Objective: To evaluate: (1) the distribution of gray matter (GM) atrophy in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4+NMOSD), and relapsing-remitting multiple sclerosis (RRMS); and (2) the relationship between GM volumes and white matter lesions in various brain regions within each disease. Methods: A retrospective, multicenter analysis of magnetic resonance imaging data included patients with MOGAD/AQP4+NMOSD/RRMS in non-acute disease stage. Voxel-wise analyses and general linear models were used to evaluate the relevance of regional GM atrophy. For significant results (p < 0.05), volumes of atrophic areas are reported. Results: We studied 135 MOGAD patients, 135 AQP4+NMOSD, 175 RRMS, and 144 healthy controls (HC). Compared with HC, MOGAD showed lower GM volumes in the temporal lobes, deep GM, insula, and cingulate cortex (75.79 cm3); AQP4+NMOSD in the occipital cortex (32.83 cm3); and RRMS diffusely in the GM (260.61 cm3). MOGAD showed more pronounced temporal cortex atrophy than RRMS (6.71 cm3), whereas AQP4+NMOSD displayed greater occipital cortex atrophy than RRMS (19.82 cm3). RRMS demonstrated more pronounced deep GM atrophy in comparison with MOGAD (27.90 cm3) and AQP4+NMOSD (47.04 cm3). In MOGAD, higher periventricular and cortical/juxtacortical lesions were linked to reduced temporal cortex, deep GM, and insula volumes. In RRMS, the diffuse GM atrophy was associated with lesions in all locations. AQP4+NMOSD showed no lesion/GM volume correlation. Interpretation: GM atrophy is more widespread in RRMS compared with the other two conditions. MOGAD primarily affects the temporal cortex, whereas AQP4+NMOSD mainly involves the occipital cortex. In MOGAD and RRMS, lesion-related tract degeneration is associated with atrophy, but this link is absent in AQP4+NMOSD.

Cortical myelin loss and repair in multiple sclerosis (MS) have been explored in neuropathological studies, but the impact of these processes on neurodegeneration and the irreversible clinical progression of the disease remains unknown. Here, we evaluated in vivo cortical demyelination and remyelination in a large cohort of people with all clinical phenotypes of MS followed up for 5 years using magnetization transfer imaging (MTI), a technique that has been shown to be sensitive to myelin content changes in the cortex. We investigated 140 people with MS (37 clinically isolated syndrome, 71 relapsing-MS, 32 progressive-MS), who were clinically assessed at baseline and after 5 years and, along with 84 healthy controls, underwent a 3 T-MRI protocol including MTI at baseline and after 1 year. Changes in cortical volume over the radiological follow-up were computed with a Jacobian integration method. Magnetization transfer ratio was employed to calculate for each patient an index of cortical demyelination at baseline and of dynamic cortical demyelination and remyelination over the follow-up period. The three indices of cortical myelin content change were heterogeneous across patients but did not significantly differ across clinical phenotypes or treatment groups. Cortical remyelination, which tended to fail in the regions closer to CSF (-11%, P < 0.001), was extensive in half of the cohort and occurred independently of age, disease duration and clinical phenotype. Higher indices of cortical dynamic demyelination (β = 0.23, P = 0.024) and lower indices of cortical remyelination (β = -0.18, P = 0.03) were significantly associated with greater cortical atrophy after 1 year, independently of age and MS phenotype. While the extent of cortical demyelination predicted a higher probability of clinical progression after 5 years in the entire cohort [odds ratio (OR) = 1.2; P = 0.043], the impact of cortical remyelination in reducing the risk of accumulating clinical disability after 5 years was significant only in the subgroup of patients with shorter disease duration and limited extent of demyelination in cortical regions (OR = 0.86, P = 0.015, area under the curve = 0.93). In this subgroup, a 30% increase in cortical remyelination nearly halved the risk of clinical progression at 5 years, independently of clinical relapses. Overall, our results highlight the critical role of cortical myelin dynamics in the cascade of events leading to neurodegeneration and to the subsequent accumulation of irreversible disability in MS. Our findings suggest that early-stage myelin repair compensating for cortical myelin loss has the potential to prevent neuro-axonal loss and its long-term irreversible clinical consequences in people with MS.

Importance: Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective: To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, setting, and participants: This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures: MS/CIS vs non-MS conditions. Main outcomes and measures: Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results: The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and relevance: The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.

Background and objectives: The optic nerve is not one of the areas of the CNS that can be used to demonstrate dissemination in space (DIS) within the 2017 McDonald criteria for the diagnosis of multiple sclerosis (MS). Objectives were (1) to assess whether optic nerve-MRI (ON-MRI), optical coherence tomography (OCT), and visual evoked potentials (VEP) detect optic nerve involvement in clinically isolated syndrome (CIS) and (2) to evaluate the contribution of the optic nerve topography to the current diagnostic criteria in a prospective, multicenter cohort. Methods: MAGNIMS centers were invited to provide prospective data on patients with CIS who underwent a visual assessment with at least 2 of 3 investigations (ON-MRI, OCT, or VEP) within 6 months of onset. Modified DIS criteria were constructed by adding the optic nerve topography, defined by each investigation separately and any combination of them, as the fifth area of the CNS. A risk assessment analysis and the performance of the different DIS criteria were analyzed using the diagnosis of MS according to the 2017 McDonald criteria as the primary outcome and new T2 lesions and/or a second relapse as the secondary outcome. Results: We included 157 patients with CIS from 5 MAGNIMS centers; 60/157 (38.2%) patients presented with optic neuritis. Optic nerve involvement on ON-MRI was found in 40.2% patients at study entry and in 72.5% of those with optic neuritis.At follow-up (mean 27.9 months, SD 14.5), 111/157 patients (70.7%) were diagnosed with MS according to the 2017 McDonald criteria. Fulfilling either 2017 DIS or any modified DIS criteria conferred a similar high risk for reaching primary and secondary outcomes. The modified DIS criteria had higher sensitivity (92.5% [with ON-MRI] vs 88.2%), but slightly lower specificity (80.0% [with GCIPL IEA ≥4 μm] vs 82.2%), with overall similar accuracy (86.6% [with ON-MRI] vs 86.5%) than 2017 DIS criteria. Consistent results were found for secondary outcomes. Discussion: In patients with CIS, the presence of an optic nerve lesion defined by MRI, OCT, or VEP is frequently detected, especially when presenting with optic neuritis. Our study supports the addition of the optic nerve as a fifth topography to fulfill DIS criteria.

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.

Background: The assessment of treatment response is a crucial step for patients with relapsing-remitting multiple sclerosis on disease-modifying therapies (DMTs). We explored whether a scoring system developed within the MAGNIMS (MRI in Multiple Sclerosis) network to evaluate treatment response to injectable drugs can be adopted also to oral DMTs. Methods: A multicentre dataset of 1200 patients who started three oral DMTs (fingolimod, teriflunomide and dimethyl fumarate) was collected within the MAGNIMS network. Disease activity after the first year was classified by the 'MAGNIMS' score based on the combination of relapses (0-≥2) and/or new T2 lesions (<3 or ≥3) on brain MRI. We explored the association of this score with the following 3-year outcomes: (1) confirmed disability worsening (CDW); (2) treatment failure (TFL); (3) relapse count between years 1 and 3. The additional value of contrast-enhancing lesions (CELs) and lesion location was explored. Results: At 3 years, 160 patients experienced CDW: 12% of them scored '0' (reference), 18% scored '1' (HR=1.82, 95% CI 1.20 to 2.76, p=0.005) and 37% scored '2' (HR=2.74, 95% CI 1.41 to 5.36, p=0.003) at 1 year. The analysis of other outcomes provided similar findings. Considering the location of new T2 lesions (supratentorial vs infratentorial/spinal cord) and the presence of CELs improved the prediction of CDW and TFL, respectively, in patients with minimal MRI activity alone (one or two new T2 lesions). Conclusions: Early relapses and substantial MRI activity in the first year of treatment are associated with worse short-term outcomes in patients treated with some of the oral DMT

Background and objectives: In multiple sclerosis (MS), functional networks undergo continuous reconfiguration and topography changes over the disease course. In this study, we aimed to investigate functional network to pography abnormalities in MS and their association with disease phenotype, clinical and cognitive disability, and structural MRI damage. Methods: This is a multicenter cross-sectional study. Enrolled participants performed MRI and neurologic and neuropsychological assessment. Network topography was assessed on resting state fMRI data using degree centrality, which counted the number of functional connections of each gray matter voxel with the rest of the brain. SPM12 age-adjusted, sex-adjusted, scanner-adjusted, framewise displacement, and gray matter-volume adjusted analysis of variance and multivariable regressions were used (p < 0.05, family-wise error [FWE] corrected). Results: We enrolled 971 patients with MS (624 female patients; mean age = 43.1 ± 11.8 years; 47 clinically isolated syndrome [CIS], 704 relapsing-remitting MS [RRMS], 145 secondary progressive MS [SPMS], and 75 primary progressive MS [PPMS]) and 330 healthy controls (186 female patients; mean age = 41.2 ± 13.3 years). Patients with MS showed reduced centrality in the salience and sensorimotor networks as well as increased centrality in the default-mode network vs controls (p < 0.05, FWE). Abnormal centrality was already found in CIS vs controls and in RRMS vs CIS (p < 0.001, uncorrected); however, it became more severe in SPMS vs RRMS (p < 0.05, FWE) and in PPMS vs controls (p < 0.001, uncorrected). Cognitively impaired patients (39%) showed reduced centrality in the salience network and increased centrality in the default-mode network vs cognitively preserved patients (p < 0.001, conjunction analysis). More severe disability correlated with increased centrality in the right precuneus (r = 0.18, p < 0.05 FWE). Higher T2 lesion volume and brain/gray matter atrophy were associated with reduced centrality in the bilateral insula and cerebellum (r = range -0.17/-0.15 and 0.26/0.28, respectively; p < 0.05, FWE). Higher brain/gray matter atrophy was also associated with increased centrality in the default-mode network (r = range -0.31/-0.22, p < 0.05, FWE). Discussion: Patients with MS presented with reduced centrality in the salience and primary sensorimotor networks and increased centrality in the default-mode network. Centrality abnormalities were specific for different disease phenotypes and associated with clinical and cognitive disability, hence suggesting that voxel-wise centrality analysis may reflect pathologic substrates underpinning disability accrual.

Background: We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes. Methods: Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups. Results: Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes. Conclusions: In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor.

MRI and clinical features of myelin oligodendrocyte glycoprotein (MOG)-antibody disease may overlap with those of other inflammatory demyelinating conditions posing diagnostic challenges, especially in non-acute phases and when serologic testing for MOG antibodies is unavailable or shows uncertain results. We aimed to identify MRI and clinical markers that differentiate non-acute MOG-antibody disease from aquaporin 4 (AQP4)-antibody neuromyelitis optica spectrum disorder and relapsing remitting multiple sclerosis, guiding in the identification of patients with MOG-antibody disease in clinical practice. In this cross-sectional retrospective study, data from 16 MAGNIMS centres were included. Data collection and analyses were conducted from 2019 to 2021. Inclusion criteria were: diagnosis of MOG-antibody disease; AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis; brain and cord MRI at least 6 months from relapse; and Expanded Disability Status Scale (EDSS) score on the day of MRI. Brain white matter T2 lesions, T1-hypointense lesions, cortical and cord lesions were identified. Random forest models were constructed to classify patients as MOG-antibody disease/AQP4-neuromyelitis optica spectrum disorder/multiple sclerosis; a leave one out cross-validation procedure assessed the performance of the models. Based on the best discriminators between diseases, we proposed a guide to target investigations for MOG-antibody disease. One hundred and sixty-two patients with MOG-antibody disease [99 females, mean age: 41 (±14) years, median EDSS: 2 (0-7.5)], 162 with AQP4-neuromyelitis optica spectrum disorder [132 females, mean age: 51 (±14) years, median EDSS: 3.5 (0-8)], 189 with multiple sclerosis (132 females, mean age: 40 (±10) years, median EDSS: 2 (0-8)] and 152 healthy controls (91 females) were studied. In young patients (<34 years), with low disability (EDSS < 3), the absence of Dawson's fingers, temporal lobe lesions and longitudinally extensive lesions in the cervical cord pointed towards a diagnosis of MOG-antibody disease instead of the other two diseases (accuracy: 76%, sensitivity: 81%, specificity: 84%, P < 0.001). In these non-acute patients, the number of brain lesions < 6 predicted MOG-antibody disease versus multiple sclerosis (accuracy: 83%, sensitivity: 82%, specificity: 83%, P < 0.001). An EDSS < 3 and the absence of longitudinally extensive lesions in the cervical cord predicted MOG-antibody disease versus AQP4-neuromyelitis optica spectrum disorder (accuracy: 76%, sensitivity: 89%, specificity: 62%, P < 0.001). A workflow with sequential tests and supporting features is proposed to guide better identification of patients with MOG-antibody disease. Adult patients with non-acute MOG-antibody disease showed distinctive clinical and MRI features when compared to AQP4-neuromyelitis optica spectrum disorder and multiple sclerosis. A careful inspection of the morphology of brain and cord lesions together with clinical information can guide further analyses towards the diagnosis of MOG-antibody disease in clinical practice.

The relationship between structural connectivity (SC) and functional connectivity (FC) captured from magnetic resonance imaging, as well as its interaction with disability and cognitive impairment, is not well understood in people with multiple sclerosis (pwMS). The Virtual Brain (TVB) is an open-source brain simulator for creating personalized brain models using SC and FC. The aim of this study was to explore SC-FC relationship in MS using TVB. Two different model regimes have been studied: stable and oscillatory, with the latter including conduction delays in the brain. The models were applied to 513 pwMS and 208 healthy controls (HC) from 7 different centers. Models were analyzed using structural damage, global diffusion properties, clinical disability, cognitive scores, and graph-derived metrics from both simulated and empirical FC. For the stable model, higher SC-FC coupling was associated with pwMS with low Single Digit Modalities Test (SDMT) score (F=3.48, P$lt$0.05), suggesting that cognitive impairment in pwMS is associated with a higher SC-FC coupling. Differences in entropy of the simulated FC between HC, high and low SDMT groups (F=31.57, P$lt$1e-5), show that the model captures subtle differences not detected in the empirical FC, suggesting the existence of compensatory and maladaptive mechanisms between SC and FC in MS.

Background: Magnetic resonance imaging (MRI) markers for chronic active lesions in MS include slowly expanding lesions (SELs) and paramagnetic rim lesions (PRLs). Objectives: To identify the relationship between SELs and PRLs in MS, and their association with disability. Methods: 61 people with MS (pwMS) followed retrospectively with MRI including baseline susceptibility-weighted imaging, and longitudinal T1 and T2-weighted scans. SELs were computed using deformation field maps; PRLs were visually identified. Mixed-effects models assessed differences in Expanded Disability Status Scale (EDSS) score changes between the group defined by the presence of SELs and or PRLs. Results: The median follow-up time was 3.2 years. At baseline, out of 1492 lesions, 616 were classified as SELs, and 80 as PRLs. 92% of patients had ⩾ 1 SEL, 56% had ⩾ 1 PRL, while both were found in 51%. SELs compared to non-SELs were more likely to also be PRLs (7% vs. 4%, p = 0.027). PRL counts positively correlated with SEL counts (ρ= 0.28, p = 0.03). SEL + PRL + patients had greater increases in EDSS over time (beta = 0.15/year, 95% confidence interval (0.04, 0.27), p = 0.009) than SEL+PRL-patients. Conclusion: SELs are more numerous than PRLs in pwMS. Compared with either SELs or PRLs found in isolation, their joint occurrence was associated with greater clinical progression.

Objectives: To evaluate the combined contribution of brain and cervical cord damage in predicting 5-year clinical worsening in a multicentre cohort of definite multiple sclerosis (MS) patients. Methods: Baseline 3.0T brain and cervical cord T2-weighted and three-dimensional T1-weighted MRI was acquired in 367 patients with MS (326 relapse-onset and 41 progressive-onset) and 179 healthy controls. Expanded Disability Status Scale (EDSS) score was obtained at baseline and after a median follow-up of 5.1 years (IQR=4.8-5.2). At follow-up, patients were classified as clinically stable/worsened according to EDSS changes. Generalised linear mixed models identified predictors of clinical worsening, evolution to secondary progressive (SP) MS and reaching EDSS=3.0, 4.0 and 6.0 milestones at 5 years. Results: At follow-up, 120/367 (33%) patients with MS worsened clinically; 36/256 (14%) patients with relapsing-remitting evolved to SPMS. Baseline predictors of EDSS worsening were progressive-onset versus relapse-onset MS (standardised beta (β)=0.97), higher EDSS (β=0.41), higher cord lesion number (β=0.41), lower normalised cortical volume (β=-0.15) and lower cord area (β=-0.28) (C-index=0.81). Older age (β=0.86), higher EDSS (β=1.40) and cord lesion number (β=0.87) independently predicted SPMS conversion (C-index=0.91). Predictors of reaching EDSS=3.0 after 5 years were higher baseline EDSS (β=1.49), cord lesion number (β=1.02) and lower normalised cortical volume (β=-0.56) (C-index=0.88). Baseline age (β=0.30), higher EDSS (β=2.03), higher cord lesion number (β=0.66) and lower cord area (β=-0.41) predicted EDSS=4.0 (C-index=0.92). Finally, higher baseline EDSS (β=1.87) and cord lesion number (β=0.54) predicted EDSS=6.0 (C-index=0.91). Conclusions: Spinal cord damage and, to a lesser extent, cortical volume loss helped predicting worse 5-year clinical outcomes in MS.

Background: White matter lesions (WMLs) on brain magnetic resonance imaging (MRI) in multiple sclerosis (MS) may contribute to misdiagnosis. In chronic active lesions, peripheral iron-laden macrophages appear as paramagnetic rim lesions (PRLs). Objective: To evaluate the sensitivity and specificity of PRLs in differentiating MS from mimics using clinical 3T MRI scanners. Method: This retrospective international study reviewed MRI scans of patients with MS (n = 254), MS mimics (n = 91) and older healthy controls (n = 217). WMLs, detected using fluid-attenuated inversion recovery MRI, were analysed with phase-sensitive imaging. Sensitivity and specificity were assessed for PRLs. Results: At least one PRL was found in 22.9% of MS and 26.1% of clinically isolated syndrome (CIS) patients. Only one PRL was found elsewhere. The identification of ⩾1 PRL was the optimal cut-off and had high specificity (99.7%, confidence interval (CI) = 98.20%-99.99%) when distinguishing MS and CIS from mimics and healthy controls, but lower sensitivity (24.0%, CI = 18.9%-36.6%). All patients with a PRL showing a central vein sign (CVS) in the same lesion (n = 54) had MS or CIS, giving a specificity of 100% (CI = 98.8%-100.0%) but equally low sensitivity (21.3%, CI = 16.4%-26.81%). Conclusion: PRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnostic biomarker, especially when used in conjunction with the CVS.

Objectives: To evaluate white matter and grey matter T1-weighted (w)/T2w ratio (T1w/T2w ratio) in healthy controls and patients with multiple sclerosis, and its association with clinical disability. Methods: In this cross-sectional study, 270 healthy controls and 434 patients with multiple sclerosis were retrospectively selected from 7 European sites. T1w/T2w ratio was obtained from brain T2w and T1w scans after intensity calibration using eyes and temporal muscle. Results: In healthy controls, T1w/T2w ratio increased until 50-60 years both in white and grey matter. Compared with healthy controls, T1w/T2w ratio was significantly lower in white matter lesions of all multiple sclerosis phenotypes, and in normal-appearing white matter and cortex of patients with relapsing-remitting and secondary progressive multiple sclerosis (p≤0.026), but it was significantly higher in the striatum and pallidum of patients with relapsing-remitting, secondary progressive and primary progressive multiple sclerosis (p≤0.042). In relapse-onset multiple sclerosis, T1w/T2w ratio was significantly lower in white matter lesions and normal-appearing white matter already at Expanded Disability Status Scale (EDSS) <3.0 and in the cortex only for EDSS ≥3.0 (p≤0.023). Conversely, T1w/T2w ratio was significantly higher in the striatum and pallidum for EDSS ≥4.0 (p≤0.005). In primary progressive multiple sclerosis, striatum and pallidum showed significantly higher T1w/T2w ratio beyond EDSS=6.0 (p≤0.001). In multiple sclerosis, longer disease duration, higher EDSS, higher brain lesional volume and lower normalised brain volume were associated with lower lesional and cortical T1w/T2w ratio and a higher T1w/T2w ratio in the striatum and pallidum (β from -1.168 to 0.286, p≤0.040). Conclusions: T1w/T2w ratio may represent a clinically relevant marker sensitive to demyelination, neurodegeneration and iron accumulation occurring at the different multiple sclerosis phases.

Background: Spatio-temporal evolution of cord atrophy in multiple sclerosis (MS) has not been investigated yet. Objective: To evaluate voxel-wise distribution and 1-year changes of cervical cord atrophy in a multicentre MS cohort. Methods: Baseline and 1-year 3D T1-weighted cervical cord scans and clinical evaluations of 54 healthy controls (HC) and 113 MS patients (14 clinically isolated syndromes (CIS), 77 relapsing-remitting (RR), 22 progressive (P)) were used to investigate voxel-wise cord volume loss in patients versus HC, 1-year volume changes and clinical correlations (SPM12). Results: MS patients exhibited baseline cord atrophy versus HC at anterior and posterior/lateral C1/C2 and C4-C6 (p < 0.05, corrected). While CIS patients showed baseline volume increase at C4 versus HC (p < 0.001, uncorrected), RRMS exhibited posterior/lateral C1/C2 atrophy versus CIS, and PMS showed widespread cord atrophy versus RRMS (p < 0.05, corrected). At 1 year, 13 patients had clinically worsened. Cord atrophy progressed in MS, driven by RRMS, at posterior/lateral C2 and C3-C6 (p < 0.05, corrected). CIS patients showed no volume changes, while PMS showed circumscribed atrophy progression. Baseline cord atrophy at posterior/lateral C1/C2 and C3-C6 correlated with concomitant and 1-year disability (r = -0.40/-0.62, p < 0.05, corrected). Conclusions: Voxel-wise analysis characterized spinal cord neurodegeneration over 1 year across MS phenotypes and helped to explain baseline and 1-year disability.

Purpose: To predict the occurrence of a second clinical event in patients with a CIS suggestive of MS, from baseline magnetic resonance imaging (MRI), by means of a pattern recognition approach. Methods: Two hundred sixty-six patients with a CIS were recruited from four participating centers. Over a follow-up of 3 years, 130 patients had a second clinical episode and 136 did not. Grey matter and white matter T1-hypointensities masks segmented from 3D T1-weighted images acquired on 3 T scanners were used as features for the classification approach. Differences between CIS that remained CIS and those that developed a second event were assessed at a global level and at a regional level, arranging the regions according to their contribution to the classification model. Results: All classification metrics were around or even below 50% for both global and regional approaches. Accuracies did not change when T1-hypointensity maps were added to the model; just the specificity was increased up to 80%. Among the 30 regions with the largest contribution, 26 were grey matter and 4 were white matter regions. For grey matter, regions contributing showed either a larger or a smaller volume in the group of patients that remained CIS, compared to those with a second event. The volume of T1-hypointensities was always larger for the group that presented a second event. Conclusions: Prediction of a second clinical event in CIS patients from baseline MRI seems to present a highly heterogeneous pattern, leading to very low classification accuracies. Adding the T1-hypointensity maps does not seem to improve the accuracy of the classification model. Keywords: Clinically isolated syndrome; Machine learning; Magnetic resonance imaging; Multiple sclerosis; Prognosis; Support vector machine.

Background and objectives: To compare the performance of the 2017 revisions to the McDonald criteria with the 2010 McDonald criteria in establishing multiple sclerosis (MS) diagnosis and predicting prognosis in patients with clinically isolated syndrome (CIS) suggestive of MS. Methods: CSF examination and brain and spinal cord MRI obtained ≤5 months from CIS onset and a follow-up brain MRI acquired within 15 months from CIS onset were evaluated in 785 patients with CIS from 9 European centers. Date of second clinical attack and of reaching Expanded Disability Status Scale score (EDSS) ≥3.0, if they occurred, were also collected. Performance of the 2017 and 2010 McDonald criteria for dissemination in space (DIS), dissemination in time (DIT) (including oligoclonal bands assessment), and DIS plus DIT for predicting a second clinical attack (clinically definite MS [CDMS]) and EDSS ≥3.0 at follow-up was evaluated. Time to MS diagnosis for the different criteria was also estimated. Results: At follow-up (median 69.1 months), 406/785 patients with CIS developed CDMS. At 36 months, the 2017 DIS plus DIT criteria had higher sensitivity (0.83 vs 0.66), lower specificity (0.39 vs 0.60), and similar area under the curve values (0.61 vs 0.63). Median time to MS diagnosis was shorter with the 2017 vs the 2010 or CDMS criteria (2017 revision, 3.2; 2010 revision, 13.0; CDMS, 58.5 months). The 2 sets of criteria similarly predicted EDSS ≥3.0 milestone. Three periventricular lesions improved specificity in patients ≥45 years. Discussion: The 2017 McDonald criteria showed higher sensitivity, lower specificity, and similar accuracy in predicting CDMS compared to 2010 McDonald criteria, while shortening time to diagnosis of MS.

Background: Considerable spinal cord (SC) atrophy occurs in multiple sclerosis (MS). While MRI-based techniques for SC cross-sectional area (CSA) quantification have improved over time, there is no common agreement on whether to measure at single vertebral levels or across larger regions and whether upper SC CSA can be reliably measured from brain images. Aim: To compare in a multicenter setting three CSA measurement methods in terms of repeatability at different anatomical levels. To analyze the agreement between measurements performed on the cervical cord and on brain MRI. Method: One healthy volunteer was scanned three times on the same day in six sites (three scanner vendors) using a 3T MRI protocol including sagittal 3D T1-weighted imaging of the brain (covering the upper cervical cord) and of the SC. Images were analyzed using two semiautomated methods [NeuroQLab (NQL) and the Active Surface Model (ASM)] and the fully automated Spinal Cord Toolbox (SCT) on different vertebral levels (C1-C2; C2/3) on SC and brain images and the entire cervical cord (C1-C7) on SC images only. Results: CSA estimates were significantly smaller using SCT compared to NQL and ASM (p < 0.001), regardless of the cord level. Inter-scanner repeatability was best in C1-C7: coefficients of variation for NQL, ASM, and SCT: 0.4, 0.6, and 1.0%, respectively. CSAs estimated in brain MRI were slightly lower than in SC MRI (all p ≤ 0.006 at the C1-C2 level). Despite protocol harmonization between the centers with regard to image resolution and use of high-contrast 3D T1-weighted sequences, the variability of CSA was partly scanner dependent probably due to differences in scanner geometry, coil design, and details of the MRI parameter settings. Conclusion: For CSA quantification, dedicated isotropic SC MRI should be acquired, which yielded best repeatability in the entire cervical cord. In the upper part of the cervical cord, use of brain MRI scans entailed only a minor loss of CSA repeatability compared to SC MRI. Due to systematic differences between scanners and the CSA quantification software, both should be kept constant within a study. The MRI dataset of this study is available publicly to test new analysis approaches.

Background: Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. Objectives: This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). Methods: A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. Results: All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0.83; inter-rater ICC ≥ 0.76 and CIgen ≥ 0.74. FASTSURF reproduced manual references excellently, with ICC ≥ 0.97 and JI ≥ 0.92. Conclusions: The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.

Background: Differentiating multiple sclerosis (MS) from vascular risk factor (VRF)-small vessel disease (SVD) can be challenging. Objective and methods: In order to determine whether or not pontine lesion location is a useful discriminator of MS and VRF-SVD, we classified pontine lesions on brain magnetic resonance imaging (MRI) as central or peripheral in 93 MS cases without VRF, 108 MS patients with VRF and 43 non-MS cases with VRF. Results: MS without VRF were more likely to have peripheral pons lesions (31.2%, 29/93) than non-MS with VRF (0%, 0/43) (Exp(B) = 29.8; 95% confidence interval (CI) = (1.98, 448.3); p = 0.014) but there were no significant differences regarding central pons lesions between MS without VRF (5.4%, 5/93) and non-MS with VRF patients (16.3%, 7/43) (Exp(B) = 0.89; 95% CI = (0.2, 3.94); p = 0.87). The presence of peripheral pons lesions discriminated between MS and VRF-SVD with 100% (95% CI = (91.8, 100)) specificity. The proportion of peripheral pons lesions in MS with VRF (30.5%, 33/108) was similar to that seen in MS without VRF (31.2%, 29/93, p = 0.99). Central lesions occurred in similar frequency in MS with VRF (8.3%, 9/108) and non-MS with VRF (16.3%, 7/43, p = 0.15). Conclusion: Peripheral pons lesion location is a good discriminator of MS from vascular lesions.

Objectives: Gay matter (GM) involvement is clinically relevant in multiple sclerosis (MS). Using source-based morphometry (SBM), we characterized GM atrophy and its 1-year evolution across different MS phenotypes. Methods: Clinical and MRI data were obtained at 8 European sites from 170 healthy controls (HCs) and 398 patients with MS (34 with clinically isolated syndrome [CIS], 226 with relapsing-remitting MS [RRMS], 95 with secondary progressive MS [SPMS], and 43 with primary progressive MS [PPMS]). Fifty-seven HCs and 144 with MS underwent 1-year follow-up. Baseline GM loss, atrophy progression, and correlations with disability and 1-year clinical worsening were assessed. Results: SBM identified 26 cerebellar, subcortical, sensory, motor, and cognitive GM components. GM atrophy was found in patients with MS vs HCs in almost all components (p range <0.001-0.04). Compared to HCs, patients with CIS showed circumscribed subcortical, cerebellar, temporal, and salience GM atrophy, while patients with RRMS exhibited widespread GM atrophy. Cerebellar, subcortical, sensorimotor, salience, and frontoparietal GM atrophy was found in patients with PPMS vs HCs and in patients with SPMS vs those with RRMS. At 1 year, 21 (15%) patients had clinically worsened. GM atrophy progressed in MS in subcortical, cerebellar, sensorimotor, and fronto-temporo-parietal components. Baseline higher disability was associated (R 2 = 0.65) with baseline lower normalized brain volume (β = -0.13, p = 0.001), greater sensorimotor GM atrophy (β = -0.12, p = 0.002), and longer disease duration (β = 0.09, p = 0.04). Baseline normalized GM volume (odds ratio 0.98, p = 0.008) and cerebellar GM atrophy (odds ratio 0.40, p = 0.01) independently predicted clinical worsening (area under the curve 0.83). Conclusion: GM atrophy differed across disease phenotypes and progressed at 1 year in MS. In addition to global atrophy measures, sensorimotor and cerebellar GM atrophy explained baseline disability and clinical worsening.

Background and rationale: Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods: Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results: In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. Conclusion: Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.

Background: MRI assessment in multiple sclerosis (MS) focuses on the presence of typical white matter (WM) lesions. Neurodegeneration characterised by brain atrophy is recognised in the research field as an important prognostic factor. It is not routinely reported clinically, in part due to difficulty in achieving reproducible measurements. Automated MRI quantification of WM lesions and brain volume could provide important clinical monitoring data. In general, lesion quantification relies on both T1 and FLAIR input images, while tissue volumetry relies on T1. However, T1-weighted scans are not routinely included in the clinical MS protocol, limiting the utility of automated quantification. Objectives: We address an aspect of this important translational challenge by assessing the performance of FLAIR-only lesion and brain segmentation, against a conventional approach requiring multi-contrast acquisition. We explore whether FLAIR-only grey matter (GM) segmentation yields more variability in performance compared with two-channel segmentation; whether this is related to field strength; and whether the results meet a level of clinical acceptability demonstrated by the ability to reproduce established biological associations. Methods: We used a multicentre dataset of subjects with a CIS suggestive of MS scanned at 1.5T and 3T in the same week. WM lesions were manually segmented by two raters, 'manual 1' guided by consensus reading of CIS-specific lesions and 'manual 2' by any WM hyperintensity. An existing brain segmentation method was adapted for FLAIR-only input. Automated segmentation of WM hyperintensity and brain volumes were performed with conventional (T1/T1 + FLAIR) and FLAIR-only methods. Results: WM lesion volumes were comparable at 1.5T between 'manual 2' and FLAIR-only methods and at 3T between 'manual 2', T1 + FLAIR and FLAIR-only methods. For cortical GM volume, linear regression measures between conventional and FLAIR-only segmentation were high (1.5T: α = 1.029, R2 = 0.997, standard error (SE) = 0.007; 3T: α = 1.019, R2 = 0.998, SE = 0.006). Age-associated change in cortical GM volume was a significant covariate in both T1 (p = 0.001) and FLAIR-only (p = 0.005) methods, confirming the expected relationship between age and GM volume for FLAIR-only segmentations. Conclusions: FLAIR-only automated segmentation of WM lesions and brain volumes were consistent with results obtained through conventional methods and had the ability to demonstrate biological effects in our study population. Imaging protocol harmonisation and validation with other MS phenotypes could facilitate the integration of automated WM lesion volume and brain atrophy analysis as clinical tools in radiological MS reporting.

Background: Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesions and atrophy is studied. Methods: On images of 21 MS subjects and 11 controls, three raters manually outlined caudate nucleus, putamen and thalamus; outlines were combined by majority voting. FSL-FIRST, FreeSurfer, Geodesic Information Flow and volBrain were evaluated. Performance was evaluated volumetrically (intra-class correlation coefficient (ICC)) and spatially (Dice similarity coefficient (DSC)). Spearman's correlations of DSC with global and local lesion volume, structure of interest volume (ROIV), and normalized brain volume (NBV) were assessed. Results: ICC with manual volumes was mostly good and spatial agreement was high. MS exhibited significantly lower DSC than controls for thalamus and putamen. For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations. Conclusions: Automated methods have impaired performance in patients. Performance generally deteriorated with higher lesion volume and lower NBV and ROIV, suggesting that these may contribute to the impaired performance.

Objective: During the natural course of multiple sclerosis (MS), the brain is exposed to aging as well as disease effects. Brain aging can be modeled statistically; the so-called "brain-age" paradigm. Here, we evaluated whether brain-predicted age difference (brain-PAD) was sensitive to the presence of MS, clinical progression, and future outcomes. Methods: In a longitudinal, multicenter sample of 3,565 magnetic resonance imaging (MRI) scans, in 1,204 patients with MS and clinically isolated syndrome (CIS) and 150 healthy controls (mean follow-up time: patients 3.41 years, healthy controls 1.97 years), we measured "brain-predicted age" using T1-weighted MRI. We compared brain-PAD among patients with MS and patients with CIS and healthy controls, and between disease subtypes. Relationships between brain-PAD and Expanded Disability Status Scale (EDSS) were explored. Results: Patients with MS had markedly higher brain-PAD than healthy controls (mean brain-PAD +10.3 years; 95% confidence interval [CI] = 8.5-12.1] versus 4.3 years; 95% CI = 2.1 to 6.4; p < 0.001). The highest brain-PADs were in secondary-progressive MS (+13.3 years; 95% CI = 11.3-15.3). Brain-PAD at study entry predicted time-to-disability progression (hazard ratio 1.02; 95% CI = 1.01-1.03; p < 0.001); although normalized brain volume was a stronger predictor. Greater annualized brain-PAD increases were associated with greater annualized EDSS score (r = 0.26; p < 0.001). Interpretation: The brain-age paradigm is sensitive to MS-related atrophy and clinical progression. A higher brain-PAD at baseline was associated with more rapid disability progression and the rate of change in brain-PAD related to worsening disability. Potentially, "brain-age" could be used as a prognostic biomarker in early-stage MS, to track disease progression or stratify patients for clinical trial enrollment.

OBJECTIVE: To determine if vascular risk factor (VRF), that is, smoking, arterial hypertension (HT), dyslipidaemia and diabetes, have an effect on multiple sclerosis (MS) pathology as measured by MS typical brain lesions, we have compared brain MRIs from patients with MS with and without VRF age-matched and sex-matched. METHODS: Brain MRIs from five centres were scored for the presence of Dawson's fingers (DF) and juxtacortical lesions (JCL). A regression model was built to predict the effect of each individual VRF on DF and JCL, considering age and disease duration. RESULTS: 92 MS cases without VRF and 106 MS with one or more VRF (80 ever-smokers, 43 hypertensives, 25 dyslipidaemics and 10 diabetics) were included. Ever-smoking associated with a higher burden of DF (Exp(B)=1.29, 95% CI 1.10 to 1.51, p<0.01) and JCL (Exp(B)=1.38, 95% CI 1.21 to 1.57, p<0.01). No other VRF had an impact on DF. Dyslipidaemia associated with increased JCL (Exp(B)=1.30, 95% CI 1.10 to 1.56, p<0.01) but HT did not associate with any of the outcomes. CONCLUSIONS: Individual VRF appear to affect MS-specific lesions differently. An increase in MS lesions was mainly seen in smokers; however, this VRF is most likely to be present from onset of MS, and other VRF effects may be partly mitigated by treatment. Our findings support that treating VRF and cessation of smoking may be important in the management of MS.

BACKGROUND:: In multiple sclerosis (MS), abnormalities of brain network dynamics and their relevance for cognitive impairment have never been investigated. OBJECTIVES:: The aim of this study was to assess the dynamic resting state (RS) functional connectivity (FC) on 62 relapsing-remitting MS patients and 65 sex-matched healthy controls enrolled at 7 European sites. METHODS:: MS patients underwent clinical and cognitive evaluation. Between-group network FC differences were evaluated using a dynamic approach (based on sliding-window correlation analysis) and grouping correlation matrices into recurrent FC states. RESULTS:: Dynamic FC analysis revealed, in healthy controls and MS patients, three recurrent FC states: two characterized by strong intra- and inter-network connectivity and one characterized by weak inter-network connectivity (State 3). A total of 23 MS patients were cognitively impaired (CI). Compared to cognitively preserved (CP), CI-MS patients had reduced RS-FC between subcortical and default-mode networks in the low-connectivity State 3 and lower dwell time (i.e. time spent in a given state) in the high-connectivity State 2. CI-MS patients lso exhibited a lower number and a less frequent switching between meta-states, as well as a smaller distance traveled through connectivity states. CONCLUSION: Time-varying RS-FC was markedly less dynamic in CI- versus CP-MS atients, suggesting that slow inter-network connectivity contributes to cognitive dysfunction in MS.

Background Recent studies have created awareness that facial features can be reconstructed from high-resolution MRI. Therefore, data sharing in neuroimaging requires special attention to protect participants’ privacy. Facial features removal (FFR) could alleviate these concerns. We assessed the impact of three FFR methods on subsequent automated image analysis to obtain clinically relevant outcome measurements in three clinical groups. Methods FFR was performed using QuickShear, FaceMasking, and Defacing. In 110 subjects of Alzheimer’s Disease Neuroimaging Initiative, normalized brain volumes (NBV) were measured by SIENAX. In 70 multiple sclerosis patients of the MAGNIMS Study Group, lesion volumes (WMLV) were measured by lesion prediction algorithm in lesion segmentation toolbox. In 84 glioblastoma patients of the PICTURE Study Group, tumor volumes (GBV) were measured by BraTumIA. Failed analyses on FFR-processed images were recorded. Only cases in which all image analyses completed successfully were analyzed. Differences between outcomes obtained from FFR-processed and full images were assessed, by quantifying the intra-class correlation coefficient (ICC) for absolute agreement and by testing for systematic differences using paired t tests. Results Automated analysis methods failed in 0–19% of cases in FFR-processed images versus 0–2% of cases in full images. ICC for absolute agreement ranged from 0.312 (GBV after FaceMasking) to 0.998 (WMLV after Defacing). FaceMasking yielded higher NBV (p = 0.003) and WMLV (p ≤ 0.001). GBV was lower after QuickShear and Defacing (both p < 0.001). Conclusions All three outcome measures were affected differently by FFR, including failure of analysis methods and both “random” variation and systematic differences. Further study is warranted to ensure high-quality neuroimaging research while protecting participants’ privacy.

BACKGROUND: Structural cortical networks (SCNs) represent patterns of coordinated morphological modifications in cortical areas, and they present the advantage of being extracted from previously acquired clinical magnetic resonance imaging (MRI) scans. SCNs have shown pathophysiological changes in many brain disorders, including multiple sclerosis. OBJECTIVE: To investigate alterations of SCNs at the individual level in patients with clinically isolated syndrome (CIS), thereby assessing their clinical relevance. METHODS: We analyzed baseline data collected in a prospective multicenter (MAGNIMS) study. CIS patients (n = 60) and healthy controls (n = 38) underwent high-resolution 3T MRI. Measures of disability and cognitive processing were obtained for patients. Single-subject SCNs were extracted from brain 3D-T1 weighted sequences; global and local network parameters were computed. RESULTS: Compared to healthy controls, CIS patients showed altered small-world topology, an efficient network organization combining dense local clustering with relatively few long-distance connections. These disruptions were worse for patients with higher lesion load and worse cognitive processing speed. Alterations of centrality measures and clustering of connections were observed in specific cortical areas in CIS patients when compared with healthy controls. CONCLUSION: Our study indicates that SCNs can be used to demonstrate clinically relevant alterations of connectivity in CIS.

OBJECTIVE: To characterize the distribution and regional evolution of cervical cord atrophy in patients with multiple sclerosis (MS) in a multicenter dataset. METHODS: MRI and clinical evaluations were acquired from 179 controls and 435 patients (35 clinically isolated syndromes [CIS], 259 relapsing-remitting multiple sclerosis [RRMS], 99 secondary progressive multiple sclerosis [SPMS], and 42 primary progressive multiple sclerosis [PPMS]). Sixty-nine controls and 178 patients underwent a 1-year MRI and clinical follow-up. Patients were classified as clinically stable/worsened according to their disability change. Longitudinal changes of cord atrophy were investigated with linear mixed-effect models. Sample size calculations were performed using age-, sex- and site-adjusted annualized percentage normalized cord cross-sectional area (CSAn) changes. RESULTS: Baseline CSAn was lower in patients with MS vs controls (p < 0.001), but not different between controls and patients with CIS or between patients with early RRMS (disease duration ≤5 years) and patients with CIS. Patients with late RRMS (disease duration >5 years) showed significant cord atrophy vs patients with early RRMS (p = 0.02). Patients with progressive MS had decreased CSAn (p < 0.001) vs patients with RRMS. Atrophy was located between C1/C2 and C5 in patients with RRMS vs patients with CIS, and widespread along the cord in patients with progressive MS vs patients with RRMS, with an additional C5/C6 involvement in patients with SPMS vs patients with PPMS. At follow-up, CSAn decreased in all phenotypes (p < 0.001), except CIS. Cord atrophy rates were highest in patients with early RRMS and clinically worsened patients, who had a more widespread cord involvement than stable patients. The sample size per arm required to detect a 50% treatment effect was 118 for patients with early RRMS. CONCLUSIONS: Cord atrophy increased in MS during 1 year, except for CIS. Faster atrophy contributed to explain clinical worsening.

OBJECTIVE: Spinal cord atrophy is a clinically relevant feature of multiple sclerosis (MS), but longitudinal assessments on magnetic resonance imaging using segmentation-based methods suffer from measurement variability, especially in multicenter studies. We compared the generalized boundary shift integral (GBSI), a registration-based method, with a standard segmentation-based method. METHODS: Baseline and 1-year spinal cord 3-dimensional T1-weighted images (1mm isotropic) were obtained from 282 patients (52 clinically isolated syndrome [CIS], 196 relapsing-remitting MS [RRMS], 34 progressive MS [PMS]), and 82 controls from 8 MAGNIMS (Magnetic Resonance Imaging in Multiple Sclerosis) sites on multimanufacturer and multi-field-strength scans. Spinal Cord Toolbox was used for C2-5 segmentation and cross-sectional area (CSA) calculation. After cord straightening and registration, GBSI measured atrophy based on the probabilistic boundary-shift region of interest. CSA and GBSI percentage annual volume change was calculated. RESULTS: GBSI provided similar rates of atrophy, but reduced measurement variability compared to CSA in all MS subtypes (CIS: -0.95 ± 2.11% vs -1.19 ± 3.67%; RRMS: -1.74 ± 2.57% vs -1.74 ± 4.02%; PMS: -2.29 ± 2.40% vs -1.29 ± 3.20%) and healthy controls (0.02 ± 2.39% vs -0.56 ± 3.77%). GBSI performed better than CSA in differentiating healthy controls from CIS (area under the curve [AUC] = 0.66 vs 0.53; p = 0.03), RRMS (AUC = 0.73 vs 0.59; p < 0.001), PMS (AUC = 0.77 vs 0.53; p < 0.001), and patients with disability progression from patients without progression (AUC = 0.59 vs 0.50; p = 0.04). Sample size to detect 60% treatment effect on spinal cord atrophy over 1 year was lower for GBSI than CSA (CIS: 106 vs 830; RRMS: 95 vs 335; PMS: 44 vs 215; power = 80%; alpha = 5%). INTERPRETATION: The registration-based method (GBSI) allowed better separation between MS patients and healthy controls and improved statistical power, when compared with a conventional segmentation-based method (CSA), although it is still far from perfect.

Machine learning classification is an attractive approach to automatically differentiate patients from healthy subjects, and to predict future disease outcomes. A clinically isolated syndrome (CIS) is often the first presentation of multiple sclerosis (MS), but it is difficult at onset to predict who will have a second relapse and hence convert to clinically definite MS. In this study, we thus aimed to distinguish CIS converters from non-converters at onset of a CIS, using recursive feature elimination and weight averaging with support vector machines. We also sought to assess the influence of cohort size and cross-validation methods on the accuracy estimate of the classification. We retrospectively collected 400 patients with CIS from six European MAGNIMS MS centres. Patients underwent brain MRI at onset of a CIS according to local standard-of-care protocols. The diagnosis of clinically definite MS at one-year follow-up was the standard against which the accuracy of the model was tested. For each patient, we derived MRI-based features, such as grey matter probability, white matter lesion load, cortical thickness, and volume of specific cortical and white matter regions. Features with little contribution to the classification model were removed iteratively through an interleaved sample bootstrapping and feature averaging approach. Classification of CIS outcome at one-year follow-up was performed with 2-fold, 5-fold, 10-fold and leave-one-out cross-validation for each centre cohort independently and in all patients together. The estimated classification accuracy across centres ranged from 64.9% to 88.1% using 2-fold cross-validation and from 73% to 92.9% using leave-one-out cross-validation. The classification accuracy estimate was higher in single-centre, smaller data sets than in combinations of data sets, being the lowest when all patients were merged together. Regional MRI features such as WM lesions, grey matter probability in the thalamus and the precuneus or cortical thickness in the cuneus and inferior temporal gyrus predicted the occurrence of a second relapse in patients at onset of a CIS using support vector machines. The increased accuracy estimate of the classification achieved with smaller and single-centre samples may indicate a model bias (overfitting) when data points were limited, but also more homogeneous. We provide an overview of classifier performance from a range of cross-validation schemes to give insight into the variability across schemes. The proposed recursive feature elimination approach with weight averaging can be used both in single- and multi-centre data sets in order to bridge the gap between group-level comparisons and making predictions for individual patients.

We provide here normative values of yearly percentage brain volume change (PBVC/y) as obtained with Structural Imaging Evaluation, using Normalization, of Atrophy, a widely used open-source software, developing a PBVC/y calculator for assessing the deviation from the expected PBVC/y in patients with neurological disorders. We assessed multicenter (34 centers, 11 acquisition protocols) magnetic resonance imaging data of 720 healthy participants covering the whole adult lifespan (16-90 years). Data of 421 participants with a follow-up > 6 months were used to obtain the normative values for PBVC/y and data of 392 participants with a follow-up <1 month were selected to assess the intrasubject variability of the brain volume measurement. A mixed model evaluated PBVC/y dependence on age, sex, and magnetic resonance imaging parameters (scan vendor and magnetic field strength). PBVC/y was associated with age (p < 0.001), with 60- to 70-year-old participants showing twice more volume decrease than participants aged 30-40 years. PBVC/y was also associated with magnetic field strength, with higher decreases when measured by 1.5T than 3T scanners (p < 0.001). The variability of PBVC/y normative percentiles was narrower as the interscan interval was longer (e.g., 80th normative percentile was 50% smaller for participants with 2-year than with 1-year follow-up). The use of these normative data, eased by the freely available calculator, might help in better discriminating pathological from physiological conditions in the clinical setting.

Importance: The central vein sign has been proposed as a specific imaging biomarker for distinguishing between multiple sclerosis (MS) and not MS, mainly based on findings from ultrahigh-field magnetic resonance imaging (MRI) studies. The diagnostic value of the central vein sign in a multicenter setting with a variety of clinical 3 tesla (T) MRI protocols, however, remains unknown. Objective: To evaluate the sensitivity and specificity of various central vein sign lesion criteria for differentiating MS from non-MS conditions using 3T brain MRI with various commonly used pulse sequences. Design, Setting, and Participants: This large multicenter, cross-sectional study enrolled participants (n = 648) of ongoing observational studies and patients included in neuroimaging research databases of 8 neuroimaging centers in Europe. Patient enrollment and MRI data collection were performed between January 1, 2010, and November 30, 2016. Data analysis was conducted between January 1, 2016, and April 30, 2018. Investigators were blinded to participant diagnosis by a novel blinding procedure. Main Outcomes and Measures: Occurrence of central vein sign was detected on 3T T2*-weighted or susceptibility-weighted imaging. Sensitivity and specificity were assessed for these MRI sequences and for different central vein sign lesion criteria, which were defined by the proportion of lesions with central vein sign or by absolute numbers of lesions with central vein sign. Results: A total of 606 participants were included in the study after exclusion of 42 participants. Among the 606 participants, 413 (68.2%) were women. Patients with clinically isolated syndrome and relapsing-remitting MS (RRMS) included 235 women (66.6%) and had a median (range) age of 37 (14.7-61.4) years, a median (range) disease duration of 2 (0-33) years, and a median (range) Expanded Disability Status Scale score of 1.5 (0-6.5). Patients without MS included 178 women (70.4%) and had a median (range) age of 54 (18-83) years. A total of 4447 lesions were analyzed in a total of 487 patients: 690 lesions in 98 participants with clinically isolated syndrome, 2815 lesions in 225 participants with RRMS, 54 lesions in 13 participants with neuromyelitis optica spectrum disorder, 54 lesions in 14 participants with systemic lupus erythematosus, 121 lesions in 29 participants with migraine or cluster headache, 240 lesions in 20 participants with diabetes, and 473 lesions in 88 participants with other types of small-vessel disease. The sensitivity was 68.1% and specificity was 82.9% for distinguishing MS from not MS using a 35% central vein sign proportion threshold. The 3 central vein sign lesion criteria had a sensitivity of 61.9% and specificity of 89.0%. Sensitivity was higher when an optimized T2*-weighted sequence was used. Conclusions and Relevance: In this study, use of the central vein sign at 3T MRI yielded a high specificity and a moderate sensitivity in differentiating MS from not MS; international, multicenter studies may be needed to ascertain whether the central vein sign-based criteria can accurately detect MS.

BACKGROUND: Compared to 1.5 T, 3 T magnetic resonance imaging (MRI) increases signal-to-noise ratio leading to improved image quality. However, its clinical relevance in clinically isolated syndrome suggestive of multiple sclerosis remains uncertain. OBJECTIVES: The purpose of this study was to investigate how 3 T MRI affects the agreement between raters on lesion detection and diagnosis. METHODS: We selected 30 patients and 10 healthy controls from our ongoing prospective multicentre cohort. All subjects received baseline 1.5 and 3 T brain and spinal cord MRI. Patients also received follow-up brain MRI at 3-6 months. Four experienced neuroradiologists and four less-experienced raters scored the number of lesions per anatomical region and determined dissemination in space and time (McDonald 2010). RESULTS: In controls, the mean number of lesions per rater was 0.16 at 1.5 T and 0.38 at 3 T ( p = 0.005). For patients, this was 4.18 and 4.40, respectively ( p = 0.657). Inter-rater agreement on involvement per anatomical region and dissemination in space and time was moderate to good for both field strengths. 3 T slightly improved agreement between experienced raters, but slightly decreased agreement between less-experienced raters. CONCLUSION: Overall, the interobserver agreement was moderate to good. 3 T appears to improve the reading for experienced readers, underlining the benefit of additional training.

Purpose To compare available methods for whole-brain and gray matter (GM) atrophy estimation in multiple sclerosis (MS) in terms of repeatability (same magnetic resonance [MR] imaging unit) and reproducibility (different system/field strength) for their potential clinical applications. Materials and Methods The softwares ANTs-v1.9, CIVET-v2.1, FSL-SIENAX/SIENA-5.0.1, Icometrix-MSmetrix-1.7, and SPM-v12 were compared. This retrospective study, performed between March 2015 and March 2017, collected data from (a) eight simulated MR images and longitudinal data (2 weeks) from 10 healthy control subjects to assess the cross-sectional and longitudinal accuracy of atrophy measures, (b) test-retest MR images in 29 patients with MS acquired within the same day at different imaging unit field strengths/manufacturers to evaluate precision, and (c) longitudinal data (1 year) in 24 patients with MS for the agreement between methods. Tissue segmentation, image registration, and white matter (WM) lesion filling were also evaluated. Multiple paired t tests were used for comparisons. Results High values of accuracy (0.87-0.97) for whole-brain and GM volumes were found, with the lowest values for MSmetrix. ANTs showed the lowest mean error (0.02%) for whole-brain atrophy in healthy control subjects, with a coefficient of variation of 0.5%. SPM showed the smallest mean error (0.07%) and coefficient of variation (0.08%) for GM atrophy. Globally, good repeatability (P > .05) but poor reproducibility (P < .05) were found for all methods. WM lesion filling technique mainly affected ANTs, MSmetrix, and SPM results (P < .05). Conclusion From this comparison, it would be possible to select a software for atrophy measurement, depending on the requirements of the application (research center, clinical trial) and its goal (accuracy and repeatability or reproducibility). An improved reproducibility is required for clinical application.

Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple sclerosis and late atrophy in primary-progressive multiple sclerosis. Patients with secondary-progressive multiple sclerosis showed the highest event-based model stage (the highest number of atrophic regions, P < 0.001) at the study entry. All multiple sclerosis phenotypes, but clinically isolated syndrome, showed a faster rate of increase in the event-based model stage than healthy controls. T2 lesion load and disease duration in all patients were associated with increased event-based model stage, but no effects of disease-modifying treatments and comorbidity on event-based model stage were observed. The annualized rate of event-based model stage was associated with the disability accumulation in relapsing-remitting multiple sclerosis, independent of disease duration (P < 0.0001). The data-driven staging of atrophy progression in a large multiple sclerosis sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across multiple sclerosis phenotypes. The spread of atrophy was associated with disease duration and with disability accumulation over time in relapsing-remitting multiple sclerosis.

BACKGROUND: In 2016, the Magnetic Resonance Imaging in Multiple Sclerosis (MAGNIMS) network proposed modifications to the MRI criteria to define dissemination in space (DIS) and time (DIT) for the diagnosis of multiple sclerosis in patients with clinically isolated syndrome (CIS). Changes to the DIS definition included removal of the distinction between symptomatic and asymptomatic lesions, increasing the number of lesions needed to define periventricular involvement to three, combining cortical and juxtacortical lesions, and inclusion of optic nerve evaluation. For DIT, removal of the distinction between symptomatic and asymptomatic lesions was suggested. We compared the performance of the 2010 McDonald and 2016 MAGNIMS criteria for multiple sclerosis diagnosis in a large multicentre cohort of patients with CIS to provide evidence to guide revisions of multiple sclerosis diagnostic criteria. METHODS: Brain and spinal cord MRI and optic nerve assessments from patients with typical CIS suggestive of multiple sclerosis done less than 3 months from clinical onset in eight European multiple sclerosis centres were included in this retrospective study. Eligible patients were 16-60 years, and had a first CIS suggestive of CNS demyelination and typical of relapsing-remitting multiple sclerosis, a complete neurological examination, a baseline brain and spinal cord MRI scan obtained less than 3 months from clinical onset, and a follow-up brain scan obtained less than 12 months from CIS onset. We recorded occurrence of a second clinical attack (clinically definite multiple sclerosis) at months 36 and 60. We evaluated MRI criteria performance for DIS, DIT, and DIS plus DIT with a time-dependent receiver operating characteristic curve analysis. FINDINGS: Between June 16, 1995, and Jan 27, 2017, 571 patients with CIS were screened, of whom 368 met all study inclusion criteria. At the last evaluation (median 50·0 months [IQR 27·0-78·4]), 189 (51%) of 368 patients developed clinically definite multiple sclerosis. At 36 months, the two DIS criteria showed high sensitivity (2010 McDonald 0·91 [95% CI 0·85-0·94] and 2016 MAGNIMS 0·93 [0·88-0·96]), similar specificity (0·33 [0·25-0·42] and 0·32 [0·24-0·41]), and similar area under the curve values (AUC; 0·62 [0·57-0·67] and 0·63 [0·58-0·67]). Performance was not affected by inclusion of symptomatic lesions (sensitivity 0·92 [0·87-0·96], specificity 0·31 [0·23-0·40], AUC 0·62 [0·57-0·66]) or cortical lesions (sensitivity 0·92 [0·87-0·95], specificity 0·32 [0·24-0·41], AUC 0·62 [0·57-0·67]). Requirement of three periventricular lesions resulted in slightly lower sensitivity (0·85 [0·78-0·90], slightly higher specificity (0·40 [0·32-0·50], and similar AUC (0·63 [0·57-0·68]). Inclusion of optic nerve evaluation resulted in similar sensitivity (0·92 [0·87-0·96]), and slightly lower specificity (0·26 [0·18-0·34]) and AUC (0·59 [0·55-0·64]). AUC values were also similar for DIT (2010 McDonald 0·61 [0·55-0·67] and 2016 MAGNIMS 0·61 [0·55-0·66]) and DIS plus DIT (0·62 [0·56-0·67] and 0·64 [0·58-0·69]). INTERPRETATION: The 2016 MAGNIMS criteria showed similar accuracy to the 2010 McDonald criteria in predicting the development of clinically definite multiple sclerosis. Inclusion of symptomatic lesions is expected to simplify the clinical use of MRI criteria without reducing accuracy, and our findings suggest that needing three lesions to define periventricular involvement might slightly increase specificity, suggesting that these two factors could be considered during further revisions of multiple sclerosis diagnostic criteria.

BJECTIVE: Gray matter (GM) atrophy occurs in all multiple sclerosis (MS) phenotypes. We investigated whether there is a spatiotemporal pattern of GM atrophy that is associated with faster disability accumulation in MS. METHODS: We analyzed 3,604 brain high-resolution T1-weighted magnetic resonance imaging scans from 1,417 participants: 1,214 MS patients (253 clinically isolated syndrome [CIS], 708 relapsing-remitting [RRMS], 128 secondary-progressive [SPMS], and 125 primary-progressive [PPMS]), over an average follow-up of 2.41 years (standard deviation [SD] = 1.97), and 203 healthy controls (HCs; average follow-up = 1.83 year; SD = 1.77), attending seven European centers. Disability was assessed with the Expanded Disability Status Scale (EDSS). We obtained volumes of the deep GM (DGM), temporal, frontal, parietal, occipital and cerebellar GM, brainstem, and cerebral white matter. Hierarchical mixed models assessed annual percentage rate of regional tissue loss and identified regional volumes associated with time-to-EDSS progression. RESULTS: SPMS showed the lowest baseline volumes of cortical GM and DGM. Of all baseline regional volumes, only that of the DGM predicted time-to-EDSS progression (hazard ratio = 0.73; 95% confidence interval, 0.65, 0.82; p < 0.001): for every standard deviation decrease in baseline DGM volume, the risk of presenting a shorter time to EDSS worsening during follow-up increased by 27%. Of all longitudinal measures, DGM showed the fastest annual rate of atrophy, which was faster in SPMS (-1.45%), PPMS (-1.66%), and RRMS (-1.34%) than CIS (-0.88%) and HCs (-0.94%; p < 0.01). The rate of temporal GM atrophy in SPMS (-1.21%) was significantly faster than RRMS (-0.76%), CIS (-0.75%), and HCs (-0.51%). Similarly, the rate of parietal GM atrophy in SPMS (-1.24-%) was faster than CIS (-0.63%) and HCs (-0.23%; all p values <0.05). Only the atrophy rate in DGM in patients was significantly associated with disability accumulation (beta = 0.04; p < 0.001). INTERPRETATION: This large, multicenter and longitudinal study shows that DGM volume loss drives disability accumulation in MS, and that temporal cortical GM shows accelerated atrophy in SPMS than RRMS. The difference in regional GM atrophy development between phenotypes needs to be taken into account when evaluating treatment effect of therapeutic interventions.

BACKGROUND AND PURPOSE: In vivoidentification 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.

BACKGROUND AND PURPOSE: The structural MR imaging correlates of cognitive impairment in multiple sclerosis are still debated. This study assessed lesional and atrophy measures of white matter and gray matter involvement in patients with MS acquired in 7 European sites to identify the MR imaging variables most closely associated with cognitive dysfunction. MATERIALS AND METHODS: Brain dual-echo, 3D T1-weighted, and double inversion recovery scans were acquired at 3T from 62 patients with relapsing-remitting MS and 65 controls. Patients with at least 2 neuropsychological tests with abnormal findings were considered cognitively impaired. Focal WM and cortical lesions were identified, and volumetric measures from WM, cortical GM, the hippocampus, and deep GM nuclei were obtained. Age- and site-adjusted models were used to compare lesion and volumetric MR imaging variables between patients with MS who were cognitively impaired and cognitively preserved. A multivariate analysis identified MR imaging variables associated with cognitive scores and disability. RESULTS: Twenty-three patients (38%) were cognitively impaired. Compared with those with who were cognitively preserved, patients with MS with cognitive impairment had higher T2 and T1 lesion volumes and a trend toward a higher number of cortical lesions. Significant brain, cortical GM, hippocampal, deep GM nuclei, and WM atrophy was found in patients with MS with cognitive impairment versus those who were cognitively preserved. Hippocampal and deep GM nuclei atrophy were the best predictors of cognitive impairment, while WM atrophy was the best predictor of disability. CONCLUSIONS: Hippocampal and deep GM nuclei atrophy are key factors associated with cognitive impairment in MS. These MR imaging measures could be applied in a multicenter context, with cognition as clinical outcome.

BACKGROUND AND PURPOSE: The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. MATERIALS AND METHODS: The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. RESULTS: We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). CONCLUSIONS: The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS.

OBJECTIVE: To provide new insights into the role of markers of response to interferon-β therapy in multiple sclerosis (MS) in a multicenter setting, focusing on the relevance of MRI lesions in combination with clinical variables. METHODS: A large multicenter clinical dataset was collected within the Magnetic Resonance Imaging in MS (MAGNIMS) network. This included a large cohort of patients with relapsing-remitting MS on interferon-β treatment, MRI and clinical assessments during the first year of treatment, and clinical follow-up of at least 2 additional years. Heterogeneity among centers was assessed before pooling the data. The association of 1-year MRI or clinical relapses with the risk of treatment failure (defined as Expanded Disability Status Scale [EDSS] worsening or treatment switch for inefficacy) and of EDSS worsening alone was evaluated using multivariate Cox models. RESULTS: A pooled dataset of 1,280 patients with relapsing-remitting MS from 9 MAGNIMS centers was analyzed. The risk of failure had a relevant increase with 1 relapse (hazard ratio [HR] 1.84, 95% confidence interval [CI] 1.39-2.44, p < 0.001) and ≥3 new T2 lesions (HR 1.55, 95% CI 0.92-2.60, p = 0.09). In patients without relapses and less than 3 new T2 lesions, the 3-year risk of failure and EDSS worsening were 17% and 15%; in patients with 1 relapse or ≥3 new T2 lesions, the risks were 27% and 22%; in patients with both conditions or more than 1 relapse, the risks were 48% (p < 0.001) and 29% (p < 0.001). CONCLUSIONS: Substantial MRI activity, particularly if in combination with clinical relapses, during the first year of treatment with interferon-β indicates significant risk of treatment failure and EDSS worsening in the short term.

OBJECTIVES: The objectives of this paper are to compare in a multicenter setting patterns of regional cortical thickness in patients with relapsing-remitting multiple sclerosis (RRMS) and cognitive impairment (CI) and those cognitively preserved (CP), and explore the relationship between cortical thinning and cognitive performance. METHODS: T1-weighted isotropic brain scans were collected at 3T from seven European centers in 60 RRMS patients and 65 healthy controls (HCs). Patients underwent clinical and neuropsychological examinations. Cortical thickness (CTh) measures were calculated using FreeSurfer (failing in four) and both lobar and vertex-based general linear model (GLM) analyses were compared between study groups. RESULTS: Twenty (36%) MS patients were classified as CI. Mean global CTh was smaller in RRMS patients compared to HCs (left 2.43 vs. 2.53 mm, right 2.44 vs. 2.54 mm, p < 0.001). Multivariate GLM regional analysis showed significantly more temporal thinning in CI compared to CP patients. Verbal memory scores correlated to regional cortical thinning in the insula whereas visual memory scores correlated to parietal thinning. CONCLUSIONS: This multicenter study showed mild global cortical thinning in RRMS. The extent of thinning is less pronounced than previously reported. Only subtle regional differences between CI and CP patients were observed, some of which related to specific cognitive domains.

In a multicenter setting, we applied voxel-based methods to different structural MR imaging modalities to define the relative contributions of focal lesions, normal-appearing white matter (NAWM), and gray matter (GM) damage and their regional distribution to cognitive deficits as well as impairment of specific cognitive domains in multiple sclerosis (MS) patients. Approval of the institutional review boards was obtained, together with written informed consent from all participants. Standardized neuropsychological assessment and conventional, diffusion tensor and volumetric brain MRI sequences were collected from 61 relapsing-remitting MS patients and 61 healthy controls (HC) from seven centers. Patients with ≥2 abnormal tests were considered cognitively impaired (CI). The distribution of focal lesions, GM and WM atrophy, and microstructural WM damage were assessed using voxel-wise approaches. A random forest analysis identified the best imaging predictors of global cognitive impairment and deficits of specific cognitive domains. Twenty-three (38%) MS patients were CI. Compared with cognitively preserved (CP), CI MS patients had GM atrophy of the left thalamus, right hippocampus and parietal regions. They also showed atrophy of several WM tracts, mainly located in posterior brain regions and widespread WM diffusivity abnormalities. WM diffusivity abnormalities in cognitive-relevant WM tracts followed by atrophy of cognitive-relevant GM regions explained global cognitive impairment. Variable patterns of NAWM and GM damage were associated with deficits in selected cognitive domains. Structural, multiparametric, voxel-wise MRI approaches are feasible in a multicenter setting. The combination of different imaging modalities is needed to assess and monitor cognitive impairment in MS.

Purpose To study the concomitant use of structural and functional magnetic resonance (MR) imaging correlates to explain information processing speed (IPS) and executive function (EF) in multiple sclerosis (MS). Materials and Methods Local ethics committee approval was obtained at all sites for this prospective, multicenter study. All subjects provided written informed consent. Twenty-six patients with relapsing-remitting MS and 32 healthy control subjects from four centers underwent structural and functional MR imaging, including a go/no-go task and neuropsychological assessment. Subtests of the Brief Repeatable Battery of Neuropsychological Tests, the Wisconsin Card Sorting Test, and the performance with the functional MR imaging paradigm were used as estimates of IPS and EF. Activation of the thalamus and the inferior frontal gyrus (pars triangularis), thalamic volume, T2 lesion load, and age were used to explain IPS and EF in regression models. Results Compared with control subjects, patients showed increased activation in a frontoparietal network, including both thalami, during the execution of the go/no-go task. Patients had decreased thalamic volume (P < .001). Among tested variables, thalamic volume (β = 0.606, P = .001), together with thalamic activation (β = -0.410, P = .022), were the best predictors of IPS and EF and helped explain 52.7% of the variance in IPS and EF. Conclusion This study highlights the potential of the combined use of functional and morphologic parameters to explain IPS and EF in patients with relapsing-remitting MS and confirms the central role of the thalamus as a relay station in executive functioning.

Background: In multiple sclerosis (MS), diffusion tensor and magnetisation transfer imaging are both abnormal in lesional and extra-lesional cortical grey matter, but differences between clinical subtypes and associations with clinical outcomes have only been partly assessed. Objective: To compare mean diffusivity, fractional anisotropy and magnetisation transfer ratio (MTR) in cortical grey matter lesions (detected using phase-sensitive inversion recovery (PSIR) imaging) and extralesional cortical grey matter, and assess associations with disability in relapse-onset MS. Methods: Seventy-two people with MS (46 relapsing–remitting (RR), 26 secondary progressive (SP)) and 36 healthy controls were included in this study. MTR, mean diffusivity and fractional anisotropy were measured in lesional and extra-lesional cortical grey matter. Results: Mean fractional anisotropy was higher and MTR lower in lesional compared with extra-lesional cortical grey matter. In extra-lesional cortical grey matter mean fractional anisotropy and MTR were lower, and mean diffusivity was higher in the MS group compared with controls. Mean MTR was lower and mean diffusivity was higher in lesional and extra-lesional cortical grey matter in SPMS when compared with RRMS. These differences were independent of disease duration. In multivariate analyses, MTR in extra-lesional more so than lesional cortical grey matter was associated with disability. Conclusion: Magnetic resonance abnormalities in lesional and extra-lesional cortical grey matter are greater in SPMS than RRMS. Changes in extra-lesional compared with lesional cortical grey matter are more consistently associated with disability.

BACKGROUND: Leber's hereditary optic neuropathy (LHON) and a multiple sclerosis (MS)-like illness appear to coexist 50 times more frequently than would be expected by chance. This association of LHON and MS (LMS) raises an important question about whether there could be a common pathophysiological mechanism involving mitochondrial dysfunction. OBJECTIVE: The primary aim was to define MRI features of LMS and LHON, and to assess the proportions of individuals displaying features typical of MS. Secondarily, we investigated the effect of gender on the risk of developing white matter lesions in the context of LHON. METHODS: A blinded standardised review of conventional brain MRIs of 30 patients with MS, 31 patients with LHON and 11 patients with LMS was conducted by three independent experts in the field. MS-like MRI features were assessed. RESULTS: All patients with LMS and 26% of patients with LHON had white matter lesions. Of these, all patients with LMS and 25% with LHON were found to have an MRI appearance typical of MS. Female patients with LHON had a significantly greater risk of having white matter lesions consistent with MS compared with male patients (relative risk 8.3). CONCLUSIONS: A blinded review of conventional brain MRIs shows that patients with LMS have a scan appearance indistinguishable from MS. Mitochondrial dysfunction could be a common pathophysiological pathway in the formation of white matter lesions. There appears to be a strong female influence on the radiological appearance as well as clinical development of MS in patients with LHON.

In this multicenter study, we applied functional magnetic resonance imaging (fMRI) to define the functional correlates of cognitive dysfunction in patients with multiple sclerosis (MS). fMRI scans during the performance of the N-back task were acquired from 42 right-handed relapsing remitting (RR) MS patients and 52 sex-matched right-handed healthy controls, studied at six European sites using 3.0 Tesla scanners. Patients with at least two abnormal (<2 standard deviations from the normative values) neuropsychological tests at a standardized evaluation were considered cognitively impaired (CI). FMRI data were analyzed using the SPM8 software, modeling regions showing load-dependent activations/deactivations with increasing task difficulty. Twenty (47%) MS patients were CI. During the N-back load condition, compared to controls and CI patients, cognitively preserved (CP) patients had increased recruitment of the right dorsolateral prefrontal cortex. As a function of increasing task difficulty, CI MS patients had reduced activations of several areas located in the fronto-parieto-temporal lobes as well as reduced deactivations of regions which are part of the default mode network compared to the other two groups. Significant correlations were found between abnormal fMRI patterns of activations and deactivations and behavioral measures, cognitive performance, and brain T2 and T1 lesion volumes. This multicenter study supports the theory that a preserved fMRI activity of the frontal lobe is associated with a better cognitive profile in MS patients. It also indicates the feasibility of fMRI to monitor disease evolution and treatment effects in future studies.

BACKGROUND: Non-enhancing black holes (neBHs) are more common in multiple sclerosis (MS) patients with longer disease durations and progressive disease subtypes. OBJECTIVE: Our aim was to analyse the added value of neBHs in patients with clinically isolated syndromes (CISs) for predicting conversion to clinically definite MS (CDMS). METHODS: Patients were classified based on the presence or absence of neBHs and on the number of Barkhof-Tintoré (B-T) criteria fulfilled. Dissemination in space (DIS) was defined as the presence of at least three of the four B-T criteria. Dissemination in time (DIT)1 was defined by simultaneous presence of enhancing and non-enhancing lesions. DIT2 was defined by simultaneous presence of neBHs and T2 lesions not apparent on T1-weighted images. RESULTS: Focal T2-hyperintense brain lesions were identified in 87.7% of the 520 CIS patients, and 41.4% of them presented at least one neBH. Patients meeting DIS, DIT1, and DIT2 had a significantly higher rate of conversion to CDMS. After adjusting for DIS, only patients who fulfilled DIT1 preserved a significant increase in CDMS conversion. CONCLUSIONS: Non-enhancing black holes in CIS patients are associated with a higher risk of conversion to CDMS. However, the predictive value of this finding is lost when added to the DIS criteria.

BACKGROUND: Understanding long-term disability in multiple sclerosis (MS) is a key goal of research; it is relevant to how we monitor and treat the disease. OBJECTIVES: The Magnetic Imaging in MS (MAGNIMS) collaborative group sought to determine the relationship of brain lesion load, and brain and spinal cord atrophy, with physical disability in patients with long-established MS. METHODS: Patients had a magnetic resonance imaging (MRI) scan of their brain and spinal cord, from which we determined brain grey (GMF) and white matter (WMF) fractional volumes, upper cervical spinal cord cross-sectional area (UCCA) and brain T2-lesion volume (T2LV). We assessed patient disability using the Expanded Disability Status Scale (EDSS). We analysed associations between EDSS and MRI measures, using two regression models (dividing cohort by EDSS into two and four sub-groups). RESULTS: In the binary model, UCCA (p < 0.01) and T2LV (p = 0.02) were independently associated with the requirement of a walking aid. In the four-category model UCCA (p < 0.01), T2LV (p = 0.02) and GMF (p = 0.04) were independently associated with disability. CONCLUSIONS: Long-term physical disability was independently linked with atrophy of the spinal cord and brain T2 lesion load, and less consistently, with brain grey matter atrophy. Combinations of spinal cord and brain MRI measures may be required to capture clinically-relevant information in people with MS of long disease duration.

OBJECTIVE: To determine whether brain atrophy and lesion volumes predict subsequent 10 year clinical evolution in multiple sclerosis (MS). DESIGN: From eight MAGNIMS (MAGNetic resonance Imaging in MS) centres, we retrospectively included 261 MS patients with MR imaging at baseline and after 1-2 years, and Expanded Disability Status Scale (EDSS) scoring at baseline and after 10 years. Annualised whole brain atrophy, central brain atrophy rates and T2 lesion volumes were calculated. Patients were categorised by baseline diagnosis as primary progressive MS (n=77), clinically isolated syndromes (n=18), relapsing-remitting MS (n=97) and secondary progressive MS (n=69). Relapse onset patients were classified as minimally impaired (EDSS=0-3.5, n=111) or moderately impaired (EDSS=4-6, n=55) according to their baseline disability (and regardless of disease type). Linear regression models tested whether whole brain and central atrophy, lesion volumes at baseline, follow-up and lesion volume change predicted 10 year EDSS and MS Severity Scale scores. RESULTS: In the whole patient group, whole brain and central atrophy predicted EDSS at 10 years, corrected for imaging protocol, baseline EDSS and disease modifying treatment. The combined model with central atrophy and lesion volume change as MRI predictors predicted 10 year EDSS with R(2)=0.74 in the whole group and R(2)=0.72 in the relapse onset group. In subgroups, central atrophy was predictive in the minimally impaired relapse onset patients (R(2)=0.68), lesion volumes in moderately impaired relapse onset patients (R(2)=0.21) and whole brain atrophy in primary progressive MS (R(2)=0.34). CONCLUSIONS: This large multicentre study points to the complementary predictive value of atrophy and lesion volumes for predicting long term disability in MS.

OBJECTIVES: To assess in a large population of patients with clinically isolated syndrome (CIS) the relevance of brain lesion location and frequency in predicting 1-year conversion to multiple sclerosis (MS). METHODS: In this multicenter, retrospective study, clinical and MRI data at onset and clinical follow-up at 1 year were collected for 1,165 patients with CIS. On T2-weighted MRI, we generated lesion probability maps of white matter (WM) lesion location and frequency. Voxelwise analyses were performed with a nonparametric permutation-based approach (p < 0.05, cluster-corrected). RESULTS: In CIS patients with hemispheric, multifocal, and brainstem/cerebellar onset, lesion probability map clusters were seen in clinically eloquent brain regions. Significant lesion clusters were not found in CIS patients with optic nerve and spinal cord onset. At 1 year, clinically definite MS developed in 26% of patients. The converting group, despite a greater baseline lesion load compared with the nonconverting group (7 ± 8.1 cm3 vs. 4.6 ± 6.7 cm3, p < 0.001), showed less widespread lesion distribution (18% vs. 25% of brain voxels occupied by lesions). High lesion frequency was found in the converting group in projection, association, and commissural WM tracts, with larger clusters being in the corpus callosum, corona radiata, and cingulum. CONCLUSIONS: Higher frequency of lesion occurrence in clinically eloquent WM tracts can characterize CIS subjects with different types of onset. The involvement of specific WM tracts, in particular those traversed by fibers involved in motor function and near the corpus callosum, seems to be associated with a higher risk of clinical conversion to MS in the short term.

BACKGROUND: Brain atrophy studies often use FSL-BET (Brain Extraction Tool) as the first step of image processing. Default BET does not always give satisfactory results on 3DT1 MR images, which negatively impacts atrophy measurements. Finding the right alternative BET settings can be a difficult and time-consuming task, which can introduce unwanted variability. AIM: To systematically analyze the performance of BET in images of MS patients by varying its parameters and options combinations, and quantitatively comparing its results to a manual gold standard. METHODS: Images from 159 MS patients were selected from different MAGNIMS consortium centers, and 16 different 3DT1 acquisition protocols at 1.5 T or 3T. Before running BET, one of three pre-processing pipelines was applied: (1) no pre-processing, (2) removal of neck slices, or (3) additional N3 inhomogeneity correction. Then BET was applied, systematically varying the fractional intensity threshold (the "f" parameter) and with either one of the main BET options ("B" - bias field correction and neck cleanup, "R" - robust brain center estimation, or "S" - eye and optic nerve cleanup) or none. For comparison, intracranial cavity masks were manually created for all image volumes. FSL-FAST (FMRIB's Automated Segmentation Tool) tissue-type segmentation was run on all BET output images and on the image volumes masked with the manual intracranial cavity masks (thus creating the gold-standard tissue masks). The resulting brain tissue masks were quantitatively compared to the gold standard using Dice overlap coefficient (DOC). Normalized brain volumes (NBV) were calculated with SIENAX. NBV values obtained using for SIENAX other BET settings than default were compared to gold standard NBV with the paired t-test. RESULTS: The parameter/preprocessing/options combinations resulted in 20,988 BET runs. The median DOC for default BET (f=0.5, g=0) was 0.913 (range 0.321-0.977) across all 159 native scans. For all acquisition protocols, brain extraction was substantially improved for lower values of "f" than the default value. Using native images, optimum BET performance was observed for f=0.2 with option "B", giving median DOC=0.979 (range 0.867-0.994). Using neck removal before BET, optimum BET performance was observed for f=0.1 with option "B", giving median DOC 0.983 (range 0.844-0.996). Using the above BET-options for SIENAX instead of default, the NBV values obtained from images after neck removal with f=0.1 and option "B" did not differ statistically from NBV values obtained with gold-standard. CONCLUSION: Although default BET performs reasonably well on most 3DT1 images of MS patients, the performance can be improved substantially. The removal of the neck slices, either externally or within BET, has a marked positive effect on the brain extraction quality. BET option "B" with f=0.1 after removal of the neck slices seems to work best for all acquisition protocols. Copyright © 2012 Elsevier Inc. All rights reserved.

BACKGROUND AND OBJECTIVES: We evaluated clinical and conventional MRI features of a large population of patients with non-disabling MS to identify potential markers of a benign disease course. METHODS: In seven MAGNIMS centres we retrospectively identified 182 patients with benign (B) MS (EDSS score ≤ 3.0, disease duration ≥ 15 years) and 187 patients with non-disabling relapsing-remitting MS (NDRRMS) (Expanded Disability Status Scale score ≤ 3.0, disease duration between 5 and 14 years), in whom clinical data were collected within two weeks from a brain T2-weighted scan. Brain T2 lesion volume (LV) was measured in all patients. In 146 BMS and 146 NDRRMS patients, clinical data were also available after a median follow up of 29 months (range: 7-104 months). RESULTS: Mean LV was higher in BMS than in NDRRMS patients (p<0.001), but the mean ratio between LV and disease duration was higher in NDRRMS than in BMS patients (1.1 vs. 0.6 ml/year, p<0.001). In BMS patients, brain LV was correlated with EDSS score increase at follow up (r=0.18, p=0.03). CONCLUSIONS: An overall low rate of brain LV increase during a long-lasting disease course might be a feature of BMS. In BMS patients, a high brain LV might be associated with worsening of locomotor disability at short-term follow up.

OBJECTIVES: Prediction of long term clinical outcome in patients with primary progressive multiple sclerosis (PPMS) using imaging has important clinical implications, but remains challenging. We aimed to determine whether spatial location of T2 and T1 brain lesions predicts clinical progression during a 10-year follow-up in PPMS. METHODS: Lesion probability maps of the T2 and T1 brain lesions were generated using the baseline scans of 80 patients with PPMS who were clinically assessed at baseline and then after 1, 2, 5 and 10 years. For each patient, the time (in years) taken before bilateral support was required to walk (time to event (TTE)) was used as a measure of progression rate. The probability of each voxel being 'lesional' was correlated with TTE, adjusting for age, gender, disease duration, centre and spinal cord cross sectional area, using a multiple linear regression model. To identify the best, independent predictor of progression, a Cox regression model was used. RESULTS: A significant correlation between a shorter TTE and a higher probability of a voxel being lesional on T2 scans was found in the bilateral corticospinal tract and superior longitudinal fasciculus, and in the right inferior fronto-occipital fasciculus (p<0.05). The best predictor of progression rate was the T2 lesion load measured along the right inferior fronto-occipital fasciculus (p=0.016, hazard ratio 1.00652, 95% CI 1.00121 to 1.01186). CONCLUSION: Our results suggest that the location of T2 brain lesions in the motor and associative tracts is an important contributor to the progression of disability in PPMS, and is independent of spinal cord involvement.

PURPOSE: To assess the effect on diffusion tensor (DT) magnetic resonance imaging (MRI) of acquiring data with different scanners. MATERIALS AND METHODS: Forty-four healthy controls and 36 multiple sclerosis patients with low disability were studied using eight MR scanners with acquisition protocols that were as close to a standard protocol as possible. Between 7 and 13 subjects were studied in each center. Region-of-interest (ROI) and histogram-based analyses of fractional anisotropy (FA), axial (D(ax)), radial (D(rad)), and mean diffusivity (MD) were performed. The influence of variables such as the acquisition center and the control/patient group was determined with an analysis of variance (ANOVA) test. RESULTS: The patient/control group explained approximately 25% of data variability of FA and D(rad) from midsagittal corpus callosum (CC) ROIs. Global FA, MD, and D(rad) in the white matter differentiated patients from controls, but with lower discriminatory power than for the CC. In the gray matter, MD discriminated patients from controls (30% of variability explained by group vs. 17% by center). CONCLUSION: Significant variability of DT-MRI data can be attributed to the acquisition center, even when a standardized protocol is used. The use of appropriate segmentation methods and statistical models allows DT-derived metrics to differentiate patients from healthy controls.

OBJECTIVE: To assess the time course of brain atrophy and the difference across clinical subtypes in multiple sclerosis (MS). METHODS: The percent brain volume change (PBVC) was computed on existing longitudinal (2 time points) T1-weighted MRI from untreated (trial and nontrial) patients with MS. Patients (n = 963) were classified as clinically isolated syndromes suggestive of MS (CIS, 16%), relapsing-remitting (RR, 60%), secondary progressive (SP, 15%), and primary progressive (9%) MS. The median length of follow-up was 14 months (range 12-68). RESULTS: There was marked heterogeneity of the annualized PBVC (PBVC/y) across MS subtypes (p = 0.003), with higher PBVC/y in SP than in CIS (p = 0.003). However, this heterogeneity disappeared when data were corrected for the baseline normalized brain volume. When the MS population was divided into trial and nontrial subjects, the heterogeneity of PBVC/y across MS subtypes was present only in the second group, due to the higher PBVC/y values found in trial data in CIS (p = 0.01) and RR (p < 0.001). The estimation of the sample sizes required for demonstrating a reduction of brain atrophy in patients in a placebo-controlled trial showed that this was larger in patients with early MS than in those with the progressive forms of the disease. CONCLUSIONS: This first large study in untreated patients with multiple sclerosis (MS) with different disease subtypes shows that brain atrophy proceeds relentlessly throughout the course of MS, with a rate that seems largely independent of the MS subtype, when adjusting for baseline brain volume.

Phase III definitive treatment trials of new multiple sclerosis (MS) therapies now routinely incorporate an annual magnetic resonance imaging protocol, with change in T2-weighted brain lesion load providing an important outcome measure. To date the accepted strategy has been to perform a core imaging protocol on all patients in such studies. The aim of this study was to provide power calculations based on this MRI endpoint. Serial MRI data from 128 patients with either relapsing remitting (RR) or secondary progressive (SP) MS were used to calculate sample size requirements using a repeated measures analysis of variance design. We provide sample size calculations based on various follow-up intervals and effect sizes. Sample sizes for the SPMS cohort were substantially larger than for the RRMS group, reflecting the greater variance in lesion load changes between patients in the SPMS group. With a follow-up of 3 years, we estimate that only 12 and 33 patients per arm are needed to show stabilisation of MRI lesion load in the RRMS and SPMS groups, respectively. Our results suggest that ongoing phase III treatment trials are more than adequately powered to detect even subtle treatment effects, and indicate that incorporating measurements from longer follow-up durations increases power substantially. We conclude that an annual imaging protocol provides a robust and powerful tool for assessing effects on the radiological appearance of the disease process.

The International Panel on the Diagnosis of Multiple Sclerosis (MS) incorporated the Barkhof/Tintoré (B/T) magnetic resonance criteria into their diagnostic scheme to provide evidence of dissemination in space of central nervous system lesions, a prerequisite for diagnosing MS in patients who present with clinically isolated syndromes (CIS). Although specific for MS, the B/T criteria were criticised for their low sensitivity and relative complexity in clinical use. We used lesion characteristics at onset from 349 CIS patients in logistic regression and recursive partitioning modelling in a search for simpler and more sensitive criteria, while maintaining current specificity. The resulting models, all based on the presence of periventricular and deep white matter lesions, performed roughly in agreement with the B/T criteria, but were unable to provide higher diagnostic accuracy based on information from a single scan. Apparently, findings from contrast-enhanced and follow-up magnetic resonance scans are needed to improve the diagnostic algorithm.

In this multicenter study, we used dynamic causal modeling to characterize the abnormalities of effective connectivity of the sensorimotor network in 61 patients with multiple sclerosis (MS) compared with 74 age-matched healthy subjects. We also investigated the correlation of such abnormalities with findings derived from structural MRI. In a subgroup of subjects, diffusion tensor (DT) MRI metrics of the corpus callosum and the left corticospinal tract (CST) were also assessed. MS patients showed increased effective connectivity relative to controls between: (a) the left primary SMC and the left dorsal premotor cortex (PMd), (b) the left PMd and the supplementary motor areas (SMA), (c) the left secondary sensorimotor cortex (SII) and the SMA, (d) the right SII and the SMA, (e) the left SII and the right SII, and (f) the right SMC and the SMA. MS patients had relatively reduced effective connectivity between the left SMC and the right cerebellum. No interaction was found between disease group and center. Coefficients of altered connectivity were weakly correlated with brain T2 LV, but moderately correlated with DT MRI-measured damage of the left CST. In conclusion, large multicenter fMRI studies of effective connectivity changes in diseased people are feasible and can facilitate studies with sample size large enough for robust outcomes. Increased effective connectivity in the patients for the simple motor task suggests local network modulation contributing to enhanced long-distance effective connectivity in MS patients. This extends and generalizes previous evidence that enhancement of effective connectivity may provide an important compensatory mechanism in MS.

BACKGROUND: A diagnosis of multiple sclerosis in patients who present for the first time with a clinically isolated syndrome (CIS) can be established with brain magnetic resonance imaging (MRI) if the MRI demonstrates demyelinating lesions with dissemination in space (DIS) and dissemination in time (DIT). OBJECTIVE: To investigate the diagnostic performance of a single MRI study obtained within the first 3 months after symptom onset in a cohort of patients with a CIS suggestive of multiple sclerosis at presentation. DESIGN: Multicenter inception cohort with a follow-up of at least 24 months. SETTING: Referral hospitals. Patients Patients with CIS onset between April 1, 1995, and September 30, 2004, who fulfilled the following criteria were included: (1) age of 14 to 50 years and (2) clinical follow-up for at least 24 months after CIS onset or until development of clinically definite multiple sclerosis (CDMS), if this occurred within 2 years. Main Outcome Measure All patients underwent 2 comparable brain MRI examinations, the first within 3 months (early) and the second between 3 and 12 months (delayed) after CIS onset. We defined DIS using several existing MRI criteria, and DIT was inferred when there were simultaneous gadolinium-enhancing and nonenhancing lesions on a single MRI. RESULTS: Two hundred fifty patients were included in the study. The comparison of the diagnostic performance of various MRI criteria for identifying early converters to CDMS showed similar sensitivity and specificity between early and delayed MRIs. In addition, the use of less stringent criteria for DIS yielded better sensitivity and similar specificity, particularly when assessed in the first weeks after CIS onset. CONCLUSION: A single brain MRI study that demonstrates DIS and shows both gadolinium-enhancing and nonenhancing lesions that suggest DIT is highly specific for predicting the early development of CDMS, even when the MRI is performed within the first 3 months after the onset of a CIS.

Short-term adaptation indicates the attenuation of the functional MRI (fMRI) response during repeated task execution. It is considered to be a physiological process, but it is unknown whether short-term adaptation changes significantly in patients with brain disorders, such as multiple sclerosis (MS). In order to investigate short-term adaptation during a repeated right-hand tapping task in both controls and in patients with MS, we analyzed the fMRI data collected in a large cohort of controls and MS patients who were recruited into a multi-centre European fMRI study. Four fMRI runs were acquired for each of the 55 controls and 56 MS patients at baseline and 33 controls and 26 MS patients at 1-year follow-up. The externally cued (1 Hz) right hand tapping movement was limited to 3 cm amplitude by using at all sites (7 at baseline and 6 at follow-up) identically manufactured wooden frames. No significant differences in cerebral activation were found between sites. Furthermore, our results showed linear response adaptation (i.e. reduced activation) from run 1 to run 4 (over a 25 minute period) in the primary motor area (contralateral more than ipsilateral), in the supplementary motor area and in the primary sensory cortex, sensory-motor cortex and cerebellum, bilaterally. This linear activation decay was the same in both control and patient groups, did not change between baseline and 1-year follow-up and was not influenced by the modest disease progression observed over 1 year. These findings confirm that the short-term adaptation to a simple motor task is a physiological process which is preserved in MS.

OBJECTIVE: Using different criteria for classifying patients into various stages of a disease can modify the stage-specific prognosis, even though the overall disease course remains unchanged. This is known as the "Will Rogers phenomenon," precluding the use of historical controls for treatment trials. We assessed whether the Will Rogers phenomenon may affect multiple sclerosis (MS) prognosis when applying different diagnostic criteria. METHODS: Patients with a clinically isolated syndrome (CIS) suggestive of MS were studied. After 1 year, each patient was classified as CIS or evolved to MS according to two diagnostic criteria (Poser and McDonald). The outcome for prognosis was the time to reach an Expanded Disability Status Scale score > or = 3.0. RESULTS: 309 patients were studied for a median period of 84 months. After 1 year, 16% of patients had MS according to Poser and 44% according to McDonald criteria. The probability to reach Expanded Disability Status Scale score > or = 3.0 at median follow-up was 11% in CIS patients according to Poser and 7% according to McDonald criteria; it was 46% in MS patients according to Poser and 27% acccording to McDonald criteria. The group with a discordant diagnosis had a worse prognosis than that of CIS patients according to both criteria (p = 0.01), but better than that of MS patients according to both criteria (p = 0.01). INTERPRETATION: The use of different diagnostic criteria may generate spurious improvements in the medium-term prognosis of MS. This calls for caution in using historical controls for MS trials.

PURPOSE: To investigate whether multiple sclerosis (MS) atrophy can be assessed by SIENA and SIENAX software using other image types from MS research protocols than T1-weighted images without contrast agent, which are not always available. MATERIALS AND METHODS: We selected 46 MS patients with identical magnetic resonance imaging (MRI) protocols at two timepoints. We calculated normalized brain volume (NBV) using SIENAX, and percentage brain volume change (PBVC) using SIENA, from T1-weighted images with and without contrast agent, T2-weighted images, and (calculated) pseudo-T1-weighted images. Relative agreement of the results was assessed using variance component estimation. RESULTS: Relative agreement with T1-weighted images without contrast agent was good for T1-weighted images with contrast agent (ICC=0.86 for NBV, ICC=0.77 for PBVC), and reasonably good for pseudo-T1 and T2-weighted images (T2: ICC=0.72 for NBV, 0.58 for PBVC; pseudo-T1: ICC=0.68 for NBV, 0.83 for PBVC). CONCLUSION: Brain atrophy can be studied using SIENA and SIENAX if T1-weighted images without contrast agent are not available. T1-weighted images with contrast agent should be used if available. Otherwise, pseudo-T1 and T2-weighted images seem acceptable and accessible alternatives. The use of these other images will greatly improve research possibilities, especially regarding older datasets.

With expanding potential clinical applications of functional magnetic resonance imaging (fMRI) it is important to test how reliable different measures of fMRI activation are between subjects and sessions and between centres. This study compared variability across 17 patients with multiple sclerosis (MS) and 22 age-matched healthy controls (HC) in 5 European centres performing an fMRI block design with hand tapping. We recruited subjects from sites using 1.5 T scanners from different manufacturers. 5 healthy volunteers also were studied at each of 4 of the centres. We found that reproducibility between runs and sessions for single individuals was consistently much greater than between individuals. There was greater run-to-run variability for MS patients than for HC. Measurements of maximum signal change (MSC) appeared to provide higher reproducibility within individuals and greater sensitivity to differences between individuals than region of interest (ROI) suprathreshold voxel counts. The variability in measurements between centres was not as great as that between individuals. Consistent with these observations, we estimated that power should not be reduced substantially with use of multi-, as opposed to single-, centre study designs with similar numbers of subjects. Multi-centre interventional studies in which fMRI is used as an outcome measure thus appear practical even when implemented in conventional clinical environments.

Rates of progression vary widely in primary progressive multiple sclerosis. This multicenter study aimed to identify predictors of progression over 10 years. A total of 101 patients who had been imaged at baseline and 2 years were scored on the expanded disability status scale after 10 years. Ordinal logistic regression identified the following independent variables that predicted progression: male sex, shorter disease duration, and slower timed walk test at baseline (best overall predictor), and deterioration in expanded disability status scale score and reduction in brain volume over 2 years. These predictors of long-term disability provide some insight into disease progression.

Although the mechanisms underlying the accumulation of disability in primary progressive (PP) multiple sclerosis (MS) are still unclear, a major role seems to be played by 'occult' tissue damage. We investigated whether conventional and magnetization transfer (MT) MRI may provide complementary information for the assessment of PPMS severity. Conventional and MT MRI scans from 226 PPMS patients and 84 healthy controls were collected for centralized analysis. The expanded disability status scale (EDSS) score was rated at the time of MRI acquisition. T2 lesion volume, normalized brain volume (NBV) and cervical cord cross-sectional area (CSA) were measured. Magnetization transfer ratio (MTR) histograms from whole brain tissue, normal-appearing white matter and grey matter (NAGM) were also obtained. Mean NBV, CSA and MTR histogram-derived metrics showed significant inter-centre heterogeneity. After correcting for the acquisition centre, pooled average MTR and histogram peak height values were different between PPMS patients and controls for all tissue classes (P-values between 0.03 and 0.0001). More severe brain and cord atrophy and MT MRI-detectable NAGM damage were found in patients who required walking aids than in those who did not (P-values: 0.03, 0.001 and 0.016). A composite score of NBV, CSA, whole brain and NAGM MTR histogram peak height z-scores was correlated with patients' EDSS (r = 0.37, P 0.001). Magnetization transfer MRI might provide information complementary to that given by conventional MRI when assessing PPMS severity. Sequence-related variability of measurements makes the standardization of MT MRI acquisition essential for the design of multicentre studies.

Motor control demands coordinated excitation and inhibition across distributed brain neuronal networks. Recent work has suggested that multiple sclerosis (MS) may be associated with impairments of neuronal inhibition as part of more general progressive impairments of connectivity. Here, we report results from a prospective, multi-centre fMRI study designed to characterise the changes in patients relative to healthy controls during a simple cued hand movement task. This study was conducted at eight European sites using 1.5 Tesla scanners. Brain deactivation during right hand movement was assessed in 56 right-handed patients with relapsing-remitting or secondary progressive MS without clinically evident hand impairment and in 60 age-matched, healthy subjects. The MS patients showed reduced task-associated deactivation relative to healthy controls in the pre- and postcentral gyri of the ipsilateral hemisphere in the region functionally specialised for hand movement control. We hypothesise that this impairment of deactivation is related to deficits of transcallosal connectivity and GABAergic neurotransmission occurring with the progression of pathology in the MS patients. This study has substantially extended previous observations with a well-powered, multicentre study. The clinical significance of these deactivation changes is still uncertain, but the functional anatomy of the affected region suggests that they could contribute to impairments of motor control.

OBJECTIVES: To define the extent of overall brain damage in patients with clinically isolated syndromes (CIS) suggestive of multiple sclerosis (MS) and to identify non-conventional magnetic resonance (MR) metrics predictive of evolution to definite MS. METHODS: Brain conventional and magnetization transfer (MT) MRI scans were obtained from 208 CIS patients and 55 matched healthy controls, recruited in four centres. Patients were assessed clinically at the time of MRI acquisition and after a median period of 3.1 years from disease onset. The following measures were derived: T2, T1 and gadolinium (Gd)- enhancing lesion volumes (LV), normalized brain volume (NBV), MTR histogram-derived quantities of the normal-appearing white matter (NAWM) and grey matter (GM). RESULTS: During the follow-up, 43 % of the patients converted to definite MS. At baseline, a significant inter-centre heterogeneity was detected for T2 LV (p = 0.003), T1 LV (p = 0.006), NBV (p < 0.001) and MTR histogram-derived metrics (p < 0.001). Pooled average MTR values differed between CIS patients and controls for NAWM (p = 0.003) and GM (p = 0.01). Gdactivity and positivity of International Panel (IP) criteria for disease dissemination in space (DIS), but not NAWM and GM MTR and NBV, were associated with evolution to definite MS. The final multivariable model retained only MRI IP criteria for DIS (p = 0.05; HR = 1.66, 95 % CI = 1.00-2.77) as an independent predictor of evolution to definite MS. CONCLUSIONS: Although irreversible tissue injury is present from the earliest clinical stages of MS, macroscopic focal lesions but not "diffuse" brain damage measured by MTR are associated to an increased risk of subsequent development of definite MS in CIS patients.

We performed a prospective multi-centre study using functional magnetic resonance imaging (fMRI) to better characterize the relationships between clinical expression and brain function in patients with multiple sclerosis (MS) at eight European sites (56 MS patients and 60 age-matched, healthy controls). Patients showed greater task-related activation bilaterally in brain regions including the pre- and post-central, inferior and superior frontal, cingulate and superior temporal gyri and insula (P < 0.05, all statistics corrected for multiple comparisons). Both patients and healthy controls showed greater brain activation with increasing age in the ipsilateral pre-central and inferior frontal gyri (P < 0.05). Patients, but not controls, showed greater brain activation in the anterior cingulate gyrus and the bilateral ventral striatum (P < 0.05) with less hand dexterity. An interaction between functional activation changes in MS and age was found. This large fMRI study over a broadly selected MS patient population confirms that movement for patients demands significantly greater cognitive 'resource allocation' and suggests age-related differences in brain responses to the disease. These observations add to evidence that brain functional responses (including potentially adaptive brain plasticity) contribute to modulation of clinical expression of MS pathology and demonstrate the feasibility of a multi-site functional MRI study of MS.

PURPOSE: To investigate intercenter agreement of brain volume (change) measurement in multiple sclerosis (MS) using structural image evaluation using normalization of atrophy (SIENA) and the cross-sectional version of SIENA (SIENAX) with additional manual editing to correct for inadequate brain extraction. MATERIALS AND METHODS: Baseline and follow-up T1-weighted MR images of 20 MS patients were dispatched to five centers. Each center performed fully-automated and manually-edited analyses for SIENAX, yielding normalized brain volume (NBV), and SIENA, yielding percentage brain volume change (PBVC). Intercenter agreement was assessed with the concordance correlation coefficient (CCC). RESULTS: Intercenter agreement was perfect for fully automated NBV and PBVC (both CCC = 1.0), and remained substantial upon manual editing (CCC = 0.94 for NBV, CCC = 0.95 for PBVC). Mean NBV values for each center decreased significantly after manual editing (overall mean NBV = 1605.3 cm(3) vs. 1651.1 cm(3) without manual editing; t = -4.58, P < 0.001). Total variance in PBVC decreased significantly by a factor of 1.8 after manual editing (sigma(2) = 2.82 before, and sigma(2) = 1.54 after manual editing, P < 0.05). CONCLUSION: Substantial intercenter agreement was found for manually-edited SIENAX and SIENA, suggesting that measurements from multiple centers may be pooled. Manual editing reduces overestimation of NBV, and is likely to increase statistical power for PBVC.

BACKGROUND: The 2001 and 2005 McDonald criteria allow MRI evidence for dissemination in space (DIS) and dissemination in time (DIT) to be used to diagnose multiple sclerosis in patients who present with clinically isolated syndromes (CIS). In 2006, new criteria were proposed in which DIS requires at least one T2 lesion in at least two of four locations (juxtacortical, periventricular, infratentorial, and spinal-cord) and DIT requires a new T2 lesion on a follow-up scan. We applied all three criteria in a large cohort of CIS patients to assess their performance by use of conversion to clinically definite multiple sclerosis (CDMS) as the outcome. METHODS: Patients who had two MRI scans within 12 months of CIS onset were identified in four centres in the Magnims European research network. The specificity and sensitivity of MRI criteria for CDMS after 3 years was assessed in 208 patients. A Cox proportional hazards model was applied in a larger cohort of 282 patients that included all patients irrespective of length of follow-up. FINDINGS: The specificity of all criteria for CDMS was high (2001 McDonald, 91%; 2005 McDonald, 88%; new, 87%). Sensitivity of the new (72%) and 2005 McDonald (60%) criteria were higher than the 2001 McDonald criteria (47%). The Cox proportional hazards model showed a higher conversion risk for all three criteria in those with both DIS and DIT than those with either DIS or DIT alone. When all three criteria were included in the model, only the new criteria had an independent significant effect on conversion risk. INTERPRETATION: The new criteria are simpler than the McDonald criteria without compromising specificity and accuracy. The presence of both DIS and DIT from two MRI scans has a higher specificity and risk for CDMS than either DIS or DIT alone.

BACKGROUND: Previous studies have shown only modest correlation between multiple sclerosis (MS) lesions on MRI and clinical disability. OBJECTIVE: To investigate the relationship between proton density/T2-weighted (T2) burden of disease (BOD) quantitatively measured on MRI scans and clinical determinants including disability. METHODS: Using the Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) database, the authors studied baseline T2 BOD data from a pooled subsample of 1,312 placebo MS patients from 11 randomized controlled trials. Univariate comparisons guided development of multiple regression models incorporating the most important clinical predictors. RESULTS: Significant, although weak to moderate, correlations were found between T2 BOD and age at disease onset, disease duration, disease course, disability (as measured by the Expanded Disability Status Scale [EDSS]), relapse rate, certain presenting symptoms, and gadolinium enhancement. An unexpected but key finding that persisted in the multiple regression analyses was a plateauing relationship between T2 BOD and disability for EDSS values above 4.5. CONCLUSIONS: This study confirmed the limited correlation between clinical manifestations and T2 burden of disease (BOD) but revealed an important plateauing relationship between T2 BOD and disability.

BACKGROUND: The McDonald International Panel accepted the Barkhof/Tintoré criteria for providing MRI evidence of dissemination in space to allow a diagnosis of multiple sclerosis in patients with clinically isolated syndromes (CIS). We applied these criteria in a large cohort of patients with CIS, representative of those seen in a general diagnostic setting, to assess their accuracy in predicting conversion to definite multiple sclerosis and to identify factors that affect this risk. METHODS: In a collaborative study of seven centres, baseline MRI and clinical follow-up data for 532 patients with CIS were studied, with the development of a second clinical event used as the main outcome. All scans were scored for lesion counts and spatial lesion distribution to assess the fulfilment--ie, at least three out of four--of the Barkhof/Tintoré criteria. We used survival analysis and 2x2 tables to assess the test characteristics of the criteria at baseline. FINDINGS: Overall conversion rate was 32.5% with a median survival time of 85.3 months. Fulfilment of the criteria at baseline showed, after a survival time of 2 years, a conversion rate of about 45% (95% CI 37-53) versus about 10% (6-16) in those with no asymptomatic lesions at baseline (p<0.0001). For patients with a follow-up of at least 2 years, the fulfilment of the MRI criteria showed an accuracy of 68% (sensitivity 49%, specificity 79%) for predicting conversion and an increase in risk of nearly four times for conversion compared with those not fulfilling the criteria (odds ratio 3.7, 95% CI 2.3-5.9; p<0.0001). Cox proportional hazards regression analysis accorded with this increased risk. No effects were recorded on the performance of the criteria by sex, presenting symptoms, or centre. Age at baseline did have a small but significant effect as predictor (hazard ratio 0.97, 0.95-0.99; p=0.002), but did not affect the prognostic value of the MRI criteria. INTERPRETATION: MRI abnormalities have important prognostic value. The cut-off, based on the Barkhof/Tintoré criteria, as incorporated in the McDonald diagnostic scheme yields acceptable specificity, but could have lower sensitivity than previously reported.

There are few longitudinal studies of cognition in patients with multiple sclerosis, and the results of these studies remain inconclusive. No serial neuropsychological data of an exclusively primary progressive series are available. Cross-sectional analyses have revealed significant correlations between cognition and magnetic resonance imaging (MRI) parameters in primary progressive multiple sclerosis (PPMS). This study investigated cognitive and MRI change in 99 PPMS patients from five European centres for 2 years. They were assessed at 12 month intervals using the Brief Repeatable Battery, a reasoning test, and a measure of depression. The MRI parameters of T1 hypointensity load, T2 lesion load, and partial brain volume were also calculated at each time point. There were no significant differences between the mean cognitive scores of the patients at year 0 and year 2. However, one-third of the patients demonstrated absolute cognitive decline on individual test scores. Results indicated that initial cognitive status on entry into the study was a good predictor of cognitive ability at 2 years. There was only a small number of significant correlations between changes in cognition and changes on MRI, notably T1 hypointensity load with the two attentional tasks (r = -0.266, P = 0.017; r = -0.303, P = 0.012). It is probable that multiple factors underlie this weak relation between the cognitive and MRI measures.

The authors sought to identify clinical and MRI predictors of outcome in primary progressive multiple sclerosis (PPMS). Clinical and MRI assessments were performed at baseline and 2 and 5 years (clinical only). At baseline, disease duration, expanded disability status scale (EDSS) and brain volume predicted outcome. Adding short-term change variables, baseline EDSS, changes in T2* lesion load and cord area, and number of new lesions were predictive. Clinical and MRI variables predict long-term outcome in PPMS.

The magnetization transfer ratio (MTR) is strongly related to the field strength (B(1)) of the saturation pulse. B(1) variations therefore can result in significant MTR variations and can affect histogram analysis, particularly if data from a large volume of interest are included. A multicenter study was performed to determine the typical range of B(1) errors and the corresponding MTR variations in brain tissue of healthy volunteers. Seven subjects were included at each center resulting in a total cohort of 28 subjects. Additionally, numerical simulations were done to study this relationship more generally for pulsed saturation. It could be demonstrated, both theoretically and empirically, that for typical B(1) errors there is a linear relationship between B(1) error and the corresponding MTR change. In addition, for proton density-weighted sequences, this relationship seems to be largely independent of the underlying relaxation properties. Mean B(1) errors in the entire brain were typically in the range between -3% and -7%. Due to different coil characteristics, significant MTR differences between different scanners and sites were observed. Using a simple correction scheme that is based on a linear regression analysis between MTR and B(1) data it was possible to reduce the intersubject variation by approximately 50%. Furthermore, interscanner variation could be reduced such that no significant differences between scanners could be detected. The correction scheme may be useful when investigating MTR as an outcome measure in single or multicenter studies.

Serial MRI studies are used to analyse change in multiple sclerosis (MS) lesion volume in clinical trials. As such an evaluation is very time consuming and subject to quantification errors, one might assess only the change in number or size of lesions using subtracted images. The advantage of subtracted images is that both new and/or enlarging and resolving and/or shrinking lesions can be evaluated, resulting in a more precise volume change than a net volume change. We studied the interobserver agreement in the detection of active MS lesions using paired dual-echo T(2)-weighted spin-echo studies (3-mm slices) of 30 MS patients with a range of MS disease activity on MRI from treatment trials. Using an automatic matching algorithm based on mutual information, the follow-up scan was registered to baseline, after which subtracted images were obtained. After a training session with formulation of guidelines, six observers identified new, enlarging, resolving and shrinking lesions on subtracted images. Weighted kappa (kappa) values were calculated to assess interobserver agreement. Good agreement was found for new lesions (kappa 0.69 +/- 0.08), while moderate agreement was found for enlarging lesions (kappa 0.52 +/- 0.06). When new and enlarging lesions were combined, good agreement was found for "positive" activity (kappa 0.71 +/-0.06). The interobserver agreement was poor for resolving lesions (kappa 0.31 +/- 0.07), and moderate for shrinking lesions (kappa 0.53 +/- 0.08). In conclusion, the use of subtracted images in the visual detection of new T(2) lesions resulted in a good level of interobserver agreement for "positive" disease activity. Subtraction of registered images is a reliable, time efficient method to assess disease progression in MS.

This study documents changes in clinical and magnetic resonance imaging (MRI) characteristics in a large cohort of patients with primary and transitional progressive multiple sclerosis (PP and TPMS) over 2 years. Patients with PPMS and TPMS were recruited from six European centres and underwent clinical and MRI examination at three time points: baseline, year one and year two. Of the 190 patients recruited clinical data were available on 125 patients (66%, five centres) and MRI data were available on 113 patients (59%, four centres) at 2 years. Significant increases were seen in T2 load and T1 hypointensity, while brain and cord volume decreased. In PPMS significantly higher lesion loads were found in those who presented with non-cord syndromes when compared to cord presentation and there was a trend to greater brain atrophy in those who deteriorated clinically over the course of the study compared to those who remained stable. Significant cord atrophy was only seen in those with a cord presentation. Measurable changes in MRI parameters can be detected in PPMS patients over a relatively short period of time. MRI quantification is likely to be useful in elucidating disease mechanisms in PPMS and in the execution of clinical trials.

Magnetic resonance imaging (MRI) has been established as the most relevant paraclinical tool for diagnosing and monitoring multiple sclerosis (MS). In this context, counting the number of new enhancing lesions on monthly MRI scans is widely used as a surrogate marker of MS activity when evaluating the effect of treatments. In this study, we investigated whether parametric models based on mixed Poisson distributions (the Negative Binomial (NB) and the Poisson-Inverse Gaussian (P-IG) distributions) were able to provide adequate fitting of new enhancing lesion counts in MS. We found that the NB model gave good approximations in relapsing-remitting and secondary progressive MS patients not selected for baseline MRI activity, whereas the P-IG distribution modelled better new enhancing lesion counts in relapsing-remitting MS patients selected for baseline activity. This study shows that parametric modelling for MS new enhancing lesion counts is feasible. This approach should provide more targeted tools for the design and the analysis of MRI monitored clinical trials in MS.

The aim of this study was to analyse the effect of image registration on interobserver agreement in the visual detection of active multiple sclerosis (MS) lesions from serial magnetic resonance (MR) scans. T2W spin-echo MR scans (3-mm slices) of 16 MS patients participating in a treatment trial were selected. For each patient, two pairs of scans were used: an original (i. e., non-registered) and a registered pair. For the original pair, baseline and month 6 were used, and for the registered pair month 3 and 9. For registration an automatic matching algorithm based on Mutual Information was used. Six observers identified active lesions on both original and registered scans. Kappa values were calculated to assess interobserver agreement. Reslicing caused a slight blurring of the images, but near perfect registration. The kappa value of 0.35 +/- 0.07 for new lesions on original images improved to 0.62 (+/- 0.06) by registration (p = 0.004). For enlarging lesions on original images it was extremely poor (kappa 0.11 +/- 0.05), and did not benefit much by registration (kappa 0.20 +/- 0.11). Thus, image registration improved interobserver agreement for visual detection of new lesions. For enlarging lesions, registration improved agreement but still not to a satisfactory level.

OBJECTIVE: A new parametric simulation procedure based on the negative binomial (NB) model was used to evaluate the sample sizes needed to achieve optimal statistical powers for parallel groups (with (PGB) and without (PG) a baseline correction scan). It was also used for baseline versus treatment (BVT) design clinical trials in relapsing-remitting (RR) and secondary progressive (SP) multiple sclerosis (MS), when using the number of new enhancing lesions seen on monthly MRI of the brain as the measure of outcome. METHODS: MRI data obtained from 120 untreated patients with RRMS selected for the presence of MRI activity at baseline, 66 untreated and unselected patients with RRMS, and 81 untreated and unselected patients with SPMS were fitted using an NB distribution. All these patients were scanned monthly for at least 6 months and were all from the placebo arms of three large scale clinical trials and one natural history study. The statistical powers were calculated for durations of follow up of 3 and 6 months. RESULTS: The frequency of new enhancing lesions in patients with SPMS was lower, but not significantly different, from that seen in unselected patients with RRMS. As expected, enhancement was more frequent in patients with RRMS selected for MRI activity at baseline than in the other two patient groups. As a consequence, the estimated sample sizes needed to detect treatment efficacy in selected patients with RRMS were smaller than those of unselected patients with RRMS and those with SPMS. Baseline correction was also seen to reduce the sample sizes of PG design trials. An increased number of scans reduced the sample sizes needed to perform BVT trials, whereas the gain in power was less evident in PG and PGB trials. CONCLUSION: This study provides reliable estimates of the sample sizes needed to perform MRI monitored clinical trials in the major MS clinical phenotypes, which should be useful for planning future studies.

In this study we evaluated the correlation between neuropsychological impairment (measured with the Brief Repeatable Battery Neuropsychological Tests) and (juxta)cortical lesions detected with FLAIR and the relative sensitivity of the FLAIR sequence compared to spin-echo MRI sequences in detecting (juxta)cortical MS lesions. A total of 39 patients with definite MS were evaluated by MRI with a conventional and fast spin echo sequence and fast FLAIR sequence, and neuropsychological tests of the Brief Repeatable Battery Neuropsychological tests were performed. The Z-score of all subtests were used to calculate a Cognitive Impairment Index. The results show that a high number of (juxta)cortical lesions is detected with thin slice FLAIR (30% of all lesions seen). This percentage was not superior to spin-echo, reflecting the thin slice thickness (3 mm) we used. The lesions detected with FLAIR were to a certain degree different ones than the lesions detected with the other techniques. While the number of non-cortical lesions correlated with the expanded disability status scale (r=0.32, P=0.045), the number of (juxta)cortical lesions detected with the FLAIR showed a correlation (r=0.34, P=0.035) with the Cognitive Impairment Index. Our study underlines the high number of (juxta)cortical lesions in MS and the value of thin slice FLAIR sequence to detect such lesions with MRI. It also stresses the importance of (juxta)cortical lesions on determining neuropsychological impairment. Multiple Sclerosis (2000) 6 280 - 285

OBJECTIVE: To document clinical and magnetic resonance imaging (MRI) characteristics of a large cohort of primary and transitional progressive multiple sclerosis (PP and TP MS) patients over one year. INTRODUCTION: Patients with PP or TP MS have been shown to have low brain T2 and T1 lesion loads and slow rates of new lesion formation with minimal gadolinium enhancement, despite their accumulating disability. Serial evaluation of these patients is needed to elucidate the pathological processes responsible for disease progression and to identify clinical and MRI measures which can monitor these processes in treatment trials. METHOD: Patients, recruited from six European centres, underwent two assessments on the expanded disability status scale (EDSS) and MRI of the brain and spinal cord, 1 year apart. RESULTS: Of the 167 patients studied (137 with PP MS and 30 with TP MS), 41 (25%; 35 PP and six TP) showed a one step increase in the EDSS. The mean number of new brain lesions seen was 0.88 in the PP group and 0.47 in the TP MS group. Both groups demonstrated change in T2 lesion load over the year (p< or =0.002), with median percentage changes of 7.3% in the PP group and 10. 8% in the TP MS group. The PP group also showed a significant change in T1 load (p< 0.001, median change 12.6%). The number of new cord lesions seen was small (mean of 0.14 in the PP group and no new cord lesions in the TP group). Both groups demonstrated a decrease in cord cross sectional area (p< 0.001, median changes; PP 3.8%, TP 4. 9%), but only the PP group showed evidence of significant brain atrophy (p<0.001, 0.95%). CONCLUSION: Although the monitoring of disease progression in this patient group is difficult, this study demonstrates changes in both lesion load and atrophy, which, if shown to correlate with clinical change over a longer time will facilitate therapeutic trial design.

Previous studies have addressed the question of the precision in assessing multiple sclerosis (MS) activity by counting enhancing lesions on gadolinium enhanced brain magnetic resonance imaging (MRI). However, counting the active lesions on serial unenhanced MRI obtained by various pulse sequences has not been yet considered. We compared the interobserver levels of agreement in reporting active MS lesions on serial enhanced and unenhanced MRI to assess whether the use of various unenhanced techniques may change the degree of interobserver measurement reproducibility. Dual-echo conventional spin echo (CSE), dual-echo fast spin echo (FSE), fast fluid-attenuated inversion recovery (FLAIR) and Gd-enhanced T1-weighted brain MRI were obtained from five MS patients at baseline and monthly for 2 months. Six experienced observers independently identified and counted active MS lesions on the two follow-up MRI scans. Active lesions were considered to be all the enhancing lesions and any new or enlarging lesion on enhanced and unenhanced scans. Interobserver levels of agreement were calculated by weighted kappa values. Very good agreement was reached only for counting total and new Gd-enhancing lesions. Good agreement was achieved for counting new lesions on the three unenhanced techniques, whereas the agreement for counting enlarging lesions was poor with all the MRI techniques. The level of agreement was significantly heterogeneous for various MRI techniques but not for various lesion sites. These results confirm that counting enhancing lesions is the most reliable method for assessing MS activity, but the use of any of the available unenhanced MRI techniques did not result in different levels of interobserver agreement when reporting new and enlarging MS lesions on serial scans.

MRI is the paraclinical test most widely used to support the diagnosis of multiple sclerosis (MS). We evaluated interobserver agreement in applying diagnostic criteria to MRI obtained at first presentation. Five experienced observers scored 25 sets of images consisting of unenhanced T2- and gadolinium-enhanced T1-weighted images (approximately half the sets were normal). We scored frontal, parietal, temporal, occipital, infratentorial and basal ganglia lesions and the total number of lesions on T2-weighted images; periventricular, callosal, juxtacortical and ovoid lesions and those > 5 mm in maximum diameter; contrast-enhancing and hypointense lesions. Based on a combination of imaging findings patients were classified as compatible or not compatible with MS according to composite criteria. Observer concordance was characterised by weighted kappa values (kappa) and mean average difference to the median (MADM) scores. Using the raw scores, there was poor agreement for the total number of lesions on T2-weighted images, and for occipital, oval, juxtacortical and hypointense lesions. Moderate agreement was found for frontal, callosal, basal ganglia and large lesions on T2 weighting. Good agreement was attained for parietal, temporal, infratentorial and periventricular lesions. After dichotomisation according to accepted cut-off values, most criteria performed better, especially the number of lesions on T2-weighted images (P < 0.05). Good agreement was found for the criteria of Paty and Fazekas and moderate agreement for those of Barkhof. While experienced observers may not agree on the total number of lesions, they show quite good agreement for commonly used cut-off points and elements in the composite criteria. This validates the use of MRI in the diagnosis of MS, and the use of dichotomised and composite criteria.

OBJECTIVES: To evaluate the durations of the follow up and the reference population sizes needed to achieve optimal and stable statistical powers for two period cross over and parallel group design clinical trials in multiple sclerosis, when using the numbers of new enhancing lesions and the numbers of active scans as end point variables. METHODS: The statistical power was calculated by means of computer simulations performed using MRI data obtained from 65 untreated relapsing-remitting or secondary progressive patients who were scanned monthly for 9 months. The statistical power was calculated for follow up durations of 2, 3, 6, and 9 months and for sample sizes of 40-100 patients for parallel group and of 20-80 patients for two period cross over design studies. The stability of the estimated powers was evaluated by applying the same procedure on random subsets of the original data. RESULTS: When using the number of new enhancing lesions as the end point, the statistical power increased for all the simulated treatment effects with the duration of the follow up until 3 months for the parallel group design and until 6 months for the two period cross over design. Using the number of active scans as the end point, the statistical power steadily increased until 6 months for the parallel group design and until 9 months for the two period cross over design. The power estimates in the present sample and the comparisons of these results with those obtained by previous studies with smaller patient cohorts suggest that statistical power is significantly overestimated when the size of the reference data set decreases for parallel group design studies or the duration of the follow up decreases for two period cross over studies. CONCLUSIONS: These results should be used to determine the duration of the follow up and the sample size needed when planning MRI monitored clinical trials in multiple sclerosis.

BACKGROUND: Ten percent of patients with MS have a progressive course from onset with no history of relapses or remissions. A smaller subgroup follow a similar progressive course but have a single relapse at some point (transitional progressive [TP] MS). To date these patients have been excluded from receiving licensed treatments for MS and from most therapeutic trials. OBJECTIVE: To document the clinical and MRI characteristics of a large cohort of progressive patients, including 158 with primary progressive (PP) MS and 33 with TPMS. Data from a small reference group of 20 patients with secondary progressive (SP) MS are also presented for reference. METHODS: Patients were recruited from six European centers. All underwent a clinical assessment including scoring on the Expanded Disability Status Scale (EDSS) and MRI of the brain and spinal cord. RESULTS: The men-to-women ratio was 81:77 (51% men) in the PP group, 14:19 (42% men) in the TP group, and 5:15 (25% men) in the SP group. The mean age at disease onset was significantly higher in the PP group than it was in the other two groups (PP 40.2 years, TP 34.9 years, SP 28.7 years). On MRI the PP group had lower mean brain T2 and T1 hypointensity lesion loads than the SP group (T2 12.02 versus 27.74 cm3, p = 0.001; T1 4.34 versus 7.04 cm3, p = 0.015). The SP and TP cohorts had significantly more T2-weighted lesions in the spinal cord than the PP patients, and the SP cohort had the greatest degree of atrophy. There was a correlation in the PP and TP patients between EDSS score and brain and spinal cord atrophy (r = 0.3, 0.2, p < or = 0.006) but not with brain lesion load. The PP and TP patients who presented with spinal cord pathology had significantly lower brain T2 and T1 lesion loads than those with non-spinal cord presentations (p = 0.002). CONCLUSIONS: The monitoring of disease progression in PPMS is difficult, although measures of atrophy correlate with the EDSS and appear most promising. This study increases our understanding of this unique patient group, which will be further expanded with the acquisition of serial data.

BACKGROUND: Reliable prognostic factors are lacking for multiple sclerosis (MS). Gadolinium enhancement in magnetic resonance imaging (MRI) of the brain detects with high sensitivity disturbance of the blood-brain barrier, an early event in the development of inflammatory lesions in MS. To investigate the prognostic value of gadolinium-enhanced MRI, we did a meta-analysis of longitudinal MRI studies. METHODS: From the members of MAGNIMS (European Magnetic Resonance Network in Multiple Sclerosis) and additional centres in the USA, we collected data from five natural-course studies and four placebo groups of clinical trials completed between 1992 and 1995. We included a total of 307 patients, 237 with relapsing disease course and 70 with secondary progressive disease course. We investigated by regression analysis the relation between initial count of gadolinium-enhancing lesions and subsequent worsening of disability or impairment as measured by the expanded disability status scale (EDSS) and relapse rate. FINDINGS: The relapse rate in the first year was predicted with moderate ability by the mean number of gadolinium-enhancing lesions in monthly scans during the first 6 months (relative risk per five lesions 1.13, p=0.023). The predictive value of the number of gadolinium-enhancing lesions in one baseline scan was less strong. The best predictor for relapse rate was the variation (SD) of lesion counts in the first six monthly scans which allowed an estimate of relapse in the first year (relative risk 1.2, p=0.020) and in the second year (risk ratio=1.59, p=0.010). Neither the initial scan nor monthly scans over six months were predictive of change in the EDSS in the subsequent 12 months or 24 months. The mean of gadolinium-enhancing-lesion counts in the first six monthly scans was weakly predictive of EDSS change after 1 year (odds ratio=1.34, p=0.082) and 2 years (odds ratio=1.65, p=0.049). INTERPRETATION: Although disturbance of the blood-brain barrier as shown by gadolinium enhancement in MRI is a predictor of the occurrence of relapses, it is not a strong predictor of the development of cumulative impairment or disability. This discrepancy supports the idea that variant pathogenetic mechanisms are operative in the occurrence of relapses and in the development of long-term disability in MS.

In multiple sclerosis (MS) the number of new enhancing lesions seen on monthly magnetic resonance imaging (MRI) scans is the most widely used response variable in MRI-monitored studies of experimental treatments. However, no statistical model has been proposed to describe the distribution of the number of such lesions across MS patients. This article briefly summarizes the statistical models for counted data. The negative binomial (NB) model is proposed to fit the number of new enhancing lesions counted in a set of 56 untreated MS patients followed for 9 months. It is shown that the large variability present in this data set is better addressed by the NB model (residual deviance=66.6, 54 degrees of freedom) than by the Poisson model (residual deviance=1830.1, 55 degrees of freedom). Applications of the parametrization of lesion counts are discussed, and an example related to computer simulations for the sample size estimation is presented.

The aim of this study was to assess the variability of lesion load measurements for repeated brain magnetic resonance imaging (MRI) scans judged to have either poor or good repositioning quality on the basis of subjective criteria used for clinical trials in multiple sclerosis (MS). Scan-rescan variability was also compared with the intra-observer variability assessed from three repeated volume measurements of the same scan. Nine patients with MS were studied; each of them underwent the scan-rescan procedure on the same day. Five scans were considered to have poor and four scans to have good repositioning. Between these two groups there were no differences in either the mean lesion loads or the measurement variance. For the whole group of patients, the intra-observer variability of repeated measurements gave a significantly lower coefficient of variation (COV = 4.9%) than the variability owing to repositioning (COV = 8.9%, P < 0.01, F test). Our results confirm that the effect of repositioning on brain MRI lesion load assessment is stronger than that owing to the intra-observer variability for repeated measurements and indicate that the simple visual judgment about the scan repositioning quality seems unable to predict the scan-rescan reproducibility.

Magnetic resonance imaging (MRI) provides a powerful tool for assessing disease activity in multiple sclerosis (MS), and its role as a surrogate marker for monitoring treatment efficacy is now becoming established. The most commonly used MRI parameters in treatment trials are (1) monthly gadolinium-enhanced MRI, with the number of active lesions serving as the outcome measure, and (2) annual lesion load quantification, in which change in MS lesion volume provides the MRI endpoint. We evaluated clinical/MRI correlations and the relationship between these two markers of disease activity in 73 patients with clinically definite MS. Quantification of T2 lesion load was performed at study entry and exit, with a median study duration of 11 months (range, 9 to 14 months). Monthly postgadolinium T1-weighted images were acquired between these time points. Lesion load at study entry was significantly correlated with the baseline Expanded Disability Status Scale (EDSS) score, but no significant longitudinal correlation was demonstrated. The number of enhancing lesions on the entry scan was predictive of subsequent relapse rate over the study duration and also correlated with the subsequent enhancing lesion activity over the study period. A significant correlation was found between change in lesion load and disease activity on the monthly scans. Our results suggest that annual lesion load quantification provides an efficient measure of ongoing disease activity, and this supports its application as a surrogate marker of disease evolution in phase III treatment trials.

In this study, we evaluated the intra- and interobserver variabilities in measuring lesion load of brain MRI abnormalities present on proton-density scans from patients with MS, using using both manual outlining or a semiautomated local thresholding technique (LTT). We also evaluated how these variabilities were affected by the use of standard rules for lesion load measurements, training, and different measurement strategies. The intraobserver variabilities obtained after establishing rules for lesion load measurements and training were not significantly different from those obtained before any consensus among the observers, both for manual outlining and for the LTT. On the contrary, the interobserver variabilities obtained with manual outlining or the LTT were significantly reduced when rules for lesion load measurements were used. For manual outlining, the intraobserver variability did not significantly change when the measurements were performed after an experienced radiologist identified lesions or when using adjacent slices and the corresponding T2-weighted images as reference for lesion identification. On the contrary, for the LTT, the intraobserver variability was significantly reduced by the use of the radiologic marking. The interobserver variabilities for both manual outlining and the LTT were reduced compared with the free condition when these measurement strategies were used. Our findings demonstrate that both lesion identification and outlining are important sources of variation for MRI lesion load measurements in MS and that there are simple strategies to reduce such variation that might be useful when planning clinical trials.

Gadolinium-enhanced MRI is a sensitive and objective means to monitor disease activity in multiple sclerosis (MS). We evaluated the interobserver agreement and the value of observer training in reporting enhancing lesions from serial MRI. Scans of 16 MS patients were evaluated by five inexperienced and five experienced observers before and after consensus formation and training. The number of lesions at baseline, and the number of new and persistent lesions at follow-up were scored. For each condition, weighted kappa values (kappa) and the mean average difference to the median (MADM) scores were calculated. Without training, the experienced readers showed good agreement on number of lesions at baseline and new lesions at follow-up, and moderate agreement for persistent lesions. The inexperienced readers showed poor agreement for baseline and persistent lesions, and moderate agreement for new lesions. After training, both groups reported lower absolute numbers of lesions, especially the inexperienced readers. The experienced readers showed good agreement for all lesion types, the inexperienced readers showed agreement for baseline and new lesions, and agreement was moderate for persistent lesions. In both groups MADM scores were < 0.72 for baseline and new lesions, but > 1.2 for persistent lesions. Interobserver agreement is improved by training, especially in inexperienced readers. Interobserver agreement in reporting gadolinium-enhanced lesions is high, which validates the use of serial, enhanced MRI as an outcome parameter in treatment trials in MS.

We compared MRI criteria used to predict conversion of suspected multiple sclerosis to clinically definite multiple sclerosis. Seventy-four patients with clinically isolated neurological symptoms suggestive of multiple sclerosis were studied with MRI. Logistic regression analysis was used to remove redundant information, and a diagnostic model was built after each MRI parameter was dichotomized according to maximum accuracy using receiver operating characteristic analysis. Clinically definite multiple sclerosis developed in 33 patients (prevalence 45%). The optimum cut-off point (number of lesions) was one for most MRI criteria (including gadolinium-enhancement and juxta-cortical lesions), but three for periventricular lesions, and nine for the total number of T2-lesions. Only gadolinium-enhancement and juxta-cortical lesions provided independent information. A final model which, in addition, included infratentorial and periventricular lesions, had an accuracy of 80%, and having more abnormal criteria, predicted conversion to clinically definite multiple sclerosis strongly. The model performed better than the criteria of Paty et al. (Neurology 1988; 38: 180-5) and of Fazekas et al. (Neurology 1988; 38: 1822-5). We concluded that a four-parameter dichotomized MRI model including gadolinium-enhancement, juxtacortical, infratentorial and periventricular lesions best predicts conversion to clinically definite multiple sclerosis.

We evaluated the effect of interscanner variation on brain MRI-measured lesion volumes and measurement reproducibility in MS. Twenty clinically definite MS patients were each scanned on two or three scanners (a total of 14 scanners were used). In addition, a formalin-fixed MS brain was studied on eight scanners from different manufacturers and with different field strengths. For the formalin-fixed MS brain, on each machine we obtained two scans with slice thicknesses of 5 and 3 mm. Only 5-mm-thick slices were obtained from patients. The lesion volume present on each scan was evaluated three times by a single observer in random order, using a local thresholding technique. In two groups of eight patients scanned on machines with different field strengths, the mean lesion volumes present on scans obtained at 1.5 T were significantly higher than those measured on scans obtained with machines operating at 0.5 and 1.0 T (p < 0.01). When a single observer repeatedly evaluated the same scan, a median introbserver agreement of 98.7% (95% CI, 97.9 to 99.1) was achieved. However, when the observer evaluated the scans from different MRI scanners, the agreement (an interscanner agreement) fell to 91.1% (CI, 90.2 to 94.1). When only scanners operating at 1.5 T were considered, the median interscanner agreement was 96.7% (CI, 95 to 97.5). Also, for the formalin-fixed MS brain, the intraobserver agreements obtained with both slice thicknesses were significantly higher than the corresponding interscanner agreements. The interscanner agreement, but not the intraobserver agreement, obtained with a slice thickness of 3 mm was higher than that obtained with a slice thickness of 5 mm. Our results indicate that lesion volume measurements in MS are influenced significantly by the use of different MR scanners and that a patient included in a serial study should be always scanned with the same MR machine using 3-mm thick slices.

In this study we evaluated and compared the inter-rater variabilities in detecting enhancing lesions in patients with MS after injection of a standard dose (s.d.) and a triple dose (TD) of gadolinium (Gd). Enhanced magnetic resonance imaging (MRI) were obtained in 15 patients, consisting of T1-weighted images 5 to 7 min after the injection of the s.d. (0.1 mmol/kg) of Gd and, after an interval of 6 to 24 h, 5 to 7 min after the injection of the TD (0.3 mmol/kg). An additional scan 1 h after the TD injection (delayed scanning-DS) was obtained in 11 patients. The scans were independently evaluated in a random order by four observers. Lesions were counted and scored according to size and location. The level of inter-observer observer concordance was very high for reporting the total numbers of enhancing lesions, their sizes and sites for the three experimental conditions. No significant differences were found in inter-observer variability in reporting the total number of enhancing lesions and their location in different brain sites in the three conditions. Our data indicate that the gain in sensitivity in detecting enhancing lesions in MS with the TD is not counteracted by a loss in reproducibility. This is important in planning clinical trials in which the number of enhancing lesions is used as a measure of outcome.

In recent years, several segmentation techniques have been developed to quantify brain MRI lesion load in multiple sclerosis and are now being used increasingly for both evaluating the natural history of the disease and monitoring the efficacy of treatment. Such techniques have been applied extensively to conventional T2-weighted images; there is less experience to date with gadolinium-enhanced scans and newer MR parameters which are thought to reflect the more destructive aspects of the pathological process. Manual outlining of lesions on T2-weighted images is moderately accurate when performed by an experienced observer and has been validated in large clinical trials, but is very time consuming. Semi-automated intensity-based techniques appear to be more reproducible, but are still slow to perform. Faster techniques with higher reproducibility are still needed. The correlations between conventional T2 lesion load and clinical outcome is strong in patients seen at first presentation with clinically isolated syndromes suggestive of multiple sclerosis, but much weaker in established multiple sclerosis. The application of quantitative assessment of the MR parameters which are more specific for the disabling aspects of the pathological process (i.e. demyelination, axonal loss and spinal cord involvement) may improve the correlation with clinical status.