poorly understood. Graph theory provides a modality invariant framework to analyze patterns of gray matter morphology and functional coactivation. We investigated, how gray matter and functional networks were affected within the same MS sample and examined their interrelationship. Magnetic resonance imaging and magnetoencephalography (MEG) were performed in 102 MS patients and 42 healthy controls. Gray matter networks were computed at the group‐level based on cortical thickness correlations between 78 regions across subjects. MEG functional networks were computed at the subject level based on the phase‐lag index between time‐series of regions in source‐space. In MS patients, we found a more regular network organization for structural covariance networks and for functional networks in the theta band, whereas we found a more random network organization for functional networks in the alpha2 band. Correlation analysis revealed a positive association between covariation in thickness and functional connectivity in especially the theta band in MS patients, and these results could not be explained by simple regional gray matter thickness measurements. This study is a first multimodal graph analysis in a sample of MS patients, and our results suggest that a disruption of gray matter network topology is important to understand alterations in functional connectivity in MS as regional gray matter fails to take into account the inherent connectivity structure of the brain. Hum Brain Mapp 35:5946–5961, 2014. © 2014 Wiley Periodicals, Inc.

Objective: To investigate the MRI manifestation pattern of asymptomatic natalizumab-associated progressive multifocal leukoencephalopathy (PML) in patients with multiple sclerosis (MS). Methods: 18 patients with MS with natalizumab-associated PML lesions on MRI were included. In 6 patients, the PML lesions were identified on MRI prospectively and in 12 patients PML lesions were identified retrospectively. MRI sequences were analysed for PML lesion distribution, appearance, grey matter/white matter involvement and possible signs of inflammation. Lesion probability maps were created to demonstrate lesion distribution pattern. Results: The frontal lobe was involved in 14 patients (77.8%) and the parietal lobe in 4 patients (22.2%). Most patients presented with focal lesions (13 patients, 72.2%) involving one single lobe (12 patients, 66.7%). The cortical grey matter was affected in 15 patients (83.3%) and 13 patients (72.2%) presented with a combination of cortical grey and white matter involvement. Signs of inflammation were detected in 7 patients (38.8%). Among patients with available diffusion-weighted imaging, 6 patients (40%) did not show high-signal-intensity lesions. A classical imaging pattern including unilateral and unilobar focal lesions in the frontal lobe affecting the cortical grey matter or the cortical grey and adjacent white matter was observed in 8 patients (44.4%). Conclusions: Asymptomatic natalizumab-associated PML manifestations on MRI show a rather localised disease, frequently located in the frontal lobes, affecting the cortical grey matter and adjacent juxtacortical white matter. Awareness of this lesion pattern facilitates an earlier diagnosis of natalizumab-associated PML in an asymptomatic stage associated with a more favourable prognosis.

To identify the measures of focal and diffuse white matter (WM) abnormalities that are related to whole-brain, deep, and cortical gray matter (GM) atrophy in long-standing multiple sclerosis (MS).The institutional review board approved the study; all subjects gave written informed consent. Magnetic resonance (MR) imaging was performed at 3 T in 208 patients with MS of long-standing duration (disease duration ≥ 10 years) and in 60 healthy control subjects. Normalized GM volume (NGMV), normalized WM volume (NWMV), normalized deep GM volume (NDGMV), cortical thickness, and normalized lesion volume (NLV) were quantified. Tissue integrity of normal-appearing WM (NAWM) and lesions was measured by using diffusion-tensor MR imaging. Multivariate associations between measures of GM atrophy and WM abnormalities were assessed in the patient group by using multiple linear regression.NGMV, NDGMV, and cortical thickness were reduced in patients with MS (all P.001). The final model for NGMV consisted of NWMV, NLV, and patient age and sex (adjusted R(2) = 0.58, P.001). NWMV, NLV, and patient sex were the explanatory variables for NDGMV (adjusted R(2) = 0.75, P.001). The model for cortical thickness consisted of fractional anisotropy of NAWM, NLV, and patient age and sex (adjusted R(2) = 0.32, P.001). The relationship between GM atrophy and WM abnormalities was weaker in primary and secondary progressive disease than in relapsing-remitting disease.Whole-brain and deep GM atrophy were particularly explained by WM atrophy and lesion volume, while cortical atrophy was associated with NAWM integrity loss. The weaker relationship between GM atrophy and WM abnormalities in patients with progressive disease might indicate a more independent neurodegenerative disease process in these patients.

OBJECTIVE Patients with longstanding type 1 diabetes may develop microangiopathy due to high cumulative glucose exposure. Also, chronic hyperglycemia is related to cerebral alterations and cognitive dysfunction. Whether the presence of microangiopathy is conditional to the development of hyperglycemia-related cerebral compromise is unclear. Since subcortical, rather than cortical, volume loss was previously related to cognitive dysfunction in other populations, we measured these brain correlates and cognitive functions in patients with longstanding type 1 diabetes with and without microangiopathy. RESEARCH DESIGN AND METHODS We evaluated differences in subcortical volume and cortical thickness and volume in type 1 diabetic patients with (n = 51) and without (n = 53) proliferative retinopathy and 49 control subjects and related volume differences to cognitive dysfunction. Analyses were corrected for age, sex, systolic blood pressure, and A1C. RESULTS Putamen and right thalamic volume loss was noted in both patients with and without proliferative retinopathy compared with control subjects (all P < 0.05). Additionally, in patients with proliferative retinopathy relative to control subjects, volume loss of the bilateral nucleus accumbens was found (all P < 0.05). No differences were observed between the two patient groups. Cortical thickness and volume were not different between groups. In pooled analyses, lower left nucleus accumbens volume was associated with cognitive dysfunction (P < 0.035). CONCLUSIONS This study shows subcortical, but not cortical, volume loss in relation to cognitive dysfunction in patients with longstanding type 1 diabetes, irrespective of microangiopathy. The time course, pathophysiology, and clinical relevance of these findings need to be established in longitudinal and mechanistic studies.

Introduction The segmentation and volumetric quantification of white matter (WM) lesions play an important role in monitoring and studying neurological diseases such as multiple sclerosis (MS) or cerebrovascular disease. This is often interactively done using 2D magnetic resonance images. Recent developments in acquisition techniques allow for 3D imaging with much thinner sections, but the large number of images per subject makes manual lesion outlining infeasible. This warrants the need for a reliable automated approach. Here we aimed to improve k nearest neighbor (kNN) classification of WM lesions by optimizing intensity normalization and using spatial tissue type priors (TTPs). Methods The kNN-TTP method used kNN classification with 3.0 T 3DFLAIR and 3DT1 intensities as well as MNI-normalized spatial coordinates as features. Additionally, TTPs were computed by nonlinear registration of data from healthy controls. Intensity features were normalized using variance scaling, robust range normalization or histogram matching. The algorithm was then trained and evaluated using a leave-one-out experiment among 20 patients with MS against a reference segmentation that was created completely manually. The performance of each normalization method was evaluated both with and without TTPs in the feature set. Volumetric agreement was evaluated using intra-class coefficient (ICC), and voxelwise spatial agreement was evaluated using Dice similarity index (SI). Finally, the robustness of the method across different scanners and patient populations was evaluated using an independent sample of elderly subjects with hypertension. Results The intensity normalization method had a large influence on the segmentation performance, with average SI values ranging from 0.66 to 0.72 when no TTPs were used. Independent of the normalization method, the inclusion of TTPs as features increased performance particularly by reducing the lesion detection error. Best performance was achieved using variance scaled intensity features and including TTPs in the feature set: this yielded ICC = 0.93 and average SI = 0.75 ± 0.08. Validation of the method in an independent sample of elderly subjects with hypertension, yielded even higher ICC = 0.96 and SI = 0.84 ± 0.14. Conclusion Adding TTPs increases the performance of kNN based MS lesion segmentation methods. Best performance was achieved using variance scaling for intensity normalization and including TTPs in the feature set, showing excellent agreement with the reference segmentations across a wide range of lesion severity, irrespective of the scanner used or the pathological substrate of the lesions., Highlights • Intensity normalization has a large influence on lesion segmentation performance. • Inclusion of tissue type priors as features increases segmentation performance. • Best performance was achieved using variance scaling and tissue type priors.

Cognitive decline is a frequent but undervalued aspect of multiple sclerosis (MS). Currently, it remains unclear what the strongest determinants of cognitive dysfunction are, with grey matter damage most directly related to cognitive impairment. Multi-parametric studies seem to indicate that individual factors of MS-pathology are highly interdependent causes of grey matter atrophy and permanent brain damage. They are associated with intermediate functional effects (e.g. in functional MRI) representing a balance between disconnection and (mal) adaptive connectivity changes. Therefore, a more comprehensive MRI approach is warranted, aiming to link structural changes with functional brain organization. To better understand the disconnection syndromes and cognitive decline in MS, this paper reviews the associations between MRI metrics and cognitive performance, by discussing the interactions between multiple facets of MS pathology as determinants of brain damage and how they affect network efficiency. Declínio cognitivo é uma situação frequente mas ainda pouco compreendida na esclerose múltipla (EM). Atualmente, não são totalmente conhecidos os principais determinantes da disfunção cognitiva na doença, tendo sido apontadas fortes associações entre danos à substância cinzenta e declínio cognitivo. Estudos multiparamétricos mostram que os diferentes fatores patológicos da EM participam como causas interdependentes de atrofia da substância cinzenta e dano cerebral permanente. Eles são associados a efeitos funcionais intermediários (detectados por RM funcional) representando um equilíbrio entre desconexão cerebral e alterações (mal) adaptativas. Portanto, uma abordagem de imagem mais abrangente é necessária, com o objetivo de encontrar associações entre alterações estruturais e a organização funcional cerebral. Para melhor compreender o declínio cognitivo na EM, esse artigo propões uma revisão dos principais métodos de imagem por RM e suas correlações com função cognitiva, discutindo as múltiplas faces patológicas da EM e seu impacto na eficiência das redes neurais.