MRI biomarkers of disease progression and conversion to secondary-progressive multiple sclerosis

Markers of secondary progression in multiple sclerosis

INTRODUCTION

There is no globally accepted definition of Secondary Progressive Multiple Sclerosis (SPMS) or set of unambiguous clinical, radiological, or other criteria that can accurately identify patients who transition to SPMS. Thus, the SPMS diagnosis is almost always a retrospective and frequently delayed process.

OBJECTIVE

The aim of this study was to elucidate the current understanding of phenotypic changes throughout MS course and provide insights into the detection of SPMS from the available literature on this diagnostic landscape.

METHODS

Comprehensive literature review aiming at detecting the transition from RRMS to SPMS. A search for relevant publications was conducted across different databases, scrutinizing studies that investigated tools and biomarkers for an accurate diagnosis of SPMS.

RESULTS

62 studies from the past two decades were included. The EDSS-plus was shown to be more sensitive than the EDSS alone in identifying disability progression. We found some helpful indicators for diagnosing SPMS, including cognitive impairment, particularly on working memory, information processing speed, and verbal fluency; presence of slowly expanding lesions on MRI; thinning of retinal layers on OCT. Also, glial markers as Glial Fibrillary Acidic Protein and Chitinase-3-like protein 1 might be more suitable to identify the conversion to progressive disease than Neurofilament light chain. Certain subjective symptoms seem to be more prevalent in the SPMS phase, although further studies are needed to understand whether patient reported outcomes' measures (PROMs) and which ones could be useful in detecting the transition to a progressive phenotype.

CONCLUSION

Our review highlights the emergence of useful biomarkers in early detection of progression of MS, such as cognitive impairment, MRI, and glial markers. We are getting closer to revolutionising the SPMS diagnosis and clinical management as we get a deeper understanding of these biomarkers.

Serum miR-34a-5p, miR-103a-3p, and miR-376a-3p as possible biomarkers of conversion from relapsing-remitting to secondary progressive multiple sclerosis

Relapsing-remitting (RR) Multiple Sclerosis (MS) is the most common form of the disease; RRMS patients can maintain their clinical phenotype throughout life or can develop a secondary progressive (SP) course over time. We investigated whether circulating miRNAs can predict RR-to-SPMS conversion. A serum miRNAs profile was initially analyzed in a cross-sectional study by qPCR in 16 patients (8 RRMS and 8 SPMS) (Discovery cohort). Three miRNAs, i.e. miR-34a-5p, miR-103a-3p and miR-376a-3p, were significantly up-regulated in SPMS compared to RRMS patients (p < 0.0 5). Serum concentration of the same miRNAs was subsequently analyzed in a retrospective study by ddPCR at baseline in 69 RRMS patients who did (N = 36 cSPMS) or did not (N = 33) convert into SPMS over a 10-year observation period (Study cohort). The results showed that these miRNAs were significantly increased at baseline only in those RRMS patients who converted to SPMS over time. miR-34a-5p and miR-376a-3p alone were significantly increased in cSPMS sera at the end of the 10-years period too. Serum concentration of miR-34a-5p, miR-103a-3p and miR-376a-3p is increased in RRMS patients several years before their conversion to SPMS. These miRNAs might be useful biomarkers to predict the conversion from RRMS to SPMS.

Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis

BACKGROUND

Robust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies.

OBJECTIVE

To evaluate whether machine learning (ML) methods can classify clinical impairment and predict worsening in people with MS (pwMS) and, if so, which combination of clinical and magnetic resonance imaging (MRI) features and ML algorithm is optimal.

METHODS

We used baseline clinical and structural MRI data from two MS cohorts (Berlin: n = 125, Amsterdam: n = 330) to evaluate the capability of five ML models in classifying clinical impairment at baseline and predicting future clinical worsening over a follow-up of 2 and 5 years. Clinical worsening was defined by increases in the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk Test (T25FW), 9-Hole Peg Test (9HPT), or Symbol Digit Modalities Test (SDMT). Different combinations of clinical and volumetric MRI measures were systematically assessed in predicting clinical outcomes. ML models were evaluated using Monte Carlo cross-validation, area under the curve (AUC), and permutation testing to assess significance.

RESULTS

The ML models significantly determined clinical impairment at baseline for the Amsterdam cohort, but did not reach significance for predicting clinical worsening over a follow-up of 2 and 5 years. High disability (EDSS ≥ 4) was best determined by a support vector machine (SVM) classifier using clinical and global MRI volumes (AUC = 0.83 ± 0.07, p = 0.015). Impaired cognition (SDMT Z-score ≤ -1.5) was best determined by a SVM using regional MRI volumes (thalamus, ventricles, lesions, and hippocampus), reaching an AUC of 0.73 ± 0.04 (p = 0.008).

CONCLUSION

ML models could aid in classifying pwMS with clinical impairment and identify relevant biomarkers, but prediction of clinical worsening is an unmet need.

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition. To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology. MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types. MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principles and has contributed several classes to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains. MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.

Glial cell injury and atrophied lesion volume as measures of chronic multiple sclerosis inflammation

BACKGROUND

Atrophied lesion volume (aLV), a proposed biomarker of disability progression in multiple sclerosis (MS) and transition into progressive MS (PMS), depicts chronic periventricular white matter (WM) pathology. Meningeal infiltrates, imaged as leptomeningeal contrast enhancement (LMCE), are linked with greater cortical pathology.

OBJECTIVES

To determine the relationship between serum-derived proteomic data with the development of aLV and LMCE in a heterogeneous group of people with MS (pwMS).

METHODS

Proteomic and MRI data for 202 pwMS (148 clinically isolated syndrome /relapsing-remitting MS and 54 progressive MS (PMS)) were acquired at baseline and at 5.4-year follow-up. The concentrations of 21 proteins related to multiple MS pathophysiology pathways were derived using a custom-developed Proximity Extension Assay on the Olink™ platform. The accrual of aLV was determined as the volume of baseline T2-weighted lesions that were replaced by cerebrospinal fluid over the follow-up. Regression models and age-adjusted analysis of covariance (ANCOVA) were used.

RESULTS

Older age (standardized beta = 0.176, p = 0.022), higher glial fibrillary acidic protein (standardized beta = 0.312, p = 0.001), and lower myelin oligodendrocyte glycoprotein levels (standardized beta = -0.271, p = 0.002) were associated with accrual of aLV over follow-up. This relationship was driven by the pwPMS population. The presence of LMCE at the follow-up visit was not predicted by any baseline proteomic biomarker nor cross-sectionally associated with any protein concentration.

CONCLUSION

Proteomic markers of glial activation are associated with chronic lesional WM pathology (measured as aLV) and may be specific to the progressive MS phenotype. LMCE presence in MS does not appear to relate to proteomic measures.

The T1-dark-rim: A novel imaging sign for detecting smoldering inflammation in multiple sclerosis

PURPOSE

Paramagnetic rim lesions (PRLs), usually identified in susceptibility-weighted imaging (SWI), are a promising prognostic biomarker of disability progression in multiple sclerosis (MS). However, SWI is not routinely performed in clinical practice. The objective of this study is to define a novel imaging sign, the T1-dark rim, identifiable in a standard 3DT1 gradient-echo inversion-recovery sequence, such as 3D T1 turbo field echo (3DT1FE) and explore its performance as a SWI surrogate to define PRLs.

METHODS

This observational cross-sectional study analyzed MS patients who underwent 3T magnetic resonance imaging (MRI) including 3DT1TFE and SWI. Rim lesions were evaluated in 3DT1TFE, processed SWI, and SWI phase and categorized as true positive, false positive, or false negative based on the value of the T1-dark rim in predicting SWI phase PRLs. Sensitivity and positive predictive values of the T1-dark rim for detecting PRLs were calculated.

RESULTS

Overall, 80 rim lesions were identified in 63 patients (60 in the SWI phase and 78 in 3DT1TFE; 58 true positives, 20 false positives, and two false negatives). The T1-dark rim demonstrated 97% sensitivity and 74% positive predictive value for detecting PRLs. More PRLs were detected in the SWI phase than in processed SWI (60 and 57, respectively).

CONCLUSION

The T1-dark rim sign is a promising and accessible novel imaging marker to detect PRLs whose high sensitivity may enable earlier detection of chronic active lesions to guide MS treatment escalation. The relevance of T1-dark rim lesions that are negative on SWI opens up a new field for analysis.

Deeply 3D-T1-TFE hypointense voxels are characteristic of phase-rim lesions in multiple sclerosis

OBJECTIVES

The development of new drugs for the treatment of progressive multiple sclerosis (MS) highlights the need for new prognostic biomarkers. Phase-rim lesions (PRLs) have been proposed as markers of progressive disease but are difficult to identify and quantify. Previous studies have identified T1-hypointensity in PRLs. The aim of this study was to compare the intensity profiles of PRLs and non-PRL white-matter lesions (nPR-WMLs) on three-dimensional T1-weighted turbo field echo (3DT1TFE) MRI. We then evaluated the performance of a derived metric as a surrogate for PRLs as potential markers for risk of disease progression.

METHODS

This study enrolled a cohort of relapsing-remitting (n = 10) and secondary progressive MS (n = 10) patients for whom 3 T MRI was available. PRLs and nPR-WMLs were segmented, and voxel-wise normalized T1-intensity histograms were analyzed. The lesions were divided equally into training and test datasets, and the fifth-percentile (p5)-normalized T1-intensity of each lesion was compared between groups and used for classification prediction.

RESULTS

Voxel-wise histogram analysis showed a unimodal histogram for nPR-WMLs and a bimodal histogram for PRLs with a large peak in the hypointense limit. Lesion-wise analysis included 1075 nPR-WMLs and 39 PRLs. The p5 intensity of PRLs was significantly lower than that of nPR-WMLs. The T1 intensity-based PRL classifier had a sensitivity of 0.526 and specificity of 0.959.

CONCLUSIONS

Profound hypointensity on 3DT1TFE MRI is characteristic of PRLs and rare in other white-matter lesions. Given the widespread availability of T1-weighted imaging, this feature might serve as a surrogate biomarker for smoldering inflammation.

CLINICAL RELEVANCE STATEMENT

Quantitative analysis of 3DT1TFE may detect deeply hypointense voxels in multiple sclerosis lesions, which are highly specific to PRLs. This could serve as a specific indicator of smoldering inflammation in MS, aiding in early detection of disease progression.

KEY POINTS

• Phase-rim lesions (PRLs) in multiple sclerosis present a characteristic T1-hypointensity on 3DT1TFE MRI. • Intensity-normalized 3DT1TFE can be used to systematically identify and quantify these deeply hypointense foci. • Deep T1-hypointensity may act as an easily detectable, surrogate marker for PRLs.

Multiple sclerosis

Multiple sclerosis remains one of the most common causes of neurological disability in the young adult population (aged 18-40 years). Novel pathophysiological findings underline the importance of the interaction between genetics and environment. Improvements in diagnostic criteria, harmonised guidelines for MRI, and globalised treatment recommendations have led to more accurate diagnosis and an earlier start of effective immunomodulatory treatment than previously. Understanding and capturing the long prodromal multiple sclerosis period would further improve diagnostic abilities and thus treatment initiation, eventually improving long-term disease outcomes. The large portfolio of currently available medications paved the way for personalised therapeutic strategies that will balance safety and effectiveness. Incorporation of cognitive interventions, lifestyle recommendations, and management of non-neurological comorbidities could further improve quality of life and outcomes. Future challenges include the development of medications that successfully target the neurodegenerative aspect of the disease and creation of sensitive imaging and fluid biomarkers that can effectively predict and monitor disease changes.

MRIO: The Magnetic Resonance Imaging Acquisition and Analysis Ontology

Objective

Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in managing and analyzing MRI data, due in large part to the heterogeneity of data acquisition.

Materials and Methods

To address this, we have developed MRIO, the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Results

MRIO provides well-reasoned classes and logical axioms for the acquisition of several MRI acquisition types and well-known, peer-reviewed analysis software, facilitating the use of MRI data. These classes provide a common language for the neuroimaging research process and help standardize the organization and analysis of MRI data for reproducible datasets. We also provide queries for automated assignment of analyses for given MRI types.

Discussion

MRIO aids researchers in managing neuroimaging studies by helping organize and annotate MRI data and integrating with existing standards such as Digital Imaging and Communications in Medicine and the Brain Imaging Data Structure, enhancing reproducibility and interoperability. MRIO was constructed according to Open Biomedical Ontologies Foundry principals and has contributed several terms to the Ontology for Biomedical Investigations to help bridge neuroimaging data to other domains.

Conclusion

MRIO addresses the need for a "common language" for MRI that can help manage the neuroimaging research, by enabling researchers to identify appropriate analyses for sets of scans and facilitating data organization and reporting.

Multimodal diagnostics in multiple sclerosis: predicting disability and conversion from relapsing-remitting to secondary progressive disease course - protocol for systematic review and meta-analysis

BACKGROUND

The number of patients diagnosed with multiple sclerosis (MS) has increased significantly over the last decade. The challenge is to identify the transition from relapsing-remitting to secondary progressive MS. Since available methods to examine patients with MS are limited, both the diagnostics and prognostication of disease progression would benefit from the multimodal approach. The latter combines the evidence obtained from disparate radiologic modalities, neurophysiological evaluation, cognitive assessment and molecular diagnostics. In this systematic review we will analyse the advantages of multimodal studies in predicting the risk of conversion to secondary progressive MS.

METHODS AND ANALYSIS

We will use peer-reviewed publications available in Web of Science, Medline/PubMed, Scopus, Embase and CINAHL databases. In vivo studies reporting the predictive value of diagnostic methods will be considered. Selected publications will be processed through Covidence software for automatic deduplication and blind screening. Two reviewers will use a predefined template to extract the data from eligible studies. We will analyse the performance metrics (1) for the classification models reflecting the risk of secondary progression: sensitivity, specificity, accuracy, area under the receiver operating characteristic curve, positive and negative predictive values; (2) for the regression models forecasting disability scores: the ratio of mean absolute error to the range of values. Then, we will create ranking charts representing performance of the algorithms for calculating disability level and MS progression. Finally, we will compare the predictive power of radiological and radiomical correlates of clinical disability and cognitive impairment in patients with MS.

ETHICS AND DISSEMINATION

The study does not require ethical approval because we will analyse publicly available literature. The project results will be published in a peer-review journal and presented at scientific conferences.

PROSPERO REGISTRATION NUMBER

CRD42022354179.

Recent Progress in the Identification of Early Transition Biomarkers from Relapsing-Remitting to Progressive Multiple Sclerosis

Despite extensive research into the pathophysiology of multiple sclerosis (MS) and recent developments in potent disease-modifying therapies (DMTs), two-thirds of relapsing-remitting MS patients transition to progressive MS (PMS). The main pathogenic mechanism in PMS is represented not by inflammation but by neurodegeneration, which leads to irreversible neurological disability. For this reason, this transition represents a critical factor for the long-term prognosis. Currently, the diagnosis of PMS can only be established retrospectively based on the progressive worsening of the disability over a period of at least 6 months. In some cases, the diagnosis of PMS is delayed for up to 3 years. With the approval of highly effective DMTs, some with proven effects on neurodegeneration, there is an urgent need for reliable biomarkers to identify this transition phase early and to select patients at a high risk of conversion to PMS. The purpose of this review is to discuss the progress made in the last decade in an attempt to find such a biomarker in the molecular field (serum and cerebrospinal fluid) between the magnetic resonance imaging parameters and optical coherence tomography measures.

Unmet needs and gaps in the identification of secondary progression in multiple sclerosis: a Southern Italy healthcare professionals' perspective

OBJECTIVE

Multiple sclerosis (MS) is a chronic disease with different clinical courses and a tendency to worsening. The relapsing-remitting MS presents acute onset and relapses of neurological symptoms, followed by their remission. This form can convert to secondary progressive MS (SPMS) with irreversible neurological worsening and disability. The identification of signs, symptoms, markers of progression, and strategies to manage MS patients is mandatory to allow early identification of those at higher risk of conversion to SPMS, for prompt intervention to cope with the progression of the disease.

METHODS

A panel of Italian experts from Southern Italy have reviewed the current knowledge on MS and its management and identified the crucial tools for SPMS recognition.

RESULTS

More effective communication between patients and clinicians should be established, with the support of digital tools. Moreover, the improvement in the clinical use of biomarkers for progression (cellular structures and tissue organization, such as neurofilaments and chitinase 3-like 1, axonal and neurons density) and of instrumental analyses for recognition of whole-brain atrophy, chronic active lesions, spinal cord lesions and atrophy, and the improvement the combination of the Expanded Disability Status Scale and the evaluation of cognitive dysfunction are discussed.

CONCLUSION

Given the availability of a pharmacological option, adequate education both for patients, regarding the evolution of the disease and the specific treatment, and for professionals, to allow more effective and sensitive communication and the best use of diagnostic and management tools, could represent a strategy to improve patient management and their quality of life.

Secondary Progressive Multiple Sclerosis

Many challenges exist in the precise diagnosis and clinical management of secondary progressive multiple sclerosis (SPMS) because of the lack of definitive clinical, imaging, immunologic, or pathologic criteria that demarcate the transition from relapsing-remitting MS to SPMS. This review provides an overview of the diagnostic criteria/definition and the heterogeneity associated with different SPMS patient populations; it also emphasizes the importance of available prospective/retrospective tools to identify patients with SPMS earlier in the disease course so that approved disease-modifying therapies and nonpharmacological strategies will translate into better outcomes. Delivery of such interventions necessitates an evolving patient-clinician dialog within the context of a multidisciplinary team.

Characteristics of cerebral blood flow in an Eastern sample of multiple sclerosis patients: A potential quantitative imaging marker associated with disease severity

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that is rare in China. At present, there are no widespread quantitative imaging markers associated with disease severity in MS. Despite several previous studies reporting cerebral blood flow (CBF) changes in MS, no consensus has been reached. In this study, we enrolled 30 Eastern MS patients to investigate CBF changes in different brain regions using the arterial spin labeling technique and their relationship with disease severity. The average CBF in MS patients were higher than those in health controls in various brain regions except cerebellum. The results indicated that MS patients with strongly increased CBF showed worse disease severity, including higher Expanded Disability Status Scale (EDSS) scores and serum neurofilament light chain (sNfL) values than those with mildly increased CBF in the parietal lobes, temporal lobes, basal ganglia, and damaged white matter (DWM). From another perspective, MS patients with worse disease severity (higher EDSS score and sNfL values, longer disease duration) showed increased CBF in parietal lobes, temporal lobes, basal ganglia, normal-appearing white matter (NAWM), and DWM. Correlation analysis showed that there was a strong association among CBF, EDSS score and sNfL. MS patients with strongly increased CBF in various brain regions had more ratio in relapsing phase than patients with mildly increased CBF. And relapsing patients showed significantly higher CBF in some regions (temporal lobes, left basal ganglia, right NAWM) compared to remitting patients. In addition, MS patients with cognitive impairment had higher CBF than those without cognitive impairment in the right parietal lobe and NAWM. However, there were no significant differences in CBF between MS patients with and without other neurologic dysfunctions (e.g., motor impairment, visual disturbance, sensory dysfunction). These findings expand our understanding of CBF in MS and imply that CBF could be a potential quantitative imaging marker associated with disease severity.

Progressive Multiple Sclerosis

PURPOSE OF REVIEW

This article provides an update on progressive forms of multiple sclerosis (MS) commonly referred to as primary progressive MS and secondary progressive MS. It discusses the importance of diagnosing and detecting progression early, the similarities between progressive forms, challenges in detecting progression, factors that could augment progression, and the importance of disease-modifying therapies in patients with evidence of active progressive MS. It also discusses the overall care of progressive MS.

RECENT FINDINGS

The pathogenesis of primary progressive MS and secondary progressive MS is overlapping, and in both presentations, patients with relapses or focal MRI activity are classified as having active, progressive MS. All currently approved disease-modifying therapies are indicated for active secondary progressive MS. The therapeutic opportunity of anti-inflammatory drugs for the treatment of progressive MS is enhanced in those who are younger and have a shorter disease duration. Vascular comorbidities may contribute to progression in MS.

SUMMARY

Several challenges remain in the diagnosis, follow-up, and treatment of progressive MS. Early identification of active progressive MS is needed to maximize treatment benefit. The advantages of optimal comorbidity management (eg, hypertension, hyperlipidemia) in delaying progression are uncertain. Clinical care guidelines for advanced, severe MS are lacking.

Comparative analysis of the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced CT for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer

Background

The purpose of this study was to investigate the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced computed tomography (CECT) for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer (PHC).

Methods

Seventy-two PHC patients admitted to Linyi Central Hospital from May 2018 to May 2020 were selected as the study subjects, with a total of 92 lesions. All patients were treated with TACE, and were followed up at 6 months postoperatively. In addition, all patients underwent digital subtraction angiography (DSA), and with DSA results serving as the gold standard for diagnosis, the efficacy and accuracy of MRI and CECT for residual and new lesions after TACE in PHC patients were evaluated.

Results

There were no significant differences in the specificity between the two diagnostic methods (P>0.05), and the diagnostic accuracy and sensitivity of MRI were markedly higher than those of CECT (P<0.05). The number of residual and new lesions diagnosed by MRI was notably higher than that by multislice spiral computed tomography (MSCT) (P<0.05), and the detection rate of residual and new lesions after TACE in PHC patients with different types of iodized oil deposition by MRI was significantly higher than that by CECT (P<0.05). Also, the number of postoperative tumor capsules diagnosed by MRI was considerably higher than that by CECT (P<0.05). There were no significant differences between the two diagnostic methods in the score of residual enhancement appearances in the arterial phase after surgery (P>0.05). Furthermore, there were no notable differences between the two diagnostic methods in the diagnosis of portal vein tumorous emboli and the source of blood supply to lesions after surgery (P>0.05).

Conclusions

The diagnostic accuracy and sensitivity of MRI for residual and new lesions after TACE in PHC patients were higher than those of CECT. However, these two diagnostic methods were similar in diagnosing portal vein tumorous emboli, the source of blood supply to lesions, and the score of residual enhancement appearances in the arterial phase after surgery.

Neuroplasticity and Motor Rehabilitation in Multiple Sclerosis: A Systematic Review on MRI Markers of Functional and Structural Changes

Background: Motor rehabilitation is routinely used in clinical practice as an effective method to reduce progressive disability gain in multiple sclerosis (MS), but rehabilitation approaches are typically unstandardized, and only few studies have investigated the impact of rehabilitation on brain neuroplasticity. Objective: To summarize and critically analyze studies applying MRI markers of functional connectivity and structural changes to assess the effect of motor rehabilitation on brain neuroplasticity in MS. Methods: Literature search was performed using PubMed and EMBASE, selecting studies having as a subject motor rehabilitation and advanced MRI techniques investigating neuroplasticity in adult patients affected by MS. Results: Seventeen out of 798 papers were selected, of which 5 applied structural MRI (4 diffusion tensor imaging, 1 volumetric measurements), 7 applied functional fMRI (5 task-related fMRI, 2 resting-state fMRI) whereas the remaining 5 applied both structural and functional imaging. Discussion: The considerable data heterogeneity and the small sample sizes characterizing the studies limit interpretation and generalization of the results. Overall, motor rehabilitation promotes clinical improvement, paralleled by positive adaptive brain changes, whose features and extent depend upon different variables, including the type of rehabilitation approach. MRI markers of functional and structural connectivity should be implemented in studies testing the efficacy of motor rehabilitation. They allow for a better understanding of neuroplastic mechanisms underlying rehabilitation-mediated clinical achievements, facilitating the identification of rehabilitation strategies tailored to patients' needs and abilities.

Disease biomarkers in multiple sclerosis: current serum neurofilament light chain perspectives

The continuous neuroinflammatory and neurodegenerative pathology in multiple sclerosis (MS) results in irreversible accumulation of physical and cognitive disability. Reliable early detection of MS disease processes can aid in the diagnosis, monitoring and treatment management of MS patients. Recent assay technological advancements now allow reliable quantification of serum-based neurofilament light chain (sNfL) levels, which provide temporal information regarding the degree of neuroaxonal damage. The relationship and predictive value of sNfL with clinical and cognitive outcomes, other paraclinical measures and treatment response is reviewed. sNfL measurement is an emerging, noninvasive and disease-responsive MS biomarker that is currently utilized in research and clinical trial settings. Understanding sNfL confounders and further assay standardization will allow clinical implementation of this biomarker.

Early predictors of conversion to secondary progressive multiple sclerosis

BACKGROUND

We conducted this study to estimated the time of conversion from relapsing-remitting MS (RRMS) to SPMS and its early predictor factors.

METHODS

In this retrospective study, demographic, clinical, and imaging data from MS patients at diagnosis were extracted. Cox proportional hazards model was used to assess the association between various baseline characteristics and conversion to SPMS. We also assessed the association brtween escalation and early intensive therapy approaches with transition to progressive phase.

RESULTS

Out of 1903 patients with RRMS at baseline, 293 (15.4%) patients progressed to SPMS during follow-up. The estimated number of patients converted to SPMS was 10% at 10-years, 50% at 20-years, and 93% at 30-years. On multivariate Cox regression analysis older age at onset (HR: 1.067, 95%CI: 1.048-1.085, p < 0.001), smoking (HR: 2.120, 95%CI: 1.203-3.736, p = 0.009), higher EDSS at onset (HR: 1.199, 95%CI: 1.109-1.295, p < 0.001), motor dysfunction (HR: 2.470, 95%CI: 1.605-3.800, p < 0.001), cerebellar dysfunction (HR: 3.096, 95%CI: 1.840-5.211, p < 0.001), and presence of lesions in spinal cord (HR: 0.573, 95%CI: 0.297-0.989, p = 0.042) increased the risk of conversion from RRMS to SPMS. No significant difference between escalation and EIT groups in the risk of transition to progressive phase (weighted HR = 1.438; 95% CI: 0.963, 2.147; p = 0.076) was found.

CONCLUSION

Our data support previous observations that smoking is a modifiable risk factor for secondary progressive MS and confirms that spinal cord involvement, age, and more severe disease at onset are prognostic factors for converting to secondary progressive MS.

Secondary Progressive Multiple Sclerosis: New Insights

In most cases, multiple sclerosis (MS) begins with a relapsing-remitting course followed by insidious disability worsening that is independent from clinically apparent relapses and is termed secondary progressive MS (SMPS). Major differences exist between relapsing-remitting MS (RRMS) and SPMS, especially regarding therapeutic response to treatment. This review provides an overview of the pathology, differentiation, and challenges in the diagnosis and treatment of SPMS. We emphasize the criticality of conversion from a relapsing-remitting to a secondary progressive disease course not only because such conversion is evidence of disability progression, but also because, until recently, treatments that effectively reduced disability progression in relapsing MS were not proven to be effective in SPMS. Clear clinical, imaging, immunologic, or pathologic criteria marking the transition from RRMS to SPMS have not yet been established. Early identification of SPMS will require tools that, together with the use of appropriate treatments, may result in better long-term outcomes for the population of patients with SPMS.