Predictive value of gadolinium-enhanced magnetic resonance imaging for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis. Gadolinium MRI Meta-analysis Group

Prognostic relevance of MRI in early relapsing multiple sclerosis: ready to guide treatment decision making?

Magnetic resonance imaging (MRI) of the brain and spinal cord plays a crucial role in the diagnosis and monitoring of multiple sclerosis (MS). There is conclusive evidence that brain and spinal cord MRI findings in early disease stages also provide relevant insight into individual prognosis. This includes prediction of disease activity and disease progression, the accumulation of long-term disability and the conversion to secondary progressive MS. The extent to which these MRI findings should influence treatment decisions remains a subject of ongoing discussion. The aim of this review is to present and discuss the current knowledge and scientific evidence regarding the utility of MRI at early MS disease stages for prognostic classification of individual patients. In addition, we discuss the current evidence regarding the use of MRI in order to predict treatment response. Finally, we propose a potential approach as to how MRI data may be categorized and integrated into early clinical decision making.

Assessing treatment response to oral drugs for multiple sclerosis in real-world setting: a MAGNIMS Study

BACKGROUND

The assessment of treatment response is a crucial step for patients with relapsing-remitting multiple sclerosis on disease-modifying therapies (DMTs). We explored whether a scoring system developed within the MAGNIMS (MRI in Multiple Sclerosis) network to evaluate treatment response to injectable drugs can be adopted also to oral DMTs.

METHODS

A multicentre dataset of 1200 patients who started three oral DMTs (fingolimod, teriflunomide and dimethyl fumarate) was collected within the MAGNIMS network. Disease activity after the first year was classified by the 'MAGNIMS' score based on the combination of relapses (0-≥2) and/or new T2 lesions (<3 or ≥3) on brain MRI. We explored the association of this score with the following 3-year outcomes: (1) confirmed disability worsening (CDW); (2) treatment failure (TFL); (3) relapse count between years 1 and 3. The additional value of contrast-enhancing lesions (CELs) and lesion location was explored.

RESULTS

At 3 years, 160 patients experienced CDW: 12% of them scored '0' (reference), 18% scored '1' (HR=1.82, 95% CI 1.20 to 2.76, p=0.005) and 37% scored '2' (HR=2.74, 95% CI 1.41 to 5.36, p=0.003) at 1 year. The analysis of other outcomes provided similar findings. Considering the location of new T2 lesions (supratentorial vs infratentorial/spinal cord) and the presence of CELs improved the prediction of CDW and TFL, respectively, in patients with minimal MRI activity alone (one or two new T2 lesions).

CONCLUSIONS

Early relapses and substantial MRI activity in the first year of treatment are associated with worse short-term outcomes in patients treated with some of the oral DMTs.

A multicenter study of radiologically isolated syndrome in children and adolescents: Can we predict the course?

OBJECTIVES

To evaluate clinical characteristics, imaging features and etiological profile of Radiologically Isolated Syndrome (RIS) along with clinical and radiological follow-up.

METHODS

Demographic, clinical and radiological data of patients younger than 18 years fulfilling the criteria for RIS were retrospectively analyzed. RIS was defined by the detection of lesions meeting the revised 2010 McDonald Criteria for dissemination in space on magnetic resonance imaging (MRI) in the absence of any symptoms of demyelinating disease or an alternative cause for the MRI findings.

RESULTS

There were total 69 patients (38 girls, 31 boys). The median age at index MRI was 15.7 years, and median follow-up time was 28 months. The most common reason for neuroimaging was headache (60.9%). A first clinical event occurred with median 11 months in 14/69 (20%) of cases. Those with oligoclonal bands (OCB) in cerebrospinal fluid (CSF) and follow-up longer than 3 years were more likely to experience a clinical event (p<0.05): 25% of those with OCB manifested clinical symptoms within the first year and 33.3% within the first two years compared to 6.3% and 9.4%, respectively in those without OCB. Radiological evolution was not associated with any variables: age, sex, reason for neuroimaging, serum 25-hydroxyvitamin D level, elevated IgG index, OCB positivity, total number and localization of lesions, presence of gadolinium enhancement, achievement of 2005 criteria for DIS and duration of follow-up.

CONCLUSION

Children and adolescents with RIS and CSF OCB should be followed-up for at least 3 years in order to detect any clinical symptoms suggestive of a demyelinating event. Because disease-modifying treatments are not approved in RIS and no consensus report justifies their use especially in pediatric RIS, close follow-up of OCB-positive patients is needed for early recognition of any clinical event and timely initiation of specific treatment.

What an adult multiple sclerosis registry can tell us about pediatric onset multiple sclerosis?

BACKGROUND

Multiple Sclerosis (MS) is an immune-mediated, chronic disease of the central nervous system that affects mainly adults. However, it is increasingly recognized that MS may start in childhood resulting in a relentlessly progressive disability and cognitive impairment. Registries across the globe are reporting inconstant data about their Pediatric-Onset Multiple Sclerosis (POMS) patients. Moreover, newer lines of treatments are emerging and showing efficacy in controlling the MS disease regardless of the onset. Therefore, there is a requirement for more research into the clinical profile of POMS in different populations and ethnicities.

METHODS

This study was a cross-sectional study that included MS patients who visited the MS unit at Alexandria University from January 2019 to January 2021. We analyzed their epidemiological, clinical, radiological data, and cerebrospinal fluid (CSF) results from their updated records as well as follow-up interviews.

RESULTS

Annual Relapse Rate (ARR) was marginally less in POMS than AOMS (0.72 ± 0.57 vs 1.04 ± 0.78 relapse/year, P =.008). POMS patients had a bigger gap to their first relapse (40.0 ± 47.35 vs 22.71 ± 34.33 months, p= .066). The difference in relapse rate between the two groups was abolished after the exclusion of patients who had a gap of more than 5 years to their first relapse. AOMS patients were significantly more likely to start with a second-line disease-modifying treatment (DMT) than POMS patients (11.5% vs 31%, p= .04), whereas POMS patients were more likely to be escalated to the second line (34.6% vs 19.3%, p= .07). ARR had a positive and significant correlation with expanded disability status scale (EDSS) progression per year (rs(24)= .57 p=.003). A Mann-Whitney test indicated that POMS patients who had infratentorial involvement in the initial MRI brain had higher EDSS (3.08 ± 1.99) than POMS who did not (1.07 ± 0.79) U=24 P =.013. IgG index had a significant and positive correlation with annual EDSS progression rate rs (8) = 0.8 p=.001.

CONCLUSION

Early disease onset does not mean a higher relapse rate when including the full spectrum of POMS and longer follow-up duration. POMS patients relapsed more on the first-line DMT and escalation should be considered early. Infratentorial involvement in the initial magnetic resonance imaging (MRI) brain and high IgG index are potential predictors for aggressive disease course in POMS.

The added value of spinal cord lesions to disability accrual in multiple sclerosis

Spinal cord MRI is not routinely performed for multiple sclerosis (MS) monitoring. Here, we explored whether spinal cord MRI activity offers any added value over brain MRI activity for clinical outcomes prediction in MS. This is a retrospective, monocentric study including 830 MS patients who underwent longitudinal brain and spinal cord MRI [median follow-up 7 years (range: < 1-26)]. According to the presence (or absence) of MRI activity defined as at least one new T2 lesion and/or gadolinium (Gd) enhancing lesion, each scan was classified as: (i) brain MRI negative/spinal cord MRI negative; (ii) brain MRI positive/spinal cord MRI negative; (iii) brain MRI negative/spinal cord MRI positive; (iv) brain MRI positive/spinal cord MRI positive. The relationship between such patterns and clinical outcomes was explored by multivariable regression models. When compared with the presence of brain MRI activity alone: (i) Gd + lesions in the spine alone and both in the brain and in the spinal cord were associated with an increased risk of concomitant relapses (OR = 4.1, 95% CI 2.4-7.1, p < 0.001 and OR = 4.9, 95% CI 4.6-9.1, p < 0.001, respectively); (ii) new T2 lesions at both locations were associated with an increased risk of disability worsening (HR = 1.4, 95% CI = 1.0-2.1, p = 0.05). Beyond the presence of brain MRI activity, new spinal cord lesions are associated with increased risk of both relapses and disability worsening. In addition, 16.1% of patients presented asymptomatic, isolated spinal cord activity (Gd + lesions). Monitoring MS with spinal cord MRI may allow a more accurate risk stratification and treatment optimization.

Recommendations for the coordination of Neurology and Neuroradiology Departments in the management of patients with multiple sclerosis

INTRODUCTION

Magnetic resonance imaging (MRI) is widely used for the diagnosis and follow-up of patients with multiple sclerosis (MS). Coordination between neurology and neuroradiology departments is crucial for performing and interpreting radiological studies as efficiently and as accurately as possible. However, improvements can be made in the communication between these departments in many Spanish hospitals.

METHODS

A panel of 17 neurologists and neuroradiologists from 8 Spanish hospitals held in-person and online meetings to draft a series of good practice guidelines for the coordinated management of MS. The drafting process included 4 phases: 1) establishing the scope of the guidelines and the methodology of the study; 2) literature review on good practices or recommendations on the use of MRI in MS; 3) discussion and consensus between experts; and 4) validation of the contents.

RESULTS

The expert panel agreed a total of 9 recommendations for improving coordination between neurology and neuroradiology departments. The recommendations revolve around 4 main pillars: 1) standardising the process for requesting and scheduling MRI studies and reports; 2) designing common protocols for MRI studies; 3) establishing multidisciplinary committees and coordination meetings; and 4) creating formal communication channels between both departments.

CONCLUSIONS

These consensus recommendations are intended to optimise coordination between neurologists and neuroradiologists, with the ultimate goal of improving the diagnosis and follow-up of patients with MS.

AI-based detection of contrast-enhancing MRI lesions in patients with multiple sclerosis

BACKGROUND

Contrast-enhancing (CE) lesions are an important finding on brain magnetic resonance imaging (MRI) in patients with multiple sclerosis (MS) but can be missed easily. Automated solutions for reliable CE lesion detection are emerging; however, independent validation of artificial intelligence (AI) tools in the clinical routine is still rare.

METHODS

A three-dimensional convolutional neural network for CE lesion segmentation was trained externally on 1488 datasets of 934 MS patients from 81 scanners using concatenated information from FLAIR and T1-weighted post-contrast imaging. This externally trained model was tested on an independent dataset comprising 504 T1-weighted post-contrast and FLAIR image datasets of MS patients from clinical routine. Two neuroradiologists (R1, R2) labeled CE lesions for gold standard definition in the clinical test dataset. The algorithmic output was evaluated on both patient- and lesion-level.

RESULTS

On a patient-level, recall, specificity, precision, and accuracy of the AI tool to predict patients with CE lesions were 0.75, 0.99, 0.91, and 0.96. The agreement between the AI tool and both readers was within the range of inter-rater agreement (Cohen's kappa; AI vs. R1: 0.69; AI vs. R2: 0.76; R1 vs. R2: 0.76). On a lesion-level, false negative lesions were predominately found in infratentorial location, significantly smaller, and at lower contrast than true positive lesions (p < 0.05).

CONCLUSIONS

AI-based identification of CE lesions on brain MRI is feasible, approaching human reader performance in independent clinical data and might be of help as a second reader in the neuroradiological assessment of active inflammation in MS patients.

CRITICAL RELEVANCE STATEMENT

Al-based detection of contrast-enhancing multiple sclerosis lesions approaches human reader performance, but careful visual inspection is still needed, especially for infratentorial, small and low-contrast lesions.

Discontinuation of disease-modifying therapy in MS patients over 60 years old and its impact on relapse rate and disease progression

BACKGROUND / AIMS

The benefit of disease-modifying therapy (DMT) is unclear for older patients with multiple sclerosis (MS), namely those who have not experienced clinical disease activity for a prolonged time. We aimed to compare baseline differences and clinical outcomes between DMT discontinuers and continuers in a cohort of MS patients older than 60 years.

METHODS

Retrospective, observational study identifying MS patients aged over 60 years, stable on DMT> 24 months. Additional inclusion criteria were a previous diagnosis of relapsing MS and a minimum follow-up period of 24 months. Differences between groups (continuers/discontinuers) were assessed. For risk of relapse and of confirmed disability worsening at follow up, a time to outcome survival model was constructed using Cox proportional hazards regression, testing for possible risk predictors.

RESULTS

Thirty-five patients were included (68.6% female), with a mean age at diagnosis of 42.1 ( ± 9.5) years and a median EDSS score of 3 (IQR 2) at the age of 60 years (baseline). Thirteen patients discontinued DMT after baseline, in a mean follow-up time of 77.1 months ( ± 40.2). No differences were found between DMT continuers vs discontinuers. DMT discontinuation did not predict risk to relapse (HR 0.38, 95%CI 0.04-3.80, p = 0.408) or disability worsening at follow-up (HR 0.83, 95%CI 0.31-2.22, p = 0.712). MRI gadolinium-enhancing lesions and EDSS score > 3 at baseline were found to be independent predictors of risk to relapse and disability worsening at follow-up, respectively.

CONCLUSION

DMT discontinuation did not seem to influence clinical outcome, equating with the perceived limited effect of continued immunomodulation on older stable and/or progressive patients.

Single-timepoint low-dimensional characterization and classification of acute versus chronic multiple sclerosis lesions using machine learning

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease characterized by the appearance of focal lesions across the central nervous system. The discrimination of acute from chronic MS lesions may yield novel biomarkers of inflammatory disease activity which may support patient management in the clinical setting and provide endpoints in clinical trials. On a single timepoint and in the absence of a prior reference scan, existing methods for acute lesion detection rely on the segmentation of hyperintense foci on post-gadolinium T1-weighted magnetic resonance imaging (MRI), which may underestimate recent acute lesion activity. In this paper, we aim to improve the sensitivity of acute MS lesion detection in the single-timepoint setting, by developing a novel machine learning approach for the automatic detection of acute MS lesions, using single-timepoint conventional non-contrast T1- and T2-weighted brain MRI. The MRI input data are supplemented via the use of a convolutional neural network generating "lesion-free" reconstructions from original "lesion-present" scans using image inpainting. A multi-objective statistical ranking module evaluates the relevance of textural radiomic features from the core and periphery of lesion sites, compared within "lesion-free" versus "lesion-present" image pairs. Then, an ensemble classifier is optimized through a recursive loop seeking consensus both in the feature space (via a greedy feature-pruning approach) and in the classifier space (via model selection repeated after each pruning operation). This leads to the identification of a compact textural signature characterizing lesion phenotype. On the patch-level task of acute versus chronic MS lesion classification, our method achieves a balanced accuracy in the range of 74.3-74.6% on fully external validation cohorts.

Synthetic Post-Contrast Imaging through Artificial Intelligence: Clinical Applications of Virtual and Augmented Contrast Media

Contrast media are widely diffused in biomedical imaging, due to their relevance in the diagnosis of numerous disorders. However, the risk of adverse reactions, the concern of potential damage to sensitive organs, and the recently described brain deposition of gadolinium salts, limit the use of contrast media in clinical practice. In recent years, the application of artificial intelligence (AI) techniques to biomedical imaging has led to the development of 'virtual' and 'augmented' contrasts. The idea behind these applications is to generate synthetic post-contrast images through AI computational modeling starting from the information available on other images acquired during the same scan. In these AI models, non-contrast images (virtual contrast) or low-dose post-contrast images (augmented contrast) are used as input data to generate synthetic post-contrast images, which are often undistinguishable from the native ones. In this review, we discuss the most recent advances of AI applications to biomedical imaging relative to synthetic contrast media.

Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning

Disability progression in multiple sclerosis remains resistant to treatment. The absence of a suitable biomarker to allow for phase 2 clinical trials presents a high barrier for drug development. We propose to enable short proof-of-concept trials by increasing statistical power using a deep-learning predictive enrichment strategy. Specifically, a multi-headed multilayer perceptron is used to estimate the conditional average treatment effect (CATE) using baseline clinical and imaging features, and patients predicted to be most responsive are preferentially randomized into a trial. Leveraging data from six randomized clinical trials (n = 3,830), we first pre-trained the model on the subset of relapsing-remitting MS patients (n = 2,520), then fine-tuned it on a subset of primary progressive MS (PPMS) patients (n = 695). In a separate held-out test set of PPMS patients randomized to anti-CD20 antibodies or placebo (n = 297), the average treatment effect was larger for the 50% (HR, 0.492; 95% CI, 0.266-0.912; p = 0.0218) and 30% (HR, 0.361; 95% CI, 0.165-0.79; p = 0.008) predicted to be most responsive, compared to 0.743 (95% CI, 0.482-1.15; p = 0.179) for the entire group. The same model could also identify responders to laquinimod in another held-out test set of PPMS patients (n = 318). Finally, we show that using this model for predictive enrichment results in important increases in power.

There are limited predictive biomarkers for drug treatment responses in individuals with multiple sclerosis. Here using existing clinical trials data, the authors propose a deep-learning predictive enrichment strategy to identify which participants are most likely to respond to a treatment.

Microglia Regulate Blood-Brain Barrier Integrity via MiR-126a-5p/MMP9 Axis during Inflammatory Demyelination

Blood-brain barrier (BBB) impairment is an early prevalent feature of multiple sclerosis (MS), and remains vital for MS progression. Microglial activation precedes BBB disruption and cellular infiltrates in the brain of MS patients. However, little is known about the function of microglia in BBB impairment. Here, microglia acts as an important modulator of BBB integrity in inflammatory demyelination. Microglial depletion profoundly ameliorates BBB impairment in experimental autoimmune encephalomyelitis (EAE). Specifically, miR-126a-5p in microglia is positively correlated with BBB integrity in four types of MS plaques. Mechanistically, microglial deletion of miR-126a-5p exacerbates BBB leakage and EAE severity. The protective effect of miR-126a-5p is mimicked and restored by specific inhibition of MMP9 in microglia. Importantly, Auranofin, an FDA-approved drug, is identified to protect BBB integrity and mitigate EAE progression via a microglial miR-126a-5p dependent mechanism. Taken together, microglia can be manipulated to protect BBB integrity and ameliorate inflammatory demyelination. Targeting microglia to regulate BBB permeability merits consideration in therapeutic interventions in MS.

Predictors of Disease Activity and Worsening in Relapsing-Remitting Multiple Sclerosis

Background and Objectives:

Disease activity in multiple sclerosis (MS) is highly variable, and there are limited prospective studies on predictors of disease outcomes. The goal of the study is to identify and assess patient characteristics in MS that predict disease activity and worsening.

Methods:

The study population consisted of a prospective cohort of 1,008 participants with relapsing-remitting (RR) onset MS enrolled in the CombiRx trial. Cox regression analysis was used to determine hazard ratio (HR) associations between baseline (BL) demographics, clinical history, MRI metrics, and treatment; with outcomes of time to first new disease activity over up to 7-years of follow-up including relapse, MRI activity, and disease worsening.

Results:

1,008 participants were randomized, with 959 eligible for assessment of disease activity and worsening on follow-up. In the multivariable models, risk of relapse was higher in participants younger than 38 at BL vs. older (HR range 1.36-1.43), with presence of Gd+ lesions at baseline (HR 1.38, [95%CI: 1.14, 1.67]), and with BL EDSS ≥3.5 vs. <3.5 (HR range 1.63-1.67). Risk of new MRI activity was higher in younger participants (HR range 1.58-1.84), with higher preexisting lesion counts greater than the median lesion count with ≥71 T2 hyperintense lesions vs. <71 (HR 1.50, [95%CI 1.27, 1.77]), with presence of BL Gd+ lesions (HR 1.75, [95%CI: 1.49, 2.06]), and higher baseline T2 lesion volume (HR 1.02 for every unit increase in baseline volume, [95% CI 1.01, 1.03]). Risk of new MRI activity was lower in those receiving combination therapy compared to either GA (HR range 0.67-0.68) or IFN (HR range 0.68-0.70). Risk of disease worsening was higher for those with higher T2 volume (HR for 1 unit increase in volume 1.01, 95% CI 1.004, 1.03) and BL EDSS <2 (HR range 2.79-2.96). There were no associations between sex, race, and disease duration on relapse, MRI activity, or disease worsening in multivariable analysis.

Conclusion:

Prospective data from a large clinical trial cohort shows that younger MS patients with high baseline relapses and MRI lesion burden have the highest risk of subsequent disease activity.

CombiRx was registered at ClinicalTrials.gov (NCT00211887) on September 21, 2005. Study enrollment began in January 2005.

MRI predictors for the conversion from contrast-enhancing to iron rim multiple sclerosis lesions

BACKGROUND

In multiple sclerosis (MS), iron rim lesions (IRLs) are characterized by progressive tissue matrix damage. Therefore, early identification could represent an interesting target for therapeutic intervention to minimize evolving tissue damage. The aim of this study was to identify magnetic resonance imaging (MRI) parameters predicting the conversion from contrast-enhancing to IRLs.

METHODS

We retrospective identified MS patients scanned on the same 3 T MRI system presenting at least one supratentorial contrast-enhancing lesion (CEL) and a second MRI including susceptibility-weighted images after at least 3 months. On baseline MRI, pattern of contrast-enhancement was categorized as "nodular" or "ring-like", apparent diffusion coefficient (ADC) maps were assessed for the presence of a peripheral hypointense rim. Lesion localization, quantitative volumes (ADC, lesion volume) and the presence of a central vein were assessed.

RESULTS

Eighty-nine acute contrast-enhancing lesions in 54 MS patients were included. On follow-up, 16/89 (18%) initially CELs converted into IRLs. CELs that converted into IRLs were larger and demonstrated significantly more often a ring-like contrast-enhancement pattern and a peripheral hypointense rim on ADC maps. Logistic regression model including the covariables pattern of contrast-enhancement and presence of a hypointense rim on ADC maps showed the best predictive performance (area under the curve = 0.932).

DISCUSSION

The combination of a ring-like contrast-enhancement pattern and a peripheral hypointense rim on ADC maps has the ability to predict the evolution from acute to IRLs. This could be of prognostic value and become a target for early therapeutic intervention to minimize the associated tissue damage.

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.

Long-term dynamics of multiple sclerosis iron rim lesions

BACKGROUND

Several studies have pointed out that seemingly chronic multiple sclerosis (MS) lesions may also be in inflammatory states. In pathological studies, up to 40% of chronic MS lesions are characterized as "chronic active" or "smoldering" lesions that are characterized by a rim of iron-laden proinflammatory macrophages/microglial cells at the lesion edge with low-grade continuous myelin breakdown. In vivo, these lesions can be visualized as "iron rim lesions" (IRLs) on susceptibility-weighted imaging (SWI). The aim of this study was to investigate the long-term dynamics of IRLs in vivo for a more detailed evolution of dynamic lesion volume changes occurring over time.

METHODS

We retrospectively identified patients with MS who were followed for at least 36 months (up to 72 months) and underwent at least an annual MRI on the same 3 Tsystem. Using Voxel-Guided Morphometry (VGM) we investigated regional volume changes within lesions and correlated these findings with SWI for the presence of a characteristic hypointense lesion rim. To estimate tissue damage, apparent diffusion coefficient (ADC) values for every lesion at baseline and follow-up MRIs were determined.

RESULTS

Forty-three patients were included in the study. Overall, we identified 302 supratentorial non-confluent MS lesions (52 persistent IRLs, nine transient IRLs, 228 non-IRLs and 13 acute contrast-enhancing lesions). During follow-up, persistent IRLs significantly enlarged, whereas non-IRLs showed a tendency to shrink. At baseline MRI, ADC values were significantly higher in persistent IRLs (1.23 × 10^-3 mm/s²) compared to non-IRLs (1.01 × 10^-3 mm/s²; p < 0.001), but not compared to transient IRLs (1.06 × 10^-3 mm/s²; p = 0.15) and contrast-enhancing lesions (1.15 × 10^-3 mm/s²; p = 1.0). During follow-up, ADC values significantly increased more often in persistent IRLs compared to all other lesion types (p < 0.0001).

CONCLUSIONS

Our long-term data demonstrate that persistent IRLs enlarge during disease duration, whereas non-IRLs show a tendency to shrink. Furthermore, IRLs are associated with sustained tissue damage, supporting the notion that IRLs could represent a new imaging biomarker in MS.

Age-related changes in multiple sclerosis and experimental autoimmune encephalomyelitis

A better understanding of the pathological mechanisms that drive neurodegeneration in people living with multiple sclerosis (MS) is needed to design effective therapies to treat and/or prevent disease progression. We propose that CNS-intrinsic inflammation and re-modelling of the sub-arachnoid space of the leptomeninges sets the stage for neurodegeneration from the earliest stages of MS. While neurodegenerative processes are clinically silent early in disease, ageing results in neurodegenerative changes that become clinically manifest as progressive disability. Here we review pathological correlates of MS disease progression, highlight emerging mouse models that mimic key progressive changes in MS, and provide new perspectives on therapeutic approaches to protect against MS-associated neurodegeneration.

Automatic segmentation of gadolinium-enhancing lesions in multiple sclerosis using deep learning from clinical MRI

Gadolinium-enhancing lesions reflect active disease and are critical for in-patient monitoring in multiple sclerosis (MS). In this work, we have developed the first fully automated method to segment and count the gadolinium-enhancing lesions from routine clinical MRI of MS patients. The proposed method first segments the potential lesions using 2D-UNet from multi-channel scans (T1 post-contrast, T1 pre-contrast, FLAIR, T2, and proton-density) and classifies the lesions using a random forest classifier. The algorithm was trained and validated on 600 MRIs with manual segmentation. We compared the effect of loss functions (Dice, cross entropy, and bootstrapping cross entropy) and number of input contrasts. We compared the lesion counts with those by radiologists using 2,846 images. Dice, lesion-wise sensitivity, and false discovery rate with full 5 contrasts were 0.698, 0.844, and 0.307, which improved to 0.767, 0.969, and 0.00 in large lesions (>100 voxels). The model using bootstrapping loss function provided a statistically significant increase of 7.1% in sensitivity and of 2.3% in Dice compared with the model using cross entropy loss. T1 post/pre-contrast and FLAIR were the most important contrasts. For large lesions, the 2D-UNet model trained using T1 pre-contrast, FLAIR, T2, PD had a lesion-wise sensitivity of 0.688 and false discovery rate 0.083, even without T1 post-contrast. For counting lesions in 2846 routine MRI images, the model with 2D-UNet and random forest, which was trained with bootstrapping cross entropy, achieved accuracy of 87.7% using T1 pre-contrast, T1 post-contrast, and FLAIR when lesion counts were categorized as 0, 1, and 2 or more. The model performs well in routine non-standardized MRI datasets, allows large-scale analysis of clinical datasets, and may have clinical applications.

Outcome measures assisting treatment optimization in multiple sclerosis

Objective

To review instruments used to assess disease stability or progression in persons with multiple sclerosis (pwMS) that can guide clinicians in optimizing therapy.

Methods

A non-systematic review of scientific literature was undertaken to explore modalities of monitoring symptoms and the disease evolution of MS.

Results

Multiple outcome measures, or tools, have been developed for use in MS research as well as for the clinical management of pwMS. Beginning with the Expanded Disability Status Scale, introduced in 1983, clinicians and researchers have developed monitoring modalities to assess all aspects of MS and the neurological impairment it causes.

Conclusions

Much progress has been made in recent decades for the management of MS and for the evaluation of disease progression. New technology, such as wearable sensors, will provide new opportunities to better understand changes in function, dexterity, and cognition. Essential work over the decades since EDSS was introduced continues to improve our ability to treat this debilitating disease.

Predicting conversion to multiple sclerosis in patients with radiologically isolated syndrome: a retrospective study

Aims

To retrospectively analyse the Bernese radiologically isolated syndrome (RIS) cohort with the goal of developing a prediction score for conversion to multiple sclerosis (MS).

Methods

A total of 31 patients with RIS were identified by screening medical records of neurological patients seen at the University Hospital of Bern between 2004 and 2017 for the diagnoses 'radiologically isolated syndrome' and 'RIS' adhering to 2009 Okuda recommendations. We analysed clinical, paraclinical and magnetic resonance imaging data during a maximum follow-up period of 3 years and identified significant predictors of conversion to MS.

Results

Data were available for 31 patients meeting 2009 Okuda RIS criteria. During the 3 years of follow up, 5/31 RIS patients converted to relapsing-remitting (RR) MS. In our univariate analysis, gadolinium (Gd) enhancement, brainstem and cerebellar hemisphere lesions, immune cell count and albumin concentration in cerebrospinal fluid (CSF), and anti-nuclear antibody (ANA) positivity in serum were identified as significant predictors of conversion to MS. Integrating these factors into our 'RIS-MS prediction score' enabled us to calculate a cut-off for prediction of conversion to MS within 3 years with high specificity [1.0, 95% confidence interval (CI) 0.84-1.00) and acceptable sensitivity (0.6, 95% CI 0.17-0.93)].

Conclusion

Our RIS-MS prediction score, if validated in an independent cohort, integrating radiological (Gd enhancement, brainstem and cerebellar hemisphere lesions) and paraclinical factors (ANA in serum, cell count and albumin in CSF) could be a useful prognostic tool for early recognition of RIS patients with a high risk of clinical progression to MS.

Inversion Recovery Ultrashort TE MR Imaging of Myelin is Significantly Correlated with Disability in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE

MR imaging has been widely used for the noninvasive evaluation of MS. Although clinical MR imaging sequences are highly effective in showing focal macroscopic tissue abnormalities in the brains of patients with MS, they are not specific to myelin and correlate poorly with disability. We investigated direct imaging of myelin using a 2D adiabatic inversion recovery ultrashort TE sequence to determine its value in assessing disability in MS.

MATERIALS AND METHODS

The 2D inversion recovery ultrashort TE sequence was evaluated in 14 healthy volunteers and 31 patients with MS. MPRAGE and T2-FLAIR images were acquired for comparison. Advanced Normalization Tools were used to correlate inversion recovery ultrashort TE, MPRAGE, and T2-FLAIR images with disability assessed by the Expanded Disability Status Scale.

RESULTS

Weak correlations were observed between normal-appearing white matter volume (R = -0.03, P = .88), lesion load (R = 0.22, P = .24), and age (R = 0.14, P = .44), and disability. The MPRAGE signal in normal-appearing white matter showed a weak correlation with age (R = -0.10, P = .49) and disability (R = -0.19, P = .31). The T2-FLAIR signal in normal-appearing white matter showed a weak correlation with age (R = 0.01, P = .93) and disability (R = 0.13, P = .49). The inversion recovery ultrashort TE signal was significantly negatively correlated with age (R = -0.38, P = .009) and disability (R = -0.44; P = .01).

CONCLUSIONS

Direct imaging of myelin correlates with disability in patients with MS better than indirect imaging of long-T2 water in WM using conventional clinical sequences.

Sunlight exposure exerts immunomodulatory effects to reduce multiple sclerosis severity

Multiple sclerosis (MS) disease risk is associated with reduced sun-exposure. This study assessed the relationship between measures of sun exposure (vitamin D [vitD], latitude) and MS severity in the setting of two multicenter cohort studies (n _NationMS = 946, n _BIONAT = 990). Additionally, effect-modification by medication and photosensitivity-associated MC1R variants was assessed. High serum vitD was associated with a reduced MS severity score (MSSS), reduced risk for relapses, and lower disability accumulation over time. Low latitude was associated with higher vitD, lower MSSS, fewer gadolinium-enhancing lesions, and lower disability accumulation. The association of latitude with disability was lacking in IFN-β-treated patients. In carriers of MC1R:rs1805008(T), who reported increased sensitivity toward sunlight, lower latitude was associated with higher MRI activity, whereas for noncarriers there was less MRI activity at lower latitudes. In a further exploratory approach, the effect of ultraviolet (UV)-phototherapy on the transcriptome of immune cells of MS patients was assessed using samples from an earlier study. Phototherapy induced a vitD and type I IFN signature that was most apparent in monocytes but that could also be detected in B and T cells. In summary, our study suggests beneficial effects of sun exposure on established MS, as demonstrated by a correlative network between the three factors: Latitude, vitD, and disease severity. However, sun exposure might be detrimental for photosensitive patients. Furthermore, a direct induction of type I IFNs through sun exposure could be another mechanism of UV-mediated immune-modulation in MS.

Positivity of oligoclonal bands in the cerebrospinal fluid predisposed to metabolic changes and rearrangement of inhibitory/excitatory neurotransmitters in subcortical brain structures in multiple sclerosis

BACKGROUND

The latest diagnostic criteria for multiple sclerosis (MS) have revitalized the role of oligoclonal bands synthesis in the cerebrospinal fluid (CSF-OCB). This study identifies predictors of CSF-OCB-positivity among in vivo metabolic markers in the subcortical gray/white matter in MS patients after their first episode (CIS) and in patients with relapsing-remitting course (RRMS).

METHODS

The study enrolled 13 CIS and 23 RRMS patients. Metabolism was evaluated using Mescher-Garwood-edited proton-magnetic resonance spectroscopy on a 3T MR scanner. In addition to N-acetyl-aspartate (tNAA), myoinositol (mIns), and choline- and creatine compounds (tCho, tCr) were also evaluated γ-aminobutyric acid (GABA) and glutamate-glutamine (Glx) ratios.

RESULTS

CSF-OCB-positivity was found in 76.9% of CIS and 78.2% of RRMS patients. GABA and Glx ratios in putamen and corpus callosum strongly determined CSF-OCB-positive CIS patients. Other essential predictors of CSF-OCB-positive CIS were mIns and Glx ratios in the putamen, and tCho/tNAA in the corpus callosum. In RRMS, GABA ratios in the right thalamus and Glx ratios in the left hippocampus strongly predicted CSF-OCB-positive patients. tCho/tNAA and tNAA/tCr in the left hippocampus were also identified as essential predictors of CSF-OCB-positive RRMS patients.

CONCLUSION

This is the first in vivo evidence of GABA-Glx rearrangement in CSF-OCB-positive patients since its early stages of MS.

Deep learning segmentation of gadolinium-enhancing lesions in multiple sclerosis

OBJECTIVE

The aim of this study is to assess the performance of deep learning convolutional neural networks (CNNs) in segmenting gadolinium-enhancing lesions using a large cohort of multiple sclerosis (MS) patients.

METHODS

A three-dimensional (3D) CNN model was trained for segmentation of gadolinium-enhancing lesions using multispectral magnetic resonance imaging data (MRI) from 1006 relapsing-remitting MS patients. The network performance was evaluated for three combinations of multispectral MRI used as input: (U5) fluid-attenuated inversion recovery (FLAIR), T2-weighted, proton density-weighted, and pre- and post-contrast T1-weighted images; (U2) pre- and post-contrast T1-weighted images; and (U1) only post-contrast T1-weighted images. Segmentation performance was evaluated using the Dice similarity coefficient (DSC) and lesion-wise true-positive (TPR) and false-positive (FPR) rates. Performance was also evaluated as a function of enhancing lesion volume.

RESULTS

The DSC/TPR/FPR values averaged over all the enhancing lesion sizes were 0.77/0.90/0.23 using the U5 model. These values for the largest enhancement volumes (>500 mm3) were 0.81/0.97/0.04. For U2, the average DSC/TPR/FPR values were 0.72/0.86/0.31. Comparable performance was observed with U1. For all types of input, the network performance degraded with decreased enhancement size.

CONCLUSION

Excellent segmentation of enhancing lesions was observed for enhancement volume ⩾70 mm3. The best performance was achieved when the input included all five multispectral image sets.

Quantitative MRI texture analysis in chronic active multiple sclerosis lesions

OBJECTIVE

Recently, there has been an increasing interest in "chronic enlarging" or "chronic active" multiple sclerosis (MS) lesions that are associated with clinical disability. However, investigation of dynamic lesion volume changes requires longitudinal MRI data from two or more time points. The aim of this study was to investigate the application of texture analysis (TA) on baseline T1-weighted 3D magnetization-prepared rapid acquisition gradient-echo (MPRAGE) images to differentiate chronic active from chronic stable MS lesions.

MATERIAL AND METHODS

To identify chronic active lesions as compared to non-enhancing stable lesions, two MPRAGE datasets acquired on a 3 T MRI at baseline and after 12 months follow-up were applied to the Voxel-Guided Morphometry (VGM) algorithm. TA was performed on the baseline MPRAGE images, 36 texture features were extracted for each lesion.

RESULTS

Overall, 374 chronic MS lesions (155 chronic active and 219 chronic stable lesions) from 60 MS patients were included in the final analysis. Multiple texture features including "DISCRETIZED_HISTO_Energy", "GLCM_Energy", "GLCM_Contrast" and "GLCM_Dissimilarity" were significantly higher in chronic active as compared to chronic stable lesions. Partial least squares regression yielded an area under the curve of 0.7 to differentiate both lesion types.

CONCLUSION

Our results suggest that multiple texture features extracted from MPRAGE images indicate higher intralesional heterogeneity, however they demonstrate only a fair accuracy to differentiate chronic active from chronic stable MS lesions.

Recommendations for the coordination of Neurology and Neuroradiology Departments in the management of patients with multiple sclerosis

INTRODUCTION

Magnetic resonance imaging (MRI) is widely used for the diagnosis and follow-up of patients with multiple sclerosis (MS). Coordination between Neurology and Neuroradiology departments is crucial for performing and interpreting radiological studies as efficiently and as accurately as possible. However, improvements can be made in the communication between these departments in many Spanish hospitals.

METHODS

A panel of 17 neurologists and neuroradiologists from 8 Spanish hospitals held in-person and online meetings to draft a series of good practice guidelines for the coordinated management of MS. The drafting process included 4 phases: 1) establishing the scope of the guidelines and the methodology of the study; 2) literature review on good practices or recommendations on the use of MRI in MS; 3) discussion and consensus between experts; and 4) validation of the contents.

RESULTS

The expert panel agreed a total of 9 recommendations for improving coordination between neurology and neuroradiology departments. The recommendations revolve around 4 main pillars: 1) standardising the process for requesting and scheduling MRI studies and reports; 2) designing common protocols for MRI studies; 3) establishing multidisciplinary committees and coordination meetings; and 4) creating formal communication channels between both departments.

CONCLUSIONS

These consensus recommendations are intended to optimise coordination between neurologists and neuroradiologists, with the ultimate goal of improving the diagnosis and follow-up of patients with MS.

Leveraging electronic health records data to predict multiple sclerosis disease activity

Objective

No relapse risk prediction tool is currently available to guide treatment selection for multiple sclerosis (MS). Leveraging electronic health record (EHR) data readily available at the point of care, we developed a clinical tool for predicting MS relapse risk.

Methods

Using data from a clinic‐based research registry and linked EHR system between 2006 and 2016, we developed models predicting relapse events from the registry in a training set (n = 1435) and tested the model performance in an independent validation set of MS patients (n = 186). This iterative process identified prior 1‐year relapse history as a key predictor of future relapse but ascertaining relapse history through the labor‐intensive chart review is impractical. We pursued two‐stage algorithm development: (1) L₁‐regularized logistic regression (LASSO) to phenotype past 1‐year relapse status from contemporaneous EHR data, (2) LASSO to predict future 1‐year relapse risk using imputed prior 1‐year relapse status and other algorithm‐selected features.

Results

The final model, comprising age, disease duration, and imputed prior 1‐year relapse history, achieved a predictive AUC and F score of 0.707 and 0.307, respectively. The performance was significantly better than the baseline model (age, sex, race/ethnicity, and disease duration) and noninferior to a model containing actual prior 1‐year relapse history. The predicted risk probability declined with disease duration and age.

Conclusion

Our novel machine‐learning algorithm predicts 1‐year MS relapse with accuracy comparable to other clinical prediction tools and has applicability at the point of care. This EHR‐based two‐stage approach of outcome prediction may have application to neurological disease beyond MS.

Macular Ganglion Cell and Inner Plexiform Layer Thickness Is More Strongly Associated With Visual Function in Multiple Sclerosis Than Bruch Membrane Opening-Minimum Rim Width or Peripapillary Retinal Nerve Fiber Layer Thicknesses

BACKGROUND

Optical coherence tomography (OCT) measurements of ganglion cell + inner plexiform layer (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) thicknesses are associated with visual function (VF) and disability in multiple sclerosis (MS). However, the value of measuring Bruch membrane opening-minimum rim width (BMO-MRW) thickness in MS remains unclear.

METHODS

Sixty-eight patients with MS and 22 healthy controls (HCs) underwent spectral domain OCT, 100%-contrast visual acuity (VA), 2.5%- and 1.25%-contrast letter acuity (LA), and Expanded Disability Status Scale (EDSS) testing. Mixed-effects linear regression models, accounting for within-subject, intereye correlations, were used to assess relationships.

RESULTS

The MS cohort exhibited significantly lower BMO-MRW (P = 0.01), pRNFL at 3.7-, 4.1-, and 4.7-mm diameters surrounding the optic disc (P < 0.001 for all), and GCIPL (P < 0.001) thicknesses than HCs. BMO-MRW thickness was associated with 100%-VA (P < 0.001, R = 0.08), 2.5%-LA (P < 0.001; R = 0.13), and 1.25%-LA (P = 0.002; R = 0.11). All measured pRNFL thicknesses were associated with high- and low-contrast VF (all: P < 0.001). GCIPL thickness was more strongly associated with 100%-VA (P < 0.001; R = 0.23), 2.5%-LA (P < 0.001; R = 0.27), and 1.25%-LA (P < 0.001; R = 0.21) than the other OCT measures assessed. All OCT measures were significantly, but weakly, associated with EDSS scores.

CONCLUSIONS

BMO-MRW and pRNFL thicknesses are reduced and associated with VF and disability in MS, but GCIPL thickness is a stronger marker of visual impairment. Our findings corroborate the utility of OCT in providing valuable information regarding the MS disease process.

Systematic review of prediction models in relapsing remitting multiple sclerosis

The natural history of relapsing remitting multiple sclerosis (RRMS) is variable and prediction of individual prognosis challenging. The inability to reliably predict prognosis at diagnosis has important implications for informed decision making especially in relation to disease modifying therapies. We conducted a systematic review in order to collate, describe and assess the methodological quality of published prediction models in RRMS. We searched Medline, Embase and Web of Science. Two reviewers independently screened abstracts and full text for eligibility and assessed risk of bias. Studies reporting development or validation of prediction models for RRMS in adults were included. Data collection was guided by the checklist for critical appraisal and data extraction for systematic reviews (CHARMS) and applicability and methodological quality assessment by the prediction model risk of bias assessment tool (PROBAST). 30 studies were included in the review. Applicability was assessed as high risk of concern in 27 studies. Risk of bias was assessed as high for all studies. The single most frequently included predictor was baseline EDSS (n = 11). T2 Lesion volume or number and brain atrophy were each retained in seven studies. Five studies included external validation and none included impact analysis. Although a number of prediction models for RRMS have been reported, most are at high risk of bias and lack external validation and impact analysis, restricting their application to routine clinical practice.

Early clinical markers of aggressive multiple sclerosis

Patients with the ‘aggressive’ form of multiple sclerosis accrue disability at an accelerated rate, typically reaching Expanded Disability Status Score (EDSS) ≥ 6 within 10 years of symptom onset. Several clinicodemographic factors have been associated with aggressive multiple sclerosis, but less research has focused on clinical markers that are present in the first year of disease. The development of early predictive models of aggressive multiple sclerosis is essential to optimize treatment in this multiple sclerosis subtype. We evaluated whether patients who will develop aggressive multiple sclerosis can be identified based on early clinical markers. We then replicated this analysis in an independent cohort. Patient data were obtained from the MSBase observational study. Inclusion criteria were (i) first recorded disability score (EDSS) within 12 months of symptom onset; (ii) at least two recorded EDSS scores; and (iii) at least 10 years of observation time, based on time of last recorded EDSS score. Patients were classified as having ‘aggressive multiple sclerosis’ if all of the following criteria were met: (i) EDSS ≥ 6 reached within 10 years of symptom onset; (ii) EDSS ≥ 6 confirmed and sustained over ≥6 months; and (iii) EDSS ≥ 6 sustained until the end of follow-up. Clinical predictors included patient variables (sex, age at onset, baseline EDSS, disease duration at first visit) and recorded relapses in the first 12 months since disease onset (count, pyramidal signs, bowel-bladder symptoms, cerebellar signs, incomplete relapse recovery, steroid administration, hospitalization). Predictors were evaluated using Bayesian model averaging. Independent validation was performed using data from the Swedish Multiple Sclerosis Registry. Of the 2403 patients identified, 145 were classified as having aggressive multiple sclerosis (6%). Bayesian model averaging identified three statistical predictors: age &gt; 35 at symptom onset, EDSS ≥ 3 in the first year, and the presence of pyramidal signs in the first year. This model significantly predicted aggressive multiple sclerosis [area under the curve (AUC) = 0.80, 95% confidence intervals (CIs): 0.75, 0.84, positive predictive value = 0.15, negative predictive value = 0.98]. The presence of all three signs was strongly predictive, with 32% of such patients meeting aggressive disease criteria. The absence of all three signs was associated with a 1.4% risk. Of the 556 eligible patients in the Swedish Multiple Sclerosis Registry cohort, 34 (6%) met criteria for aggressive multiple sclerosis. The combination of all three signs was also predictive in this cohort (AUC = 0.75, 95% CIs: 0.66, 0.84, positive predictive value = 0.15, negative predictive value = 0.97). Taken together, these findings suggest that older age at symptom onset, greater disability during the first year, and pyramidal signs in the first year are early indicators of aggressive multiple sclerosis.

Reaching an evidence-based prognosis for personalized treatment of multiple sclerosis

Personalized treatment is ideal for multiple sclerosis (MS) owing to the heterogeneity of clinical features, but current knowledge gaps, including validation of biomarkers and treatment algorithms, limit practical implementation. The contemporary approach to personalized MS therapy depends on evidence-based prognostication, an initial treatment choice and evaluation of early treatment responses to identify the need to switch therapy. Prognostication is directed by baseline clinical, environmental and demographic factors, MRI measures and biomarkers that correlate with long-term disability measures. The initial treatment choice should be a shared decision between the patient and physician. In addition to prognosis, this choice must account for patient-related factors, including comorbidities, pregnancy planning, preferences of the patients and their comfort with risk, and drug-related factors, including safety, cost and implications for treatment sequencing. Treatment response has traditionally been assessed on the basis of relapse rate, MRI lesions and disability progression. Larger longitudinal data sets have enabled development of composite outcome measures and more stringent standards for disease control. Biomarkers, including neurofilament light chain, have potential as early surrogate markers of prognosis and treatment response but require further validation. Overall, attainment of personalized treatment for MS is complex but will be refined as new data become available.

Efficacy and Safety of Oral Therapies for Relapsing-Remitting Multiple Sclerosis

Disease-modifying therapies have now become standard treatment for multiple sclerosis. These include five oral therapies for relapsing-remitting multiple sclerosis, namely fingolimod, dimethyl fumarate, teriflunomide, cladribine, and siponimod, although there is some discrepancy on the relative efficacy and safety of these agents. To gain further insight on these oral agents in relapsing-remitting multiple sclerosis, we performed a narrative review of fingolimod, dimethyl fumarate, teriflunomide, cladribine, and siponimod. We limited the analysis to randomized clinical studies in which a comparator was used (i.e., placebo or other disease-modifying therapy). As relapsing-remitting multiple sclerosis is a chronic disease and treatment is lifelong, long-term outcomes were an additional focus. A total of 37 studies met inclusion criteria: 15 for fingolimod, 8 for dimethyl fumarate, 7 for teriflunomide, 4 for cladribine, and 3 for siponimod. All drugs showed some functional and magnetic resonance imaging benefit in nearly all clinical studies. The reduction in annual relapse rate was similar for fingolimod, dimethyl fumarate, and cladribine, and somewhat greater than for teriflunomide; there is limited information on the annual relapse rate for siponimod. For all drugs, the benefits reported at short follow-up times are broadly consistent with those seen at longer follow-up times. For fingolimod and dimethyl fumarate, there was a definite trend towards a progressively lower annual relapse rate with continuing treatment. The safety profile of all five drugs was considered to be acceptable, even after extended treatment. While these results should be treated with caution, they highlight that future head-to-head studies are needed to better understand the long-term benefits of disease-modifying therapies. Such information will be of value when considering the risk-benefit profile of these oral therapies.

Diagnosis and management of secondary-progressive multiple sclerosis: time for change

Identifying the transition of relapsing-remitting multiple sclerosis (MS) to the secondary-progressive MS form remains a clinical challenge due to the gradual nature of the transition, superimposed relapses, the heterogeneous course of disease among patients and the absence of validated biomarkers and diagnostic tools. The uncertainty associated with the transition makes clinical care challenging for both patients and physicians. The emergence of new disease-modifying treatments for progressive MS and the increasing emphasis of nonpharmacological strategies mark a new era in the treatment of progressive MS. This article summarizes challenges in diagnosis and management, discusses novel treatment strategies and highlights the importance of establishing a clear diagnosis and instituting an interdisciplinary management plan in the care of patients with progressive MS.

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

Treatment of internuclear ophthalmoparesis in multiple sclerosis with fampridine: A randomized double-blind, placebo-controlled cross-over trial

Aim

To examine whether the velocity of saccadic eye movements in internuclear ophthalmoparesis (INO) improves with fampridine treatment in patients with multiple sclerosis (MS).

Methods

Randomized, double‐blind, placebo‐controlled, cross‐over trial with fampridine in patients with MS and INO. Horizontal saccades were recorded at baseline and at multiple time points post‐dose. Main outcome measures were the change of peak velocity versional dysconjugacy index (PV‐VDI) and first‐pass amplitude VDI (FPA‐VDI). Both parameters were compared between fampridine and placebo using a mixed model analysis of variance taking patients as their own control. Pharmacokinetics was determined by serial blood sampling.

Results

Thirteen patients had a bilateral and 10 had a unilateral INO. One patient had an INO of abduction (posterior INO of Lutz) and was excluded. Fampridine significantly reduced both PV‐VDI (−17.4%, 95% CI: −22.4%, −12.1%; P < 0.0001) and FPA‐VDI (−12.5%, 95% CI: −18.9%, −5.5%; P < 0.01). Pharmacokinetics demonstrated that testing coincided with the average t_max at 2.08 hours (SD 45 minutes). The main adverse event reported after administration of fampridine was dizziness (61%).

Conclusion

Fampridine improves saccadic eye movements due to INO in MS. Treatment response to fampridine may gauge patient selection for inclusion to remyelination strategies in MS using saccadic eye movements as primary outcome measure.

Blood neurofilament light chain as a biomarker of MS disease activity and treatment response

Objective

To assess the value of blood neurofilament light chain (NfL) as a biomarker of recent, ongoing, and future disease activity and tissue damage and its utility to monitor treatment response in relapsing-remitting multiple sclerosis.

Methods

We measured NfL in blood samples from 589 patients with relapsing-remitting multiple sclerosis (from phase 3 studies of fingolimod vs placebo, FREEDOMS and interferon [IFN]-β-1a, TRANSFORMS) and 35 healthy controls and compared NfL levels with clinical and MRI-related outcomes.

Results

At baseline, NfL levels (pg/mL) were higher in patients than in healthy controls (30.5 and 27.0 vs 16.9, p = 0.0001) and correlated with T2 lesion load and number of gadolinium-enhancing T1 lesions (p < 0.0001, both). Baseline NfL levels, treatment, and number of new or enlarging T2 lesions during the studies predicted NfL levels at the end of study (all p < 0.01). High vs low baseline NfL levels were associated (estimate [95% confidence interval]) with an increased number of new or enlarging T2 lesions (ratio of mean: 2.64 [1.51–4.60]; p = 0.0006), relapses (rate ratio: 2.53 [1.67–3.83]; p < 0.0001), brain volume loss (difference in means: −0.78% [−1.02 to −0.54]; p < 0.0001), and risk of confirmed disability worsening (hazard ratio: 1.94 [0.97–3.87]; p = 0.0605). Fingolimod significantly reduced NfL levels already at 6 months (vs placebo 0.73 [0.656–0.813] and IFN 0.789 [0.704–0.884]), which was sustained until the end of the studies (vs placebo 0.628 [0.552–0.714] and IFN 0.794 [0.705–0.894]; p < 0.001, both studies at all assessments).

Conclusions

Blood NfL levels are associated with clinical and MRI-related measures of disease activity and neuroaxonal damage and have prognostic value. Our results support the utility of blood NfL as an easily accessible biomarker of disease evolution and treatment response.

Core temperature is not elevated at rest in people with relapsing-remitting multiple sclerosis

PURPOSE

To reassess the notion that people with multiple sclerosis (MS) do not demonstrate an elevated resting core temperature when measured using best-practice precision thermometry.

METHOD

Across two international data collection sites (Australia and USA), twenty-eight relapsing-remitting MS patients and 27 aged-matched controls (CON) were exposed to either 30 °C, 30% relative humidity (RH) (Sydney) or 25 °C, 30% RH (Dallas). Resting rectal (T_re) and esophageal (T_eso) temperature and resting oxygen consumption (VO₂) was measured in MS (n = 28) and CON (n = 27) groups who completed the 25 °C and 30 °C trials. Tympanic membrane (T_tym) temperature was measured in MS (n = 16) and CON (n = 15) groups in the 30 °C condition. A modified fatigue impact scale (MFIS) questionnaire was used to assess subjective measures of psychosocial, physical and cognitive fatigue in the 30 °C condition.

RESULTS

Irrespective of ambient temperature, no group differences were observed for T_re (MS: 37.07 ± 0.30 °C; CON: 37.18 ± 0.30 °C; P = 0.29), T_eso (MS: 36.84 ± 0.42 °C; CON: 36.92 ± 0.29 °C; P = 0.36) or resting VO₂ (MS: 3.89 ± 0.18 ml⋅kg^-1⋅min^-1; CON: 3.98 ± 0.17 ml⋅kg^-1⋅min^-1; P = 0.67). Similarly, no group differences were observed for T_tym (MS: 36.52 ± 0.38 °C; CON: 36.61 ± 0.33 °C; P = 0.55) in the 30 °C condition. Resting T_re did not correlate with subjective measures of fatigue: physical: r = -0.11, P = 0.67; cognitive: r = -0.14, P = 0.60; and psychosocial: r = 0.05, P = 0.84.

CONCLUSION

Contrary to recent reports, resting core temperature is not elevated in relapsing-remitting MS patients compared to healthy controls when measured using precision thermometry. Furthermore, no association was observed between resting T_re and any subjective measures of fatigue in a subset of participants with MS.

Silent lesions on MRI imaging - Shifting goal posts for treatment decisions in multiple sclerosis

BACKGROUND

The current best practice suggests yearly magnetic resonance imaging (MRI) to monitor treatment response in multiple sclerosis (MS) patients.

OBJECTIVE

To evaluate the current practice of clinicians changing MS treatment based on subclinical new MRI lesions alone.

METHODS

Using MSBase, an international MS patient registry with MRI data, we analysed the probability of treatment change among patients with clinically silent new MRI lesions.

RESULTS

A total of 8311 MRI brain scans of 4232 patients were identified. Around 26.9% (336/1247) MRIs with one new T2 lesion were followed by disease-modifying therapy (DMT) change, increasing to 50.2% (129/257) with six new T2 lesions. DMT change was twice as likely with new T1 contrast enhancing compared to new T2 lesions odds ratio (OR): 2.43, 95% confidence interval (CI): 2.00-2.96 vs OR: 1.26 (95% CI: 1.22-1.29). DMT change with new MRI lesions occurred most frequently with 'injectable' DMTs. The probability of switching therapy was greater only after high-efficacy therapies became available in 2007 (after, OR: 1.43, 95% CI: 1.28-1.59 vs before, OR: 0.98, 95% CI: 0.520-1.88).

CONCLUSION

MS clinicians rely increasingly on MRI alone in their treatment decisions, utilizing low thresholds (1 new T2 lesion) for optimizing MS therapy. This signals a shift towards no evidence of disease activity (NEDA)-3 since high-efficacy therapies became available.

Multiple Sclerosis: Improved Detection of Active Cerebral Lesions With 3-Dimensional T1 Black-Blood Magnetic Resonance Imaging Compared With Conventional 3-Dimensional T1 GRE Imaging

OBJECTIVES

The aim of this study was to assess the diagnostic accuracy of a modified high-resolution whole-brain three-dimensional T1-weighted black-blood sequence (T1-weighted modified volumetric isotropic turbo spin echo acquisition [T1-mVISTA]) in comparison to a standard three-dimensional T1-weighted magnetization-prepared rapid gradient echo (MP-RAGE) sequence for detection of contrast-enhancing cerebral lesions in patients with relapsing-remitting multiple sclerosis (MS).

MATERIALS AND METHODS

After institutional review board approval and informed consent, 22 patients (8 men; aged 31.0 ± 9.2 years) with relapsing-remitting MS were included in this monocentric prospective cohort study.Contrast-enhanced T1-mVISTA and MP-RAGE, both with 0.8 mm resolution, were performed in all patients. In a substudy of 12 patients, T1-mVISTA was compared with a T1-mVISTA with 1.0 mm resolution (T1-mVISTA_1.0). Reference lesions were defined by an experienced neuroradiologist using all available sequences and served as the criterion standard. T1-mVISTA, T1-mVISTA_1.0, and MP-RAGE sequences were read in random order 4 weeks apart. Image quality, visual contrast enhancement, contrast-to-noise-ratio (CNR), diagnostic confidence, and lesion size were assessed and compared by Wilcoxon and Mann-Whitney U tests.

RESULTS

Eleven of 22 patients displayed contrast-enhancing lesions. Visual contrast enhancement, CNR, and diagnostic confidence of contrast-enhancing MS lesions were significantly increased in T1-mVISTA compared with MP-RAGE (P < 0.001). Significantly more contrast-enhancing lesions were detected with T1-mVISTA than with MP-RAGE (71 vs 39, respectively; P < 0.001). With MP-RAGE, 25.6% of lesions were missed in the initial reading, whereas only 4.2% of lesions were missed with T1-mVISTA. Increase of the voxel volume from 0.8 mm to 1.0 mm isotropic in T1-mVISTA_1.0 did not affect the detectability of lesions, whereas scan time was decreased from 4:43 to 1:55 minutes.

CONCLUSIONS

Three-dimensional T1-mVISTA improves the detection rates of contrast-enhancing cerebral MS lesions compared with conventional 3D MP-RAGE sequences by increasing CNR of lesions and might, therefore, be useful in patient management.

Magnetic Resonance Imaging in Multiple Sclerosis

Since its technical development in the early 1980s, magnetic resonance imaging (MRI) has quickly been adopted as an essential tool in supporting the diagnosis, longitudinal monitoring, evaluation of therapeutic response, and scientific investigations in multiple sclerosis (MS). The clinical usage of MRI has increased in parallel with technical innovations in the technique itself; the widespread adoption of clinically routine MRI at 1.5T has allowed sensitive qualitative and quantitative assessments of macroscopic central nervous system (CNS) inflammatory demyelinating lesions and tissue atrophy. However, conventional MRI lesion measures lack specificity for the underlying MS pathology and only weakly correlate with clinical status. Higher field strength units and newer, advanced MRI techniques offer increased sensitivity and specificity in the detection of disease activity and disease severity. This review summarizes the current status and future prospects regarding the role of MRI in the characterization of MS-related brain and spinal cord involvement.

Blood brain barrier (BBB)-disruption in intracortical silicon microelectrode implants

Chronically implanted microelectrodes in the neural tissue elicit inflammatory responses that are time varying and have been shown to depend on multiple factors. Among these factors, blood brain barrier (BBB)-disruption has been hypothesized as one of the dominant factors resulting in electrode failure. A series of events that includes BBB and cell-membrane disruption occurs during electrode implantation that triggers multiple biochemical cascades responsible for microglial and astroglial activation, hemorrhage, edema, and release of pro-inflammatory neurotoxic cytokines that causes neuronal degeneration and dysfunction. Typically, microwire arrays and silicon probes are inserted slowly into the neural tissue whereas the silicon Utah MEAs (UMEA) are inserted at a high speed using a pneumatic inserter. In this work, we report the sequelae of electrode-implant induced cortical injury at various acute time points in UMEAs implanted in the brain tissue by quantifying the expression profile for key genes mediating the inflammatory response and tight junction (TJ) and adherens junction (AJ) proteins that form the BBB and are critical to the functioning of the BBB. Our results indicated upregulation of most pro-inflammatory genes relative to naïve controls for all time points. Expression levels for the genes that form the TJ and AJ were downregulated suggestive of BBB-dysfunction. Moreover, there was no significant difference between stab and implant groups suggesting the effects of UMEA insertion-related trauma in the brain tissue. Our results provide an insight into the physiological events related to neuroinflammation and BBB-disruption occurring at acute time-points following insertion of UMEAs.

Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI

BACKGROUND

There are concerns over gadolinium deposition from gadolinium-based contrast agents (GBCA) administration.

PURPOSE

To reduce gadolinium dose in contrast-enhanced brain MRI using a deep learning method.

STUDY TYPE

Retrospective, crossover.

POPULATION

Sixty patients receiving clinically indicated contrast-enhanced brain MRI.

SEQUENCE

3D T₁ -weighted inversion-recovery prepped fast-spoiled-gradient-echo (IR-FSPGR) imaging was acquired at both 1.5T and 3T. In 60 brain MRI exams, the IR-FSPGR sequence was obtained under three conditions: precontrast, postcontrast images with 10% low-dose (0.01mmol/kg) and 100% full-dose (0.1 mmol/kg) of gadobenate dimeglumine. We trained a deep learning model using the first 10 cases (with mixed indications) to approximate full-dose images from the precontrast and low-dose images. Synthesized full-dose images were created using the trained model in two test sets: 20 patients with mixed indications and 30 patients with glioma.

ASSESSMENT

For both test sets, low-dose, true full-dose, and the synthesized full-dose postcontrast image sets were compared quantitatively using peak-signal-to-noise-ratios (PSNR) and structural-similarity-index (SSIM). For the test set comprised of 20 patients with mixed indications, two neuroradiologists scored blindly and independently for the three postcontrast image sets, evaluating image quality, motion-artifact suppression, and contrast enhancement compared with precontrast images.

STATISTICAL ANALYSIS

Results were assessed using paired t-tests and noninferiority tests.

RESULTS

The proposed deep learning method yielded significant (n = 50, P < 0.001) improvements over the low-dose images (>5 dB PSNR gains and >11.0% SSIM). Ratings on image quality (n = 20, P = 0.003) and contrast enhancement (n = 20, P < 0.001) were significantly increased. Compared to true full-dose images, the synthesized full-dose images have a slight but not significant reduction in image quality (n = 20, P = 0.083) and contrast enhancement (n = 20, P = 0.068). Slightly better (n = 20, P = 0.039) motion-artifact suppression was noted in the synthesized images. The noninferiority test rejects the inferiority of the synthesized to true full-dose images for image quality (95% CI: -14-9%), artifacts suppression (95% CI: -5-20%), and contrast enhancement (95% CI: -13-6%).

DATA CONCLUSION

With the proposed deep learning method, gadolinium dose can be reduced 10-fold while preserving contrast information and avoiding significant image quality degradation.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 5 J. MAGN. RESON. IMAGING 2018;48:330-340.

Early Relapsing Multiple Sclerosis

PURPOSE OF REVIEW

This article provides an evidence-based approach to the management of patients with early relapsing multiple sclerosis (MS).

RECENT FINDINGS

Numerous clinical trials have shown the role of disease-modifying therapies in reducing relapses and new MRI lesions in patients with relapsing MS. Many of these trials also show the ability of these agents to delay disability progression, and a few suggest that disease-modifying therapies may slow brain atrophy in relapsing MS; however, very few suggest that disease-modifying therapies can improve symptoms or disability. The therapeutic armamentarium of disease-modifying therapies includes five interferon formulations, two versions of glatiramer acetate, mitoxantrone, natalizumab, fingolimod, teriflunomide, dimethyl fumarate, and alemtuzumab.

SUMMARY

Although multiple disease-modifying therapies exist, the risks of these vary markedly, head-to-head comparator trials are limited, and no prospective biomarkers for treatment efficacy exist; therefore, choosing a disease-modifying therapy for an individual patient with MS is a difficult decision. This difficulty is compounded by limitations in predicting a patient's disease course, and the risk tolerance of the patient and opinions of the care partner need to be factored into the decision analysis as well. After a disease-modifying therapy is chosen, vigilance for clinical or radiographic breakthrough disease is very important, as this may suggest a suboptimal response to the chosen therapy. Furthermore, the role of symptom management and wellness should always remain part of the approach to the patient with MS.