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Spinal cord (SC) atrophy obtained from structural magnetic resonance imaging has gained relevance as an indicator of neurodegeneration in various neurological disorders. The common method to assess SC atrophy is by comparing numerical differences of the cross-sectional spinal cord area (CSA) between time points. However, this indirect approach leads to considerable variability in the obtained results. Studies showed that this limitation can be overcome by using a registration-based technique.The present study introduces the Structural Image Evaluation using Normalization of Atrophy on the Spinal Cord (SIENA-SC), which is an adapted version of the original SIENA method, designed to directly calculate the percentage of SC volume change over time from clinical brain MRI acquired with an extended field of view to cover the superior part of the cervical SC.In this work, we compared SIENA-SC with the Generalized Boundary Shift Integral (GBSI) and the CSA change. On a scan-rescan dataset, SIENA-SC was shown to have the lowest measurement error than the other two methods. When comparing a group of 190 Healthy Controls with a group of 65 Multiple Sclerosis patients, SIENA-SC provided significantly higher yearly rates of atrophy in patients than in controls and a lower sample size when measured for treatment effect sizes of 50%, 30% and 10%.Our findings indicate that SIENA-SC is a robust, reproducible, and sensitive approach for assessing longitudinal changes in spinal cord volume, providing neuroscientists with an accessible and automated tool able to reduce the need for manual intervention and minimize variability in measurements.

Background: White matter (WM) lesions and brain atrophy are present early in multiple sclerosis (MS). However, their spatio-temporal relationship remains unclear. Methods: Yearly magnetic resonance images were analysed in 387 patients with a first clinical demyelinating event (FCDE) from the 5-year REFLEXION study. Patients received early (from baseline; N = 258; ET) or delayed treatment (from month-24; N = 129; DT) with subcutaneous interferon beta-1a. FSL-SIENA/VIENA were used to provide yearly percentage volume change of brain (PBVC) and ventricles (PVVC). Yearly total lesion volume change (TLVC) was determined by a semi-automated method. Using linear mixed models and voxel-wise analyses, we firstly investigated the overall relationship between TLVC and PBVC and between TLVC and PVVC in the same follow-up period. Analyses were then separately performed for: the untreated period of DT patients (first two years), the first year of treatment (year 1 for ET and year 3 for DT), and a period where patients had received at least 1 year of treatment (stable treatment; ET: years 2, 3, 4, and 5; DT: years 4 and 5). Results: Whole brain: across the whole study period, lower TLVC was related to faster atrophy (PBVC: B = 0.046, SE = 0.013, p

Background: White matter lesions and brain atrophy are both present early in multiple sclerosis. However, the spatio-temporal relationship between atrophy and lesion processes remains unclear. Methods: Yearly magnetic resonance images were analyzed in 392 patients with clinically isolated syndrome from the 5-year REFLEX/REFLEXION studies. Patients received early treatment (from baseline; N = 262) or delayed treatment (from month-24; N = 130) with subcutaneous interferon beta-1a. Global and central atrophy were assessed using FSL-SIENA to provide yearly percentage volume change of brain and ventricles, respectively. Yearly total lesion volume change was calculated by subtracting the sum of the negative lesion volume change (disappearing + shrinking) from the positive lesion volume change (new + enlarging) for each yearly interval, as determined by an in-house developed semi-automated method. Using linear mixed models, during the period where patients had received ≥1 year of treatment, we investigated whether total lesion volume change was associated with percentage brain volume change or percentage ventricular volume change in the next year, and vice versa. Results: Higher total lesion volume change was related to significantly faster global atrophy (percentage brain volume change) in the next year (B = − 0.113, SE = 0.022, p

There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.

Background: Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion’s metrics and clinical outcomes in relapse-onset MS has not been widely investigated. Objectives: To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. Methods: 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was ≤ 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). Results: Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p

Atrophy of the brain grey matter (GM) is an accepted and important feature of multiple sclerosis (MS). However, its accurate measurement is hampered by various technical, pathological and physiological factors. As a consequence, it is challenging to investigate the role of GM atrophy in the disease process as well as the effect of treatments that aim to reduce neurodegeneration. In this paper we discuss the most important challenges currently hampering the measurement and interpretation of GM atrophy in MS. The focus is on measurements that are obtained in individual patients rather than on group analysis methods, because of their importance in clinical trials and ultimately in clinical care. We discuss the sources and possible solutions of the current challenges, and provide recommendations to achieve reliable measurement and interpretation of brain GM atrophy in MS. Keywords: Multiple sclerosis, Brain atrophy, Grey matter, Magnetic resonance imaging