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Multiple sclerosis is a heterogeneous progressive disease. Here, the authors use an unsupervised machine learning algorithm to determine multiple sclerosis subtypes, progression, and response to potential therapeutic treatments based on neuroimaging data.

Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient’s lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are.We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders.Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions.

Objective: To reveal the immediate extent of trauma-induced neurodegenerative changes rostral to the level of lesion and determine the predictive clinical value of quantitative MRI (qMRI) following acute spinal cord injury (SCI). Methods: Twenty-four acute SCI patients and 23 healthy controls underwent a high-resolution T1-weighted protocol. Eighteen of those patients and 20 of controls additionally underwent a multi-parameter mapping (MPM) MRI protocol sensitive to the content of tissue structure, including myelin and iron. Patients were examined clinically at baseline, 2, 6, 12, and 24 months post-SCI. We assessed volume and microstructural changes in the spinal cord and brain using T1-weighted MRI, magnetization transfer (MT), longitudinal relaxation rate (R1), and effective transverse relaxation rate (R2*) maps. Regression analysis determined associations between acute qMRI parameters and recovery. Results: At baseline, cord area and its anterior-posterior width were decreased in patients, whereas MT, R1, and R2* parameters remained unchanged in the cord. Within the cerebellum, volume decrease was paralleled by increases of MT and R2* parameters. Early grey matter changes were observed within the primary motor cortex and limbic system. Importantly, early volume and microstructural changes of the cord and cerebellum predicted functional recovery following injury. Conclusions: Neurodegenerative changes rostral to the level of lesion occur early in SCI, with varying temporal and spatial dynamics. Early qMRI markers of spinal cord and cerebellum are predictive of functional recovery. These neuroimaging biomarkers may supplement clinical assessments and provide insights into the potential of therapeutic interventions to enhance neural plasticity. Keywords: Spinal cord injury, Quantitative neuroimaging, Acute micro-structural changes, Brain and spinal cord atrophy, Voxel-based morphometry and quantification

Introduction There remains a high unmet need for disease-modifying therapies that can impact disability progression in secondary progressive multiple sclerosis (SPMS). Following positive results of the phase 2 MS-STAT study, the MS-STAT2 phase 3 trial will evaluate the efficacy and cost-effectiveness of repurposed high-dose simvastatin in slowing the progression of disability in SPMS.Methods and analysis MS-STAT2 will be a multicentre, randomised, placebo-controlled, double-blind trial of participants aged between 25 and 65 (inclusive) who have SPMS with an Expanded Disability Status Scale (EDSS) score of 4.0–6.5 (inclusive). Steady progression rather than relapse must be the major cause of increasing disability in the preceding 2 years.Participants will be allocated to simvastatin or placebo in a 1:1 ratio. The active treatment will be 80 mg daily, after 1 month at 40 mg daily. 31 hospitals across the UK will participate.The primary outcome is (confirmed) disability progression at 6 monthly intervals, measured as change from EDSS baseline score. Recruitment of 1050 participants will be required to achieve a total of 330 progression events, giving 90% power to demonstrate a 30% relative reduction in disability progression versus placebo. The follow-up period is 36 months, extendable by up to 18 months for patients without confirmed progression.Clinician-reported measures include Timed 25 Foot Walk; 9 Hole Peg Test; Single Digit Modalities Test; Sloan Low Contrast Visual Acuity; Relapse assessment; modified Rankin Scale and Brief International Cognitive Assessment For Multiple Sclerosis. Patient-reported outcomes include MS-specific walking, fatigue and impact scales. A health economic analysis will occur.Ethics and dissemination The protocol was approved by the London-Westminster REC (17/LO/1509). This manuscript is based on protocol version 8.0, 26 February 2024. Trial findings will be disseminated through peer-reviewed publications and conference presentations.Trial registration numbers NCT03387670; ISRCTN82598726.

To derive a simple predictive model to guide the use of corticosteroids in patients with relapsing remitting MS suffering an acute relapse.We analysed individual patient randomised controlled trial data (n=98) using a binary logistic regression model based on age, gender, baseline disability scores [physician-observed: expanded disability status scale (EDSS) and patient reported: multiple sclerosis impact scale 29 (MSIS-29)], and the time intervals between symptom onset or referral and treatment.Based on two a priori selected cut-off points (improvement in EDSS ≥ 0.5 and ≥ 1.0), we found that variables which predicted better response to corticosteroids after 6 weeks were younger age and lower MSIS-29 physical score at the time of relapse (model fit 71.2% - 73.1%).This pilot study suggests two clinical variables which may predict the majority of the response to corticosteroid treatment in patients undergoing an MS relapse. The study is limited in being able to clearly distinguish factors associated with treatment response or spontaneous recovery and needs to be replicated in a larger prospective study.

Magnetic resonance spectroscopy (MRS) studies have previously described metabolite changes associated with aging of the healthy brain and provided insights into normal brain aging that can assist us in differentiating age-related changes from those associated with neurological disease. The present study investigates whether age-related changes in metabolite concentrations occur in the healthy cervical spinal cord. 25 healthy volunteers, aged 23-65 years, underwent conventional imaging and single-voxel MRS of the upper cervical cord using an optimised point resolved spectroscopy sequence on a 3T Achieva system. Metabolite concentrations normalised to unsuppressed water were quantified using LCModel and associations between age and spinal cord metabolite concentrations were examined using multiple regressions. A linear decline in total N-Acetyl-aspartate concentration (0.049 mmol/L lower per additional year of age, p = 0.010) and Glutamate-Glutamine concentration (0.054 mmol/L lower per additional year of age, p = 0.002) was seen within our sample age range, starting in the early twenties. The findings suggest that neuroaxonal loss and/or metabolic neuronal dysfunction, and decline in glutamate-glutamine neurotransmitter pool progress with aging.

Traumatic spinal cord injury (SCI) leads to disruption of axons and macroscopic tissue loss. Using diffusion tensor imaging (DTI), we assessed degeneration of the corticospinal tract (CST) in the cervical cord above a traumatic lesion and explored its relationship with cervical atrophy, remote axonal changes within the cranial CST and upper limb function.Nine cervical injured volunteers with bilateral motor and sensory impairment and ten controls were studied. DTI of the cervical cord and brain provided measurements of fractional anisotropy (FA), while anatomical MRI assessed cross-sectional spinal cord area (i.e. cord atrophy). Spinal and central regions of interest (ROI) included the bilateral CST in the cervical cord and brain. Regression analysis identified correlations between spinal FA and cranial FA in the CST and disability.In individuals with SCI, FA was significantly lower in both CSTs throughout the cervical cord and brain when compared with controls (p≤0.05). Reduced FA of the cervical cord in patients with SCI was associated with smaller cord area (p = 0.002) and a lower FA of the cranial CST at the internal capsule level (p = 0.001). Lower FA in the cervical CST also correlated with impaired upper limb function, independent of cord area (p = 0.03).Axonal degeneration of the CST in the atrophic cervical cord, proximal to the site of injury, parallels cranial CST degeneration and is associated with disability. This DTI protocol can be used in longitudinal assessment of microstructural changes immediately following injury and may be utilised to predict progression and monitor interventions aimed at promoting spinal cord repair.