Grey Matter Atrophy and its Relationship with White Matter Lesions in Patients with Myelin Oligodendrocyte Glycoprotein Antibody-associated Disease, Aquaporin-4 Antibody-Positive Neuromyelitis Optica Spectrum Disorder, and Multiple Sclerosis.

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. ANN NEUROL 2024;96:276-288.

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

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

Clinical and MRI measures to identify non-acute MOG-antibody disease in adults.

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.

Automatic estimation of brain parenchymal fraction in patients with multple sclerosis: a comparison between synthetic MRI and an established automated brain segmentation software based on FSL.

PURPOSE: We aimed to validate the estimation of the brain parenchymal fraction (BPF) in patients with multiple sclerosis (MS) using synthetic magnetic resonance imaging (SyMRI) by comparison with software tools of the FMRIB Software Library (FSL). In addition to a cross-sectional method comparison, longitudinal volume changes were assessed to further elucidate the suitability of SyMRI for quantification of disease-specific changes. METHODS: MRI data from 216 patients with MS and 28 control participants were included for volume estimation by SyMRI and FSL-SIENAX. Moreover, longitudinal data from 35 patients with MS were used to compare registration-based percentage brain volume changes estimated using FSL-SIENA to difference-based calculations of volume changes using SyMRI. RESULTS: We observed strong correlations of estimated brain volumes between the two methods. While SyMRI overestimated grey matter and BPF compared to FSL-SIENAX, indicating a systematic bias, there was excellent agreement according to intra-class correlation coefficients for grey matter and good agreement for BPF and white matter. Bland-Altman plots suggested that the inter-method differences in BPF were smaller in patients with brain atrophy compared to those without atrophy. Longitudinal analyses revealed a tendency for higher atrophy rates for SyMRI than for SIENA, but SyMRI had a robust correlation and a good agreement with SIENA. CONCLUSION: In summary, BPF based on data from SyMRI and FSL-SIENAX is not directly transferable because an overestimation and higher variability of SyMRI values were observed. However, the consistency and correlations between the two methods were satisfactory, and SyMRI was suitable to quantify disease-specific atrophy in MS.

Spinal cord lesions and brain grey matter atrophy independently predict clinical worsening in definite multiple sclerosis: a 5-year, multicentre study.

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 (ß)=0.97), higher EDSS (ß=0.41), higher cord lesion number (ß=0.41), lower normalised cortical volume (ß=-0.15) and lower cord area (ß=-0.28) (C-index=0.81). Older age (ß=0.86), higher EDSS (ß=1.40) and cord lesion number (ß=0.87) independently predicted SPMS conversion (C-index=0.91). Predictors of reaching EDSS=3.0 after 5 years were higher baseline EDSS (ß=1.49), cord lesion number (ß=1.02) and lower normalised cortical volume (ß=-0.56) (C-index=0.88). Baseline age (ß=0.30), higher EDSS (ß=2.03), higher cord lesion number (ß=0.66) and lower cord area (ß=-0.41) predicted EDSS=4.0 (C-index=0.92). Finally, higher baseline EDSS (ß=1.87) and cord lesion number (ß=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.

Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes.

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.

Early spinal cord pseudoatrophy in interferon-beta-treated multiple sclerosis.

BACKGROUND AND PURPOSE: Brain pseudoatrophy has been shown to play a pivotal role in the interpretation of brain atrophy measures during the first year of disease-modifying therapy in multiple sclerosis. Whether pseudoatrophy also affects the spinal cord remains unclear. The aim of this study was to analyze the extent of pseudoatrophy in the upper spinal cord during the first 2 years after therapy initiation and compare this to the brain. METHODS: A total of 129 patients from a prospective longitudinal multicentric national cohort study for whom magnetic resonance imaging scans at baseline, 12 months, and 24 months were available were selected for brain and spinal cord volume quantification. Annual percentage brain volume and cord area change were calculated using SIENA (Structural Image Evaluation of Normalized Atrophy) and NeuroQLab, respectively. Linear mixed model analyses were performed to compare patients on interferon-beta therapy (n = 84) and untreated patients (n = 45). RESULTS: Patients treated with interferon-beta demonstrated accelerated annual percentage brain volume and cervical cord area change in the first year after treatment initiation, whereas atrophy rates stabilized to a similar and not significantly different level compared to untreated patients during the second year. CONCLUSIONS: These results suggest that pseudoatrophy occurs not only in the brain, but also in the spinal cord during the first year of interferon-beta treatment.

Association of smoking but not HLA-DRB1*15:01, APOE or body mass index with brain atrophy in early multiple sclerosis.

BACKGROUND: The course of multiple sclerosis (MS) shows substantial inter-individual variability. The underlying determinants of disease severity likely involve genetic and environmental factors. OBJECTIVE: The aim of this study was to assess the impact of APOE and HLA polymorphisms as well as smoking and body mass index (BMI) in the very early MS course. METHODS: Untreated patients ( n = 263) with a recent diagnosis of relapsing-remitting (RR) MS or clinically isolated syndrome underwent standardized magnetic resonance imaging (MRI). Genotyping was performed for single-nucleotide polymorphisms (SNPs) rs3135388 tagging the HLA-DRB1*15:01 haplotype and rs7412 (Ɛ2) and rs429358 (Ɛ4) in APOE. Linear regression analyses were applied based on the three SNPs, smoking and BMI as exposures and MRI surrogate markers for disease severity as outcomes. RESULTS: Current smoking was associated with reduced gray matter fraction, lower brain parenchymal fraction and increased cerebrospinal fluid fraction in comparison to non-smoking, whereas no effect was observed on white matter fraction. BMI and the SNPs in HLA and APOE were not associated with structural MRI parameters. CONCLUSIONS: Smoking may have an unfavorable effect on the gray matter fraction as a potential measure of MS severity already in early MS. These findings may impact patients' counseling upon initial diagnosis of MS.

Multiple sclerosis risk loci correlate with cervical cord atrophy and may explain the course of disability.

Genome-wide association studies (GWAS) underscore the genetic basis of multiple sclerosis (MS); however, only few of the newly reported genetic variations relevant in MS have been replicated or correlated for clinical/paraclinical phenotypes such as spinal cord atrophy in independent patient cohorts. We genotyped 141 MS patients for 58 variations reported to reach significance in GWAS. Expanded disability status scale (EDSS) and disease duration (DD) are available from regular clinical examinations. MRI included sagittal high-resolution 3D T1-weighted magnetization-prepared rapid acquisition gradient echo of the cervical cord region used for volumetry. Due dependency of mean upper cervical cord area (MUCCA) with EDSS and/or DD, correction operations were performed compensating for EDSS/DD. We assessed each MS risk locus for possible MUCCA association. We identified twelve risk loci that significantly correlated with MUCCA. For nine loci-BATF, CYP27B1, IL12B, NFKB1, IL7, PLEK, EVI5, TAGAP and nrs669607-patients revealed significantly higher degree of atrophy; TYK2, RGS1 and CLEC16A revealed inverse effects. The weighted genetic risk score over the twelve loci showed significant correlation with MUCCA. Our data reveal a risk gene depending paraclinical/clinical phenotype. Since MUCCA clearly correlates with disability, the candidates identified here may serve as prognostic markers for disability progression.

Cervical spinal cord volume loss is related to clinical disability progression in multiple sclerosis.

OBJECTIVE: To examine the temporal evolution of spinal cord (SC) atrophy in multiple sclerosis (MS), and its association with clinical progression in a large MS cohort. METHODS: A total of 352 patients from two centres with MS (relapsing remitting MS (RRMS): 256, secondary progressive MS (SPMS): 73, primary progressive MS (PPMS): 23) were included. Clinical and MRI parameters were obtained at baseline, after 12 months and 24 months of follow-up. In addition to conventional brain and SC MRI parameters, the annualised percentage brain volume change and the annualised percentage upper cervical cord cross-sectional area change (aUCCA) were quantified. Main outcome measure was disease progression, defined by expanded disability status scale increase after 24 months. RESULTS: UCCA was lower in SPMS and PPMS compared with RRMS for all time points. aUCCA over 24 months was highest in patients with SPMS (-2.2% per year) and was significantly higher in patients with disease progression (-2.3% per year) than in stable patients (-1.2% per year; p=0.003), while annualised percentage brain volume change did not differ between subtypes (RRMS: -0.42% per year; SPMS -0.6% per year; PPMS: -0.46% per year) nor between progressive and stable patients (p=0.055). Baseline UCCA and aUCCA over 24 months were found to be relevant contributors of expanded disability status scale at month-24, while baseline UCCA as well as number of SC segments involved by lesions at baseline but not aUCCA were relevant contributors of disease progression. CONCLUSIONS: SC MRI parameters including baseline UCCA and SC lesions were significant MRI predictors of disease progression. Progressive 24-month upper SC atrophy occurred in all MS subtypes, and was faster in patients exhibiting disease progression at month-24.

Greater cortical thinning and microstructural integrity loss in myotonic dystrophy type 1 compared to myotonic dystrophy type 2.

BACKGROUND: Myotonic dystrophy is a multisystem disorder characterized by widespread organic involvement including central nervous system symptoms. Although myotonic dystrophy disease types 1 (DM1) and 2 (DM2) cover a similar spectrum of symptoms, more pronounced clinical and brain alterations have been described in DM1. Here, we investigated brain volumetric and white matter alterations in both disease types and compared to healthy controls (HC). METHODS: MRI scans were obtained from 29 DM1, 27 DM2, and 56 HC. We assessed macro- and microstructural brain changes by surface-based analysis of cortical thickness of anatomical images and tract-based spatial statistics of fractional anisotropy (FA) obtained by diffusion-weighted imaging, respectively. Global MRI measures were related to clinical and neuropsychological scores to evaluate their clinical relevance. RESULTS: Cortical thickness was reduced in both patient groups compared to HC, showing similar patterns of regional distribution in DM1 and DM2 (occipital, temporal, frontal) but more pronounced cortical thinning for DM1. Similarly, FA values showed a widespread decrease in DM1 and DM2 compared to HC. Interestingly, FA was significantly lower in DM1 compared to DM2 within most parts of the brain. CONCLUSION: Comparisons between DM1 and DM2 indicate a more pronounced cortical thinning of grey matter and a widespread reduction in microstructural integrity of white matter in DM1. Future studies are required to unravel the underlying and separating mechanisms for the disease courses of the two types and their neuropsychological symptoms.

Cortical atrophy patterns in myelin oligodendrocyte glycoprotein antibody-associated disease.

OBJECTIVES: Global brain volume changes in patients with myelin oligodendrocyte glycoprotein antibody-associated disease compared with healthy controls (HC) could be revealed by magnetic resonance imaging, but specific atrophy patterns of cortical structures and relation to cognitive impairment are not yet comprehensively known. Thus, we aimed to investigate cortical thickness differences in patients with myelin oligodendrocyte glycoprotein antibody-associated disease compared with HC. METHODS: 3-Tesla brain magnetic resonance imaging was performed in 23 patients with myelin oligodendrocyte glycoprotein antibody-associated disease and 49 HC for voxel-wise group comparisons and neuropsychological testing in patients. Surface-based morphometry with region of interest-based surface analysis and region of interest-based extraction of cortical thickness was performed in patients compared with HC and in patient subgroups with and without cognitive impairment. RESULTS: Comparing patients with myelin oligodendrocyte glycoprotein antibody-associated disease with HC, exploratory surface-based morphometry demonstrated cortical volume reduction in pericalcarine and lingual cortical regions. Region of interest-based surface analysis specified reduced cortical thickness in the adjacent pericalcarine and orbitofrontal regions in myelin oligodendrocyte glycoprotein antibody-associated disease, as well as reduced temporal cortical thickness in patients with cognitive impairment (n = 10). Patients without cognitive impairment (n = 13) showed only circumscribed cortical brain volume loss compared with HC in the pericalcarine region. INTERPRETATION: In conclusion, cortical atrophy in myelin oligodendrocyte glycoprotein antibody-associated disease was characterized by cortical thickness reduction in the adjacent pericalcarine and orbitofrontal regions, with a tendency of temporal thickness reduction in cognitively impaired patients.

Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.

BACKGROUND AND OBJECTIVES: Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific effects. In this study, we investigated whether a disease-specific model might complement the brain-age gap (BAG) by capturing aspects unique to MS. METHODS: In this retrospective study, we collected 3D T1-weighted brain MRI scans of PwMS to build (1) a cross-sectional multicentric cohort for age and disease duration (DD) modeling and (2) a longitudinal single-center cohort of patients with early MS as a clinical use case. We trained and evaluated a 3D DenseNet architecture to predict DD from minimally preprocessed images while age predictions were obtained with the DeepBrainNet model. The brain-predicted DD gap (the difference between predicted and actual duration) was proposed as a DD-adjusted global measure of MS-specific brain damage. Model predictions were scrutinized to assess the influence of lesions and brain volumes while the DD gap was biologically and clinically validated within a linear model framework assessing its relationship with BAG and physical disability measured with the Expanded Disability Status Scale (EDSS). RESULTS: We gathered MRI scans of 4,392 PwMS (69.7% female, age: 42.8 ± 10.6 years, DD: 11.4 ± 9.3 years) from 15 centers while the early MS cohort included 749 sessions from 252 patients (64.7% female, age: 34.5 ± 8.3 years, DD: 0.7 ± 1.2 years). Our model predicted DD better than chance (mean absolute error = 5.63 years, R2 = 0.34) and was nearly orthogonal to the brain-age model (correlation between DD and BAGs: r = 0.06 [0.00-0.13], p = 0.07). Predictions were influenced by distributed variations in brain volume and, unlike brain-predicted age, were sensitive to MS lesions (difference between unfilled and filled scans: 0.55 years [0.51-0.59], p < 0.001). DD gap significantly explained EDSS changes (B = 0.060 [0.038-0.082], p < 0.001), adding to BAG (ΔR2 = 0.012, p < 0.001). Longitudinally, increasing DD gap was associated with greater annualized EDSS change (r = 0.50 [0.39-0.60], p < 0.001), with an incremental contribution in explaining disability worsening compared with changes in BAG alone (ΔR2 = 0.064, p < 0.001). DISCUSSION: The brain-predicted DD gap is sensitive to MS-related lesions and brain atrophy, adds to the brain-age paradigm in explaining physical disability both cross-sectionally and longitudinally, and may be used as an MS-specific biomarker of disease severity and progression.

Relevance of spinal cord abnormalities to clinical disability in multiple sclerosis: MR imaging findings in a large cohort of patients.

PURPOSE: To determine whether spinal cord atrophy differs among disease subtypes in multiple sclerosis (MS) and whether it offers diagnostic and clinical correlative information beyond that provided by other magnetic resonance (MR) imaging markers. MATERIALS AND METHODS: The institutional review board approved the study; all subjects gave written informed consent. Upper cervical cord cross-sectional area (UCCA), brain and spinal cord lesion loads, and brain atrophy were measured in 440 patients with MS (311 with relapsing-remitting [RR] MS, 92 with secondary-progressive [SP] MS, and 37 with primary-progressive [PP] MS) studied in two centers. Disability was scored with the Expanded Disability Status Scale (EDSS), the timed 25-foot walk test (TWT), and the nine-hole peg test. UCCA was compared between groups with the Mann-Whitney U test. Correlations were assessed with the Spearman ρ test. Multivariate associations between UCCA and clinical and other MR imaging parameters, including number of hypointense brain lesions on T1-weighted MR images, presence of diffuse abnormalities, and number of involved segments in the spinal cord, were assessed by using multiple linear regression, adjusted for study center site. RESULTS: The UCCA in patients with SP MS (median, 79 mm(2); interquartile range, 72.4-84.9 mm(2)) and PP MS (median, 77.3 mm(2); interquartile range, 69-82.5 mm(2)) was significantly smaller (P < .001) than that in patients with RR MS (median, 84 mm(2); interquartile range, 78.7-89.3 mm(2)). UCCA was inversely correlated with EDSS score, TWT, and nine-hole peg test findings (ρ ≤ -0.29, P < .001 for all comparisons). UCCA, number of hypointense brain lesions on T1-weighted MR images, presence of diffuse abnormalities, and number of involved segments in the spinal cord were found to be significant explanatory factors for clinical disability (R(2) = 0.564). The UCCA and the number of hypointense brain lesions on T1-weighted images were the strongest MR imaging parameters for explaining physical disability, as measured with the EDSS. CONCLUSION: Spinal cord abnormalities have a strong effect on clinical disability in MS. MR imaging-derived UCCA was found to be the most significant spinal cord parameter for explaining EDSS score.

1H-magnetic resonance spectroscopy in diffuse and focal cervical cord lesions in multiple sclerosis.

OBJECTIVES: To investigate differences between focal and diffuse cervical lesions in multiple sclerosis (MS) by proton magnetic resonance spectroscopy ((1)H-MRS) at 1.5 T in comparison to quantitative MR imaging of the upper cervical cord area and T2 relaxometry at baseline and follow-up. METHODS: Including 22 MS patients with persistent spinal cord symptoms by either diffuse or focal lesions and 17 controls, we acquired MRS, the mean cord area and the water T2 relaxation time and disability at baseline and follow-up. Cross-sectional analyses included group-level comparisons and correlation studies. Follow-up studies covered assessment of reproducibility and progression of the baseline results. RESULTS: Compared with focal lesions, diffuse lesions were attended by more cord atrophy, longer T2, elevated levels of creatine (Cre) and reduced N-acetyl aspartate (NAA)/Cre (focal/diffuse: 83 ± 9/73 ± 15 mm(2), 121 ± 21/104 ± 13 ms, 3.6 ± 1.1/5.1 ± 2.4 mM, 2.4 ± 1.1/2.0 ± 0.9). NAA/Cre at baseline was associated significantly with cord atrophy and with clinical progression during follow-up. Baseline MRS results were not significantly correlated to the clinical disability parameters. The reproducibility of MRS was 0.17-0.30. Longitudinal changes of the MRS results were not statistically significant. CONCLUSIONS: MRS indicated differences in demyelination and gliosis between diffuse and focal cervical lesions in MS. Although longitudinal spectral and clinical changes were sparse, NAA/Cre turned out to be the most sensitive spectral parameter.

Relaxometry and brain myelin quantification with synthetic MRI in MS subtypes and their associations with spinal cord atrophy.

Immune-mediated demyelination and neurodegeneration are pathophysiological hallmarks of Multiple Sclerosis (MS) and main drivers of disease related disability. The principal method for evaluating qualitatively demyelinating events in the clinical context is contrast-weighted magnetic resonance imaging (MRI). Moreover, advanced MRI sequences provide reliable quantification of brain myelin offering new opportunities to study tissue pathology in vivo. Towards neurodegenerative aspects of the disease, spinal cord atrophy - besides brain atrophy - is a powerful and validated predictor of disease progression. The etiology of spinal cord volume loss is still a matter of research, as it remains unclear whether the impact of local lesion pathology or the interaction with supra- and infratentorial axonal degeneration and demyelination of the long descending and ascending fiber tracts are the determining factors. Quantitative synthetic MR using a multiecho acquisition of saturation recovery pulse sequence provides fast automatic brain tissue and myelin volumetry based on R1 and R2 relaxation rates and proton density quantification, making it a promising modality for application in the clinical routine. In this cross sectional study a total of 91 MS patients and 31 control subjects were included to investigate group differences of global and regional measures of brain myelin and relaxation rates, in different MS subtypes, using QRAPMASTER sequence and SyMRI postprocessing software. Furthermore, we examined associations between these quantitative brain parameters and spinal cord atrophy to draw conclusions about possible pathophysiological relationships. Intracranial myelin volume fraction of the global brain exhibited statistically significant differences between control subjects (10.4%) and MS patients (RRMS 9.4%, PMS 8.1%). In a LASSO regression analysis with total brain lesion load, intracranial myelin volume fraction and brain parenchymal fraction, the intracranial myelin volume fraction was the variable with the highest impact on spinal cord atrophy (standardized coefficient 4.52). Regional supratentorial MRI metrics showed altered average myelin volume fraction, R1, R2 and proton density in MS patients compared to controls most pronounced in PMS. Interestingly, quantitative MRI parameters in supratentorial regions showed strong associations with upper cord atrophy, suggesting an important role of brain diffuse demyelination on spinal cord pathology possibly in the context of global disease activity. R1, R2 or proton density of the thalamus, cerebellum and brainstem correlated with upper cervical cord atrophy, probably reflecting the direct functional connection between these brain structures and the spinal cord as well as the effects of retrograde and anterograde axonal degeneration. By using Synthetic MR-derived myelin volume fraction, we were able to effectively detect significant differences of myelination in relapsing and progressive MS subtypes. Total intracranial brain myelin volume fraction seemed to predict spinal cord volume loss better than brain atrophy or total lesion load. Furthermore, demyelination in highly myelinated supratentorial regions, as an indicator of diffuse disease activity, as well as alterations of relaxation parameters in adjacent infratentorial and midbrain areas were strongly associated with upper cervical cord atrophy.

Quantification of individual remyelination during short-term disease course by synthetic magnetic resonance imaging.

MRI is an important diagnostic tool for evaluation of myelin content in multiple sclerosis and other CNS diseases, being especially relevant for studies investigating remyelinating pharmacotherapies. In this study, we evaluated a new synthetic MRI-based myelin estimation in methylenetetrahydrofolate reductase deficiency as a treatable primary demyelinating disorder and compared this method with established diffusion tensor imaging in both methylenetetrahydrofolate reductase deficiency patients and healthy controls. This is the first synthetic MRI-based in vivo evaluation of treatment-associated remyelination. 1.5 T synthetic MRI and 3 T diffusion MRI were obtained from three methylenetetrahydrofolate reductase deficiency patients at baseline and 6 months after therapy initiation, as well as from age-matched healthy controls (diffusion tensor imaging: n = 14, synthetic MRI: n = 9). Global and regional synthetic MRI parameters (myelin volume fraction, proton density, and relaxation rates) were compared with diffusion metrics (fractional anisotropy, mean/radial/axial diffusivity) and related to healthy controls by calculating z-scores and z-deviation maps. Whole-brain myelin (% of intracranial volume) of the index patient was reduced to 6 versus 10% in healthy controls, which recovered to a nonetheless subnormal level of 6.6% following initiation of high-dosage betaine. Radial diffusivity was higher at baseline compared with healthy controls (1.34 versus 0.79 × 10-3 mm2/s), recovering at follow-up (1.19 × 10-3 mm2/s). The index patient's lesion volume diminished by 58% under treatment. Regional analysis within lesion area and atlas-based regions revealed lower mean myelin volume fraction (12.7Baseline/14.71Follow-up%) and relaxation rates, higher proton density, as well as lower fractional anisotropy and higher radial diffusivity (1.08 × 10-3 Baseline/0.94 × 10-3 Follow-up) compared with healthy controls. The highest z-scores were observed for myelin volume fraction in the posterior thalamic radiation, with greater deviation from controls at baseline and reduced deviation at follow-up. Z-deviations of diffusion metrics were less pronounced for radial and mean diffusivity than for myelin volume fraction. Z-maps for myelin volume fraction of the index patient demonstrated high deviation within and beyond lesion areas, among others in the precentral and postcentral gyrus, as well as in the cerebellum, and partial remission of these alterations at follow-up, while radial diffusivity demonstrated more widespread deviations in supra- and infratentorial regions. Concordant changes of myelin volume fraction and radial diffusivity after treatment initiation, accompanied by dramatic clinical and paraclinical improvement, indicate the consistency of the methods, while myelin volume fraction seems to characterize remyelinated regions more specifically. Synthetic MRI-based myelin volume fraction provides myelin estimation consistent with changes of diffusion metrics to monitor short-term myelin changes on individual patient level.

A new sulcus-corrected approach for assessing cerebellar volume in spinocerebellar ataxia.

Precise volumetry of the cerebellum still remains challenging, due to thin sulci and gyri. We present a new fast and reliable sulcus-corrected approach for quantitative assessment of cerebellar atrophy, evaluated on patients with spinocerebellar ataxia (SCA). Thin-sliced T1-weighted magnetic resonance images (MPRAGE) were acquired in 11 genetically confirmed SCA6 patients and in a group of age-matched control subjects (n=14). Post-processing involves a morphological image segmentation pipeline as a basis for a sulcus-corrected cerebellar volume measurement. Cerebellar volumes and intra-rater, inter-rater and scan-rescan reproducibility were quantified. Reliability of the measurements was validated using an anatomical preparation of the cerebellum. Repeatability coefficients (RC: intra-rater/inter-rater/scan-rescan) of the method were 1.07%/1.11%/1.35%. Absolute cerebellar volumes showed good agreement with the actual volume of the anatomical preparation. The cerebellar volume of the SCA 6 was 96.3±12.1ml (mean±S.D.), which was significantly lower than the results of the corresponding control groups. The cerebellar volume correlated significantly to clinical dysfunction in SCA6. This is the first study to demonstrate the feasibility of a new sulcus-corrected approach to assess cerebellar volume. In contrast to currently used methods, this new approach may be more sensitive even to small atrophic changes affecting sulcal widening.