Multimodal imaging assessment of neurodegeneration and neuroplasticity in multiple sclerosis

Background The advent of advanced magnetic resonance imaging (MRI) techniques has allowed to study multiple sclerosis (MS) evolution over time, providing qualitative information and quantitative measures related to tissue damage. However some relevant questions remain unanswered, mainly concerning a better definition of structural and functional features of disease progression as well as the identification of causal factors for disease evolution over time Aims to characterize different aspects of disease progression, by applying a multimodal imaging approach. Methods Together with traditional measures of lesion volumes, such as T1-weighted and T2-weighted lesion loads, and of global and regional brain volumes, we applied: quantitative susceptibility mapping (QSM) to quantify iron; diffusion tensor imaging (DTI) to analyze microstructural tissue properties; functional MRI (fMRI) to analyze activity pattern in response to a motor task; resting state fMRI to analyze functional connectivity within regions of interest; optical coherence tomography (OCT) to evaluate the usefulness of an alternative imaging technique in the study of neuroaxonal damage Results We showed that disease progression is related to iron dyshomeostasis in deep grey matter structures. We confirmed the usefulness of a novel MRI marker such as atrophied T2-LV, reflecting both lesion accrual and simultaneously occurring irreversible tissue loss. Moreover, we confirmed the role of sNfL and OCT measures as markers reflective of neuroaxonal degeneration. Finally, we analyzed the effect of motor rehabilitation on clinical and MRI markers, supporting its usefulness as a non-pharmacological treatment able to impact on disability. Discussion/Conclusions The findings here reported highlight that MS disease progression cannot be properly characterized using conventional radiological imaging, or even a single advanced neuroimaging modality. Only the combination of structural and functional MRI techniques investigating complementary aspects of MS-related pathogenetic mechanisms can lead to a better understanding of disease progression

Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple Sclerosis

Applying Artificial Intelligence (AI) and Machine Learning (ML) in critical contexts, such as medicine, requires the implementation of safety measures to reduce risks of harm in case of prediction errors. Spotting ML failures is of paramount importance when ML predictions are used to drive clinical decisions. ML predictive reliability measures the degree of trust of a ML prediction on a new instance, thus allowing decision-makers to accept or reject it based on its reliability. To assess reliability, we propose a method that implements two principles. First, our approach evaluates whether an instance to be classified is coming from the same distribution of the training set. To do this, we leverage Autoencoders (AEs) ability to reconstruct the training set with low error. An instance is considered Out-of-Distribution (OOD) if the AE reconstructs it with a high error. Second, it is evaluated whether the ML classifier has good performances on samples similar to the newly classified instance by using a proxy model. We show that this approach is able to assess reliability both in a simulated scenario and on a model trained to predict disease progression of Multiple Sclerosis patients. We also developed a Python package, named relAI, to embed reliability measures into ML pipelines. We propose a simple approach that can be used in the deployment phase of any ML model to suggest whether to trust predictions or not. Our method holds the promise to provide effective support to clinicians by spotting potential ML failures during deployment.Comment: 20 pages, 7 figure

Intensive Multimodal Training to Improve Gait Resistance, Mobility, Balance and Cognitive Function in Persons With Multiple Sclerosis: A Pilot Randomized Controlled Trial

Introduction: Persons with multiple sclerosis (MS) have deficits in many aspects of physical and cognitive functioning that can impact on mobility and participation in daily life. The effect of a 4 week intensive multimodal treadmill training on functional mobility, balance, executive functions and participation in persons with MS with moderate to severe disability was investigated.Methods: Thirty eight persons with MS admitted to a rehabilitation center participated in a two arm randomized 2:1 controlled trial. Participants in the experimental group received supervised intensive treadmill training including cognitive and motor dual tasks (DT-group, N = 26), 5 sessions per week and a control group received the same amount of supervised strength training (S-group, N = 12). The participants were assessed before and after the rehabilitation period with the 2 Minutes Walking Test (2MWT), speed and, static and dynamic balance measures, the Frontal Assessment Battery and the Short Form-12 questionnaire. The main hypothesis was related to the superiority of the treadmill intervention based on a greater proportion of people making a clinically relevant gain (15% increase on 2MWT) in gait resistance following treatment. ANCOVA (Analysis of covariance) models adjusting for baseline measurement of the respective outcome variable, as well as sex and age, were used to evaluate differences in efficacy for all variables. P was set at 0.05.Results: Nineteen out of 26 persons in the DT-group made a clinically relevant gain and two out of 12 in the S-Group (P = 0.001). The DT-group improved more in gait resistance, speed and mobility (P < 0.01). Balance and executive functions instead improved moderately in both groups following training while perception of health remained similar in both groups.Conclusion: A four week multimodal training on treadmill was highly effective in augmenting gait resistance and mobility in moderately to severely affected persons with MS

Determinants of Disability in Multiple Sclerosis: An Immunological and MRI Study

Multiple sclerosis (MS) is characterized by a wide interpatient clinical variability and available biomarkers of disease severity still have suboptimal reliability. We aimed to assess immunological and MRI-derived measures of brain tissue damage in patients with different motor impairment degrees, for in vivo investigating the pathogenesis of MS-related disability. Twenty-two benign (B), 26 secondary progressive (SP), and 11 early, nondisabled relapsing-remitting (RR) MS patients and 37 healthy controls (HC) underwent conventional and diffusion tensor brain MRI and, as regards MS patients, immunophenotypic and functional analysis of stimulated peripheral blood mononuclear cells (PBMC). Corticospinal tract (CST) fractional anisotropy and grey matter volume were lower and CST diffusivity was higher in SPMS compared to RRMS and BMS patients. CD14+IL6+ and CD4+IL25+ cell percentages were higher in BMS than in SPMS patients. A multivariable model having EDSS as the dependent variable retained the following independent predictors: grey matter volume, CD14+IL6+ and CD4+IL25+ cell percentages. In patients without motor impairment after long-lasting MS, the grey matter and CST damage degree seem to remain as low as in the earlier disease stages and an immunological pattern suggestive of balanced pro- and anti-inflammatory activity is observed. MRI-derived and immunological measures might be used as complementary biomarkers of MS severity

The Potential Role of SARS-CoV-2 Infection and Vaccines in Multiple Sclerosis Onset and Reactivation: A Case Series and Literature Review

: The recent SARS-CoV-2 pandemic and related vaccines have raised several issues. Among them, the potential role of the viral infection (COVID-19) or anti-SARS-CoV-2 vaccines as causal factors of dysimmune CNS disorders, as well as the safety and efficacy of vaccines in patients affected by such diseases and on immune-active treatments have been analyzed. The aim is to better understand the relationship between SARS-CoV-2 infection/vaccines with dysimmune CNS diseases by describing 12 cases of multiple sclerosis/myelitis onset or reactivation after exposure to SARS-CoV-2 infection/vaccines and reviewing all published case reports or case series in which MS onset or reactivation was temporally associated with either COVID-19 (8 case reports, 3 case series) or anti-SARS-CoV-2 vaccines (13 case reports, 6 case series). All the cases share a temporal association between viral/vaccine exposure and symptoms onset. This finding, together with direct or immune-based mechanisms described both during COVID-19 and MS, claims in favor of a role for SARS-CoV-2 infection/vaccines in unmasking dysimmune CNS disorders. The most common clinical presentations involve the optic nerve, brainstem and spinal cord. The preferential tropism of the virus together with the presence of some host-related genetic/immune factors might predispose to the involvement of specific CNS districts

NMO-IgG-negative relapsing myelitis

Objective:Idiopathic transverse myelitis (I-TM) is typically monophasic, while relapsing forms are usually referred to spinal cord-restricted neuromyelitis optica (NMO), atypical multiple sclerosis (MS), or myelitis during the course of infections and connectivitis. Our objective was to evaluate the frequency of recurrent I-TM; to clarify the nosology of these forms through comparison with NMO and post-infectious TM (P-TM).Design:Prospective cohort study on patients presenting with I-TM was carried out inpatients of Infectious and Neurologic Disease Clinics, Italy.Methods:Over an 8-year period, we recruited 13 patients with I-TM and 16 with P-TM. The patients were followed-up for at least 3 years with repeated brain and spinal cord magnetic resonance imaging (MRI) examinations, multimodal evoked potentials and serum screen for connectivitis. Relapses were defined on clinical and imaging criteria.Results:Four patients with I-TM (31%) had a relapsing course . They were all males with age >50, and severe at-onset disability. The final outcome was poor in three out of four patients. Serum NMO-immunoglobulin G was undetectable in all patients. Longitudinally extensive myelitis was not predictive of relapses. I-TM and P-TM shared clinical, cerebrospinal fluid (CSF) and MRI features, as well as a similar rate (54 vs 38%) of peripheral nervous system involvement (polyradiculoneuritis), and an identical rate of relapses (31% for both forms).Conclusions:Our series support the existence of relapsing I-TM as a disease entity that does not appear related to NMO, nor to MS, cannot be further specified and shares many features with P-TM. The likelihood of relapses was unpredictable based on clinical, CSF and MRI finding