The Role of T1-Weighted Derived Measures of Neurodegeneration for Assessing Disability Progression in Multiple Sclerosis

Trajectories of self-reported fatigue following initiation of multiple sclerosis disease-modifying therapy

BACKGROUND

We analysed the COMparison Between All immunoTherapies for Multiple Sclerosis (NCT03193866), a Swedish nationwide observational study in relapsing-remitting multiple sclerosis (RRMS), to identify trajectories of fatigue and their association with physical disability following start of disease-modifying therapy (DMT).

METHODS

Using a group-modelling approach, we assessed trajectories of fatigue with the Fatigue Scale for Motor and Cognitive Functions and physical disability with Expanded Disability Status Scale among 1587 and 1818 individuals who initiated a first DMT and had a first DMT switch, respectively, followed during 2011-2022. We investigated predictors of fatigue trajectories using group membership as a multinomial outcome and calculated conditional probabilities linking membership across the trajectories.

RESULTS

We identified five trajectories of fatigue in participants who initiated their first DMT: no fatigue (mean starting values=23.7; 18.2% of population), low (35.5; 23.9%), mild (49.0; 21.6%), moderate (61.3; 20.1%) and severe (78.7; 16.1%). While no, low, mild and severe fatigue trajectories remained stable, the moderate trajectory increased to severe fatigue. Similarly, we identified six fatigue trajectories among participants who did a DMT switch, all indicating stable values over time. Women initiating a first DMT were more likely than men to display a severe fatigue trajectory, relative to the no fatigue one. There was a strong association between fatigue and physical disability trajectories.

CONCLUSIONS

In this cohort of people with actively treated RRMS, self-reported fatigue remained stable or increased over the years following DMT start. There was a strong association between fatigue and disability after DMT start.

Clinical variables influencing the perception of fatigue in people with multiple sclerosis: a cross-sectional study using FSIQ-RMS

BACKGROUND

Physical fatigue is one of the most disabling symptoms in people with Multiple Sclerosis (PwMS). Several factors might influence the development of fatigue, such as gender, education, body mass index (BMI), Expanded Disability Status Scale (EDSS), disease duration, working status (Ws), physiotherapy (Ph), and disease-modifying therapies (DMTs). Fatigue Symptoms and Impacts Questionnaire-Relapsing Multiple Sclerosis (FSIQ-RMS) is a patient-reported outcome (PRO) that allows one to define the impact of fatigue in PwMS clearly. This study aimed to assess fatigue impact on PwMS by using FSIQ-RMS.

METHODS

The participants were enrolled from May to July 2021 in MS Centers of Sant'Andrea Hospital and Policlinico Umberto I Hospital in Rome. Fatigue was evaluated using the FSIQ-RMS, validated, and culturally adapted in Italian. Clinical and demographic data were collected at the same time.

RESULTS

We enrolled 178 PwMS [Female 74.16%; RMS 82.58%, SPMS 17.52%]. FSIQ-RMS scores were significantly correlated with EDSS (p-value < 0.01). Analysis of variance between means showed a statistically significant difference between the BMI groups at the 24hours_FSIQ-RMS score and the 7days_FSIQ-RMS score (p < 0.01), with the lower BMI group having the highest scores. Furthermore, perceived fatigue significantly improved both in subjects performing Ph (p < 0.05) and in those who actively work (p < 0.01).

CONCLUSIONS

The use of FSIQ-RMS in a real-world setting confirmed that underweight and high levels of disability are closely related to fatigue. In addition, Ph and active Ws are strongly correlated with fatigue in PwMS.

Sensitive Identification of Asymmetries and Neuromuscular Deficits in Lower Limb Function in Early Multiple Sclerosis

BACKGROUND

In the early stages of multiple sclerosis (MS), there are no objective sensitive functional assessments to identify and quantify early subclinical neuromuscular deficits and lower limb strength asymmetries during complex movements. Single-countermovement jumps (SLCMJ), a maximum single leg vertical jump, on a force plate allow functional evaluation of unilateral lower limb performance in performance diagnostics and could therefore provide early results on asymmetries in MS.

OBJECTIVE

Objective evaluation of early lower limb neuromuscular deficits and asymmetries in people with multiple sclerosis (pwMS) using SLCMJ on a force plate.

METHODS

A study was conducted with pwMS (N = 126) and healthy controls (N = 97). All participants performed 3 maximal SLCMJs on a force plate. Temporal, kinetic, and power jump parameters were collected. The Expanded Disability Status Scale (EDSS) was performed on all participants. A repeated measures analysis of covariance (ANCOVA) with age, Body-Mass-Index, and gender as covariates was used.

RESULTS

PwMS with normal muscle strength according to the manual muscle tests showed significantly reduced SLCMJ performance compared to HC. In both groups, jumping performance differed significantly between the dominant and non-dominant leg, with higher effect size for pwMS. A significant interaction effect between leg dominance and group was found for propulsive time, where the pwMS showed an even higher difference between the dominant and non-dominant leg compared to HC. Furthermore, there was a significant small correlation between leg asymmetries and EDSS in pwMS.

CONCLUSION

The study shows that the SLCMJ on a force plate is suitable for the early detection of subclinical lower limb neuromuscular deficits and strength asymmetries in MS.

T1 hypointense brain lesions in NMOSD and its relevance with disability: a single institution cross-sectional study

BACKGROUND

T1 hypointense lesions are considered a surrogate marker of tissue destruction. Although there is a shortage of evidence about T1 hypointense brain lesions, black holes, in patients with Neuromyelitis Optica Spectrum Disorder (NMOSD), the clinical significance of these lesions is not well determined.

OBJECTIVES

The impact of T1 hypointense brain lesions on the clinical status and the disability level of patients with NMOSD was sought in this study.

METHODS

A total of 83 patients with the final diagnosis of NMOSD were recruited. Aquaporin-4 measures were collected. The expanded disability status scale (EDSS) and MRI studies were also extracted. T1 hypointense and T2/FLAIR hyperintense lesions were investigated. The correlation of MRI findings, AQP-4, and EDSS was assessed.

RESULTS

T1 hypointense brain lesions were detected in 22 patients. Mean ± SD EDSS was 3.7 ± 1.5 and significantly higher in patients with brain T1 hypointense lesions than those without them (p-value = 0.01). Noticeably, patients with more than four T1 hypointense lesions had EDSS scores ≥ 4. The presence of T2/FLAIR hyperintense brain lesions correlated with EDSS (3.6 ± 1.6 vs 2.3 ± 1.7; p-value = 0.01). EDSS was similar between those with and without positive AQP-4 (2.7 ± 1.6 vs. 3.2 ± 1.7; p-value = 0.17). Also, positive AQP-4 was not more prevalent in patients with T1 hypointense brain lesions than those without them (50.9 vs 45.4%; p-value = 0.8).

CONCLUSION

We demonstrated that the presence of the brain T1-hypointense lesions corresponds to a higher disability level in NMOSD.

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.

Functional connectome fingerprinting and stability in multiple sclerosis

Background

Functional connectome fingerprinting can identify individuals based on their functional connectome. Previous studies relied mostly on short intervals between fMRI acquisitions.

Objective

This cohort study aimed to determine the stability of connectome-based identification and their underlying signatures in patients with multiple sclerosis and healthy individuals with long follow-up intervals.

Methods

We acquired resting-state fMRI in 70 patients with multiple sclerosis and 273 healthy individuals with long follow-up times (up to 4 and 9 years, respectively). Using functional connectome fingerprinting, we examined the stability of the connectome and additionally investigated which regions, connections and networks supported individual identification. Finally, we predicted cognitive and behavioural outcome based on functional connectivity.

Results

Multiple sclerosis patients showed connectome stability and identification accuracies similar to healthy individuals, with longer time delays between imaging sessions being associated with accuracies dropping from 89% to 76%. Lesion load, brain atrophy or cognitive impairment did not affect identification accuracies within the range of disease severity studied. Connections from the fronto-parietal and default mode network were consistently most distinctive, i.e., informative of identity. The functional connectivity also allowed the prediction of individual cognitive performances.

Conclusion

Our results demonstrate that discriminatory signatures in the functional connectome are stable over extended periods of time in multiple sclerosis, resulting in similar identification accuracies and distinctive long-lasting functional connectome fingerprinting signatures in patients and healthy individuals.

Neuromuscular rate of force development discriminates fallers in ambulatory persons with multiple sclerosis - an exploratory study

BACKGROUND

Falls as well as fall-related injuries (e.g., bone fractures) are common in persons with multiple sclerosis (pwMS). Whilst some studies have identified lower extremity maximal muscle strength (Fmax) as one among several risk factors, no previous studies have investigated the association between rate of force development (RFD; ability to generate a rapid rise in muscle force) and falls in pwMS. Not only is RFD substantially compromised (and more so than Fmax) in pwMS, studies involving other neurodegenerative populations have shown that RFD - to a greater extent than Fmax - is crucial for counteracting unexpected perturbations and avoiding falling.

OBJECTIVE

To explore whether knee extensor RFD (and Fmax) can discriminate fallers from non-fallers in pwMS.

METHODS

Knee extensor neuromuscular function (comprising RFD_50ms and RFD_200ms (force developed in the interval 0-50 ms and 0-200 ms, respectively) as well as Fmax) of the weaker leg was assessed by isokinetic dynamometry. Falls were determined by 1-year patient recall, with pwMS subsequently being classified as non-fallers (0 falls), fallers (1-2 falls), or recurrent fallers (≥3 falls).

RESULTS

A total of n=53 pwMS were enrolled in the study, with n=24 classified as non-fallers (63% females, 48 years, EDSS 2.2), n=16 as fallers (88% females, 57 years, EDSS 3.3), and n=13 as recurrent fallers (46% females, 60 years, EDSS 4.2). Compared with non-fallers, neuromuscular function was reduced in both fallers (RFD₅₀ -4.42 [-7.47;-1.37] Nm^.s^-1.kg^-1, -48%; RFD₂₀₀ -1.45 [-2.98;0.07] Nm^.s^-1.kg^-1, -24%; Fmax -0.42 [-0.81;-0.03] Nm^.kg^-1, -21%) and recurrent fallers (RFD₅₀ -5.69 [-8.94;-2.43] Nm^.s^-1.kg^-1, -62%; RFD₂₀₀ -2.26 [-3.89;-0.63] Nm^.s^-1.kg^-1, -38%; Fmax -0.38 [-0.80;0.03] Nm^.kg^-1, -19%). Across all participants, associations were observed between RFD_50ms and falls (r_s = -0.46 [-0.67;-0.24], between RFD_200ms and falls (r_s = -0.34 [-0.59;-0.09]), and between Fmax and falls (r_s = -0.24 [-0.48;0.01]).

CONCLUSION

In this exploratory study, knee extensor neuromuscular function was able to discriminate fallers from non-fallers in pwMS, with RFD being superior to Fmax. Routine assessment of lower extremity neuromuscular function (RFD_50ms in particular) may be a helpful tool in identifying pwMS at future risk of falling.

Brain Atrophy and Physical and Cognitive Disability in Multiple Sclerosis

Introduction

Brain atrophy is associated with physical disability in multiple sclerosis (MS), but there is a great variability between different studies and methodologies, and its use is still limited to research projects. We aimed to analyze the relationship between several volumetric measurements and physical disability and cognitive functioning in MS patients in a clinical practice setting.

Methods

This is a cross-sectional study. A total of 41 patients (31 relapsing-remitting MS, 6 secondary-progressive MS, and 4 primary-progressive MS) were included. Whole brain volume (WBV), gray matter volume (GMV), and T2 lesion load (T2L) were obtained using Icometrix® software. Physical disability was measured with the Expanded Disability Status Scale (EDSS), and cognitive status was evaluated with the brief repeatable battery of neuropsychological tests (BRB-N). The relationship between brain volumes and EDSS was analyzed through linear multivariate regression. The association between volumetry measurements and the number of affected cognitive domains was studied with negative binomial regression.

Results

GMV was associated with age (b=-1.7, P=0.014) and with EDSS (b=-7.55, P=0.013). T2L was associated with EDSS (b=2.29, P=0.032). The number of affected cognitive domains was associated with clinical phenotype, worse in primary progressive MS (PPMS). There was not correlations between cognitive impairment and cerebral volumes.

Conclusion

Brain atrophy measurement is feasible in clinical practice setting, and it is helpful in monitoring the EDSS progression. Primary progressive phenotype is associated with greater risk of cognitive dysfunction.

Highlights

The T2 lesion load is associated with physical disability in patients with multiple sclerosis (MS).The gray matter volume is associated with age and physical disability in patients with MS.There is no significant correlation between cognitive impairment and cerebral volumes in patients with MS.

Plain Language Summary

Conventional magnetic resonance imaging (MRI) is still used for diagnosing and monitoring multiple sclerosis (MS). Analysis of Brain volumes including Whole brain volume (WBV), gray matter volume (GMV), and T2 lesion load (T2L) allows the evaluation of its neurodegenerative mechanisms. Robust evidence links brain atrophy with disability in MS. This study aims to analyze the relationship between advanced MRI sequences and physical disability and cognitive functioning in MS patients. According to the results, T2L was associated with physical disability and GMV was associated with age and physical disability. There was no significant correlation between cognitive impairment and cerebral volumes in patients with MS.

Multiple sclerosis: role of meningeal lymphoid aggregates in progression independent of relapse activity

The emphasis on mechanisms driving multiple sclerosis (MS) symptomatic worsening suggests that we move beyond categorical clinical classifiers such as relapsing-remitting MS (RR-MS) and progressive MS (P-MS). Here, we focus on the clinical phenomenon progression independent of relapse activity (PIRA), which begins early in the disease course. PIRA occurs throughout MS, becoming more phenotypically evident as patients age. The underlying mechanisms for PIRA include chronic-active demyelinating lesions (CALs), subpial cortical demyelination, and nerve fiber injury following demyelination. We propose that much of the tissue injury associated with PIRA is driven by autonomous meningeal lymphoid aggregates, present before disease onset and unresponsive to current therapeutics. Recently, specialized magnetic resonance imaging (MRI) has identified and characterized CALs as paramagnetic rim lesions in humans, enabling novel radiographic-biomarker-clinical correlations to further understand and treat PIRA.

Predictors of patient-reported fatigue symptom severity in a nationwide multiple sclerosis cohort

BACKGROUND

Fatigue is a debilitating symptom of multiple sclerosis (MS), but its relation to sociodemographic and disease-related characteristics has not been investigated in larger studies. The objectives of this study were to evaluate predictors of self-reported fatigue in a Swedish nationwide register-based MS cohort.

METHODS

Using a repeated cross-sectional design, we included 2,165 persons with relapsing- remitting and secondary progressive MS with one or multiple Fatigue Scale for Motor and Cognitive Functions (FSMC) scores, which was modelled using multivariable linear regressions for multiple predictors.

RESULTS

Only associations to expanded disability status scale (EDSS) and Symbol Digit Modalities Test (SDMT) were considered clinically meaningful among MS-associated characteristics in our main model; compared to mild disability (EDSS 0-2.5), those with severe disability (EDSS ≥6) scored 17.6 (95% CI 13.1-22.2) FSMC points higher, while the difference was 10.7 (95% CI 8.0-13.4) points for the highest and lowest quartiles of SDMT. Differences between highest and lowest quartiles of health-related quality of life (HRQoL) instruments were even greater and considered clinically meaningful; EuroQoL Visual Analogue Scale (EQ-VAS) 31.9 (95% CI 29.9-33.8), Multiple Sclerosis Impact Scale (MSIS-29) psychological component 35.6 (95% CI 33.8-37.4) and MSIS-29 physical component 45.5 (95% CI 43.7-47.4).

CONCLUSION

Higher self-reported fatigue is associated with higher disability level and worse cognitive processing speed, while associations to other MS-associated characteristics including MS type, line of disease modifying therapy (DMT), MS duration, relapse and new cerebral lesions are weak. Furthermore, we found a strong correlation between high fatigue rating and lower ratings on health-related quality of life instruments.

Using personalized prognosis in the treatment of relapsing multiple sclerosis: A practical guide

The clinical course of multiple sclerosis (MS) is highly variable among patients, thus creating important challenges for the neurologist to appropriately treat and monitor patient progress. Despite some patients having apparently similar symptom severity at MS disease onset, their prognoses may differ greatly. To this end, we believe that a proactive disposition on the part of the neurologist to identify prognostic “red flags” early in the disease course can lead to much better long-term outcomes for the patient in terms of reduced disability and improved quality of life. Here, we present a prognosis tool in the form of a checklist of clinical, imaging and biomarker parameters which, based on consensus in the literature and on our own clinical experiences, we have established to be associated with poorer or improved clinical outcomes. The neurologist is encouraged to use this tool to identify the presence or absence of specific variables in individual patients at disease onset and thereby implement sufficiently effective treatment strategies that appropriately address the likely prognosis for each patient.

Histological analysis of sleep and circadian brain circuitry in cranial radiation-induced hypersomnolence (C-RIH) mouse model

Disrupted sleep, including daytime hypersomnolence, is a core symptom reported by primary brain tumor patients and often manifests after radiotherapy. The biological mechanisms driving the onset of sleep disturbances after cranial radiation remains unclear but may result from treatment-induced injury to neural circuits controlling sleep behavior, both circadian and homeostatic. Here, we develop a mouse model of cranial radiation-induced hypersomnolence which recapitulates the human experience. Additionally, we used the model to explore the impact of radiation on the brain. We demonstrated that the DNA damage response following radiation varies across the brain, with homeostatic sleep and cognitive regions expressing higher levels of γH2AX, a marker of DNA damage, than the circadian suprachiasmatic nucleus (SCN). These findings were supported by in vitro studies comparing radiation effects in SCN and cortical astrocytes. Moreover, in our mouse model, MRI identified structural effects in cognitive and homeostatic sleep regions two-months post-treatment. While the findings are preliminary, they suggest that homeostatic sleep and cognitive circuits are vulnerable to radiation and these findings may be relevant to optimizing treatment plans for patients.

Objectively assessed physiological, physical, and cognitive function along with patient-reported outcomes during the first 2 years of Alemtuzumab treatment in multiple sclerosis: a prospective observational study

INTRODUCTION

In persons with multiple sclerosis (pwMS), little evidence exist on the effects of Alemtuzumab on physiological, physical, and cognitive function along with patient-reported outcomes, despite these domains are being rated as highly important. Therefore, our purpose was to perform a prospective observational study to examine these outlined outcomes during the first two years of Alemtuzumab treatment in pwMS.

METHODS

In n = 17 relapsing-remitting pwMS, physiological function [body composition; bone mineral content; muscle strength; aerobic capacity], physical function [6-min walk test (6MWT, primary outcome); timed 25 ft walk test (T25FWT); six spot step test (SSST); 9-step stair ascend (9SSA); timed up and go test (TUG); 5 × sit to stand test (5STS)], cognitive function [selective reminding test (SRT); symbol digit modalities test (SDMT)], and patient-reported outcomes [multiple sclerosis impact scale-29 (MSIS29); 12-item multiple sclerosis walking scale (MSWS12); modified fatigue impact scale (MFIS); hospital anxiety and depression scale (HADS)] were assessed prior to Alemtuzumab treatment initiation as well as 3, 6, 12, and 24 months into the treatment.

RESULTS

Improvements were observed at 24-month follow-up in T25FWT (+ 8%), SSST (+ 10%), SDMT (+ 5.2 points, 53% improved more than the clinical cut-off score) and SRT, whereas the primary outcome 6MWT, and all other remaining outcomes, remained stable throughout the Alemtuzumab treatment period.

CONCLUSION

The present findings suggest that Alemtuzumab treatment in relapsing-remitting pwMS can improve certain domains of physical function (short distance walking) and cognitive function (processing speed, memory), and furthermore stabilize physiological and physical function along with patient-reported outcomes.

TRIAL REGISTRATION

Registered at clinicaltrials.gov: NCT03806387.

Predictive MRI Biomarkers in MS—A Critical Review

Background and Objectives: In this critical review, we explore the potential use of MRI measurements as prognostic biomarkers in multiple sclerosis (MS) patients, for both conventional measurements and more novel techniques such as magnetization transfer, diffusion tensor, and proton spectroscopy MRI. Materials and Methods: All authors individually and comprehensively reviewed each of the aspects listed below in PubMed, Medline, and Google Scholar. Results: There are numerous MRI metrics that have been proven by clinical studies to hold important prognostic value for MS patients, most of which can be readily obtained from standard 1.5T MRI scans. Conclusions: While some of these parameters have passed the test of time and seem to be associated with a reliable predictive power, some are still better interpreted with caution. We hope this will serve as a reminder of how vast a resource we have on our hands in this versatile tool—it is up to us to make use of it.

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis

BACKGROUND AND PURPOSE

Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor- or computationally intensive. We therefore developed an automated deep learning-based CC segmentation tool and hypothesized that its output would correlate with disability.

METHODS

A cohort of 631 MS patients (449 females, baseline age 41 ± 11 years) with both 3-dimensional T1-weighted and T2-weighted fluid-attenuated inversion recovery (FLAIR) MRI was used for the development. Data from 204 patients were manually segmented to train convolutional neural networks in extracting the midsagittal intracranial and CC areas. Remaining data were used to compare segmentations with FreeSurfer and benchmark the outputs with regard to clinical correlations. A 1.5 and 3 Tesla reproducibility cohort of 9 MS patients evaluated the segmentation robustness.

RESULTS

The deep learning-based tool was accurate in selecting the appropriate slice for segmentation (98% accuracy within 3 mm of the manual ground truth) and segmenting the CC (Dice coefficient .88-.91) and intracranial areas (.97-.98). The accuracy was lower with higher atrophy. Reproducibility was excellent (intraclass correlation coefficient > .90) for T1-weighted scans and moderate-good for FLAIR (.74-.75). Segmentations were associated with baseline and future (average follow-up time 6-7 years) Expanded Disability Status Scale (ρ = -.13 to -.24) and Symbol Digit Modalities Test (r = .18-.29) scores.

CONCLUSIONS

We present a fully automatic deep learning-based CC segmentation tool optimized to modern imaging in MS with clinical correlations on par with computationally expensive alternatives.

Rationale and design of the brain magnetic resonance imaging protocol for FutureMS: a longitudinal multi-centre study of newly diagnosed patients with relapsing-remitting multiple sclerosis in Scotland

Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. Magnetic resonance imaging (MRI) can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. This paper provides an overview of MRI data acquisition, management and processing in FutureMS. FutureMS is registered with the Integrated Research Application System (IRAS, UK) under reference number 169955. Methods and analysis: MRI is performed at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. Conclusions: FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland.

Spinal cord atrophy predicts progressive disease in relapsing multiple sclerosis

Objective

A major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS).

Methods

From a single‐center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12‐year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion.

Results

Patients who developed SPMS showed faster cord atrophy rates (−2.19%/yr) at least 4 years before conversion compared to their RRMS matches (−0.88%/yr, p < 0.001). Spinal cord atrophy rates decelerated after conversion (−1.63%/yr, p = 0.010) towards those of SPMS patients from study entry (−1.04%). Each 1% faster spinal cord atrophy rate was associated with 69% (p < 0.0001) and 53% (p < 0.0001) shorter time to silent progression and SPMS conversion, respectively.

Interpretation

Silent progression and conversion to secondary progressive disease are predominantly related to cervical cord atrophy. This atrophy is often present from the earliest disease stages and predicts the speed of silent progression and conversion to Progressive MS. Diagnosis of SPMS is rather a late recognition of this neurodegenerative process than a distinct disease phase. ANN NEUROL 2022;91:268–281

Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis

Background: Magnetic resonance (MR) scans are routine clinical procedures for monitoring people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial burden motivate the need to accelerate MR scan time. We examined the clinical application of a deep learning (DL) model in restoring the image quality of accelerated routine clinical brain MR scans for PwMS.

Methods: We acquired fast 3D T1w BRAVO and fast 3D T2w FLAIR MRI sequences (half the phase encodes and half the number of slices) in parallel to conventional parameters. Using a subset of the scans, we trained a DL model to generate images from fast scans with quality similar to the conventional scans and then applied the model to the remaining scans. We calculated clinically relevant T1w volumetrics (normalized whole brain, thalamic, gray matter, and white matter volume) for all scans and T2 lesion volume in a sub-analysis. We performed paired t-tests comparing conventional, fast, and fast with DL for these volumetrics, and fit repeated measures mixed-effects models to test for differences in correlations between volumetrics and clinically relevant patient-reported outcomes (PRO).

Results: We found statistically significant but small differences between conventional and fast scans with DL for all T1w volumetrics. There was no difference in the extent to which the key T1w volumetrics correlated with clinically relevant PROs of MS symptom burden and neurological disability.

Conclusion: A deep learning model that improves the image quality of the accelerated routine clinical brain MR scans has the potential to inform clinically relevant outcomes in MS.

Thalamus Atrophy in the Peri-Pregnancy Period in Clinically Stable Multiple Sclerosis Patients: Preliminary Results

Radiological activity in the post-partum period in MS patients is a well-known phenomenon, but there is no data concerning the influence of pregnancy on regional brain atrophy. The aim of this article was to investigate local brain atrophy in the peri-pregnancy period (PPP) in patients with MS. Thalamic volume (TV); corpus callosum volume (CCV) and classical MRI activity (new gadolinium enhancing lesions (Gd+), new T2 lesions, T1 lesions volume (T1LV) and T2 lesions volume (T2LV)) were analyzed in 12 clinically stable women with relapsing–remitting MS and with MRI performed in the PPP. We showed that there was a significant decrease in TV (p = 0.021) in the PPP. We also observed a significant increase in the T1 lesion volume (p = 0.028), new gadolinium-enhanced and new T2 lesions (in 46% and 77% of the scans, respectively) in the post-partum period. Our results suggest that the PPP in MS may be associated not only with classical MRI activity but, also, with regional brain atrophy.

Deep grey matter injury in multiple sclerosis: a NAIMS consensus statement

Although multiple sclerosis has traditionally been considered a white matter disease, extensive research documents the presence and importance of grey matter injury including cortical and deep regions. The deep grey matter exhibits a broad range of pathology and is uniquely suited to study the mechanisms and clinical relevance of tissue injury in multiple sclerosis using magnetic resonance techniques. Deep grey matter injury has been associated with clinical and cognitive disability. Recently, MRI characterization of deep grey matter properties, such as thalamic volume, have been tested as potential clinical trial end points associated with neurodegenerative aspects of multiple sclerosis. Given this emerging area of interest and its potential clinical trial relevance, the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative held a workshop and reached consensus on imaging topics related to deep grey matter. Herein, we review current knowledge regarding deep grey matter injury in multiple sclerosis from an imaging perspective, including insights from histopathology, image acquisition and post-processing for deep grey matter. We discuss the clinical relevance of deep grey matter injury and specific regions of interest within the deep grey matter. We highlight unanswered questions and propose future directions, with the aim of focusing research priorities towards better methods, analysis, and interpretation of results.

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

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

A Critical Systematic Review of Current Evidence on the Effects of Physical Exercise on Whole/Regional Grey Matter Brain Volume in Populations at Risk of Neurodegeneration

BACKGROUND

Despite the intriguing potential of physical exercise being able to preserve or even restore brain volume (grey matter volume in particular)-a tissue essential for both cognitive and physical function-no reviews have so far synthesized the existing knowledge from randomized controlled trials investigating exercise-induced changes of the brain's grey matter volume in populations at risk of neurodegeneration. Our objective was to critically review the existing evidence regarding this topic.

METHODS

A systematic search was carried out in MEDLINE and EMBASE databases primo April 2020, to identify randomized controlled trials evaluating the effects of aerobic training, resistance training or concurrent training on brain grey volume changes (by MRI) in adult clinical or healthy elderly populations.

RESULTS

A total of 20 articles (from 19 RCTs) evaluating 3-12 months of aerobic, resistance, or concurrent training were identified and included, involving a total of 1662 participants (populations: healthy older adults, older adults with mild cognitive impairment or Alzheimer's disease, adults with schizophrenia or multiple sclerosis or major depression). While few studies indicated a positive effect-although modest-of physical exercise on certain regions of brain grey matter volume, the majority of study findings were neutral (i.e., no effects/small effect sizes) and quite divergent across populations. Meta-analyses showed that different exercise modalities failed to elicit any substantial effects on whole brain grey volume and hippocampus volume, although with rather large confidence interval width (i.e., variability).

CONCLUSION

Altogether, the current evidence on the effects of physical exercise on whole/regional grey matter brain volume appear sparse and inconclusive, and does not support that physical exercise is as potent as previously proposed when it comes to affecting brain grey matter volume.

Approaches and challenges in the diagnosis and management of secondary progressive multiple sclerosis: A Central Eastern European perspective from healthcare professionals

Secondary progressive multiple sclerosis (SPMS) is a debilitating condition characterized by gradual worsening after an initial relapsing disease course. Despite the recent advances in our understanding of the disease, the diagnosis and treatment of SPMS continue to be challenging in routine clinical practice. The aim of this review article is to present the views of leading MS experts on the challenges in the diagnosis and management of SPMS and clinicians' perspectives in Central and Eastern Europe. This article also provides recommendations of MS experts to improve the situation with diagnosis and management of SPMS. Many countries within Central and Eastern Europe have high prevalence of MS (>100 per 100,000 population). Consistent with the global trend, in the absence of reliable tests or biomarkers, SPMS at early stage remains undiagnosed. Due to diagnostic uncertainty and lack of a universally accepted disease definition, clinicians rely more on retrospective analysis of the clinical symptoms to confirm the diagnosis. With the lack of awareness and poor understanding of the timing of the onset of SPMS, clinicians may tend to direct attention to relapses than the symptoms of progression, which leads to underestimation of SPMS. Although several predictors of progression to SPMS have been identified, their predictive value is highly variable. Therefore, defining the transitioning period as a separate stage of MS is essential. According to experts' opinion, frequent follow-up of patients and periodic assessment of progression are recommended for the timely identification of patients transitioning from RRMS to SPMS. MSProDiscuss Tool is an example of a quick assessment tool for identifying patients progressing from RRMS to SPMS. MS progression is usually assessed by changes in Expanded Disability Status Scale (EDSS) scores. As EDSS scores tend to fluctuate when measured in the short term (3-6 months), a longer period (≥12 months) may be needed to confirm the progression. Assessment of cognitive function is also important for evaluating secondary progression. Compartmentalization of inflammation within the central nervous system is an important reason behind the limited success of disease-modifying therapies (DMTs) for treating SPMS. Most of the DMTs fail to cross the blood-brain barrier; only 38% of the tested DMTs achieved their primary endpoint in SPMS. In Europe, siponimod is the first oral treatment for adults with active SPMS. Particularly, in Central and Eastern Europe, patients with SPMS are still being prescribed less efficacious DMTs and interferons. The absence of alternative treatments in SPMS supports the use of new products (siponimod and others); however the decision to initiate siponimod therapy in more severe patients (EDSS score of 7 or higher) should be individualized in consultation with the payers. The focus should be on early treatment initiation to delay disease progression.

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

BACKGROUND AND RATIONALE

Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining.

METHODS

Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor.

RESULTS

In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings.

CONCLUSION

Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.

Neurophysiological impairments in multiple sclerosis-Central and peripheral motor pathways

A systematic review of the literature was conducted comparing neurophysiological outcomes in persons with multiple sclerosis (PwMS) to healthy controls (HC), in studies of the central nervous system (CNS) function comprising motor evoked potentials (MEP) elicited by transcranial magnetic stimulation (TMS) and in studies of the peripheral nervous system (PNS) function comprising electroneuronography (ENG) outcomes elicited by peripheral nerve stimulation. Studies comparing neuromuscular function, assessed during maximal voluntary contraction (MVC) of muscle, were included if they reported muscle strength along with muscle activation by use of electromyography (EMG) and/or interpolated twitch technique (ITT). Studies investigating CNS function showed prolonged central motor conduction times, asymmetry of nerve conduction motor pathways, and prolonged latencies in PwMS when compared to HC. Resting motor threshold, amplitude, and cortical silent periods showed conflicting results. CNS findings generally correlated with disabilities. Studies of PNS function showed near significant prolongation in motor latency of the median nerve, reduced nerve conduction velocities in the tibial and peroneal nerves, and decreased compound muscle action potential amplitudes of the tibial nerve in PwMS. ENG findings did not correlate with clinical severity of disabilities. Studies of neuromuscular function showed lower voluntary muscle activation and increased central fatigue in PwMS, whereas EMG showed divergent muscle activation (ie, EMG amplitude) during MVC. When comparing the existing literature on neurophysiological motor examinations in PwMS and HC, consistent and substantial impairments of CNS function were seen in PwMS, whereas impairments of the PNS were less pronounced and inconsistent. In addition, impairments in muscle activation were observed in PwMS.

Characterization of multiple sclerosis lesions with distinct clinical correlates through quantitative diffusion MRI

Diffusion magnetic resonance imaging can reveal quantitative information about the tissue changes in multiple sclerosis. The recently developed multi-compartment spherical mean technique can map different microscopic properties based only on local diffusion signals, and it may provide specific information on the underlying microstructural modifications that arise in multiple sclerosis. Given that the lesions in multiple sclerosis may reflect different degrees of damage, we hypothesized that quantitative diffusion maps may help characterize the severity of lesions "in vivo" and correlate these to an individual's clinical profile. We evaluated this in a cohort of 59 multiple sclerosis patients (62% female, mean age 44.7 years), for whom demographic and disease information was obtained, and who underwent a comprehensive physical and cognitive evaluation. The magnetic resonance imaging protocol included conventional sequences to define focal lesions, and multi-shell diffusion imaging was used with b-values of 1000, 2000 and 3000 s/mm² in 180 encoding directions. Quantitative diffusion properties on a macro- and micro-scale were used to discriminate distinct types of lesions through a k-means clustering algorithm, and the number and volume of those lesion types were correlated with parameters of the disease. The combination of diffusion tensor imaging metrics (fractional anisotropy and radial diffusivity) and multi-compartment spherical mean technique values (microscopic fractional anisotropy and intra-neurite volume fraction) differentiated two type of lesions, with a prediction strength of 0.931. The B-type lesions had larger diffusion changes compared to the A-type lesions, irrespective of their location (P < 0.001). The number of A and B type lesions was similar, although in juxtacortical areas B-type lesions predominated (60%, P < 0.001). Also, the percentage of B-type lesion volume was higher (64%, P < 0.001), indicating that these lesions were larger. The number and volume of B-type lesions was related to the severity of disease evolution, clinical disability and cognitive decline (P = 0.004, Bonferroni correction). Specifically, more and larger B-type lesions were correlated with a worse Multiple Sclerosis Severity Score, cerebellar function and cognitive performance. Thus, by combining several microscopic and macroscopic diffusion properties, the severity of damage within focal lesions can be characterized, further contributing to our understanding of the mechanisms that drive disease evolution. Accordingly, the classification of lesion types has the potential to permit more specific and better-targeted treatment of patients with multiple sclerosis.

Measurements of the corpus callosum index and fractional anisotropy of the corpus callosum and their cutoff values are useful to assess global brain volume loss in multiple sclerosis

OBJECTIVES

Recent studies suggest that parameters of the corpus callosum (CC), such as the CC index (CCI) and fractional anisotropy (FA) of the CC, may be related to the degree of brain volume loss (BVL) in MS patients; however, cutoff values that determine the degree of BVL have not been set.

METHODS

Seventy-five MS patients and 21 healthy controls (HCs) underwent volumetric MRI examinations. MS patients were also evaluated for T2 lesion load, the CCI, and FA of the CC. Among the 75 MS patients, 20 had undergone cognitive assessments with the Symbol Digit Modalities Test (SDMT). After 75 MS patients were categorized into mild, moderate, or severe BVL subgroups according to our previous report, we performed receiver operating characteristic analysis to determine the cutoff values of CCI and FA, categorizing the MS patients into the three subgroups.

RESULTS

The volume of the CC was significantly reduced in MS patients compared to that in HCs. The CCI and FA were significantly associated with EDSS, disease duration, clinical phenotype, T2-lesion load, and whole brain volume. The FA was significantly correlated with the SDMT score. We identified optimal cutoff values for the CCI and FA of 0.32 (85% sensitivity, 92% specificity) and 0.39 (100% sensitivity, 92% specificity), respectively, which discriminated the severe BVL group from others, and 0.385 (84% sensitivity, 74% specificity) and 0.45 (81% sensitivity, 89% specificity), respectively, which discriminated the mild BVL group from others.

CONCLUSION

The CCI and FA cutoff values may be useful for evaluating the degree of MS brain atrophy in clinical practice.

Approved and Emerging Disease Modifying Therapies on Neurodegeneration in Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune, chronic, progressive disease leading to a combination of inflammation, demyelination, and neurodegeneration throughout the central nervous system (CNS). The outcome of these processes can be visualized in magnetic resonance imaging (MRI) scans as brain atrophy, or brain volume loss (BVL), as well as lesions, “black holes” and spinal cord atrophy. MRI outcomes such as BVL have been used as biomarkers of neurodegeneration and other measures of MS disease progression in clinical research settings. Several FDA-approved medications seek to alleviate disease progression by reducing the impact of such factors as demyelination and neurodegeneration, but there are still many shortcomings that current clinical research aims to mitigate. This review attempts to provide an overview of the FDA-approved medications available for treating multiple sclerosis and their effect on neurodegeneration, measured by BVL.

Visualizing the Central Nervous System: Imaging Tools for Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) are autoimmune central nervous system conditions with increasing incidence and prevalence. While MS is the most frequent inflammatory CNS disorder in young adults, NMOSD is a rare disease, that is pathogenetically distinct from MS, and accounts for approximately 1% of demyelinating disorders, with the relative proportion within the demyelinating CNS diseases varying widely among different races and regions. Most immunomodulatory drugs used in MS are inefficacious or even harmful in NMOSD, emphasizing the need for a timely and accurate diagnosis and distinction from MS. Despite distinct immunopathology and differences in disease course and severity there might be considerable overlap in clinical and imaging findings, posing a diagnostic challenge for managing neurologists. Differential diagnosis is facilitated by positive serology for AQP4-antibodies (AQP4-ab) in NMOSD, but might be difficult in seronegative cases. Imaging of the brain, optic nerve, retina and spinal cord is of paramount importance when managing patients with autoimmune CNS conditions. Once a diagnosis has been established, imaging techniques are often deployed at regular intervals over the disease course as surrogate measures for disease activity and progression and to surveil treatment effects. While the application of some imaging modalities for monitoring of disease course was established decades ago in MS, the situation is unclear in NMOSD where work on longitudinal imaging findings and their association with clinical disability is scant. Moreover, as long-term disability is mostly attack-related in NMOSD and does not stem from insidious progression as in MS, regular follow-up imaging might not be useful in the absence of clinical events. However, with accumulating evidence for covert tissue alteration in NMOSD and with the advent of approved immunotherapies the role of imaging in the management of NMOSD may be reconsidered. By contrast, MS management still faces the challenge of implementing imaging techniques that are capable of monitoring progressive tissue loss in clinical trials and cohort studies into treatment algorithms for individual patients. This article reviews the current status of imaging research in MS and NMOSD with an emphasis on emerging modalities that have the potential to be implemented in clinical practice.

Cortical axonal loss is associated with both gray matter demyelination and white matter tract pathology in progressive multiple sclerosis: Evidence from a combined MRI-histopathology study

Background:

Neuroaxonal degeneration is one of the hallmarks of clinical deterioration in progressive multiple sclerosis (PMS).

Objective:

To elucidate the association between neuroaxonal degeneration and both local cortical and connected white matter (WM) tract pathology in PMS.

Methods:

Post-mortem in situ 3T magnetic resonance imaging (MRI) and cortical tissue blocks were collected from 16 PMS donors and 10 controls. Cortical neuroaxonal, myelin, and microglia densities were quantified histopathologically. From diffusion tensor MRI, fractional anisotropy, axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were quantified in normal-appearing white matter (NAWM) and white matter lesions (WML) of WM tracts connected to dissected cortical regions. Between-group differences and within-group associations were investigated through linear mixed models.

Results:

The PMS donors displayed significant axonal loss in both demyelinated and normal-appearing (NA) cortices (p < 0.001 and p = 0.02) compared with controls. In PMS, cortical axonal density was associated with WML MD and AD (p = 0.003; p = 0.02, respectively), and NAWM MD and AD (p = 0.04; p = 0.049, respectively). NAWM AD and WML AD explained 12.6% and 22.6%, respectively, of axonal density variance in NA cortex. Additional axonal loss in demyelinated cortex was associated with cortical demyelination severity (p = 0.002), explaining 34.4% of axonal loss variance.

Conclusion:

Reduced integrity of connected WM tracts and cortical demyelination both contribute to cortical axonal loss in PMS.

Gray matter network reorganization in multiple sclerosis from 7-Tesla and 3-Tesla MRI data

Objective

The objective of this study was to determine the ability of 7T‐MRI for characterizing brain tissue integrity in early relapsing‐remitting MS patients compared to conventional 3T‐MRI and to investigate whether 7T‐MRI improves the performance for detecting cortical gray matter neurodegeneration and its associated network reorganization dynamics.

Methods

Seven early relapsing‐remitting MS patients and seven healthy individuals received MRI at 7T and 3T, whereas 30 and 40 healthy controls underwent separate 3T‐ and 7T‐MRI sessions, respectively. Surface‐based cortical thickness (CT) and gray‐to‐white contrast (GWc) measures were used to model morphometric networks, analyzed with graph theory by means of modularity, clustering coefficient, path length, and small‐worldness.

Results

7T‐MRI had lower CT and higher GWc compared to 3T‐MRI in MS. CT and GWc measures robustly differentiated MS from controls at 3T‐MRI. 7T‐ and 3T‐MRI showed high regional correspondence for CT (r = 0.72, P = 2e‐78) and GWc (r = 0.83, P = 5.5e‐121) in MS patients. MS CT and GWc morphometric networks at 7T‐MRI showed higher modularity, clustering coefficient, and small‐worldness than 3T, also compared to controls.

Interpretation

7T‐MRI allows to more precisely quantify morphometric alterations across the cortical mantle and captures more sensitively MS‐related network reorganization. Our findings open new avenues to design more accurate studies quantifying brain tissue loss and test treatment effects on tissue repair.

A validation study of manual atrophy measures in patients with Multiple Sclerosis

PURPOSE

Manual measures such as corpus callosum index, normalized corpus callosum area, and width of the third ventricle are potential biomarkers for brain atrophy. In this work, we investigate their suitability to assess the neurodegenerative component of multiple sclerosis (MS) by comparing them to volumetric measures and expanded disability status scale (EDSS).

METHODS

Fifty-eight patients with a clinically isolated syndrome, 48 MS patients treated with interferon β, and 26 treated with natalizumab underwent a brain MRI at baseline and after 1 year. Manual measures were evaluated by two observers using Jim v.6.0 at both time points. Volumetric tools (SIENA/x and Freesurfer) were used to calculate normalized brain volume, brain parenchymal fraction, annualized percentage of brain volume change, corpus callosum volume, ventricle volume, and volume of the third ventricle. Statistical analyses were performed with SPSS v.13.

RESULTS

Usage of corpus callosum volume and third ventricle volume to validate normalized corpus callosum area and width of the third ventricle, respectively, showed very good correlations (r = 0.85, r = 0.83; p < 0.01). Width of the third ventricle, corpus callosum index, and normalized corpus callosum area correlations were significant with EDSS in all patients and moderate to strong with normalized brain volume and brain parenchymal fraction in natalizumab-treated patients (respectively r = - 0.54, r = - 0.61; r = 0.55, r = 0.67; and r = 0.58, r = 0.67; with p < 0.05).

CONCLUSION

Width of the third ventricle and normalized corpus callosum area seem the more robust manual measures regarding correlation with volumetric measures and EDSS, especially in patients with more advanced disease.

Number of MRI T1-hypointensity corrected by T2/FLAIR lesion volume indicates clinical severity in patients with multiple sclerosis

INTRODUCTION

Progressive brain atrophy, development of T1-hypointense areas, and T2-fluid-attenuated inversion recovery (FLAIR)-hyperintense lesion formation in multiple sclerosis (MS) are popular volumetric data that are often utilized as clinical outcomes. However, the exact clinical interpretation of these volumetric data has not yet been fully established.

METHODS

We enrolled 42 consecutive patients with MS who fulfilled the revised McDonald criteria of 2010. They were followed-up for more than 3 years from onset, and cross-sectional brain volumetry was performed. Patients with no brain lesions were excluded in advance from this study. For the brain volumetric data, we evaluated several parameters including age-adjusted gray-matter volume atrophy, age-adjusted white-matter volume atrophy, and T2-FLAIR lesion volume. The numbers of T1-hypointense and T2-FLAIR-hyperintense areas were also measured along the same timeline. The clinical data pertaining to disease duration, expanded disability status scale (EDSS), and MS severity score (MSSS) at the timing of volumetry were collected.

RESULTS

Among the 42 patients with MS and brain lesions, the number of T1-hypointensity (rho = 0.51, p<0.001), gray-matter atrophy (rho = 0.40, p<0.01) and white-matter atrophy (rho = 0.49, p<0.001) correlated with the EDSS. T1-hypointensity count divided by FLAIR lesion volume correlated with the MSSS (rho = 0.60, p<0.001). Meanwhile, counts or volumes of FLAIR-hyperintense lesions were associated only with the times of past relapses, and did not correlate with present neurological disability level or ongoing disease activity. These findings were consistent regardless of the presence of spinal cord lesions.

CONCLUSION

Numbers of T1-hypointensities and brain atrophy equally indicated the current neurological disability in MS. The number of T1-hypointensities divided by FLAIR lesion volume represented the clinical severity. The size or number of FLAIR lesions reflected earlier relapses but was not a good indicator of neurological disability or clinical severity.

Early perfusion changes in multiple sclerosis patients as assessed by MRI using arterial spin labeling

Background

Gadolinium-perfusion magnetic resonance (MR) identifies gray matter abnormalities in early multiple sclerosis (MS), even in the absence of structural differences. These perfusion changes could be related to the cognitive disability of these patients, especially in the working memory. Arterial spin labeling (ASL) is a relatively recent perfusion technique that does not require intravenous contrast, making the technique especially attractive for clinical research.

Purpose

To verify the perfusion alterations in early MS, even in the absence of cerebral volume changes. To introduce the ASL sequence as a suitable non-invasive method in the monitoring of these patients.

Material and Methods

Nineteen healthy controls and 28 patients were included. The neuropsychological test EDSS and SDMT were evaluated. Cerebral blood flow and bolus arrival time were collected from the ASL study. Cerebral volume and cortical thickness were obtained from the volumetric T1 sequence. Spearman's correlation analyzed the correlation between EDSS and SDMT tests and perfusion data. Differences were considered significant at a level of P < 0.05.

Results

Reduction of the cerebral blood flow and an increase in the bolus arrival time were found in patients compared to controls. A negative correlation between EDSS and thalamus transit time, and between EDSS and cerebral blood flow in the frontal cortex, was found.

Conclusion

ASL perfusion might detect changes in MS patients even in absent structural volumetric changes. More longitudinal studies are needed, but perfusion parameters could be biomarkers for monitoring these patients.

Low CSF β-amyloid levels predict early regional grey matter atrophy in multiple sclerosis

BACKGROUND AND PURPOSE

Grey matter (GM) atrophy is present from the earliest stages of multiple sclerosis (MS) and occurs largely in a nonrandom manner. However, the biological mechanisms underlying the progression of regional atrophy are still unclear. Aim of this study is to investigate whether amyloid pathology might be involved in determining the pattern of GM atrophy over time.

METHODS

Forty-six subjects were recruited: 31 newly diagnosed relapsing-remitting (RR-) MS patients and 15 age- and sex-matched healthy controls (HC). Aβ levels were determined in CSF samples from all subjects. All participants underwent brain magnetic resonance imaging (MRI) at baseline, and 23 out of 31 patients at one year follow-up. T1-weighted scans were segmented using the Geodesic Information Flows software. Non-parametric statistical tests were used for between-group comparisons and multiple regression analyses.

RESULTS

CSF Aβ concentration was the best predictor of global GM loss over time after age (β = 0.403; p = 0.024), in particular in the left precuneus (p = 0.045), in the left middle cingulate gyrus (p = 0.009), in the left precentral gyrus (p = 0.021) and in the right angular gyrus (p = 0.029).

CONCLUSIONS

CSF Aβ levels seem to be crucial in MS early brain volume loss as GM atrophy manifests in regions particularly vulnerable to early Aβ deposition.

Brain atrophy in multiple sclerosis: mechanisms, clinical relevance and treatment options

Multiple sclerosis (MS) is an immune-mediated disease of the central nervous system characterized by focal or diffuse inflammation, demyelination, axonal loss and neurodegeneration. Brain atrophy can be seen in the earliest stages of MS, progresses faster compared to healthy adults, and is a reliable predictor of future physical and cognitive disability. In addition, it is widely accepted to be a valid, sensitive and reproducible measure of neurodegeneration in MS. Reducing the rate of brain atrophy has only recently been incorporated as a critical endpoint into the clinical trials of new or emerging disease modifying drugs (DMDs) in MS. With the advent of easily accessible neuroimaging softwares along with the accumulating evidence, clinicians may be able to use brain atrophy measures in their everyday clinical practice to monitor disease course and response to DMDs. In this review, we will describe the different mechanisms contributing to brain atrophy, their clinical relevance on disease presentation and course and the effect of current or emergent DMDs on brain atrophy and neuroprotection.

Brain and lesion segmentation in multiple sclerosis using fully convolutional neural networks: A large-scale study

OBJECTIVE

To investigate the performance of deep learning (DL) based on fully convolutional neural network (FCNN) in segmenting brain tissues in a large cohort of multiple sclerosis (MS) patients.

METHODS

We developed a FCNN model to segment brain tissues, including T2-hyperintense MS lesions. The training, validation, and testing of FCNN were based on ~1000 magnetic resonance imaging (MRI) datasets acquired on relapsing-remitting MS patients, as a part of a phase 3 randomized clinical trial. Multimodal MRI data (dual-echo, FLAIR, and T1-weighted images) served as input to the network. Expert validated segmentation was used as the target for training the FCNN. We cross-validated our results using the leave-one-center-out approach.

RESULTS

We observed a high average (95% confidence limits) Dice similarity coefficient for all the segmented tissues: 0.95 (0.92-0.98) for white matter, 0.96 (0.93-0.98) for gray matter, 0.99 (0.98-0.99) for cerebrospinal fluid, and 0.82 (0.63-1.0) for T2 lesions. High correlations between the DL segmented tissue volumes and ground truth were observed (R² > 0.92 for all tissues). The cross validation showed consistent results across the centers for all tissues.

CONCLUSION

The results from this large-scale study suggest that deep FCNN can automatically segment MS brain tissues, including lesions, with high accuracy.

Gray Matter Atrophy to Explain Subclinical Oculomotor Deficit in Multiple Sclerosis

Eye movement deficits are frequently noted in multiple sclerosis during bedside clinical examination, but subtle dysfunction may remain undetected and might only be identified with advanced approaches. While classical neurology provides insight into the complex functional anatomy of oculomotor functions, little is known about the structural background of this dysfunction in MS. Thirty four clinically stable, treated relapsing-remitting MS patients with mild disability and 34 healthy controls were included in our study. Group difference and correlation with clinical parameters were analyzed in case of the latency, peak-velocity, gain, dysconjugacy index, and performance during a saccade and anti-saccade task. High-resolution T1 weighted, T2 FLAIR, and double inversion recovery images were acquired on 3T to evaluate the correlation between behavioral and MRI parameters, such as T2 lesion and T1 black-hole burden, global brain, gray, and white matter atrophy. VBM style analysis was used to identify the focal gray matter atrophy responsible for oculomotor dysfunction. Significantly increased latency in the prosaccade task and significantly worse performance in the anti-saccade task were found in MS patients. The detailed examination of conjugated eye movements revealed five subclinical internuclear ophthalmoparesis cases. The peak velocity and latency of the anti-saccade movement correlated with the number of black holes, but none of the eye movement parameters were associated with the T2 lesion burden or location. Global gray matter volume correlated with saccade and anti-saccade latency, whereas white matter and total brain volume did not. Local gray matter atrophy in the left inferio-parietal lobule and temporo-occipital junction correlated with anti-saccade peak velocity. Our results show that neurodegeneration-like features of the MRI (black-hole, gray matter atrophy) are the best predictors of eye movement deficit in MS. Concurring with the clinico-radiological paradox, T2 lesion burden cannot explain the behavioral results. Importantly, anti-saccade peak velocity correlates with gray matter atrophy in the left parietal regions, which are frequently implicated in attention tasks.

Cross-Sectional and Longitudinal MRI Brain Scans Reveal Accelerated Brain Aging in Multiple Sclerosis

Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By combining longitudinal MRI-based brain morphometry and brain age estimation using machine learning, we tested the hypothesis that MS patients have higher brain age relative to chronological age than healthy controls (HC) and that longitudinal rate of brain aging in MS patients is associated with clinical course and severity. Seventy-six MS patients [71% females, mean age 34.8 years (range 21-49) at inclusion] were examined with brain MRI at three time points with a mean total follow up period of 4.4 years (±0.4 years). We used additional cross-sectional MRI data from 235 HC for case-control comparison. We applied a machine learning model trained on an independent set of 3,208 HC to estimate individual brain age and to calculate the difference between estimated and chronological age, termed brain age gap (BAG). We also assessed the longitudinal change rate in BAG in individuals with MS. MS patients showed significantly higher BAG (4.4 ± 6.6 years) compared to HC (Cohen's D = 0.69, p = 4.0 × 10-6). Longitudinal estimates of BAG in MS patients showed high reliability and suggested an accelerated rate of brain aging corresponding to an annual increase of 0.41 (SE = 0.15) years compared to chronological aging (p = 0.008). Multiple regression analyses revealed higher rate of brain aging in patients with more brain atrophy (Cohen's D = 0.86, p = 4.3 × 10-15) and increased white matter lesion load (WMLL) (Cohen's D = 0.55, p = 0.015). On average, patients with MS had significantly higher BAG compared to HC. Progressive brain aging in patients with MS was related to brain atrophy and increased WMLL. No significant clinical associations were found in our sample, future studies are warranted on this matter. Brain age estimation is a promising method for evaluation of subtle brain changes in MS, which is important for predicting clinical outcome and guide choice of intervention.

Evaluation of Intra- and Interscanner Reliability of MRI Protocols for Spinal Cord Gray Matter and Total Cross-Sectional Area Measurements

BACKGROUND

In vivo quantification of spinal cord atrophy in neurological diseases using MRI has attracted increasing attention.

PURPOSE

To compare across different platforms the most promising imaging techniques to assess human spinal cord atrophy.

STUDY TYPE

Test/retest multiscanner study.

SUBJECTS

Twelve healthy volunteers.

FIELD STRENGTH/SEQUENCE

Three different 3T scanner platforms (Siemens, Philips, and GE) / optimized phase sensitive inversion recovery (PSIR), T1 -weighted (T1 -w), and T2 *-weighted (T2 *-w) protocols.

ASSESSMENT

On all images acquired, two operators assessed contrast-to-noise ratio (CNR) between gray matter (GM) and white matter (WM), and between WM and cerebrospinal fluid (CSF); one experienced operator measured total cross-sectional area (TCA) and GM area using JIM and the Spinal Cord Toolbox (SCT).

STATISTICAL TESTS

Coefficient of variation (COV); intraclass correlation coefficient (ICC); mixed effect models; analysis of variance (t-tests).

RESULTS

For all the scanners, GM/WM CNR was higher for PSIR than T2 *-w (P < 0.0001) and WM/CSF CNR for T1 -w was the highest (P < 0.0001). For TCA, using JIM, median COVs were smaller than 1.5% and ICC >0.95, while using SCT, median COVs were in the range 2.2-2.75% and ICC 0.79-0.95. For GM, despite some failures of the automatic segmentation, median COVs using SCT on T2 *-w were smaller than using JIM manual PSIR segmentations. In the mixed effect models, the subject was always the main contributor to the variance of area measurements and scanner often contributed to TCA variance (P < 0.05). Using JIM, TCA measurements on T2 *-w were different than on PSIR (P = 0.0021) and T1 -w (P = 0.0018), while using SCT, no notable differences were found between T1 -w and T2 *-w (P = 0.18). JIM and SCT-derived TCA were not different on T1 -w (P = 0.66), while they were different for T2 *-w (P < 0.0001). GM area derived using SCT/T2 *-w versus JIM/PSIR were different (P < 0.0001).

DATA CONCLUSION

The present work sets reference values for the magnitude of the contribution of different effects to cord area measurement intra- and interscanner variability.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;49:1078-1090.

Brazilian Consensus for the Treatment of Multiple Sclerosis: Brazilian Academy of Neurology and Brazilian Committee on Treatment and Research in Multiple Sclerosis

The expanding therapeutic arsenal in multiple sclerosis (MS) has allowed for more effective and personalized treatment, but the choice and management of disease-modifying therapies (DMTs) is becoming increasingly complex. In this context, experts from the Brazilian Committee on Treatment and Research in Multiple Sclerosis and the Neuroimmunology Scientific Department of the Brazilian Academy of Neurology have convened to establish this Brazilian Consensus for the Treatment of MS, based on their understanding that neurologists should be able to prescribe MS DMTs according to what is better for each patient, based on up-to-date evidence and practice. We herein propose practical recommendations for the treatment of MS, with the main focus on the choice and management of DMTs, as well as present a review of the scientific rationale supporting therapeutic strategies in MS.

MRI in multiple sclerosis: clinical and research update

PURPOSE OF REVIEW

Clinical MRI is of paramount importance for multiple sclerosis diagnosis but lacks the specificity to investigate the pathogenic mechanisms underlying disease onset and progression. The application of advanced MR sequences allows the characterization of diverse and complex pathological mechanisms, granting insights into multiple sclerosis natural history and response to treatment.

RECENT FINDINGS

This review provides an update on the most recent international guidelines for optimal standard imaging of multiple sclerosis and discusses advantages and limitations of advanced imaging approaches for investigating inflammation, demyelination and neurodegeneration. An overview is provided for methods devoted to imaging leptomeningeal enhancement, microglial activation, demyelination, neuronal metabolic damage and neuronal loss.

SUMMARY

The application of magnetic resonance (MR) guidelines to standard-of-care MR protocols, although still limited, would substantially contribute to the optimization of multiple sclerosis management. From an academic perspective, different mechanism-specific imaging techniques are available and offer a powerful tool to elucidate multiple sclerosis pathogenesis, monitor disease progression and guide therapeutic choices.