Streamline density and lesion volume reveal a postero–anterior gradient of corpus callosum damage in multiple sclerosis

Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies

INTRODUCTION

Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS.

METHODS

In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.

RESULTS

A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.

CONCLUSION

This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.

Corpus callosum damage to account for cognitive, affective, and social-cognitive dysfunctions in multiple sclerosis: A model of callosal disconnection syndrome?

The corpus callosum (CC) is the major commissure interconnecting the two hemispheres and is particularly affected in multiple sclerosis (MS). In the present review, we aimed to investigate the role played by callosal damages in the pathogenesis of MS-related dysfunctions and examine whether a model of callosal disconnection syndrome is a valid model for MS. For this purpose, we will first review structural and functional evidence of callosal pathology in MS. Second, we will account for the potential role of CC abnormalities in MS-related dysfunctions. Finally, we will report data concurring with a "multiple disconnection hypothesis" that has been proposed to explain those dysfunctions, and we will examine evidence pointing toward MS as a "callosal disconnection syndrome." We will end by discussing the contribution of this interpretation to the understanding of MS and MS-related deficits.

Classification of multiple sclerosis patients based on structural disconnection: A robust feature selection approach

Background and Purpose

Although structural disconnection represents the hallmark of multiple sclerosis (MS) pathophysiology, classification attempts based on structural connectivity have achieved low accuracy levels. Here, we set out to fill this gap, exploring the performance of supervised classifiers on features derived from microstructure informed tractography and selected applying a novel robust approach.

Methods

Using microstructure informed tractography with diffusion MRI data, we created quantitative connectomes of 55 MS patients and 24 healthy controls. We then used a robust approach—based on two classical methods of feature selection— to select relevant features from three network representations (whole connectivity matrices, node strength, and local efficiency). Classification accuracy of the selected features was tested with five different classifiers, while their meaningfulness was tested via correlation with clinical scales. As a comparison, the same classifiers were run on features selected with the standard procedure in network analysis (thresholding).

Results

Our procedure identified 11 features for the whole net, five for local efficiency, and seven for node strength. For all classifiers, the accuracy was in the range 64.5%‐91.1%, with features extracted from the whole net reaching the maximum, and overcoming results obtained with the standard procedure in all cases. Correlations with clinical scales were identified across functional domains, from motor and cognitive abilities to fatigue and depression.

Conclusion

Applying a robust feature selection procedure to quantitative structural connectomes, we were able to classify MS patients with excellent accuracy, while providing information on the white matter connections and gray matter regions more affected by MS pathology.

The central vein sign helps in differentiating multiple sclerosis from its mimickers: lessons from Fabry disease

OBJECTIVES

Although the use of specific MRI criteria has significantly increased the diagnostic accuracy of multiple sclerosis (MS), reaching a correct neuroradiological diagnosis remains a challenging task, and therefore the search for new imaging biomarkers is crucial. This study aims to evaluate the incidence of one of the emerging neuroradiological signs highly suggestive of MS, the central vein sign (CVS), using data from Fabry disease (FD) patients as an index of microvascular disorder that could mimic MS.

METHODS

In this retrospective study, after the application of inclusion and exclusion criteria, MRI scans of 36 FD patients and 73 relapsing-remitting (RR) MS patients were evaluated. Among the RRMS participants, 32 subjects with a disease duration inferior to 5 years (early MS) were also analyzed. For all subjects, a Fazekas score (FS) was recorded, excluding patients with FS = 0. Different neuroradiological signs, including CVS, were evaluated on FLAIR T2-weighted and spoiled gradient recalled echo sequences.

RESULTS

Among all the recorded neuroradiological signs, the most striking difference was found for the CVS, with a detectable prevalence of 78.1% (57/73) in RRMS and of 71.4% (25/32) in early MS patients, while this sign was absent in FD (0/36).

CONCLUSIONS

Our results confirm the high incidence of CVS in MS, also in the early phases of the disease, while it seems to be absent in conditions with a different etiology. These results corroborate the possible role of CVS as a useful neuroradiological sign highly suggestive of MS.

KEY POINTS

• The search for new imaging biomarkers is crucial to achieve a correct neuroradiological diagnosis of MS. • The CVS shows an incidence superior to 70% in MS patients, even in the early phases of the disease, while it appears to be absent in FD. • These findings further corroborate the possible future central role of CVS in distinguishing between MS and its mimickers.

Cerebellar pathology and disability worsening in relapsing-remitting multiple sclerosis: A retrospective analysis from the CombiRx trial

BACKGROUND AND PURPOSE

Cerebellar damage is a valuable predictor of disability, particularly in progressive multiple sclerosis. It is not clear if it could be an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype.

AIM

We aimed to determine whether cerebellar damage is an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype.

METHODS

Cerebellar lesion loads and volumes were estimated using baseline magnetic resonance imaging from the CombiRx trial (n = 838). The relationship between cerebellar damage and time to disability worsening (confirmed disability progression [CDP], timed 25-foot walk test [T25FWT] score worsening, nine-hole peg test [9HPT] score worsening) was tested in stagewise and stepwise Cox proportional hazards models, accounting for demographics and supratentorial damage.

RESULTS

Shorter time to 9HPT score worsening was associated with higher baseline Expanded Disability Status Scale (EDSS) score (hazard ratio [HR] 1.408, p = 0.0042) and higher volume of supratentorial and cerebellar T2 lesions (HR 1.005 p = 0.0196 and HR 2.211, p = 0.0002, respectively). Shorter time to T25FWT score worsening was associated with higher baseline EDSS (HR 1.232, p = 0.0006). Shorter time to CDP was associated with older age (HR 1.026, p = 0.0010), lower baseline EDSS score (HR 0.428, p < 0.0001) and higher volume of supratentorial T2 lesions (HR 1.024, p < 0.0001).

CONCLUSION

Among the explored outcomes, single time-point evaluation of cerebellar damage only allows the prediction of manual dexterity worsening. In clinical studies the selection of imaging biomarkers should be informed by the outcome of interest.

A comparison of upper limb function in subjects with multiple sclerosis and healthy controls using an inertial measurement unit

Upper limbs (UL) dysfunction is frequent in people with Multiple Sclerosis (PwMS). Several objective measures of UL function are proposed; however, their use is mostly confined to assess subjects with mild-to-moderate disability and requires fine motor skills, often impaired in high disability level subjects. Thus, a tool to score UL function in the advanced disease stage is lacking. The aim of the study is to analyse and compare UL unilateral and bilateral movements of healthy control (HC) and PwMS, at different disability levels, using an instrumented version (Inertial Measurement Unit, IMU) of the 15-seconds finger-to-nose test (FNT). Each movement cycle was segmented in going/adjusting/returning phases. The inter-hand interval (IHI) allowed assessing bilateral coordination (i.e. synchrony) in each phase. The larger IHI, the more severe the bilateral coordination impairment is. After stratifying PwMS for disability level (PwMS_LOW, Expanded Disability Status Scale, EDSS≤5.5 and PwMS_HIGH, EDSS≥6), the ANOVA on IHI showed significant differences between PwMS and HC (p<0.001) in all phases. However, only the going phase IHI showed significantly higher asynchrony in PwMS_HIGH than PwMS_LOW and HC (p<0.001) and no differences between PwMS_LOW and HC. The going phase IHI seems to be a clinical marker specific for high disability level PwMS. These findings suggest inertial sensors during FNT could be an easy-to-use method for a more detailed quantitative characterization of UL function in PwMS also in subjects with EDSS greater than 6.

A matter of atrophy: differential impact of brain and spine damage on disability worsening in multiple sclerosis

As atrophy represents the most relevant driver of progression in multiple sclerosis (MS), we investigated the impact of different patterns of brain and spinal cord atrophy on disability worsening in MS. We acquired clinical and MRI data from 90 patients with relapsing–remitting MS and 24 healthy controls (HC). Clinical progression at follow-up (mean 3.7 years) was defined according to the Expanded Disability Status Scale-Plus. Brain and spinal cord volumes were computed on MRI brain scans. After normalizing each participants’ brain and spine volume to the mean of the HC, z-score cut-offs were applied to separate pathologically atrophic from normal brain and spine volumes (accepting a 2.5% error probability). Accordingly, MS patients were classified into four groups (Group I: no brain or spinal cord atrophy N = 40, Group II: brain atrophy/no spinal cord atrophy N = 11, Group III: no brain atrophy/ spinal cord atrophy N = 32, Group IV: both brain and spinal cord atrophy N = 7). All patients’ groups showed significantly lower brain volume than HC (p < 0.0001). Group III and IV showed lower spine volume than HC (p < 0.0001 for both). Higher brain lesion load was identified in Group II (p = 0.049) and Group IV (p = 0.023) vs Group I, and in Group IV (p = 0.048) vs Group III. Spinal cord atrophy (OR = 3.75, p = 0.018) and brain + spinal cord atrophy (OR = 5.71, p = 0.046) were significant predictors of disability progression. The presence of concomitant brain and spinal cord atrophy is the strongest correlate of progression over time. Isolated spinal cord atrophy exerts a similar effect, confirming the leading role of spinal cord atrophy in the determination of motor disability.

Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis

Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.