The association between brain volume loss and disability in multiple sclerosis: A systematic review

Clinical and MRI features contributing to the clinico-radiological dissociation in a large cohort of people with multiple sclerosis

BACKGROUND

People with Multiple Sclerosis (PwMS) often show a mismatch between disability and T2-hyperintense white matter (WM) lesion volume (LV), that in general is referred to as the clinico-radiological paradox.

OBJECTIVES

This study aimed to understand how an extensive clinical, neuropsychological, and MRI analysis could better elucidate the clinico-radiological dissociation in a large cohort of PwMS.

METHODS

Clinical scores, such as Expanded Disability Status Scale (EDSS), 9 Hole Peg Test (9HPT), 25-foot Walking Test (25-FWT), Paced Auditory Serial Addition Test at 3 s (PASAT3), Symbol digit Modalities Test (SDMT), demographics, and 3 T-MRI of 717 PwMS and 284 healthy subjects (HS) were downloaded from the INNI database. Considering medians of LV and EDSS scores, PwMS were divided into four groups: low LV and disability (LL/LD); high LV and low disability (HL/LD); low LV and high disability (LL/HD); high LV and disability (HL/HD). MRI measures included: volumes of gray matter (GM), WM, cerebellum, basal ganglia and thalamus, spinal cord (SC) area, and functional connectivity of resting-state networks.

RESULTS

The clinico-radiological dissociation involved 36% of our sample. HL/LD showed worse SDMT scores and lower global and deep GM volumes than HS and LL/LD. LL/HD showed lower GM, thalamus, and cerebellum volumes, and SC area than HS, and lower SC area than LL/LD.

CONCLUSIONS

A more extensive clinical assessment, including cognitive tests, and MRI evaluation including deep GM and SC, could better describe the real status of the disease and help clinicians in early and tailored treatment in PwMS.

Conventional and Advanced Magnetic Resonance Imaging Biomarkers of Multiple Sclerosis in the Brain

Multiple sclerosis (MS) is a heterogeneous disease, and each MS patient exhibits different clinical symptoms that are reflected in their magnetic resonance imaging (MRI) results. Each MS lesion should be interpreted carefully and evaluated in conjunction with a clinical examination. MRI plays a major role in evaluating how MS lesions are aggregated in the central nervous system and how they change over time. There are several conventional MRI biomarkers of MS that could be utilized to evaluate each MS phenotype. MRI is useful for clinical decisions, aiding in the determination of disease-modifying treatment or disease prognosis. Despite its higher sensitivity, MRI provides low specificity due to the heterogeneity of MS lesions. However, advanced MRI biomarkers show promise in terms of defining MS lesions, as each imaging biomarker correlates differently with the clinical scenario of each MS phenotype. The aim of this review is to summarise the current state of MRI biomarkers for MS in the brain and how they relate to neurological disabilities.

Higher effect sizes for the detection of accelerated brain volume loss and disability progression in multiple sclerosis using deep-learning

PURPOSE

Clinical validation of "BrainLossNet", a deep learning-based method for fast and robust estimation of brain volume loss (BVL) from longitudinal T1-weighted MRI, for the detection of accelerated BVL in multiple sclerosis (MS) and for the discrimination between MS patients with versus without disability progression.

MATERIALS AND METHODS

A longitudinal normative database of healthy controls (n = 563), two mono-scanner MS cohorts (n = 414, 156) and a mixed-scanner cohort acquired for various indications (n = 216) were included retrospectively. Mean observation period from the baseline (BL) to the last follow-up (FU) MRI scan was 2-3 years. Expanded Disability Status Scale (EDSS) at BL and FU was available in 149 MS patients. Annual BVL was computed using BrainLossNet and Siena and then adjusted for age. Repeated-measures ANOVA and Cohen's effect size were used to compare BrainLossNet and Siena regarding the detection of accelerated BVL and the differentiation between MS patients with versus without EDSS progression.

RESULTS

Cohen's effect size for the differentiation of patients from healthy controls based on the age-adjusted annual BVL was larger with BrainLossNet than with Siena (MS cohort 1: 0.927 versus 0.495, MS cohort 2: 0.671 versus 0.456, mixed-scanner cohort: 0.918 versus 0.730, all p < 0.001). Cohen's effect size for the discrimination between MS patients with (n = 51) versus without (n = 98) EDSS progression was larger with BrainLossNet (0.503 versus 0.400, p = 0.048).

CONCLUSION

BrainLossNet can provide added value in clinical routine and MS therapy trials regarding the detection of accelerated BVL in MS and the differentiation between MS patients with versus without disability progression.

Brain atrophy assessment in multiple sclerosis: technical- and subject-related barriers for translation to real-world application in individual subjects

INTRODUCTION

Brain atrophy is a well-established MRI outcome for predicting clinical progression and monitoring treatment response in persons with multiple sclerosis (pwMS) at the group level. Despite the important progress made, the translation of brain atrophy assessment into clinical practice faces several challenges.

AREAS COVERED

In this review, the authors discuss technical- and subject-related barriers for implementing brain atrophy assessment as part of the clinical routine at the individual level. Substantial progress has been made to understand and mitigate technical barriers behind MRI acquisition. Numerous research and commercial segmentation techniques for volume estimation are available and technically validated, but their clinical value has not been fully established. A systematic assessment of subject-related barriers, which include genetic, environmental, biological, lifestyle, comorbidity, and aging confounders, is critical for the interpretation of brain atrophy measures at the individual subject level. Educating both medical providers and pwMS will help better clarify the benefits and limitations of assessing brain atrophy for disease monitoring and prognosis.

EXPERT OPINION

Integrating brain atrophy assessment into clinical practice for pwMS requires overcoming technical and subject-related challenges. Advances in MRI standardization, artificial intelligence, and clinician education will facilitate this process, improving disease management and potentially reducing long-term healthcare costs.

Biomarkers of tau phosphorylation state are associated with the clinical course of multiple sclerosis

BACKGROUND

Mechanisms underlying neurodegeneration in multiple sclerosis (MS) remain poorly understood but mostly implicate molecular pathways that are not unique to MS. Recently detected tau seeding activity in MS brain tissues corroborates previous neuropathological reports of hyperphosphorylated tau (p-tau) accumulation in secondary and primary progressive MS (PPMS). We aimed to investigate whether aberrant tau phosphorylation can be detected in the cerebrospinal fluid (CSF) of MS patients by using novel ultrasensitive immunoassays for different p-tau biomarkers.

METHODS

CSF samples of patients with MS (n = 55) and non-inflammatory neurological disorders (NIND, n = 31) were analysed with in-house Single molecule array (Simoa) assays targeting different tau phosphorylation sites (p-tau181, p-tau212, p-tau217 and p-tau231). Additionally, neurofilament light (NFL) and glial fibrillary acidic protein (GFAP) were measured with a multiplexed Simoa assay. Patients were diagnosed with clinically isolated syndrome (CIS, n = 10), relapsing-remitting MS (RRMS, n = 21) and PPMS (n = 24) according to the 2017 McDonald criteria and had MRI, EDSS and basic CSF analysis performed at the time of diagnosis.

RESULTS

Patients with progressive disease course had between 1.4-fold (p-tau217) and 2.2-fold (p-tau212) higher p-tau levels than relapsing MS patients (PPMS compared with CIS + RRMS, p < 0.001 for p-tau181, p-tau212, p-tau231 and p = 0.042 for p-tau217). P-tau biomarkers were associated with disease duration (ρ=0.466-0.622, p < 0.0001), age (ρ=0.318-0.485, p < 0.02, all but p-tau217) and EDSS at diagnosis and follow-up (ρ=0.309-0.440, p < 0.02). In addition, p-tau biomarkers correlated with GFAP (ρ=0.517-0.719, p ≤ 0.0001) but not with the albumin quotient, CSF cell count or NFL. Patients with higher MRI lesion load also had higher p-tau levels p ≤ 0.01 (<10 vs. ≥ 10 lesions, all p ≤ 0.01).

CONCLUSION

CSF concentrations of novel p-tau biomarkers point to a higher degree of tau phosphorylation in PPMS than in RRMS. Associations with age, disease duration and EDSS suggest this process increases with disease severity; however, replication of these results in larger cohorts is needed to further clarify the relevance of altered tau phosphorylation throughout the disease course in MS.

BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRI

PURPOSE

MRI-derived brain volume loss (BVL) is widely used as neurodegeneration marker. SIENA is state-of-the-art for BVL measurement, but limited by long computation time. Here we propose "BrainLossNet", a convolutional neural network (CNN)-based method for BVL-estimation.

METHODS

BrainLossNet uses CNN-based non-linear registration of baseline(BL)/follow-up(FU) 3D-T1w-MRI pairs. BVL is computed by non-linear registration of brain parenchyma masks segmented in the BL/FU scans. The BVL estimate is corrected for image distortions using the apparent volume change of the total intracranial volume. BrainLossNet was trained on 1525 BL/FU pairs from 83 scanners. Agreement between BrainLossNet and SIENA was assessed in 225 BL/FU pairs from 94 MS patients acquired with a single scanner and 268 BL/FU pairs from 52 scanners acquired for various indications. Robustness to short-term variability of 3D-T1w-MRI was compared in 354 BL/FU pairs from a single healthy men acquired in the same session without repositioning with 116 scanners (Frequently-Traveling-Human-Phantom dataset, FTHP).

RESULTS

Processing time of BrainLossNet was 2-3 min. The median [interquartile range] of the SIENA-BrainLossNet BVL difference was 0.10% [- 0.18%, 0.35%] in the MS dataset, 0.08% [- 0.14%, 0.28%] in the various indications dataset. The distribution of apparent BVL in the FTHP dataset was narrower with BrainLossNet (p = 0.036; 95th percentile: 0.20% vs 0.32%).

CONCLUSION

BrainLossNet on average provides the same BVL estimates as SIENA, but it is significantly more robust, probably due to its built-in distortion correction. Processing time of 2-3 min makes BrainLossNet suitable for clinical routine. This can pave the way for widespread clinical use of BVL estimation from intra-scanner BL/FU pairs.

Digital outcome measures are associated with brain atrophy in patients with multiple sclerosis

BACKGROUND

Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression.

OBJECTIVE

To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS.

METHODS

In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates.

RESULTS

In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12.

CONCLUSION

Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.

Impact of dance classes on motor and cognitive functions and gut microbiota composition in multiple sclerosis patients: Randomized controlled trial

Evidence suggests that multiple sclerosis (MS) induces a decline in motor and cognitive function and provokes a shift in gut microbiome composition in patients. Therefore, the aim of the study was to explore the effect of dance classes on the motor and cognitive functions and gut microbiota composition of MS patients. In this randomized controlled trial, 36 patients were randomly divided into two groups: the experimental group (n = 18) and the passive control group (n = 18). Supervised rock and roll and sports dance classes were performed for 12 weeks at a frequency of two times a week. Before and after the intervention, fecal samples were taken and the motor and cognitive function assessments were completed. Fecal microbiota were categorized using primers targeting the V3-V4 region of 16S rDNA. Our results revealed significant differences in mobility performance (T25-FWT), attention and working memory (TMT B), and finger dexterity (9-HPT) within the experimental group. Furthermore, we reported favorable shifts in gut microbial communities (an increase in Blautia stercoris and a decrease in Ruminococcus torques) within the experimental group. In conclusion, our randomized control trial on the effects of 12-week dance classes in MS patients found significant improvements in motor and cognitive functions, with further moderate influence on gut microbiota composition.

Treatment Monitoring in Multiple Sclerosis - Efficacy and Safety

Magnetic resonance imaging is the most sensitive method for detecting inflammatory activity in multiple sclerosis, particularly in the brain where it reveals subclinical inflammation. Established MRI markers include contrast-enhancing lesions and active T2 lesions. Recent promising markers like slowly expanding lesions and phase rim lesions are being explored for monitoring chronic inflammation, but require further validation for clinical use. Volumetric and quantitative MRI techniques are currently limited to clinical trials and are not yet recommended for routine clinical use. Additionally, MRI is crucial for detecting complications from disease-modifying treatments and for implementing MRI-based pharmacovigilance strategies, such as in patients treated with natalizumab.

Familial vs sporadic multiple sclerosis in the Israeli population: Differences in ethnicity distribution and disease progression, with anticipation in successive generations

BACKGROUND

Multiple Sclerosis (MS) may cluster in families, an entity known as familial MS (FMS), possibly due to aggregation of genetic and environmental factors. Though previous studies have characterized FMS in different populations, no study to the best of our knowledge has yet characterized FMS in the unique Israeli population, which is comprised of relatively endogamous ethnicities. Our goal in this study was to compare demographic and clinical characteristics between FMS and sporadic MS (SMS), and to search for intra-familial patterns.

METHODS

In a retrospective study of 101 FMS patients and 508 SMS patients, ethnicity and sex distribution was assessed. Clinical aspects were compared between 172 paired FMS and SMS patients, matched for sex, age and ethnicity, and between generations of the FMS cohort.

RESULTS

Females comprised 75.3 % of FMS and 67.5 % of SMS patients (p = 0.1). Ethnic distribution was significantly different between FMS and SMS (p = 0.014), with the former comprising a higher proportion of Christian-Arabs (15.4% vs. 5.1 %, p = 0.004) and lower proportion of Jews (60% vs. 74.2 %, p = 0.016). Age at disease onset or diagnosis, frequency of positive Oligoclonal bands and comorbidity of other autoimmune/inflammatory disease or chronic diseases was comparable between FMS and SMS, yet motor symptoms at onset were more prevalent in FMS (34% vs. 20 %, p = 0.02). Annualized relapse rates throughout 10 years from onset were comparable. Among FMS, mean Expanded-Disability-Status-Scale (EDSS) and slope of deterioration in EDSS over 20 years from diagnosis were higher (p = 0.0004 and p = 0.023, respectively), time to EDSS ≥ 3 was shorter (7.1 vs. 12.1 years, HR 1.6, p = 0.036) and MS-Severity-Score (MSSS) was higher (3.84 vs. 2.95, p = 0.04), compared to SMS. Following adjustment for smoking, which tended to be higher among FMS patients (P = 0.06), mean EDSS and slope of deterioration in EDSS over 20 years remained significantly higher (p = 0.0006 and p = 0.025, respectively) in FMS, time to EDSS ≥ 3 tended to be higher (HR 1.5, p = 0.06), while MSSS was comparable. An inter-generational analysis of the total FMS cohort, as well as an intra-familial analysis, both adjusted for year of diagnosis, revealed significantly earlier age of onset (p < 0.0001 and p < 0.0001) and diagnosis (p = 0.001 and p < 0.0001) in the younger compared to the older generations, respectively.

CONCLUSION

In this Israeli cohort, the proportions of specific ethnicities differ between FMS and SMS, indicating that FMS has a population-specific prevalence pattern, and that further investigation for susceptibility genes is warranted. Disease progression is faster in FMS patients and anticipation is observed in families with multiple cases of MS. Closer surveillance and application of a pro-active induction or early highly-effective therapeutic strategy for FMS patients should be considered, to reduce high disease activity and fast disability progression.

Volumetric and Asymmetric Index Analysis of Subcortical Structures in Multiple Sclerosis Patients: A Retrospective Study Using volBrain Software

Introduction Multiple sclerosis (MS) is a chronic and autoimmune disease that has a significant influence on the central nervous system, such as the brain and spinal cord, affecting millions of individuals globally. Understanding the connection between subcortical brain regions and MS is crucial for effective diagnostic and therapeutic approaches for treating this disabling disease. This study explores the relationship between volume and contours of asymmetry index of subcortical brain regions in individuals with MS using volBrain software (https://www.volbrain.net; developed by José V. Manjón (Valencia Polytechnic University, Valencia, Spain) and Pierrick Coupé (University of Bordeaux, Bordeaux, France)). Methods In our retrospective investigation, we admitted 100 Turkish individuals, comprising 50 patients diagnosed with relapsing-remitting MS (RRMS) (24 (48%) males and 26 (52%) females) and 50 healthy controls (23 (46%) males and 27 (54%) females), registered between October 2017 and February 2022 for five years and underwent assessment in the radiology department at the Teaching and Research Hospital of Kocaeli University; 1,150 Turkish patients were excluded from our study based on our exclusion criteria. We used magnetic resonance imaging with a 3-Tesla (3T) scanner and volBrain software to assess volumes (cm3) and asymmetry indexes due to asymmetry for different levels of atrophy of total intracranial, total brain, gray matter, white matter, and subcortical regions, the most affected regions in MS patients for both patient and control cohorts. Results Statistical analysis revealed a significant difference between patient and control groups (p < 0.001), with patient group mean age at 38.32 years and control group mean age at 32.88 years. Patient group exhibited lower values for total intracranial, total brain, gray matter, white matter, and cerebrospinal fluid volume compared to control group (p < 0.05). The results indicated a statistically significant decrease (p < 0.05) in the values for total intracranial and total brain volume, whereas all other values remained unchanged. We compared volumes of subcortical structures on the right and left sides and found that the putamen, thalamus, and globus pallidus had statistically lower values in the patient group than in the control group (p < 0.001), apart from the lateral ventricle. Furthermore, our retrospective investigation demonstrated a statistically significant difference in the globus pallidus asymmetry index, indicating a preference for the patient group (p < 0.05). A lower asymmetry index value signifies a larger volume for the right side of the subcortical regions of the brain when compared to the left side. Conclusion Brain atrophy, although characterized by irreversible tissue damage, is targeted by therapeutic interventions to prevent progression. It is, therefore, imperative to develop a universally accepted measurement standard for subcortical structures that also considers the inherent variability present within each structure. Our findings serve as an important basis and indicator for the determination of subcortical atrophy and asymmetry in MS, the prognosis of the disease, and the etiology of clinical symptoms. Subsequent research may benefit by adopting the novel approach of considering brain atrophy as an outcome rather than a predictor, thereby facilitating the elucidation of the intricate biological mechanisms that give rise to volume loss.

Adiponectin Alleviates Cell Injury due to Cerebrospinal Fluid from Multiple Sclerosis Patients by Inhibiting Oxidative Stress and Proinflammatory Response

Multiple sclerosis (MS) is the most common disabling neurological disease characterized by chronic inflammation and neuronal cell viability impairment. Based on previous studies reporting that adiponectin exhibits neuroprotective effects in some models of neurodegenerative diseases, we analyzed the effects of AdipoRon treatment, alone or in combination with the cerebrospinal fluid of patients with MS (MS-CSF), to verify whether this adipokine acts on the basal neuronal cellular processes. To this aim, SH-SY5Y and U-87 cells (models of neuronal and glial cells, respectively) were exposed to MS-CSF alone or in co-treatment with AdipoRon. The cell viability was determined via MTT assay, and the possible underlying mechanisms were investigated via the alterations of oxidative stress and inflammation. MTT assay confirmed that AdipoRon alone did not affect the viability of both cell lines; whereas, when used in combination with MS-CSF, it reduces MS-CSF inhibitory effects on the viability of both SH-SY5Y and U-87 cell lines. In addition, MS-CSF treatment causes an increase in pro-inflammatory cytokines, whereas it determines the reduction in anti-inflammatory IL-10. Interestingly, the co-administration of AdipoRon counteracts the MS-CSF-induced production of pro-inflammatory cytokines, whereas it determines an enhancement of IL-10. In conclusion, our data suggest that AdipoRon counteracts the cytotoxic effects induced by MS-CSF on SH-SY5Y and U-87 cell lines and that one of the potential molecular underlying mechanisms might occur via reduction in oxidative stress and inflammation. Further in vivo and in vitro studies are essential to confirm whether adiponectin could be a neuro-protectant candidate against neuronal cell injury.