The detection of new or enlarged white-matter lesions in multiple sclerosis is a vital task in the monitoring of patients undergoing disease-modifying treatment for multiple sclerosis. However, the definition of 'new or enlarged' is not fixed, and it is known that lesion-counting is highly subjective, with high degree of inter-and intra-rater variability. Automated methods for lesion quantification, if accurate enough, hold the potential to make the detection of new and enlarged lesions consistent and repeatable. However, the majority of lesion segmentation algorithms are not evaluated for their ability to separate radiologically progressive from radiologically stable patients, despite this being a pressing clinical use-case. In this paper we demonstrate that change in volumetric measurements of lesion load alone is not a good method for performing this separation, even for highly performing segmentation methods. Instead, we propose a method for identifying lesion changes of high certainty, and establish on an internal dataset of longitudinal multiple sclerosis cases that this method is able to separate progressive from stable timepoints with a very high level of discrimination (AUC = 0.999), while changes in lesion volume are much less able to perform this separation (AUC = 0.71). Validation of the method on a second external dataset confirms that the method is able to generalize beyond the setting in which it was trained, achieving an accuracy of 83 % in separating stable and progressive timepoints.Both lesion volume and lesion count have previously been shown to be, together with clinical covariates, strong predictors of disease course across a population. However, in this paper we demonstrate that for individual patients, changes in these measures are not an adequate means of establishing no evidence of disease activity. Meanwhile, directly detecting tissue which changes, with high confidence, from non-lesion to lesion is a feasible methodology for identifying radiologically active patients.

Background: In multiple sclerosis (MS), the frequency of hypogammaglobulinemia is unknown. We aimed to evaluate the frequency of reduced immunoglobulin (Ig) concentrations and its association with immunotherapy and disease course in two independent MS cohorts. Methods: In our retrospective cross-sectional study, MS patients and control patients with head or neck pain from Bern University Hospital (Bern, Switzerland) and Eginition University Hospital (Athens, Greece) were included. The lower limits of normal (LLN) for serum Ig concentration were IgG < 700 mg/dl, IgM < 40 mg/dl, and IgA < 70 mg/dl. Mann–Whitney U test, analysis of variance test, and multiple linear regression analysis were employed. Results: In total, 327 MS patients were retrospectively identified (Bern/Athens: n = 226/101). Serum IgG concentrations were frequently under LLN in both MS cohorts (Bern/Athens: 15.5%/14.9%), even when considering only untreated patients (Bern/Athens: 7.9%/8.6%). MS patients ( n = 327) were significantly more likely to have IgG concentrations below LLN and below 600 mg/dl in comparison with controls ( n = 58) ( p = 0.015 and 0.047, respectively). Between both patient groups, no significant differences were found in frequencies of IgA and IgM concentrations under LLN [ n (MS patients/controls): IgA 203/30, IgM 224/24]. Independently of age, secondary progressive MS patients had lower IgG concentrations than relapsing–remitting and primary progressive patients (both: p ⩽ 0.01). After adjusting for sex, age, and disease course, IgG concentrations were lower in patients treated with rituximab ( p = 0.001; n = 42/327), intravenous corticosteroids ( p < 0.001; n = 16/327), natalizumab ( p < 0.001; n = 48/327), and fingolimod ( p = 0.003; n = 6/327). Conclusion: Our study demonstrated high prevalence rates of reduced serum IgG concentrations in MS patients with and without disease-modifying treatments. The significance of lower IgG concentrations at the levels noted is unclear considering that infections or interference with antibody production generally occur when IgG levels are much lower, at or below 400 mg/dl. However, the information is useful to monitor IgG levels especially with anti-B-cell therapies and consider IgG substitution when levels drop below 400 mg/dl.

Background: Dimethyl fumarate (DMF) is licensed for treatment of relapsing–remitting multiple sclerosis (RRMS). DMF can induce lymphopenia, which is assumed to increase the risk for opportunistic infections like progressive multifocal leukoencephalopathy. Our goal for this work was to estimate the frequency of grade 3 lymphopenia in DMF-treated patients with RRMS and to characterize patient-sided factors influencing the time course of lymphocyte repopulation after DMF withdrawal. Material and methods: A single-center retrospective data analysis was performed at University Hospital Bern, Switzerland. Patients with DMF treatment were analyzed for lymphocyte counts. Demographic factors were statistically analyzed in grade 3 lymphopenic patients. Results: We estimated a grade 3 lymphopenia frequency of 11/246 (4.5%), corroborating previous studies. In all patients, lymphocytes recovered to values ⩾800/µl within 0.5 years. Multivariate linear regression analysis unmasked older age as being associated with a longer duration of repopulation. Conclusion: Considering the aging population, our findings warrant further investigations of DMF-induced lymphopenia.