MRI in multiple sclerosis: correlation with expanded disability status scale (EDSS)

Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

Quantitative susceptibility mapping (QSM) is a quantitative measure based on magnetic resonance imaging sensitive to iron and myelin content. This makes QSM a promising non-invasive tool for multiple sclerosis (MS) in research and clinical practice.

OBJECTIVE

We performed a systematic review and meta-analysis on the use of QSM in MS.

METHODS

Our review was prospectively registered on PROSPERO (CRD42022309563). We searched five databases for studies published between inception and 30th April 2023. We identified 83 English peer-reviewed studies that applied QSM images on MS cohorts. Fifty-five included studies had at least one of the following outcome measures: deep grey matter QSM values in MS, either compared to healthy controls (HC) (k = 13) or correlated with the score on the Expanded Disability Status Scale (EDSS) (k = 7), QSM lesion characteristics (k = 22) and their clinical correlates (k = 17), longitudinal correlates (k = 11), histological correlates (k = 7), or correlates with other imaging techniques (k = 12). Two meta-analyses on deep grey matter (DGM) susceptibility data were performed, while the remaining findings could only be analyzed descriptively.

RESULTS

After outlier removal, meta-analyses demonstrated a significant increase in the basal ganglia susceptibility (QSM values) in MS compared to HC, caudate (k = 9, standardized mean difference (SDM) = 0.54, 95 % CI = 0.39-0.70, I2 = 46 %), putamen (k = 9, SDM = 0.38, 95 % CI = 0.19-0.57, I2 = 59 %), and globus pallidus (k = 9, SDM = 0.48, 95 % CI = 0.28-0.67, I2 = 60 %), whereas thalamic QSM values exhibited a significant reduction (k = 12, SDM = -0.39, 95 % CI = -0.66--0.12, I2 = 84 %); these susceptibility differences in MS were independent of age. Further, putamen QSM values positively correlated with EDSS (k = 4, r = 0.36, 95 % CI = 0.16-0.53, I2 = 0 %). Regarding rim lesions, four out of seven studies, representing 73 % of all patients, reported rim lesions to be associated with more severe disability. Moreover, lesion development from initial detection to the inactive stage is paralleled by increasing, plateauing (after about two years), and gradually decreasing QSM values, respectively. Only one longitudinal study provided clinical outcome measures and found no association. Histological data suggest iron content to be the primary source of QSM values in DGM and at the edges of rim lesions; further, when also considering data from myelin water imaging, the decrease of myelin is likely to drive the increase of QSM values within WM lesions.

CONCLUSIONS

We could provide meta-analytic evidence for DGM susceptibility changes in MS compared to HC; basal ganglia susceptibility is increased and, in the putamen, associated with disability, while thalamic susceptibility is decreased. Beyond these findings, further investigations are necessary to establish the role of QSM in MS for research or even clinical routine.

Treatment reduces the incidence of newly appearing multiple sclerosis lesions evolving into chronic active, slowly expanding lesions: A retrospective analysis

BACKGROUND AND PURPOSE

Newly appearing lesions in multiple sclerosis (MS) may evolve into chronically active, slowly expanding lesions (SELs), leading to sustained disability progression. The aim of this study was to evaluate the incidence of newly appearing lesions developing into SELs, and their correlation to clinical evolution and treatment.

METHODS

A retrospective analysis of a fingolimod trial in primary progressive MS (PPMS; INFORMS, NCT00731692) was undertaken. Data were available from 324 patients with magnetic resonance imaging scans up to 3 years after screening. New lesions at year 1 were identified with convolutional neural networks, and SELs obtained through a deformation-based method. Clinical disability was assessed annually by Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test, Timed 25-Foot Walk, and Paced Auditory Serial Addition Test. Linear, logistic, and mixed-effect models were used to assess the relationship between the Jacobian expansion in new lesions and SELs, disability scores, and treatment status.

RESULTS

One hundred seventy patients had ≥1 new lesions at year 1 and had a higher lesion count at screening compared to patients with no new lesions (median = 27 vs. 22, p = 0.007). Among the new lesions (median = 2 per patient), 37% evolved into definite or possible SELs. Higher SEL volume and count were associated with EDSS worsening and confirmed disability progression. Treated patients had lower volume and count of definite SELs (β = -0.04, 95% confidence interval [CI] = -0.07 to -0.01, p = 0.015; β = -0.36, 95% CI = -0.67 to -0.06, p = 0.019, respectively).

CONCLUSIONS

Incident chronic active lesions are common in PPMS, and fingolimod treatment can reduce their number.

Quantitative T1 brain mapping in early relapsing-remitting multiple sclerosis: longitudinal changes, lesion heterogeneity and disability

OBJECTIVES

To quantify brain microstructural changes in recently diagnosed relapsing-remitting multiple sclerosis (RRMS) using longitudinal T1 measures, and determine their associations with clinical disability.

METHODS

Seventy-nine people with recently diagnosed (< 6 months) RRMS were recruited from a single-centre cohort sub-study, and underwent baseline and 1-year brain MRI, including variable flip angle T1 mapping. Median T1 was measured in white matter lesions (WML), normal-appearing white matter (NAWM), cortical/deep grey matter (GM), thalami, basal ganglia and medial temporal regions. Prolonged T1 (≥ 2.00 s) and supramedian T1 (relative to cohort WML values) WML voxel counts were also measured. Longitudinal change was assessed with paired t-tests and compared with Bland-Altman limits of agreement from healthy control test-retest data. Regression analyses determined relationships with Expanded Disability Status Scale (EDSS) score and dichotomised EDSS outcomes (worsening or stable/improving).

RESULTS

Sixty-two people with RRMS (mean age 37.2 ± 10.9 [standard deviation], 48 female) and 11 healthy controls (age 44 ± 11, 7 female) contributed data. Prolonged and supramedian T1 WML components increased longitudinally (176 and 463 voxels, respectively; p < .001), and were associated with EDSS score at baseline (p < .05) and follow-up (supramedian: p < .01; prolonged: p < .05). No cohort-wide median T1 changes were found; however, increasing T1 in WML, NAWM, cortical/deep GM, basal ganglia and thalami was positively associated with EDSS worsening (p < .05).

CONCLUSION

T1 is sensitive to brain microstructure changes in early RRMS. Prolonged WML T1 components and subtle changes in NAWM and GM structures are associated with disability.

CLINICAL RELEVANCE STATEMENT

MRI T1 brain mapping quantifies disability-associated white matter lesion heterogeneity and subtle microstructural damage in normal-appearing brain parenchyma in recently diagnosed RRMS, and shows promise for early objective disease characterisation and stratification.

KEY POINTS

• Quantitative T1 mapping detects brain microstructural damage and lesion heterogeneity in recently diagnosed relapsing-remitting multiple sclerosis. • T1 increases in lesions and normal-appearing parenchyma, indicating microstructural damage, are associated with worsening disability. • Brain T1 measures are objective markers of disability-relevant pathology in early multiple sclerosis.

The complex relationship between obesity and neurodegenerative diseases: an updated review

Obesity is a global epidemic, affecting roughly 30% of the world's population and predicted to rise. This disease results from genetic, behavioral, societal, and environmental factors, leading to excessive fat accumulation, due to insufficient energy expenditure. The adipose tissue, once seen as a simple storage depot, is now recognized as a complex organ with various functions, including hormone regulation and modulation of metabolism, inflammation, and homeostasis. Obesity is associated with a low-grade inflammatory state and has been linked to neurodegenerative diseases like multiple sclerosis (MS), Alzheimer's (AD), and Parkinson's (PD). Mechanistically, reduced adipose expandability leads to hypertrophic adipocytes, triggering inflammation, insulin and leptin resistance, blood-brain barrier disruption, altered brain metabolism, neuronal inflammation, brain atrophy, and cognitive decline. Obesity impacts neurodegenerative disorders through shared underlying mechanisms, underscoring its potential as a modifiable risk factor for these diseases. Nevertheless, further research is needed to fully grasp the intricate connections between obesity and neurodegeneration. Collaborative efforts in this field hold promise for innovative strategies to address this complex relationship and develop effective prevention and treatment methods, which also includes specific diets and physical activities, ultimately improving quality of life and health.

Towards a more precise rating of neurological disability in multiple sclerosis: A new automatic and linear quantification of limbs function

INTRODUCTION

The Expanded Disability Status Scale (EDSS) is the gold standard for evaluating clinical disability in multiple sclerosis (MS) in daily practice. However, more precise clinical assessment tools are needed. We assessed a new, automated rating of the neurological examination obtained with a mobile application (Quantified Neurological Examination - QNE).

METHOD

Consecutive MS patients were assessed for EDSS score and QNE application that calculates, from the description of the examination, a global score and subscores (qFSS) corresponding to the EDSS functional system scores (FSS). Brain MRI was analysed to obtain automatic measures of brain atrophy.

RESULTS

We performed 200 examinations and included 78 patients in the MRI analysis. The global QNE score was strongly correlated with the EDSS. qFSS was statistically different according to the corresponding FSS for each function, except for the visual FSS. EDSS was predominantly correlated to the pyramidal function of the lower limbs. QNE score and qFSS had at least equivalent correlation to MRI measures than EDSS, particularly regarding the gray matter and cortical volumes.

DISCUSSION

We propose an automated method to rate neurological disability in MS. While QNE strongly correlates with EDSS, it may allow a more precise way to monitor the evolution of disability.

Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset

Introduction

Conventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS), but due to its lack of specificity is unable to provide accurate prognoses, explain disease heterogeneity and reconcile the gap between observed clinical symptoms and radiological evidence. Quantitative MRI provides measures of physiological abnormalities, otherwise invisible to conventional MRI, that correlate with MS severity. Analyzing quantitative MRI measures through machine learning techniques has been shown to improve the understanding of the underlying disease by better delineating its alteration patterns.

Methods

In this retrospective study, a cohort of healthy controls (HC) and MS patients with different subtypes, followed up 15 years from clinically isolated syndrome (CIS), was analyzed to produce a multi-modal set of quantitative MRI features encompassing relaxometry, microstructure, sodium ion concentration, and tissue volumetry. Random forest classifiers were used to train a model able to discriminate between HC, CIS, relapsing remitting (RR) and secondary progressive (SP) MS patients based on these features and, for each classification task, to identify the relative contribution of each MRI-derived tissue property to the classification task itself.

Results and discussion

Average classification accuracy scores of 99 and 95% were obtained when discriminating HC and CIS vs. SP, respectively; 82 and 83% for HC and CIS vs. RR; 76% for RR vs. SP, and 79% for HC vs. CIS. Different patterns of alterations were observed for each classification task, offering key insights in the understanding of MS phenotypes pathophysiology: atrophy and relaxometry emerged particularly in the classification of HC and CIS vs. MS, relaxometry within lesions in RR vs. SP, sodium ion concentration in HC vs. CIS, and microstructural alterations were involved across all tasks.

Incremental validity of brief and abbreviated neuropsychological tests toward predicting functional outcomes in multiple sclerosis

OBJECTIVE

This study examined the relationships among functional outcomes and performance on standard-length and abbreviated cognitive screening measures for multiple sclerosis (MS).

METHOD

72 adults with MS underwent neurological examination and cognitive screening. They completed standard-length and abbreviated versions of tests from the Minimal Assessment of Cognitive Function in MS (MACFIMS), the abbreviated aMACFIMS, and the Brief International Cognitive Assessment for MS (BICAMS). Functional outcomes included neurological disability, physical and psychological dysfunction, and employment status.

RESULTS

Concordance of impairment classifications was examined between standard-length and abbreviated tests using logistic regression and ROC curve analyses. Overall, the abbreviated test versions showed a broad range of concordance with impairment classifications made using the full-length tests. Processing speed was the strongest correlate of neurological disability and employment status; immediate recall was the strongest predictor of subjective physical dysfunction. Test performance provided unique value toward predicting neurological disability and employment status, but not physical and psychological dysfunction.

CONCLUSIONS

The findings replicate some support for abbreviated tests in MS assessment, although caveats regarding loss of validity associated with abbreviation remain. The findings extend prior research showing that abbreviated tests of processing speed and immediate recall can provide unique predictive information regarding objective functional outcomes.

The clinical-radiological paradox in multiple sclerosis: myth or truth?

BACKGROUND

Multiple sclerosis (MS) is an inflammatory, degenerative, demyelinating disease that ranges from benign to rapidly progressive forms. A striking characteristic of the disease is the clinical-radiological paradox.

OBJECTIVES

The present study was conducted to determine whether, in our cohort, the clinical-radiological paradox exists and whether lesion location is related to clinical disability in patients with MS.

METHODS

Retrospective data from 95 patients with MS (60 women and 35 men) treated at a single center were examined. One head-and-spine magnetic resonance imaging (MRI) examination from each patient was selected randomly, and two independent observers calculated lesion loads (LLs) on T2/fluid attenuation inversion recovery sequences manually, considering the whole brain and four separate regions (periventricular, juxtacortical, posterior fossa, and spinal cord). The LLs were compared with the degree of disability, measured by the Kurtzke Expanded Disability Status Scale (EDSS), at the time of MRI examination in the whole cohort and in patients with relapsing-remitting (RR), primarily progressive, and secondarily progressive MS.

RESULTS

High LLs correlated with high EDSS scores in the whole cohort (r = 0.34; p < 0.01) and in the RRMS group (r = 0.27; p = 0.02). The EDSS score correlated with high regional LLs in the posterior fossa (r = 0.31; p = 0.002) and spinal cord (r = 0.35; p = 0.001).

CONCLUSIONS

Our results indicate that the clinical-radiological paradox is a myth and support the logical connection between lesion location and neurological repercussion.

Serum Neurofilament Identifies Patients With Multiple Sclerosis With Severe Focal Axonal Damage in a 6-Year Longitudinal Cohort

BACKGROUND AND OBJECTIVES

Immunomodulatory therapies reduce the relapse rate but only marginally control disability progression in patients with MS. Although serum neurofilament light chain (sNfL) levels correlate best with acute signs of inflammation (e.g., relapses and gadolinium-enhancing [Gd+] lesions), their role in predicting progressive biology and irreversible axonal damage is less clear. We aimed to determine the ability of sNfL to dissect distinct measures of disease severity and predict future (no) evidence of disease activity (EDA/no evidence of disease activity [NEDA]).

METHODS

One hundred fifty-three of 221 patients with relapsing-remitting MS initially enrolled in the Neurofilament and longterm outcome in MS cohort at the MS outpatient clinic of the University Medical Center Mainz (Germany) met the inclusion criteria for this prospective observational cohort study with a median follow-up of 6 years (interquartile range 4-7 years). Progressive disease forms were excluded. Inclusion criteria consisted of Expanded Disability Status Scale (EDSS) assessment within 3 months and MRI within 12 months around blood sampling at baseline (y0) and follow-up (y6). EDSS progression at y6 had to be confirmed 12 weeks later. sNfL was measured by single-molecule array, and the following additional variables were recorded: therapy, medical history, and detailed MRI parameters (T2 hyperintense lesions, Gd+ lesions, and new persistent T1 hypointense lesions).

RESULTS

Patients experiencing EDSS progression or new persistent T1 lesions at y6 showed increased sNfL levels at y0 compared with stable patients or patients with inflammatory activity only. As a potential readily accessible marker of neurodegeneration, we incorporated the absence of persistent T1 lesions to the NEDA-3 concept (NEDA-3^T1: n = 54, 35.3%; EDA^T1: n = 99, 64.7%) and then evaluated a risk score with factors that distinguish patients with and without NEDA-3^T1 status. Adding sNfL to this risk score significantly improved NEDA-3^T1 prediction (0.697 95% CI 0.616-0.770 vs 0.819 95% CI 0.747-0.878, p < 0.001). Patients with sNfL values ≤8.6 pg/mL showed a 76% risk reduction for EDA^T1 at y6 (hazard ratio 0.244, 95% CI 0.142-0.419, p < 0.001).

DISCUSSION

sNfL levels associate with severe focal axonal damage as reflected by development of persistent T1 lesions. Baseline sNfL values predicted NEDA-3^T1 status at 6-year follow-up.

Assessment of T2 lesion-based disease activity volume outcomes in predicting disease progression in multiple sclerosis over 10 years

BACKGROUND

New/enlarging T2 lesion count and T2-lesion volume (LV) are used as conventional secondary endpoints in clinical trials of patients with multiple sclerosis (PwMS). However, those outcomes may have several limitations, such as inability to account for heterogeneity of lesion formation/enlargement frequency and their dynamic volumetric behavior. Measurement of volume rather than count of new/enlarging lesions may be more representative outcome of dynamic changes over time.

OBJECTIVES

To investigate whether new/enlarging T2-LV is more predictive of confirmed disability progression (CDP), compared to total T2-LV or new/enlarging T2 lesion count over long-term follow-up.

METHODS

We studied 176 early relapsing-remitting PwMS who were followed with annual MRI examinations over 10 years. T2-LV, new/enlarging T2-LV, and new/enlarging lesion count were determined. Cumulative count/volumes were obtained. 10-year CDP was confirmed after 48-weeks. ANCOVA analysis detected MRI outcome differences in stable (n = 76) and CDP (n = 100) groups at different time points, after correction for multiple comparisons.

RESULTS

PwMS with CDP had greater cumulative new/enlarging T2-LV at 4 years (p = 0.049), and enlarging T2-LV at 4- (p = 0.039) and 6-year follow-up (p = 0.032), compared to stable patients. PwMS with CDP did not differ from stable ones in new/enlarging T2 lesion count or total T2-LV at any of the study timepoints. PwMS with Expanded Disability Status Scale change >2.0 had significantly greater enlarging T2 lesion count (p = 0.01) and enlarging T2-LV (p = 0.038) over the 10-year follow-up.

CONCLUSION

Enlargement of T2 lesions is more strongly associated with long-term disability progression compared to other conventional T2 lesion-based outcomes.

Status of ALS Treatment, Insights into Therapeutic Challenges and Dilemmas

Amyotrophic lateral sclerosis (ALS) is an extremely heterogeneous disease of motor neurons that eventually leads to death. Despite impressive advances in understanding the genetic, molecular, and pathological mechanisms of the disease, the only drug approved to date by both the FDA and EMA is riluzole, with a modest effect on survival. In this opinion view paper, we will discuss how to address some challenges for drug development in ALS at the conceptual, technological, and methodological levels. In addition, socioeconomic and ethical issues related to the legitimate need of patients to benefit quickly from new treatments will also be addressed. In conclusion, this brief review takes a more optimistic view, given the recent approval of two new drugs in some countries and the development of targeted gene therapies.

Linking lesions in sensorimotor cortex to contralateral hand function in multiple sclerosis: a 7 T MRI study

Cortical lesions constitute a key manifestation of multiple sclerosis and contribute to clinical disability and cognitive impairment. Yet it is unknown whether local cortical lesions and cortical lesion subtypes contribute to domain-specific impairments attributable to the function of the lesioned cortex.

In this cross-sectional study, we assessed how cortical lesions in the primary sensorimotor hand area (SM1-HAND) relate to corticomotor physiology and sensorimotor function of the contralateral hand. 50 relapse-free patients with relapsing-remitting or secondary-progressive multiple sclerosis and 28 healthy age- and sex-matched participants underwent whole-brain 7 T MRI to map cortical lesions. Brain scans were also used to estimate normalized brain volume, pericentral cortical thickness, white matter lesion fraction of the corticospinal tract, infratentorial lesion volume and the cross-sectional area of the upper cervical spinal cord. We tested sensorimotor hand function and calculated a motor and sensory composite score for each hand. In 37 patients and 20 healthy controls, we measured maximal motor evoked potential (MEP) amplitude, resting motor threshold and corticomotor conduction time with transcranial magnetic stimulation (TMS) and the N20 latency from somatosensory evoked potentials (SSEPs).

Patients showed at least one cortical lesion in the SM1-HAND in 47 of 100 hemispheres. The presence of a lesion was associated with worse contralateral sensory (P = 0.014) and motor (P = 0.009) composite scores. TMS of a lesion-positive SM1-HAND revealed a decreased maximal MEP amplitude (P &lt; 0.001) and delayed corticomotor conduction (P = 0.002) relative to a lesion-negative SM1-HAND. Stepwise mixed linear regressions showed that the presence of an SM1-HAND lesion, higher white-matter lesion fraction of the corticospinal tract, reduced spinal cord cross-sectional area and higher infratentorial lesion volume were associated with reduced contralateral motor hand function. Cortical lesions in SM1-HAND, spinal cord cross-sectional area and normalized brain volume were also associated with smaller maximal MEP amplitude and longer corticomotor conduction times. The effect of cortical lesions on sensory function was no longer significant when controlling for MRI-based covariates. Lastly, we found that intracortical and subpial lesions had the largest effect on reduced motor hand function, intracortical lesions on reduced MEP amplitude and leukocortical lesions on delayed corticomotor conduction.

Together, this comprehensive multi-level assessment of sensorimotor brain damage shows that the presence of a cortical lesion in SM1-HAND is associated with impaired corticomotor function of the hand, after accounting for damage at the subcortical level. The results also provide preliminary evidence that cortical lesion types may affect the various facets of corticomotor function differentially.

A tractometry principal component analysis of white matter tract network structure and relationships with cognitive function in relapsing-remitting multiple sclerosis

Understanding the brain changes underlying cognitive dysfunction is a key priority in multiple sclerosis (MS) to improve monitoring and treatment of this debilitating symptom. Functional connectivity network changes are associated with cognitive dysfunction, but it is less well understood how changes in normal appearing white matter relate to cognitive symptoms. If white matter tracts have network structure it would be expected that tracts within a network share susceptibility to MS pathology. In the present study, we used a tractometry approach to explore patterns of variance in white matter metrics across white matter (WM) tracts, and assessed how such patterns relate to neuropsychological test performance across cognitive domains. A sample of 102 relapsing-remitting MS patients and 27 healthy controls underwent MRI and neuropsychological testing. Tractography was performed on diffusion MRI data to extract 40 WM tracts and microstructural measures were extracted from each tract. Principal component analysis (PCA) was used to decompose metrics from all tracts to assess the presence of any co-variance structure among the tracts. Similarly, PCA was applied to cognitive test scores to identify the main cognitive domains. Finally, we assessed the ability of tract co-variance patterns to predict test performance across cognitive domains. We found that a single co-variance pattern which captured microstructure across all tracts explained the most variance (65% variance explained) and that there was little evidence for separate, smaller network patterns of pathology. Variance in this pattern was explained by effects related to lesions, but one main co-variance pattern persisted after this effect was regressed out. This main WM tract co-variance pattern contributed to explaining a modest degree of variance in one of our four cognitive domains in MS. These findings highlight the need to investigate the relationship between the normal appearing white matter and cognitive impairment further and on a more granular level, to improve the understanding of the network structure of the brain in MS.

Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis

Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [β = 0.12 (-0.56 to 0.80), t-value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [β = 0.037 (-0.14 to 0.22), t-value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [r = -0.32 (95% CI -0.46 to -0.17); z-value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio.

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

CNS endothelial derived extracellular vesicles are biomarkers of active disease in multiple sclerosis

Background

Multiple sclerosis (MS) is a complex, heterogenous disease characterized by inflammation, demyelination, and blood–brain barrier (BBB) permeability. Currently, active disease is determined by physician confirmed relapse or detection of contrast enhancing lesions via MRI indicative of BBB permeability. However, clinical confirmation of active disease can be cumbersome. As such, disease monitoring in MS could benefit from identification of an easily accessible biomarker of active disease. We believe extracellular vesicles (EV) isolated from plasma are excellent candidates to fulfill this need. Because of the critical role BBB permeability plays in MS pathogenesis and identification of active disease, we sought to identify EV originating from central nervous system (CNS) endothelial as biomarkers of active MS. Because endothelial cells secrete more EV when stimulated or injured, we hypothesized that circulating concentrations of CNS endothelial derived EV will be increased in MS patients with active disease.

Methods

To test this, we developed a novel method to identify EV originating from CNS endothelial cells isolated from patient plasma using flow cytometry. Endothelial derived EV were identified by the absence of lymphocyte or platelet markers CD3 and CD41, respectively, and positive expression of pan-endothelial markers CD31, CD105, or CD144. To determine if endothelial derived EV originated from CNS endothelial cells, EV expressing CD31, CD105, or CD144 were evaluated for expression of the myelin and lymphocyte protein MAL, a protein specifically expressed by CNS endothelial cells compared to endothelial cells of peripheral organs.

Results

Quality control experiments indicate that EV detected using our flow cytometry method are 0.2 to 1 micron in size. Flow cytometry analysis of EV isolated from 20 healthy controls, 16 relapsing–remitting MS (RRMS) patients with active disease not receiving disease modifying therapy, 14 RRMS patients with stable disease not receiving disease modifying therapy, 17 relapsing-RRMS patients with stable disease receiving natalizumab, and 14 RRMS patients with stable disease receiving ocrelizumab revealed a significant increase in the plasma concentration of CNS endothelial derived EV in patients with active disease compared to all other groups (p = 0.001). Conclusions: For the first time, we have identified a method to identify CNS endothelial derived EV in circulation from human blood samples. Results from our pilot study indicate that increased levels of CNS endothelial derived EV may be a biomarker of BBB permeability and active disease in MS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12987-021-00299-4.

Multiple sclerosis: Inflammation, autoimmunity and plasticity

In recent years, experimental studies have clarified that immune system influences the functioning of the central nervous system (CNS) in both physiologic and pathologic conditions. The neuro-immune crosstalk plays a crucial role in neuronal development and may be critically involved in mediating CNS response to neuronal damage. Multiple sclerosis (MS) represents a good model to investigate how the immune system regulates neuronal activity. Accordingly, a growing body of evidence has demonstrated that increased levels of pro-inflammatory mediators may significantly impact synaptic mechanisms, influencing overall neuronal excitability and synaptic plasticity expression. In this chapter, we provide an overview of preclinical data and clinical studies exploring synaptic functioning noninvasively with transcranial magnetic stimulation (TMS) in patients with MS. Moreover, we examine how inflammation-driven synaptic dysfunction could affect synaptic plasticity expression, negatively influencing the MS course. Contrasting CSF inflammation together with pharmacologic enhancement of synaptic plasticity and application of noninvasive brain stimulation, alone or in combination with rehabilitative treatments, could improve the clinical compensation and prevent the accumulating deterioration in MS.

Functional neurological disorder: lighting the way to a new paradigm for medicine

In this Essay, Mark Edwards argues that the plight of people with functional neurological disorder within healthcare highlights a general problem with a broken paradigm of modern medicine. He argues that the passivity of the traditional sick role needs replacing with a participatory, rehabilitative medical practice.

Imaging cortical multiple sclerosis lesions with ultra-high field MRI

BACKGROUND

Cortical lesions are abundant in multiple sclerosis (MS), yet difficult to visualize in vivo. Ultra-high field (UHF) MRI at 7 T and above provides technological advances suited to optimize the detection of cortical lesions in MS.

PURPOSE

To provide a narrative and quantitative systematic review of the literature on UHF MRI of cortical lesions in MS.

METHODS

A systematic search of all literature on UHF MRI of cortical lesions in MS published before September 2020. Quantitative outcome measures included cortical lesion numbers reported using 3 T and 7 T MRI and between 7 T MRI sequences, along with sensitivity of UHF MRI towards cortical lesions verified by histopathology.

RESULTS

7 T MRI detected on average 52 ± 26% (mean ± 95% confidence interval) more cortical lesions than the best performing image contrast at 3 T, with the largest increase in type II-IV intracortical lesion detection. Across all studies, the mean cortical lesion number was 17 ± 6 per patient. In progressive MS cohorts, approximately four times more cortical lesions were reported than in CIS/early RRMS, and RRMS. Yet, there was no difference in lesion type ratio between these MS subtypes. Furthermore, superiority of one MRI sequence over another could not be established from available data. Post-mortem lesion detection with UHF MRI agreed only modestly with pathological examinations. Mean pro- and retrospective sensitivity was 33 ± 6% and 71 ± 10%, respectively, with the highest sensitivity towards type I and type IV lesions.

CONCLUSION

UHF MRI improves cortical lesion detection in MS considerably compared to 3 T MRI, particularly for type II-IV lesions. Despite modest sensitivity, 7 T MRI is still capable of visualizing all aspects of cortical lesion pathology and could potentially aid clinicians in diagnosing and monitoring MS, and progressive MS in particular. However, standardization of acquisition and segmentation protocols is needed.

Prediction in treatment outcomes in multiple sclerosis: challenges and recent advances

INTRODUCTION

Multiple Sclerosis (MS) is a chronic autoimmune and neurodegenerative disease of the central nervous system with a course dependent on early treatment response. Increasing evidence also suggests that despite eliminating disease activity (relapses and lesions), many patients continue to accrue disability, highlighting the need for a more comprehensive definition of treatment success. Optimizing disability outcome measures, as well as continuously improving our understanding of neuroinflammatory and neurodegenerative biomarkers is required.

AREAS COVERED

This review describes the challenges inherent in classifying and monitoring disease phenotype in MS. The review also provides an assessment of clinical, radiological, and blood biomarker tools for current and future practice.

EXPERT OPINION

Emerging MRI techniques and standardized patient outcome assessments will increase the accuracy of initial diagnosis and understanding of disease progression.

A Combined Radiomics and Machine Learning Approach to Overcome the Clinicoradiologic Paradox in Multiple Sclerosis

BACKGROUND AND PURPOSE

Conventional MR imaging explains only a fraction of the clinical outcome variance in multiple sclerosis. We aimed to evaluate machine learning models for disability prediction on the basis of radiomic, volumetric, and connectivity features derived from routine brain MR images.

MATERIALS AND METHODS

In this retrospective cross-sectional study, 3T brain MR imaging studies of patients with multiple sclerosis, including 3D T1-weighted and T2-weighted FLAIR sequences, were selected from 2 institutions. T1-weighted images were processed to obtain volume, connectivity score (inferred from the T2 lesion location), and texture features for an atlas-based set of GM regions. The site 1 cohort was randomly split into training (n = 400) and test (n = 100) sets, while the site 2 cohort (n = 104) constituted the external test set. After feature selection of clinicodemographic and MR imaging-derived variables, different machine learning algorithms predicting disability as measured with the Expanded Disability Status Scale were trained and cross-validated on the training cohort and evaluated on the test sets. The effect of different algorithms on model performance was tested using the 1-way repeated-measures ANOVA.

RESULTS

The selection procedure identified the 9 most informative variables, including age and secondary-progressive course and a subset of radiomic features extracted from the prefrontal cortex, subcortical GM, and cerebellum. The machine learning models predicted disability with high accuracy (r approaching 0.80) and excellent intra- and intersite generalizability (r ≥ 0.73). The machine learning algorithm had no relevant effect on the performance.

CONCLUSIONS

The multidimensional analysis of brain MR images, including radiomic features and clinicodemographic data, is highly informative of the clinical status of patients with multiple sclerosis, representing a promising approach to bridge the gap between conventional imaging and disability.

Early multiple sclerosis: diagnostic challenges in clinically and radiologically isolated syndrome patients

PURPOSE OF REVIEW

With the introduction of new diagnostic criteria, the sensibility for multiple sclerosis (MS) diagnosis increased and the number of cases with the clinically isolated syndrome (CIS) decreased. Nevertheless, a misdiagnosis might always be around the corner, and the exclusion of a 'better explanation' is mandatory.There is a pressing need to provide an update on the main prognostic factors that increase the risk of conversion from CIS or from radiologically isolated syndrome (RIS) to MS, and on the potential 'red flags' to consider during the diagnostic workup.

RECENT FINDINGS

We discuss diagnostic challenges when facing patients presenting with a first demyelinating attack or with a RIS, with a focus on recently revised diagnostic criteria, on other neuroinflammatory conditions to be considered in the differential diagnosis and on factors distinguishing patients at risk of developing MS.A correct definition of a 'typical' demyelinating attack, as well as a correct interpretation of MRI findings, remains crucial in the diagnostic process. The cerebrospinal fluid examination is warmly recommended to confirm the dissemination in time of the demyelinating process and to increase the diagnostic accuracy.

SUMMARY

An early and accurate diagnosis of MS requires careful consideration of all clinical, paraclinical and radiological data, as well the reliable exclusion of other mimicking pathological conditions. This is advocated to promptly initiate an appropriate disease-modifying therapy, which can impact positively on the long-term outcome of the disease.

Assessment of Disability Progression Independent of Relapse and Brain MRI Activity in Patients with Multiple Sclerosis in Poland

The aim of the study was to verify the association of clinical relapses and brain activity with disability progression in relapsing/remitting multiple sclerosis patients receiving disease-modifying treatments in Poland. Disability progression was defined as relapse-associated worsening (RAW), progression independent of relapse activity (PIRA), and progression independent of relapses and brain MRI Activity (PIRMA). Data from the Therapeutic Program Monitoring System were analyzed. Three panels of patients were identified: R0, no relapse during treatment, and R1 and R2 with the occurrence of relapse during the first and the second year of treatment, respectively. In the R0 panel, we detected 4.6% PIRA patients at 24 months (p < 0.001, 5.0% at 36 months, 5.6% at 48 months, 6.1% at 60 months). When restricting this panel to patients without brain MRI activity, we detected 3.0% PIRMA patients at 12 months, 4.5% at 24 months, and varying from 5.3% to 6.2% between 36 and 60 months of treatment, respectively. In the R1 panel, RAW was detected in 15.6% patients at 12 months and, in the absence of further relapses, 9.7% at 24 months and 6.8% at 36 months of treatment. The R2 group was associated with RAW significantly more frequently at 24 months compared to the R1 at 12 months (20.7%; p < 0.05), but without a statistical difference later on. In our work, we confirmed that disability progression was independent of relapses and brain MRI activity.

A Comparison of Quantitative R1 and Cortical Thickness in Identifying Age, Lifespan Dynamics, and Disease States of the Human Cortex

Brain development and aging are complex processes that unfold in multiple brain regions simultaneously. Recently, models of brain age prediction have aroused great interest, as these models can potentially help to understand neurological diseases and elucidate basic neurobiological mechanisms. We test whether quantitative magnetic resonance imaging can contribute to such age prediction models. Using R1, the longitudinal rate of relaxation, we explore lifespan dynamics in cortical gray matter. We compare R1 with cortical thickness, a well-established biomarker of brain development and aging. Using 160 healthy individuals (6-81 years old), we found that R1 and cortical thickness predicted age similarly, but the regions contributing to the prediction differed. Next, we characterized R1 development and aging dynamics. Compared with anterior regions, in posterior regions we found an earlier R1 peak but a steeper postpeak decline. We replicate these findings: firstly, we tested a subset (N = 10) of the original dataset for whom we had additional scans at a lower resolution; and second, we verified the results on an independent dataset (N = 34). Finally, we compared the age prediction models on a subset of 10 patients with multiple sclerosis. The patients are predicted older than their chronological age using R1 but not with cortical thickness.

The neuroanatomical-functional paradox in spinal cord injury

Although lesion size is widely considered to be the most reliable predictor of outcome after CNS injury, lesions of comparable size can produce vastly different magnitudes of functional impairment and subsequent recovery. This neuroanatomical-functional paradox is likely to contribute to the many failed attempts to independently replicate findings from animal models of neurotrauma. In humans, the analogous clinical-radiological paradox could explain why individuals with similar injuries can respond differently to rehabilitation. We describe the neuroanatomical-functional paradox in the context of traumatic spinal cord injury (SCI) and discuss the underlying mechanisms of the paradox, including the concepts of lesion-affected and recovery-related networks. We also consider the various secondary complications that further limit the accuracy of outcome prediction in SCI and provide suggestions for how to increase the predictive, translational value of preclinical SCI models.

Comparison of susceptibility weighted imaging with conventional MRI sequences in multiple sclerosis plaque assessment: A cross-sectional study

Background:

The current study was performed to compare susceptibility-weighted imaging (SWI) with magnetic resonance imaging (MRI) methods of T2-weighted (T2W) and fluid-attenuated inversion recovery (FLAIR) imaging in multiple sclerosis (MS) plaque assessment

Materials and Methods:

This cross-sectional study was conducted among 50 MS patients referred to Shafa Imaging Center, Isfahan, Iran. Patients who fulfilled McDonald criteria and were diagnosed with MS by a professional neurologist at least 1 year before the study initiation were included in the study. Eligible patients underwent brain scans using SWI, T2W imaging, and FLAIR. Plaques’ number and volume were detected separately for each imaging sequence. Moreover, identified lesions in SWI sequence were evaluated in terms of iron deposition and central veins

Results:

Totally 50 patients (10 males and 40 females) with a mean age of 28.48 ± 5.25 years were included in the current study. Majority of patients (60%) had a disease duration of >5 years, and mean expanded disability status score was 2.56 ± 1.32. There was no significant difference between different imaging modalities in terms of plaques’ number and volume (P > 0.05). It was also found that there was a high correlation between SWI and conventional imaging techniques of T2W (r = 0.97, 0.91, P < 0.001) and FLAIR (r = 0.99, 0.99, P < 0.001) in the estimation of both the number and volume of plaques (P < 0.001)

Conclusion:

The results of the present study indicated that SWI and conventional MRI sequences have similar efficiency for plaque assessment in MS patients.

Siponimod: Disentangling disability and relapses in secondary progressive multiple sclerosis

Background:

In multiple sclerosis, impact of treatment on disability progression can be confounded if treatment also reduces relapses.

Objective:

To distinguish siponimod’s direct effects on disability progression from those on relapses in the EXPAND phase 3 trial.

Methods:

Three estimands, one based on principal stratum and two on hypothetical scenarios (no relapses, or equal relapses in both treatment arms), were defined to determine the extent to which siponimod’s effects on 3- and 6-month confirmed disability progression were independent of on-study relapses.

Results:

Principal stratum analysis estimated that siponimod reduced the risk of 3- and 6-month confirmed disability progression by 14%–20% and 29%–33%, respectively, compared with placebo in non-relapsing patients. In the hypothetical scenarios, risk reductions independent of relapses were 14%–18% and 23% for 3- and 6-month confirmed disability progression, respectively.

Conclusion:

By controlling the confounding impact of on-study relapses on confirmed disability progression, these statistical approaches provide a methodological framework to assess treatment effects on disability progression in relapsing and non-relapsing patients. The analyses support that siponimod may be useful for treating secondary progressive multiple sclerosis in patients with or without relapses.

Magnetization Transfer Ratio and Morphometrics of the Spinal Cord Associates with Surgical Recovery in Patients with Degenerative Cervical Myelopathy

OBJECTIVES

We assessed the prognostic value of the preoperative magnetization transfer ratio (MTR) and morphometrics of the spinal cord in patients with degenerative cervical myelopathy (DCM) in a longitudinal cohort study.

METHODS

Thirteen subjects with DCM underwent 3T magnetization transfer imaging. The MTR was calculated for the spinal cord regions and specific white matter tracts. Morphometric measures were extracted. Clinical (modified Japanese Orthopaedics Association [mJOA] and Nurick scale scores) and health-related quality of life scores were assessed before and after cervical decompression surgery. The association between the magnetic resonance imaging (MRI) metrics and postoperative recovery was assessed (Spearman's correlation). Receiver operating characteristics were used to assess the accuracy of MRI metrics in identifying ≥50% recovery in function.

RESULTS

Preoperative anterior cord MTRs were associated with recovery in mJOA scores (ρ = 0.608; P = 0.036; area under the curve [AUC], 0.66). Preoperative lateral cord MTR correlated with the neck disability index (ρ = 0.699; P = 0.011) and pain interference scale (ρ = 0.732; P = 0.007). Preoperative rubrospinal tract MTR was associated with mJOA score recovery (ρ = 0.573; P = 0.041; AUC, 0.86). Preoperative corticospinal tract and reticulospinal MTRs were related to recovery in pain interference scores (ρ = 0.591; P = 0.033; and ρ = 0.583; P = 0.035, respectively). Eccentricity of the cord was associated with Nurick scores (ρ = 0.606; P = 0.028) and mJOA scores (ρ = 0.651; P = 0.025; AUC, 0.92).

CONCLUSIONS

Preoperative MTR and eccentricity measurements of the spinal cord have prognostic value in assessing the response to surgery and recovery in patients with DCM. Advanced MRI and atlas-based postprocessing techniques can inform interventions and advance the healthcare received by patients with DCM.

In vivo imaging of chronic active lesions in multiple sclerosis

New clinical activity in multiple sclerosis (MS) is often accompanied by acute inflammation which subsides. However, there is growing evidence that a substantial proportion of lesions remain active well beyond the acute phase. Chronic active lesions are most frequently found in progressive MS and are characterised by a border of inflammation associated with iron-enriched cells, leading to ongoing tissue injury. Identifying imaging markers for chronic active lesions in vivo are thus a major research goal. We reviewed the literature on imaging of chronic active lesion in MS, focussing on ‘slowly expanding lesions’ (SELs), detected by volumetric longitudinal magnetic resonance imaging (MRI) and ‘rim-positive’ lesions, identified by susceptibility iron-sensitive MRI. Both SELs and rim-positive lesions have been found to be prognostically relevant to future disability. Little is known about the co-occurrence of rims around SELs and their inter-relationship with other emerging techniques such as dynamic contrast enhancement (DCE) and positron emission tomography (PET).

7T MPFLAIR versus MP2RAGE for Quantifying Lesion Volume in Multiple Sclerosis

BACKGROUND AND PURPOSE

Use of fluid-attenuated inversion recovery (FLAIR) scans to quantify multiple sclerosis (MS) lesion volume on 7 Tesla (7T) magnetic resonance imaging (MRI) has many downsides, including poor image homogeneity. There are little data about the relative benefit of alternative modalities. The purpose of this paper is to investigate if magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) is a viable alternative to FLAIR for robust lesion volume measurement and disability correlations.

METHODS

Forty-seven participants with MS underwent annual brain 7T MRIs. Magnetization-prepared FLAIR (MPFLAIR) and MP2RAGE (both at .7 mm³ isotropic resolution) sequences from a total of 80 MRI scans from 47 subjects were reviewed. White matter lesion (WML) masks were manually constructed from MPFLAIR and T1 maps (from MP2RAGE). Lesion volumes (normalized to intracranial volume) were compared to clinical characteristics and disability scales scores by Pearson or Spearman correlation, as appropriate. Relative correlation strength was compared by Fisher r- to z-transformation.

RESULTS

Normalized lesion volume was greater in MPFLAIR masks (median .005 [range, .001-.030]) than from T1 maps (median .003 [range, .000-.015]). However, lesion volumes between MPFLAIR and T1 maps were highly correlated (rho = .87, P < .001). WML masks from both modalities correlated with most disability measures with no significant difference in the strength of correlation.

CONCLUSIONS

7T MPFLAIR and MP2RAGE T1 map-based WML volumes are highly intercorrelated and both correlate with disability. Thus, MP2RAGE may be a viable alternative to FLAIR-based methods for WML measurement on 7T MRI in MS research.

TAPAS: A Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis

Total brain white matter lesion (WML) volume is the most widely established magnetic resonance imaging (MRI) outcome measure in studies of multiple sclerosis (MS). To estimate WML volume, there are a number of automatic segmentation methods available, yet manual delineation remains the gold standard approach. Automatic approaches often yield a probability map to which a threshold is applied to create lesion segmentation masks. Unfortunately, few approaches systematically determine the threshold employed; many methods use a manually selected threshold, thus introducing human error and bias into the automated procedure. In this study, we propose and validate an automatic thresholding algorithm, Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis (TAPAS), to obtain subject-specific threshold estimates for probability map automatic segmentation of T2-weighted (T2) hyperintense WMLs. Using multimodal MRI, the proposed method applies an automatic segmentation algorithm to obtain probability maps. We obtain the true subject-specific threshold that maximizes the Sørensen-Dice similarity coefficient (DSC). Then the subject-specific thresholds are modeled on a naive estimate of volume using a generalized additive model. Applying this model, we predict a subject-specific threshold in data not used for training. We ran a Monte Carlo-resampled split-sample cross-validation (100 validation sets) using two data sets: the first obtained from the Johns Hopkins Hospital (JHH) on a Philips 3 Tesla (3T) scanner (n = 94) and a second collected at the Brigham and Women's Hospital (BWH) using a Siemens 3T scanner (n = 40). By means of the proposed automated technique, in the JHH data we found an average reduction in subject-level absolute error of 0.1 mL per one mL increase in manual volume. Using Bland-Altman analysis, we found that volumetric bias associated with group-level thresholding was mitigated when applying TAPAS. The BWH data showed similar absolute error estimates using group-level thresholding or TAPAS likely since Bland-Altman analyses indicated no systematic biases associated with group or TAPAS volume estimates. The current study presents the first validated fully automated method for subject-specific threshold prediction to segment brain lesions.

Tractography in the presence of multiple sclerosis lesions

Accurate anatomical localisation of specific white matter tracts and the quantification of their tract-specific microstructural damage in conditions such as multiple sclerosis (MS) can contribute to a better understanding of symptomatology, disease evolution and intervention effects. Diffusion MRI-based tractography is being used increasingly to segment white matter tracts as regions-of-interest for subsequent quantitative analysis. Since MS lesions can interrupt the tractography algorithm’s tract reconstruction, clinical studies frequently resort to atlas-based approaches, which are convenient but ignorant to individual variability in tract size and shape. Here, we revisit the problem of individual tractography in MS, comparing tractography algorithms using: (i) The diffusion tensor framework; (ii) constrained spherical deconvolution (CSD); and (iii) damped Richardson-Lucy (dRL) deconvolution. Firstly, using simulated and in vivo data from 29 MS patients and 19 healthy controls, we show that the three tracking algorithms respond differentially to MS pathology. While the tensor-based approach is unable to deal with crossing fibres, CSD produces spurious streamlines, in particular in tissue with high fibre loss and low diffusion anisotropy. With dRL, streamlines are increasingly interrupted in pathological tissue. Secondly, we demonstrate that despite the effects of lesions on the fibre orientation reconstruction algorithms, fibre tracking algorithms are still able to segment tracts that pass through areas with a high prevalence of lesions. Combining dRL-based tractography with an automated tract segmentation tool on data from 131 MS patients, the corticospinal tracts and arcuate fasciculi could be reconstructed in more than 90% of individuals. Comparing tract-specific microstructural parameters (fractional anisotropy, radial diffusivity and magnetisation transfer ratio) in individually segmented tracts to those from a tract probability map, we show that there is no systematic disease-related bias in the individually reconstructed tracts, suggesting that lesions and otherwise damaged parts are not systematically omitted during tractography. Thirdly, we demonstrate modest anatomical correspondence between the individual and tract probability-based approach, with a spatial overlap between 35 and 55%. Correlations between tract-averaged microstructural parameters in individually segmented tracts and the probability-map approach ranged between r = .53 (p < .001) for radial diffusivity in the right cortico-spinal tract and r = .97 (p < .001) for magnetisation transfer ratio in the arcuate fasciculi. Our results show that MS white matter lesions impact fibre orientation reconstructions but this does not appear to hinder the ability to anatomically reconstruct white matter tracts in MS. Individual tract segmentation in MS is feasible on a large scale and could prove a powerful tool for investigating diagnostic and prognostic markers.

Diffusion basis spectrum imaging provides insights into MS pathology

Objective

To use diffusion basis spectrum imaging (DBSI) to assess how damage to normal-appearing white matter (NAWM) in the corpus callosum (CC) influences neurologic impairment in people with MS (pwMS).

Methods

Using standard MRI, the primary pathologies in MS of axonal injury/loss, demyelination, and inflammation are not differentiated well. DBSI has been shown in animal models, phantoms, and in biopsied and autopsied human CNS tissues to distinguish these pathologies. Fifty-five pwMS (22 relapsing-remitting, 17 primary progressive, and 16 secondary progressive) and 13 healthy subjects underwent DBSI analyses of NAWM of the CC, the main WM tract connecting the cerebral hemispheres. Tract-based spatial statistics were used to minimize misalignment. Results were correlated with scores from a battery of clinical tests focused on deficits typical of MS.

Results

Normal-appearing CC in pwMS showed reduced fiber fraction and increased nonrestricted isotropic fraction, with the most extensive abnormalities in secondary progressive MS (SPMS). Reduced DBSI-derived fiber fraction and increased DBSI-derived nonrestricted isotropic fraction of the CC correlated with worse cognitive scores in pwMS. Increased nonrestricted isotropic fraction in the body of the CC correlated with impaired hand function in the SPMS cohort.

Conclusions

DBSI fiber fraction and nonrestricted isotropic fraction were the most useful markers of injury in the NAWM CC. These 2 DBSI measures reflect axon loss in animal models. Because of its ability to reveal axonal loss, as well as demyelination, DBSI may be a useful outcome measure for trials of CNS reparative treatments.

Does CSF pleocytosis have a predictive value for disease course in MS?

Objective

MS is a demyelinating CNS disorder with a spectrum of clinical patterns regarding course and prognosis. Although several prognostic factors are considered in the initial evaluation of patients, biological markers defining the disease course and guiding treatments are currently lacking. It is unknown whether patients with CSF pleocytosis differ in regard to symptoms, disease course, and prognosis from those without. The aim of this study was to evaluate whether CSF pleocytosis during the initial presentation has an impact on the clinical course and progression of MS.

Methods

We retrospectively evaluated patients attending the MS Clinic at Rabin Medical Center between January 1999 and January 2016 who underwent lumbar puncture (LP) at disease presentation, considering CSF cell count, clinical diagnosis (clinically isolated syndrome [CIS] and relapsing-remitting MS [RRMS]), annualized relapse rate (ARR), paraclinical findings (imaging, CSF oligoclonal bands, and evoked potentials), and disease progression, expressed by the Expanded Disability Status Scale (EDSS).

Results

One hundred fourteen patients (72 females) underwent LP at disease presentation (RRMS: n = 100, CIS: n = 14). Age at diagnosis was 32.4 ± 12.2 years, and the follow-up time was 9.4 ± 3.8 years. Forty-six patients showed a pleocytic CSF (≥5 cells per μL). Compared with patients with <4 cells per μL, patients with pleocytosis had a higher ARR (0.60 ± 0.09 vs 0.48 ± 0.04; p = 0.0267) and a steeper increase (slope) in the EDSS score throughout the follow-up period (correlation coefficient: r2 = 0.04; p = 0.0251).

Conclusions

CSF pleocytosis may be considered a biological unfavorable predictive factor regarding disease course and progression in MS.

Three-dimensional MRI sequences in MS diagnosis and research

The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).

A computer-aided diagnosis of multiple sclerosis based on mfVEP recordings

Introduction

The aim of this study is to develop a computer-aided diagnosis system to identify subjects at differing stages of development of multiple sclerosis (MS) using multifocal visual-evoked potentials (mfVEPs). Using an automatic classifier, diagnosis is performed first on the eyes and then on the subjects.

Patients

MfVEP signals were obtained from patients with Radiologically Isolated Syndrome (RIS) (n = 30 eyes), patients with Clinically Isolated Syndrome (CIS) (n = 62 eyes), patients with definite MS (n = 56 eyes) and 22 control subjects (n = 44 eyes). The CIS and MS groups were divided into two subgroups: those with eyes affected by optic neuritis (ON) and those without (non-ON).

Methods

For individual eye diagnosis, a feature vector was formed with information about the intensity, latency and singular values of the mfVEP signals. A flat multiclass classifier (FMC) and a hierarchical classifier (HC) were tested and both were implemented using the k-Nearest Neighbour (k-NN) algorithm. The output of the best eye classifier was used to classify the subjects. In the event of divergence, the eye with the best mfVEP recording was selected.

Results

In the eye classifier, the HC performed better than the FMC (accuracy = 0.74 and extended Matthew Correlation Coefficient (MCC) = 0.68). In the subject classification, accuracy = 0.95 and MCC = 0.93, confirming that it may be a promising tool for MS diagnosis.

Conclusion

In addition to amplitude (axonal loss) and latency (demyelination), it has shown that the singular values of the mfVEP signals provide discriminatory information that may be used to identify subjects with differing degrees of the disease.

Silent progression in disease activity-free relapsing multiple sclerosis

Objective

Rates of worsening and evolution to secondary progressive multiple sclerosis (MS) may be substantially lower in actively treated patients compared to natural history studies from the pretreatment era. Nonetheless, in our recently reported prospective cohort, more than half of patients with relapsing MS accumulated significant new disability by the 10th year of follow‐up. Notably, “no evidence of disease activity” at 2 years did not predict long‐term stability. Here, we determined to what extent clinical relapses and radiographic evidence of disease activity contribute to long‐term disability accumulation.

Methods

Disability progression was defined as an increase in Expanded Disability Status Scale (EDSS) of 1.5, 1.0, or 0.5 (or greater) from baseline EDSS = 0, 1.0–5.0, and 5.5 or higher, respectively, assessed from baseline to year 5 (±1 year) and sustained to year 10 (±1 year). Longitudinal analysis of relative brain volume loss used a linear mixed model with sex, age, disease duration, and HLA‐DRB1*15:01 as covariates.

Results

Relapses were associated with a transient increase in disability over 1‐year intervals (p = 0.012) but not with confirmed disability progression (p = 0.551). Relative brain volume declined at a greater rate among individuals with disability progression compared to those who remained stable (p < 0.05).

Interpretation

Long‐term worsening is common in relapsing MS patients, is largely independent of relapse activity, and is associated with accelerated brain atrophy. We propose the term silent progression to describe the insidious disability that accrues in many patients who satisfy traditional criteria for relapsing–remitting MS. Ann Neurol 2019;85:653–666

Comparing MRI metrics to quantify white matter microstructural damage in multiple sclerosis

Quantifying white matter damage in vivo is becoming increasingly important for investigating the effects of neuroprotective and repair strategies in multiple sclerosis (MS). While various approaches are available, the relationship between MRI‐based metrics of white matter microstructure in the disease, that is, to what extent the metrics provide complementary versus redundant information, remains largely unexplored. We obtained four microstructural metrics from 123 MS patients: fractional anisotropy (FA), radial diffusivity (RD), myelin water fraction (MWF), and magnetisation transfer ratio (MTR). Coregistration of maps of these four indices allowed quantification of microstructural damage through voxel‐wise damage scores relative to healthy tissue, as assessed in a group of 27 controls. We considered three white matter tissue‐states, which were expected to vary in microstructural damage: normal appearing white matter (NAWM), T2‐weighted hyperintense lesional tissue without T1‐weighted hypointensity (T2L), and T1‐weighted hypointense lesional tissue with corresponding T2‐weighted hyperintensity (T1L). All MRI indices suggested significant damage in all three tissue‐states, the greatest damage being in T1L. The correlations between indices ranged from r = 0.18 to r = 0.87. MWF was most sensitive when differentiating T2L from NAWM, while MTR was most sensitive when differentiating T1L from NAWM and from T2L. Combining the four metrics into one, through a principal component analysis, did not yield a measure more sensitive to damage than any single measure. Our findings suggest that the metrics are (at least partially) correlated with each other, but sensitive to the different aspects of pathology. Leveraging these differences could be beneficial in clinical trials testing the effects of therapeutic interventions.

Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease with a complex clinical course characterized by inflammation, demyelination, and axonal degeneration. Diagnosis of MS most commonly includes finding lesions in at least two separate areas of the central nervous system (CNS), including the brain, spinal cord, and optic nerves. In recent years, there has been a remarkable increase in the number of available treatments for MS. An optimal treatment is usually based on a personalized approach determined by an individual patient's prognosis and treatment risks. Biomarkers that can predict disability progression, monitor ongoing disease activity, and assess treatment response are integral in making important decisions regarding MS treatment. This review describes MS biomarkers that are currently being used in clinical practice; it also reviews and consolidates published findings from clinically relevant potential MS biomarkers in recent years. The work also discusses the challenges of validating and application of biomarkers in MS clinical practice.

A dual modeling approach to automatic segmentation of cerebral T2 hyperintensities and T1 black holes in multiple sclerosis

BACKGROUND AND PURPOSE

Magnetic resonance imaging (MRI) is crucial for in vivo detection and characterization of white matter lesions (WML) in multiple sclerosis (MS). The most widely established MRI outcome measure is the volume of hyperintense lesions on T2-weighted images (T2L). Unfortunately, T2L are non-specific for the level of tissue destruction and show a weak relationship to clinical status. Interest in lesions that appear hypointense on T1-weighted images (T1L) ("black holes") has grown because T1L provide more specificity for axonal loss and a closer link to neurologic disability. The technical difficulty of T1L segmentation has led investigators to rely on time-consuming manual assessments prone to inter- and intra-rater variability. This study aims to develop an automatic T1L segmentation approach, adapted from a T2L segmentation algorithm.

MATERIALS AND METHODS

T1, T2, and fluid-attenuated inversion recovery (FLAIR) sequences were acquired from 40 MS subjects at 3 Tesla (3 T). T2L and T1L were manually segmented. A Method for Inter-Modal Segmentation Analysis (MIMoSA) was then employed.

RESULTS

Using cross-validation, MIMoSA proved to be robust for segmenting both T2L and T1L. For T2L, a Sørensen-Dice coefficient (DSC) of 0.66 and partial AUC (pAUC) up to 1% false positive rate of 0.70 were achieved. For T1L, 0.53 DSC and 0.64 pAUC were achieved. Manual and MIMoSA segmented volumes were correlated and resulted in 0.88 for T1L and 0.95 for T2L. The correlation between Expanded Disability Status Scale (EDSS) scores and manual versus automatic volumes were similar for T1L (0.32 manual vs. 0.34 MIMoSA), T2L (0.33 vs. 0.32), and the T1L/T2L ratio (0.33 vs 0.33).

CONCLUSIONS

Though originally designed to segment T2L, MIMoSA performs well for segmenting T1 black holes in patients with MS.

The Effect of Glatiramer Acetate on Retinal Nerve Fiber Layer Thickness in Patients with Relapsing-Remitting Multiple Sclerosis: A Longitudinal Optical Coherence Tomography Study

BACKGROUND

Optical coherence tomography (OCT) is a technique that allows for the assessment of retinal nerve fiber layer thickness (RNFLT) and total macular volume (TMV), which reflect neuroaxonal integrity within the retina. As such it has been used in multiple sclerosis (MS) to study neurodegeneration. Glatiramer acetate (GA) is a widely used treatment for MS, which is suggested to have a possible neuroprotective role.

OBJECTIVE

The aim of this study was to assess RFNLT and TMV changes in relapsing-remitting MS (RRMS) patients who started treatment with GA and were followed for a 24-month period.

METHODS

A cohort of 60 RRMS patients and 40 healthy controls (HCs) were imaged with OCT at baseline and follow-up. All subjects also underwent clinical and neurological examination. Measurements were compared between the RRMS patients and HCs as well as between optic neuritis (ON)-affected and ON-unaffected eyes.

RESULTS

At baseline, MS patients showed lower average RNFLT (p = 0.046) and TMV (p = 0.013) when compared with HCs. No significant differences in the evolution of OCT measures were detected over the follow-up between MS patients and HCs. MS patients with both affected and unaffected eyes showed significantly lower average RNFLT, temporal inferior RNFLT, and TMV at baseline, compared with HCs. No significant differences between ON-affected and ON-unaffected eyes in MS patients were detected over the follow-up, except for the nasal superior RNFLT (p = 0.019).

CONCLUSIONS

This study suggests a beneficial role of GA on retinal axonal degeneration in MS, and further confirms the utility of OCT to monitor the neuroprotective effect of disease-modifying treatment.

Preservation of neuronal function as measured by clinical and MRI endpoints in relapsing-remitting multiple sclerosis: how effective are current treatment strategies?

INTRODUCTION

Approved medications for relapsing-remitting multiple sclerosis have shown to be effective in terms of their anti-inflammatory potential. However, it is also crucial to evaluate what long-term effects a patient can expect from current MS drugs in terms of preventing neurodegeneration. Here we aim to provide an overview of the current treatment strategies in MS with a specific focus on potential neuroprotective effects. Areas covered: Randomized, double-blind and placebo or referral-drug controlled phase 2a/b and phase 3 trials were examined; non-blinded phase 4 studies (extension studies) were included to provide long-term data, if not otherwise available. Endpoints considered were expanded disability status scale, various neuropsychological tests, percent brain volume change and T1-hypointense lesions as well as multiple sclerosis functional composite, confirmed disease progression, and no evidence of disease activity. Expert commentary: Overall, neuroprotective functions of classical MS therapeutics are not sufficiently investigated, but available data show limited effects. Thus, further research and development in neuroprotection are warranted. When counselling patients, potential long-term beneficial effects should be presented more conservatively.

The clinical perspective: How to personalise treatment in MS and how may biomarkers including imaging contribute to this?

BACKGROUND

Multiple sclerosis (MS) is a highly heterogeneous disease, both in its course and in its response to treatments. Effective biomarkers may help predict disability progression and monitor patients' treatment responses.

OBJECTIVE

The aim of this review was to focus on how biomarkers may contribute to treatment individualisation in MS patients.

METHODS

This review reflects the content of presentations, polling results and discussions on the clinical perspective of MS during the first and second Pan-European MS Multi-stakeholder Colloquia in Brussels in May 2014 and 2015.

RESULTS

In clinical practice, magnetic resonance imaging (MRI) measures play a significant role in the diagnosis and follow-up of MS patients. Together with clinical markers, the rate of MRI-visible lesion accrual once a patient has started treatment may also help to predict subsequent treatment responsiveness. In addition, several molecular (immunological, genetic) biomarkers have been established that may play a role in predictive models of MS relapses and progression. To reach personalised treatment decisions, estimates of disability progression and likely treatment response should be carefully considered alongside the risk of serious adverse events, together with the patient's treatment expectations.

CONCLUSION

Although biomarkers may be very useful for individualised decision making in MS, many are still research tools and need to be validated before implementation in clinical practice.