MRI: how to understand it

MRI is a staple of the neurologist’s armoury when facing diagnostic challenges. At times, it can reveal or confirm the diagnosis with clarity, at others it brings us no further forwards, or even muddies the water. We rely on the expertise of neuroradiology colleagues to interpret MR images, but the choice of protocol for MR acquisition and its interpretation hinge crucially on the clinical information we provide. Having a degree of understanding about how MRI works, its limitations and pitfalls, can help to optimise what we learn from a scan

Secondary antibody deficiency: a complication of anti-CD20 therapy for neuroinflammation

B-cell depleting anti-CD20 monoclonal antibody therapies are being increasingly used as long-term maintenance therapy for neuroinflammatory disease compared to many non-neurological diseases where they are used as remission-inducing agents. While hypogammaglobulinaemia is known to occur in over half of patients treated with medium to long-term B-cell-depleting therapy (in our cohort IgG 38, IgM 56 and IgA 18%), the risk of infections it poses seems to be under-recognised. Here, we report five cases of serious infections associated with hypogammaglobulinaemia occurring in patients receiving rituximab for neuromyelitis optica spectrum disorders. Sixty-four per cent of the whole cohort of patients studied had hypogammaglobulinemia. We discuss the implications of these cases to the wider use of anti-CD20 therapy in neuroinflammatory disease

Beyond lesion-load: tractometry-based metrics for characterizing white matter lesions within fibre pathways

In multiple sclerosis studies, lesion volume (or lesion load) derived from conventional T2 imaging correlates modestly with clinical assessment. Determining which specific white matter pathways are impacted by lesions may provide additional insights regarding task-specific clinical impairment. Using diffusion MRI, we introduce a set of tract-based metrics that go beyond traditional lesion load approaches and show how they relate to task performance (i.e., working memory, information processing and verbal fluency) in a cohort of 40 patients with multiple sclerosis

Tractography in the presence of multiple sclerosis lesions

Accurate anatomical localisation of specific white matter tracts and the quantification of their tract-specific microstructural damage in conditions such as multiple sclerosis (MS) can contribute to a better understanding of symptomatology, disease evolution and intervention effects. Diffusion MRI-based tractography is being used increasingly to segment white matter tracts as regions-of-interest for subsequent quantitative analysis. Since MS lesions can interrupt the tractography algorithm’s tract reconstruction, clinical studies frequently resort to atlas-based approaches, which are convenient but ignorant to individual variability in tract size and shape. Here, we revisit the problem of individual tractography in MS, comparing tractography algorithms using: (i) The diffusion tensor framework; (ii) constrained spherical deconvolution (CSD); and (iii) damped Richardson-Lucy (dRL) deconvolution. Firstly, using simulated and in vivo data from 29 MS patients and 19 healthy controls, we show that the three tracking algorithms respond differentially to MS pathology. While the tensor-based approach is unable to deal with crossing fibres, CSD produces spurious streamlines, in particular in tissue with high fibre loss and low diffusion anisotropy. With dRL, streamlines are increasingly interrupted in pathological tissue. Secondly, we demonstrate that despite the effects of lesions on the fibre orientation reconstruction algorithms, fibre tracking algorithms are still able to segment tracts that pass through areas with a high prevalence of lesions. Combining dRL-based tractography with an automated tract segmentation tool on data from 131 MS patients, the cortico-spinal tracts and arcuate fasciculi could be reconstructed in more than 90% of individuals. Comparing tract-specific microstructural parameters (fractional anisotropy, radial diffusivity and magnetisation transfer ratio) in individually segmented tracts to those from a tract probability map, we show that there is no systematic disease-related bias in the individually reconstructed tracts, suggesting that lesions and otherwise damaged parts are not systematically omitted during tractography. Thirdly, we demonstrate modest anatomical correspondence between the individual and tract probability-based approach, with a spatial overlap between 35 and 55%. Correlations between tract-averaged microstructural parameters in individually segmented tracts and the probability-map approach ranged between r=.53 ( p<.001 ) for radial diffusivity in the right cortico-spinal tract and r=.97 ( p<.001 ) for magnetisation transfer ratio in the arcuate fasciculi. Our results show that MS white matter lesions impact fibre orientation reconstructions but this does not appear to hinder the ability to anatomically reconstruct white matter tracts in MS. Individual tract segmentation in MS is feasible on a large scale and could prove a powerful tool for investigating diagnostic and prognostic markers

Predictors of training-related improvement in visuomotor performance in patients with multiple sclerosis: a behavioural and MRI study

Background: The development of tailored recovery-oriented strategies in multiple sclerosis requires early identification of an individual’s potential for functional recovery. Objective: To identify predictors of visuomotor performance improvements, a proxy of functional recovery, using a predictive statistical model that combines demographic, clinical and magnetic resonance imaging (MRI) data. Methods: Right-handed multiple sclerosis patients underwent baseline disability assessment and MRI of the brain structure, function and vascular health. They subsequently undertook 4 weeks of right upper limb visuomotor practice. Changes in performance with practice were our outcome measure. We identified predictors of improvement in a training set of patients using lasso regression; we calculated the best performing model in a validation set and applied this model to a test set. Results: Patients improved their visuomotor performance with practice. Younger age, better visuomotor abilities, less severe disease burden and concurrent use of preventive treatments predicted improvements. Neuroimaging localised outcome-relevant sensory motor regions, the microstructure and activity of which correlated with performance improvements. Conclusion: Initial characteristics, including age, disease duration, visuo-spatial abilities, hand dexterity, self-evaluated disease impact and the presence of disease-modifying treatments, can predict functional recovery in individual patients, potentially improving their clinical management and stratification in clinical trials. MRI is a correlate of outcome, potentially supporting individual prognosis

Clinical observation during alemtuzumab administration

• Alemtuzumab has been associated with stroke and cervicocephalic dissections. • Monitoring blood pressure is currently recommended by the EMA. • Monitoring blood pressure is not useful in predicting these rare side effects

Modelling disease progression of Multiple Sclerosis in a South Wales cohort

Objectives: To model multiple sclerosis (MS) disease progression and compare disease trajectories by sex, age of onset, and year of diagnosis. Study Design and settings: Longitudinal EDSS scores (20,854 observations) were collected for 1787 relapse-onset MS patients at MS clinics in South Wales and modelled using a multilevel model (MLM). The MLM adjusted for baseline covariates (sex, age of onset, year of diagnosis, and disease modifying treatments (DMTs)), and included interactions between baseline covariates and time variables. Results: The optimal model was truncated at 30 years after disease onset and excluded EDSS recorded within 3 months of relapse. As expected, older age of onset was associated with faster disease progression at 15 years (effect size (ES): 0.75; CI: 0.63, 0.86; P: 2011) progressed more slowly than those diagnosed historically (<2006); (ES: -0.46; CI: -0.75, -0.16; P: 0.006) and (ES: -0.95; CI: -1.20, -0.70; P: <0.001), respectively. Conclusion: We present a novel model of MS outcomes, accounting for the nonlinear trajectory of MS and effects of baseline covariates, validating well-known risk factors (sex and age of onset) associated with disease progression. Also, patients diagnosed more recently progressed more slowly than those diagnosed historically