MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice

Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?

OBJECTIVES

This study investigates the influence of normal cohort (NC) size and the impact of different NCs on automated MRI-based brain atrophy estimation.

METHODS

A pooled NC of 3945 subjects (NCpool) was retrospectively created from five publicly available cohorts. Voxel-wise gray matter volume atrophy maps were calculated for 48 Alzheimer's disease (AD) patients (55-82 years) using veganbagel and dynamic normal templates with an increasing number of healthy subjects randomly drawn from NCpool (initially three, and finally 100 subjects). Over 100 repeats of the process, the mean over a voxel-wise standard deviation of gray matter z-scores was established and plotted against the number of subjects in the templates. The knee point of these curves was defined as the minimum number of subjects required for consistent brain atrophy estimation. Atrophy maps were calculated using each NC for AD patients and matched healthy controls (HC). Two readers rated the extent of mesiotemporal atrophy to discriminate AD/HC.

RESULTS

The maximum knee point was at 15 subjects. For 21 AD/21 HC, a sufficient number of subjects were available in each NC for validation. Readers agreed on the AD diagnosis in all cases (Kappa for the extent of atrophy, 0.98). No differences in diagnoses between NCs were observed (intraclass correlation coefficient, 0.91; Cochran's Q, p = 0.19).

CONCLUSION

At least 15 subjects should be included in age- and sex-specific normal templates for consistent brain atrophy estimation. In the study's context, qualitative interpretation of regional atrophy allows reliable AD diagnosis with a high inter-reader agreement, irrespective of the NC used.

CLINICAL RELEVANCE STATEMENT

The influence of normal cohorts (NCs) on automated brain atrophy estimation, typically comparing individual scans to NCs, remains largely unexplored. Our study establishes the minimum number of NC-subjects needed and demonstrates minimal impact of different NCs on regional atrophy estimation.

KEY POINTS

• Software-based brain atrophy estimation often relies on normal cohorts for comparisons. • At least 15 subjects must be included in an age- and sex-specific normal cohort. • Using different normal cohorts does not influence regional atrophy estimation.

Routine MR Imaging Protocol and Standardization in Central Nervous System Demyelinating Diseases

Standardized MR imaging protocols are important for the diagnosis and monitoring of patients with multiple sclerosis (MS) and the appropriate use of MR imaging in routine clinical practice. Advances in using MR imaging to establish an earlier diagnosis of MS, safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MR imaging for diagnostic, prognostic, and monitoring purposes suggest a changing role of MR imaging for the management and care of MS patients. The MR imaging protocol emphasizes 3 dimensional acquisitions for optimal comparison over time.

Advanced Brain Imaging in Central Nervous System Demyelinating Diseases

In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.

Treatment Monitoring in Multiple Sclerosis - Efficacy and Safety

Magnetic resonance imaging is the most sensitive method for detecting inflammatory activity in multiple sclerosis, particularly in the brain where it reveals subclinical inflammation. Established MRI markers include contrast-enhancing lesions and active T2 lesions. Recent promising markers like slowly expanding lesions and phase rim lesions are being explored for monitoring chronic inflammation, but require further validation for clinical use. Volumetric and quantitative MRI techniques are currently limited to clinical trials and are not yet recommended for routine clinical use. Additionally, MRI is crucial for detecting complications from disease-modifying treatments and for implementing MRI-based pharmacovigilance strategies, such as in patients treated with natalizumab.

Digital outcome measures are associated with brain atrophy in patients with multiple sclerosis

BACKGROUND

Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression.

OBJECTIVE

To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS.

METHODS

In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates.

RESULTS

In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12.

CONCLUSION

Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.

Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis

Clinical, pathological, and imaging evidence in multiple sclerosis (MS) suggests that a smoldering inflammatory activity is present from the earliest stages of the disease and underlies the progression of disability, which proceeds relentlessly and independently of clinical and radiological relapses (PIRA). The complex system of pathological events driving "chronic" worsening is likely linked with the early accumulation of compartmentalized inflammation within the central nervous system as well as insufficient repair phenomena and mitochondrial failure. These mechanisms are partially lesion-independent and differ from those causing clinical relapses and the formation of new focal demyelinating lesions; they lead to neuroaxonal dysfunction and death, myelin loss, glia alterations, and finally, a neuronal network dysfunction outweighing central nervous system (CNS) compensatory mechanisms. This review aims to provide an overview of the state of the art of neuropathological, immunological, and imaging knowledge about the mechanisms underlying the smoldering disease activity, focusing on possible early biomarkers and their translation into clinical practice. ANN NEUROL 2024;96:1-20.

Advanced neuroimaging techniques to explore the effects of motor and cognitive rehabilitation in multiple sclerosis

INTRODUCTION

Progress in magnetic resonance imaging (MRI) technology and analyses is improving our comprehension of multiple sclerosis (MS) pathophysiology. These advancements, which enable the evaluation of atrophy, microstructural tissue abnormalities, and functional plasticity, are broadening our insights into the effectiveness and working mechanisms of motor and cognitive rehabilitative treatments.

AREAS COVERED

This narrative review with selected studies discusses findings derived from the application of advanced MRI techniques to evaluate structural and functional neuroplasticity modifications underlying the effects of motor and cognitive rehabilitative treatments in people with MS (PwMS). Current applications as outcome measure in longitudinal trials and observational studies, their interpretation and possible pitfalls and limitations in their use are covered. Finally, we examine how the use of these techniques could evolve in the future to improve monitoring of motor and cognitive rehabilitative treatments.

EXPERT COMMENTARY

Despite substantial variability in study design and participant characteristics in rehabilitative studies for PwMS, improvements in motor and cognitive functions accompanied by structural and functional brain modifications induced by rehabilitation can be observed. However, significant enhancements to refine rehabilitation strategies are needed. Future studies in this field should strive to implement standardized methodologies regarding MRI acquisition and processing, possibly integrating multimodal measures. This will help identifying relevant markers of treatment response in PwMS, thus improving the use of rehabilitative interventions at individual level. The combination of motor and cognitive strategies, longer periods of treatment, as well as adequate follow-up assessments will contribute to enhance the quality of evidence in support of their routine use.

Novel and Emerging Treatments to Target Pathophysiological Mechanisms in Various Phenotypes of Multiple Sclerosis

The objective is to comprehensively review novel pharmacotherapies used in multiple sclerosis (MS) and the possibilities they may carry for therapeutic improvement. Specifically, we discuss pathophysiological mechanisms worth targeting in MS, ranging from well known targets, such as autoinflammation and demyelination, to more novel and advanced targets, such as neuroaxonal damage and repair. To set the stage, a brief overview of clinical MS phenotypes is provided, followed by a comprehensive recapitulation of both clinical and paraclinical outcomes available to assess the effectiveness of treatments in achieving these targets. Finally, we discuss various promising novel and emerging treatments, including their respective hypothesized modes of action and currently available evidence from clinical trials. SIGNIFICANCE STATEMENT: This comprehensive review discusses pathophysiological mechanisms worth targeting in multiple sclerosis. Various promising novel and emerging treatments, including their respective hypothesized modes of action and currently available evidence from clinical trials, are reviewed.

Spinal cord and brain atrophy patterns in neuromyelitis optica spectrum disorder and multiple sclerosis

BACKGROUND

Spinal cord and brain atrophy are common in neuromyelitis optica spectrum disorder (NMOSD) and relapsing-remitting multiple sclerosis (RRMS) but harbor distinct patterns accounting for disability and cognitive impairment.

METHODS

This study included 209 NMOSD and 304 RRMS patients and 436 healthy controls. Non-negative matrix factorization was used to parse differences in spinal cord and brain atrophy at subject level into distinct patterns based on structural MRI. The weights of patterns were obtained using a linear regression model and associated with Expanded Disability Status Scale (EDSS) and cognitive scores. Additionally, patients were divided into cognitive impairment (CI) and cognitive preservation (CP) groups.

RESULTS

Three patterns were observed in NMOSD: (1) Spinal Cord-Deep Grey Matter (SC-DGM) pattern was associated with high EDSS scores and decline of visuospatial memory function; (2) Frontal-Temporal pattern was associated with decline of language learning function; and (3) Cerebellum-Brainstem pattern had no observed association. Patients with CI had higher weights of SC-DGM pattern than CP group. Three patterns were observed in RRMS: (1) DGM pattern was associated with high EDSS scores, decreased information processing speed, and decreased language learning and visuospatial memory functions; (2) Frontal-Temporal pattern was associated with overall cognitive decline; and (3) Occipital pattern had no observed association. Patients with CI trended to have higher weights of DGM and Frontal-Temporal patterns than CP group.

CONCLUSION

This study estimated the heterogeneity of spinal cord and brain atrophy patterns in NMOSD and RRMS patients at individual level, and evaluated the clinical relevance of these patterns, which may contribute to stratifying participants for targeted therapy.

Age-related decline in cerebral oxygen consumption in multiple sclerosis

Cerebral oxygen metabolism is altered in relapsing-remitting multiple sclerosis (RRMS), possibly a result of disease related cerebral atrophy with subsequent decreased oxygen demand. However, MS inflammation can also inhibit brain metabolism. Therefore, we measured cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) using MRI phase contrast mapping and susceptibility-based oximetry in 44 patients with early RRMS and 36 healthy controls. Cerebral atrophy and white matter lesion load were assessed from high-resolution structural MRI. Expanded Disability Status Scale (EDSS) scores were collected from medical records. The CMRO2 was significantly lower in patients (-15%, p = 0.002) and decreased significantly with age in patients relative to the controls (-1.35 µmol/100 g/min/year, p = 0.036). The lower CMRO2 in RRMS was primarily driven by a higher venous oxygen saturation in the sagittal sinus (p = 0.007) and not a reduction in CBF (p = 0.69). There was no difference in cerebral atrophy between the groups, and no correlation between CMRO2 and MS lesion volume or EDSS score. Therefore, the progressive CMRO2 decline observed before the occurrence of significant cerebral atrophy and despite adequate CBF supports emerging evidence of dysfunctional cellular respiration as a potential pathogenic mechanism and therapeutic target in RRMS.

Efficacy of intrathecal mesenchymal stem cell-neural progenitor therapy in progressive MS: results from a phase II, randomized, placebo-controlled clinical trial

BACKGROUND

Mesenchymal stem cell-neural progenitors (MSC-NPs) are a bone marrow mesenchymal stem cell (MSC)-derived ex vivo manipulated cell product with therapeutic potential in multiple sclerosis (MS). The objective of this study was to determine efficacy of intrathecal (IT) MSC-NP treatment in patients with progressive MS.

METHODS

The study is a phase II randomized, double-blind, placebo-controlled clinical trial with a compassionate crossover design conducted at a single site. Subjects were stratified according to baseline Expanded Disability Status Scale (EDSS) (3.0-6.5) and disease subtype (secondary or primary progressive MS) and randomized into either treatment or placebo group to receive six IT injections of autologous MSC-NPs or saline every two months. The primary outcome was EDSS Plus, defined by improvement in EDSS, timed 25-foot walk (T25FW) or nine-hole peg test. Secondary outcomes included the individual components of EDSS Plus, the six-minute walk test (6MWT), urodynamics testing, and brain atrophy measurement.

RESULTS

Subjects were randomized into MSC-NP (n = 27) or saline (n = 27) groups. There was no difference in EDSS Plus improvement between the MSC-NP (33%) and saline (37%) groups. Exploratory subgroup analysis demonstrated that in subjects who require assistance for ambulation (EDSS 6.0-6.5) there was a significantly higher percentage of improvement in T25FW and 6MWT in the MSC-NP group (3.7% ± 23.1% and - 9.2% ± 18.2%) compared to the saline group (-54.4% ± 70.5% and - 32.1% ± 30.0%), (p = 0.030 and p = 0.036, respectively). IT-MSC-NP treatment was also associated with improved bladder function and reduced rate of grey matter atrophy on brain MRI. Biomarker analysis demonstrated increased MMP9 and decreased CCL2 levels in the cerebrospinal fluid following treatment.

CONCLUSION

Results from exploratory outcomes suggest that IT-MSC-NP treatment may be associated with a therapeutic response in a subgroup of MS patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03355365, registered November 14, 2017, https://clinicaltrials.gov/study/NCT03355365?term=NCT03355365&rank=1 .

Lifestyle management and brain MRI metrics in female Australian adults living with multiple sclerosis: a feasibility and acceptability study

BACKGROUND

Limited studies of multiple sclerosis (MS) exist whereby magnetic resonance imaging (MRI) of the brain with consistent imaging protocols occurs at the same time points as collection of healthy lifestyle measures. The aim of this study was to test the feasibility, acceptability and preliminary efficacy of acquiring MRI data as an objective, diagnostic and prognostic marker of MS, at the same time point as brain-healthy lifestyle measures including diet.

METHODS

Participants living with relapsing remitting MS partook in one structural MRI scanning session of the brain, completed two online 24-hour dietary recalls and demographic and self-reported lifestyle questionnaires (e.g. self-reported disability, comorbidities, physical activity, smoking status, body mass index (BMI), stress). Measures of central tenancy and level of dispersion were calculated for feasibility and acceptability of the research protocols. Lesion count was determined by one radiologist and volumetric analyses by a data analysis pipeline based on FreeSurfer software suite. Correlations between white matter lesion count, whole brain volume analyses and lifestyle measures were assessed using Spearman's rank-order correlation coefficient.

RESULTS

Thirteen female participants were included in the study: eligibility rate 90.6% (29/32), recruitment rate 46.9% (15/32) and compliance rate 87% (13/15). The mean time to complete all required tasks, including MRI acquisition was 115.86 minutes ( ± 23.04), over 4 days. Conversion to usual dietary intake was limited by the small sample. There was one strong, negative correlation between BMI and brain volume (rs = -0.643, p = 0.018) and one strong, positive correlation between physical activity and brain volume (rs = 0.670, p = 0.012) that were both statistically significant.

CONCLUSIONS

Acquiring MRI brain scans at the same time point as lifestyle profiles in adults with MS is both feasible and accepted among adult females living with MS. Quantification of volumetric MRI data support further investigations using semi-automated pipelines among people living with MS, with pre-processing steps identified to increase automated feasibility. This protocol may be used to determine relationships between elements of a brain-healthy lifestyle, including dietary intake, and measures of disease burden and brain health, as assessed by T1-weighted and T2-weighted lesion count and whole brain volume, in an adequately powered sample.

TRIAL REGISTRATION

The study protocol was retrospectively registered in the Australia New Zealand Clinical Trials Registry (ACTRN12624000296538).

Brain and spinal cord atrophy in NMOSD and MOGAD: Current evidence and future perspectives

Neuromyelitis optica spectrum disorder (NMOSD) is a severe form of inflammation of the central nervous system (CNS) including acute myelitis, optic neuritis and brain syndrome. Currently, the classification of NMOSD relies on serologic testing, distinguishing between seropositive or seronegative anti-aquaporin-4 antibody (AQP4) status. However, the situation has recently grown more intricate with the identification of patients exhibiting the NMOSD phenotype and myelin oligodendrocyte glycoprotein antibodies (MOGAD). NMOSD is primarily recognized as a relapsing disorder; MOGAD can manifest with either a monophasic or relapsing course. Significant symptomatic inflammatory CNS injuries with stability in clinical findings outside the acute phase are reported in both diseases. Nevertheless, recent studies have proposed the existence of a subclinical pathological process, revealing longitudinal changes in brain and spinal cord atrophy. Within this context, we summarise key studies investigating brain and spinal cord measurements in adult NMOSD and MOGAD. We also explore their relationship with clinical aspects, highlight differences from multiple sclerosis (MS), and address future challenges. This exploration is crucial for determining the presence of chronic damage processes, enabling the customization of therapeutic interventions irrespective of the acute phase of the disease.

The Time Trajectory of Choroid Plexus Enlargement in Multiple Sclerosis

Choroid plexus (CP) can be seen as a watchtower of the central nervous system (CNS) that actively regulates CNS homeostasis. A growing body of literature suggests that CP alterations are involved in the pathogenesis of multiple sclerosis (MS) but the underlying mechanisms remain elusive. CPs are enlarged and inflamed in relapsing-remitting (RRMS) but also in clinically isolated syndrome (CIS) and radiologically isolated syndrome (RIS) stages, far beyond MS diagnosis. Increases in the choroid plexus/total intracranial volume (CP/TIV) ratio have been robustly associated with increased lesion load, higher translocator protein (TSPO) uptake in normal-appearing white matter (NAWM) and thalami, as well as with higher annual relapse rate and disability progression in highly active RRMS individuals, but not in progressive MS. The CP/TIV ratio has only slightly been correlated with magnetic resonance imaging (MRI) findings (cortical or whole brain atrophy) and clinical outcomes (EDSS score) in progressive MS. Therefore, we suggest that plexus volumetric assessments should be mainly applied to the early disease stages of MS, whereas it should be taken into consideration with caution in progressive MS. In this review, we attempt to clarify the pathological significance of the temporal CP volume (CPV) changes in MS and highlight the pitfalls and limitations of CP volumetric analysis.

Magnetic Resonance Imaging Evidence Supporting the Efficacy of Cladribine Tablets in the Treatment of Relapsing-Remitting Multiple Sclerosis

Numerous therapies are currently available to modify the disease course of multiple sclerosis (MS). Magnetic resonance imaging (MRI) plays a pivotal role in assessing treatment response by providing insights into disease activity and clinical progression. Integrating MRI findings with clinical and laboratory data enables a comprehensive assessment of the disease course. Among available MS treatments, cladribine is emerging as a promising option due to its role as a selective immune reconstitution therapy, with a notable impact on B cells and a lesser effect on T cells. This work emphasizes the assessment of MRI's contribution to MS treatment, particularly focusing on the influence of cladribine tablets on imaging outcomes, encompassing data from pivotal and real-world studies. The evidence highlights that cladribine, compared with placebo, not only exhibits a reduction in inflammatory imaging markers, such as T1-Gd+, T2 and combined unique active (CUA) lesions, but also mitigates the effect on brain volume loss, particularly within grey matter. Importantly, cladribine reveals early action by reducing CUA lesions within the first months of treatment, regardless of a patient's initial conditions. The selective mechanism of action, and sustained efficacy beyond year 2, combined with its early onset of action, collectively position cladribine tablets as a pivotal component in the therapeutic paradigm for MS. Overall, MRI, along with clinical measures, has played a substantial role in showcasing the effectiveness of cladribine in addressing both the inflammatory and neurodegenerative aspects of MS.

Psychometric evaluation of the 5-item Medication Adherence Report Scale questionnaire in persons with multiple sclerosis

The 5-item Medication Adherence Report Scale (MARS-5) is a reliable and valid questionnaire for evaluating adherence in patients with asthma, hypertension, and diabetes. Validity has not been determined in multiple sclerosis (MS). We aimed to establish criterion validity and reliability of the MARS-5 in persons with MS (PwMS). Our prospective study included PwMS on dimethyl fumarate (DMF). PwMS self-completed the MARS-5 on the same day before baseline and follow-up brain magnetic resonance imaging (MRI) 3 and 9 months after treatment initiation and were graded as highly and medium adherent upon the 24-cut-off score, established by receiver operator curve analysis. Health outcomes were represented by relapse occurrence from the 1st DMF dispense till follow-up brain MRI and radiological progression (new T2 MRI lesions and quantitative analysis) between baseline and follow-up MRI. Criterion validity was established by association with the Proportion of Days Covered (PDC), new T2 MRI lesions, and Beliefs in Medicines questionnaire (BMQ). The reliability evaluation included internal consistency and the test-retest method. We included 40 PwMS (age 37.6 ± 9.9 years, 75% women), 34 were treatment-naive. No relapses were seen during the follow-up period but quantitative MRI analysis showed new T2 lesions in 6 PwMS. The mean (SD) MARS-5 score was 23.1 (2.5), with 24 PwMS graded as highly adherent. The higher MARS-5 score was associated with higher PDC (b = 0.027, P<0.001, 95% CI: (0.0134-0.0403)) and lower medication concerns (b = -1.25, P<0.001, 95% CI: (-1.93-(-0,579)). Lower adherence was associated with increased number (P = 0.00148) and total volume of new T2 MRI lesions (P = 0.00149). The questionnaire showed acceptable internal consistency (Cronbach α = 0.72) and moderate test-retest reliability (r = 0.62, P < 0.0001, 95% CI: 0.33-0.79). The MARS-5 was found to be valid and reliable for estimating medication adherence and predicting medication concerns in persons with MS.

Clinical trials for progressive multiple sclerosis: progress, new lessons learned, and remaining challenges

Despite the success of disease-modifying treatments in relapsing multiple sclerosis, for many individuals living with multiple sclerosis, progressive disability continues to accrue. How to interrupt the complex pathological processes underlying progression remains a daunting and ongoing challenge. Since 2014, several immunomodulatory approaches that have modest but clinically meaningful effects have been approved for the management of progressive multiple sclerosis, primarily for people who have active inflammatory disease. The approval of these drugs required large phase 3 trials that were sufficiently powered to detect meaningful effects on disability. New classes of drug, such as Bruton tyrosine-kinase inhibitors, are coming to the end of their trial stages, several candidate neuroprotective compounds have been successful in phase 2 trials, and innovative approaches to remyelination are now also being explored in clinical trials. Work continues to define intermediate outcomes that can provide results in phase 2 trials more quickly than disability measures, and more efficient trial designs, such as multi-arm multi-stage and futility approaches, are increasingly being used. Collaborations between patient organisations, pharmaceutical companies, and academic researchers will be crucial to ensure that future trials maintain this momentum and generate results that are relevant for people living with progressive multiple sclerosis.

Consensus statement of the Spanish Society of Neurology on the treatment of multiple sclerosis and holistic patient management in 2023

The last consensus statement of the Spanish Society of Neurology's Demyelinating Diseases Study Group on the treatment of multiple sclerosis (MS) was issued in 2016. Although many of the positions taken remain valid, there have been significant changes in the management and treatment of MS, both due to the approval of new drugs with different action mechanisms and due to the evolution of previously fixed concepts. This has enabled new approaches to specific situations such as pregnancy and vaccination, and the inclusion of new variables in clinical decision-making, such as the early use of high-efficacy disease-modifying therapies (DMT), consideration of the patient's perspective, and the use of such novel technologies as remote monitoring. In the light of these changes, this updated consensus statement, developed according to the Delphi method, seeks to reflect the new paradigm in the management of patients with MS, based on the available scientific evidence and the clinical expertise of the participants. The most significant recommendations are that immunomodulatory DMT be started in patients with radiologically isolated syndrome with persistent radiological activity, that patient perspectives be considered, and that the term "lines of therapy" no longer be used in the classification of DMTs (> 90% consensus). Following diagnosis of MS, the first DMT should be selected according to the presence/absence of factors of poor prognosis (whether epidemiological, clinical, radiological, or biomarkers) for the occurrence of new relapses or progression of disability; high-efficacy DMTs may be considered from disease onset.

Early-stage volume losses in the corpus callosum and thalamus predict the progression of brain atrophy in patients with multiple sclerosis

BACKGROUND

A method that can be used in the early stage of multiple sclerosis (MS) to predict the progression of brain volume loss (BVL) has not been fully established.

METHODS

To develop a method of predicting progressive BVL in patients with MS (pwMS), eighty-two consecutive Japanese pwMS-with either relapsing-remitting MS (86%) or secondary progressive MS (14%)-and 41 healthy controls were included in this longitudinal retrospective analysis over an observational period of approximately 3.5 years. Using a hierarchical cluster analysis with multivariate imaging data obtained by FreeSurfer analysis, we classified the pwMS into clusters.

RESULTS

At baseline and follow-up, pwMS were cross-sectionally classified into three major clusters (Clusters 1, 2, and 3) in ascending order by disability and BVL. Among the patients included in Cluster 1 at baseline, approximately one-third of patients (12/52) transitioned into Cluster 2 at follow-up. The volumes of the corpus callosum, the thalamus, and the whole brain excluding the ventricles were significantly decreased in the transition group compared with the nontransition group and were found to be the most important predictors of transition.

CONCLUSION

Decreased volumes of the corpus callosum and thalamus in the relatively early stage of MS may predict the development of BVL.

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.

Growing importance of brain morphometry analysis in the clinical routine: The hidden impact of MR sequence parameters

Volumetric assessment based on structural MRI is increasingly recognized as an auxiliary tool to visual reading, also in examinations acquired in the clinical routine. However, MRI acquisition parameters can significantly influence these measures, which must be considered when interpreting the results on an individual patient level. This Technical Note shall demonstrate the problem. Using data from a dedicated experiment, we show the influence of two crucial sequence parameters on the GM/WM contrast and their impact on the measured volumes. A simulated contrast derived from acquisition parameters TI/TR may serve as surrogate and is highly correlated (r=0.96) with the measured contrast.

Enlarged choroid plexus in multiple sclerosis is associated with increased lesion load and atrophy in white matter but not gray matter atrophy

BACKGROUND

Enlargement of the choroid plexus (CP) is reported to associate with inflammatory activity and contribute to brain atrophy in patients with multiple sclerosis (pwMS). However, a recent study in healthy volunteers (HVTs) has suggested that CP enlargement can be attributed to ventriculomegaly.

OBJECTIVES

To clarify the pathological significance of the enlargement of CP in multiple sclerosis (MS).

METHODS

A total of 102 pwMS (89 with relapsing-remitting MS and 13 with secondary progressive MS) and 41 HVTs were cross-sectionally evaluated using brain volumetry. The CP volume was compared between disease groups and investigated for the relationships with other brain regional volumes.

RESULTS

CP volume was significantly larger in pwMS than in HVTs in the univariate analysis, but not in multivariable analysis. Meanwhile, the CP and lateral ventricle (LV) volumes were significantly correlated. CP enlargement was significantly associated with increased lesion load and cerebral white matter (WM) atrophy, even after adjusting for LV volume. In contrast, multivariable analyses revealed that LV enlargement, but not CP enlargement, was associated with total gray matter (GM) atrophy.

CONCLUSION

CP enlargement was closely associated with LV enlargement. After adjusting for LV volume, CP enlargement in pwMS was associated with increased lesion load and WM atrophy but not GM atrophy.

An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression

INTRODUCTION

While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear.

AREAS COVERED

The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning.

EXPERT OPINION

Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.

Recent Advances in Diagnostic, Prognostic, and Disease-Monitoring Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is a highly heterogeneous disease. Currently, a combination of clinical features, MRI, and cerebrospinal fluid markers are used in clinical practice for diagnosis and treatment decisions. In recent years, there has been considerable effort to develop novel biomarkers that better reflect the pathologic substrates of the disease to aid in diagnosis and early prognosis, evaluation of ongoing inflammatory activity, detection and monitoring of disease progression, prediction of treatment response, and monitoring of disease-modifying treatment safety. In this review, the authors provide an overview of promising recent developments in diagnostic, prognostic, and disease-monitoring/treatment-response biomarkers in MS.

Hallmarks of spinal cord pathology in multiple sclerosis

A disparity exists between spinal cord and brain involvement in multiple sclerosis (MS), each independently contributing to disability. Underlying differences between brain and cord are not just anatomical in nature (volume, white/grey matter organization, vascularization), but also in barrier functions (differences in function and composition of the blood-spinal cord barrier compared to blood-brain barrier) and possibly in repair mechanisms. Also, immunological phenotypes seem to influence localization of inflammatory activity. Whereas the brain has gained a lot of attention in MS research, the spinal cord lags behind. Advanced imaging techniques and biomarkers are improving and providing us with tools to uncover the mechanisms of spinal cord pathology in MS. In the present review, we elaborate on the underlying anatomical and physiological factors driving differences between brain and cord involvement in MS and review current literature on pathophysiology of spinal cord involvement in MS and the observed differences to brain involvement.

Association of Spinal Cord Atrophy and Brain Paramagnetic Rim Lesions With Progression Independent of Relapse Activity in People With MS

BACKGROUND AND OBJECTIVES

Progression independent of relapse activity (PIRA) is a crucial determinant of overall disability accumulation in multiple sclerosis (MS). Accelerated brain atrophy has been shown in patients experiencing PIRA. In this study, we assessed the relation between PIRA and neurodegenerative processes reflected by (1) longitudinal spinal cord atrophy and (2) brain paramagnetic rim lesions (PRLs). Besides, the same relationship was investigated in progressive MS (PMS). Last, we explored the value of cross-sectional brain and spinal cord volumetric measurements in predicting PIRA.

METHODS

From an ongoing multicentric cohort study, we selected patients with MS with (1) availability of a susceptibility-based MRI scan and (2) regular clinical and conventional MRI follow-up in the 4 years before the susceptibility-based MRI. Comparisons in spinal cord atrophy rates (explored with linear mixed-effect models) and PRL count (explored with negative binomial regression models) were performed between: (1) relapsing-remitting (RRMS) and PMS phenotypes and (2) patients experiencing PIRA and patients without confirmed disability accumulation (CDA) during follow-up (both considering the entire cohort and the subgroup of patients with RRMS). Associations between baseline MRI volumetric measurements and time to PIRA were explored with multivariable Cox regression analyses.

RESULTS

In total, 445 patients with MS (64.9% female; mean [SD] age at baseline 45.0 [11.4] years; 11.2% with PMS) were enrolled. Compared with patients with RRMS, those with PMS had accelerated cervical cord atrophy (mean difference in annual percentage volume change [MD-APC] -1.41; p = 0.004) and higher PRL load (incidence rate ratio [IRR] 1.93; p = 0.005). Increased spinal cord atrophy (MD-APC -1.39; p = 0.0008) and PRL burden (IRR 1.95; p = 0.0008) were measured in patients with PIRA compared with patients without CDA; such differences were also confirmed when restricting the analysis to patients with RRMS. Baseline volumetric measurements of the cervical cord, whole brain, and cerebral cortex significantly predicted time to PIRA (all p ≤ 0.002).

DISCUSSION

Our results show that PIRA is associated with both increased spinal cord atrophy and PRL burden, and this association is evident also in patients with RRMS. These findings further point to the need to develop targeted treatment strategies for PIRA to prevent irreversible neuroaxonal loss and optimize long-term outcomes of patients with MS.

Differences in Brain Atrophy Pattern between People with Multiple Sclerosis and Systemic Diseases with Central Nervous System Involvement Based on Two-Dimensional Linear Measures

Conventional brain magnetic resonance imaging (MRI) in systemic diseases with central nervous system involvement (SDCNS) may imitate MRI findings of multiple sclerosis (MS). In order to better describe the MRI characteristics of these conditions, in our study we assessed brain volume parameters in MS (n = 58) and SDCNS (n = 41) patients using two-dimensional linear measurements (2DLMs): bicaudate ratio (BCR), corpus callosum index (CCI) and width of third ventricle (W3V). In SDCNS patients, all 2DLMs were affected by age (CCI p = 0.005, BCR p < 0.001, W3V p < 0.001, respectively), whereas in MS patients only BCR and W3V were (p = 0.001 and p = 0.015, respectively). Contrary to SDCNS, in the MS cohort BCR and W3V were associated with T1 lesion volume (T1LV) (p = 0.020, p = 0.009, respectively) and T2 lesion volume (T2LV) (p = 0.015, p = 0.009, respectively). CCI was associated with T1LV in the MS cohort only (p = 0.015). Moreover, BCR was significantly higher in the SDCNS group (p = 0.01) and CCI was significantly lower in MS patients (p = 0.01). The best predictive model to distinguish MS and SDCNS encompassed gender, BCR and T2LV as the explanatory variables (sensitivity 0.91; specificity 0.68; AUC 0.86). Implementation of 2DLMs in the brain MRI analysis of MS and SDCNS patients allowed for the identification of diverse patterns of local brain atrophy in these clinical conditions.

Disease Modifying Strategies in Multiple Sclerosis: New Rays of Hope to Combat Disability?

Multiple sclerosis (MS) is the most prevalent chronic autoimmune inflammatory- demyelinating disorder of the central nervous system (CNS). It usually begins in young adulthood, mainly between the second and fourth decades of life. Usually, the clinical course is characterized by the involvement of multiple CNS functional systems and by different, often overlapping phenotypes. In the last decades, remarkable results have been achieved in the treatment of MS, particularly in the relapsing- remitting (RRMS) form, thus improving the long-term outcome for many patients. As deeper knowledge of MS pathogenesis and respective molecular targets keeps growing, nowadays, several lines of disease-modifying treatments (DMT) are available, an impressive change compared to the relative poverty of options available in the past. Current MS management by DMTs is aimed at reducing relapse frequency, ameliorating symptoms, and preventing clinical disability and progression. Notwithstanding the relevant increase in pharmacological options for the management of RRMS, research is now increasingly pointing to identify new molecules with high efficacy, particularly in progressive forms. Hence, future efforts should be concentrated on achieving a more extensive, if not exhaustive, understanding of the pathogenetic mechanisms underlying this phase of the disease in order to characterize novel molecules for therapeutic intervention. The purpose of this review is to provide a compact overview of the numerous currently approved treatments and future innovative approaches, including neuroprotective treatments as anti-LINGO-1 monoclonal antibody and cell therapies, for effective and safe management of MS, potentially leading to a cure for this disease.

Disease progression in the first 5 years of treatment in multiple sclerosis: Predictive value of early brain and lesion volume changes

BACKGROUND

Whether the degree of inflammation (and its resolution) and neurodegeneration after treatment initiation predicts disease progression in multiple sclerosis (MS) remains unclear.

OBJECTIVES

To assess the predictive value of magnetic resonance imaging (MRI)-derived brain and lesion volume (LV) changes in years 1 and 2 of treatment for disease progression.

METHODS

Patients receiving early interferon beta-1a treatment in REFLEX/REFLEXION (N = 262) were included. Predictive regression models included new/enlarging LV (positive activity), disappearing/shrinking LV (negative activity), and global/central atrophy during years 1 and 2.

RESULTS

Faster global atrophy and/or pseudo-atrophy and positive lesion activity in years 1 and 2 related to an increased probability and faster conversion to clinically definite multiple sclerosis (CDMS). Negative lesion activity in year 1 and slower central atrophy in year 2 were predictive of confirmed disability progression (9-Hole Peg Test). Positive lesion activity in year 2 was predictive of faster global atrophy, while positive lesion activity in years 1 and 2 was predictive of faster central atrophy.

CONCLUSIONS

A higher degree of global atrophy and/or pseudo-atrophy in year 1 was predictive of CDMS. Positive lesion activity in any year was related to CDMS and neurodegeneration. Disability was related to negative lesion activity in year 1 and slower central atrophy in year 2.

Multi-contrast high-field quality image synthesis for portable low-field MRI using generative adversarial networks and paired data

Introduction

Portable low-field strength (64mT) MRI scanners promise to increase access to neuroimaging for clinical and research purposes, however these devices produce lower quality images compared to high-field scanners. In this study, we developed and evaluated a deep learning architecture to generate high-field quality brain images from low-field inputs using a paired dataset of multiple sclerosis (MS) patients scanned at 64mT and 3T.

Methods

A total of 49 MS patients were scanned on portable 64mT and standard 3T scanners at Penn (n=25) or the National Institutes of Health (NIH, n=24) with T1-weighted, T2-weighted and FLAIR acquisitions. Using this paired data, we developed a generative adversarial network (GAN) architecture for low- to high-field image translation (LowGAN). We then evaluated synthesized images with respect to image quality, brain morphometry, and white matter lesions.

Results

Synthetic high-field images demonstrated visually superior quality compared to low-field inputs and significantly higher normalized cross-correlation (NCC) to actual high-field images for T1 (p=0.001) and FLAIR (p<0.001) contrasts. LowGAN generally outperformed the current state-of-the-art for low-field volumetrics. For example, thalamic, lateral ventricle, and total cortical volumes in LowGAN outputs did not differ significantly from 3T measurements. Synthetic outputs preserved MS lesions and captured a known inverse relationship between total lesion volume and thalamic volume.

Conclusions

LowGAN generates synthetic high-field images with comparable visual and quantitative quality to actual high-field scans. Enhancing portable MRI image quality could add value and boost clinician confidence, enabling wider adoption of this technology.

Understanding the Pathophysiology and Magnetic Resonance Imaging of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

Magnetic resonance imaging (MRI) has been extensively applied in the study of multiple sclerosis (MS), substantially contributing to diagnosis, differential diagnosis, and disease monitoring. MRI studies have significantly contributed to the understanding of MS through the characterization of typical radiological features and their clinical or prognostic implications using conventional MRI pulse sequences and further with the application of advanced imaging techniques sensitive to microstructural damage. Interpretation of results has often been validated by MRI-pathology studies. However, the application of MRI techniques in the study of neuromyelitis optica spectrum disorders (NMOSD) remains an emerging field, and MRI studies have focused on radiological correlates of NMOSD and its pathophysiology to aid in diagnosis, improve monitoring, and identify relevant prognostic factors. In this review, we discuss the main contributions of MRI to the understanding of MS and NMOSD, focusing on the most novel discoveries to clarify differences in the pathophysiology of focal inflammation initiation and perpetuation, involvement of normal-appearing tissue, potential entry routes of pathogenic elements into the CNS, and existence of primary or secondary mechanisms of neurodegeneration.

Treatment Effect on Brain Atrophy Correlates with Treatment Effect on Cognition in Multiple Sclerosis

OBJECTIVE

The purpose of this study was to evaluate the extent to which treatment effect on magnetic resonance imaging (MRI)-derived measures of brain atrophy and focal lesions can mediate, at the trial level, the treatment effect on cognitive outcomes in multiple sclerosis (MS).

METHODS

We collected all published randomized clinical trials in MS lasting at least 2 years and including as end points: active MRI lesions (defined as new/enlarging T2 lesions), brain atrophy (defined as a change in brain volume between month 12 and month 24), and change in cognitive performance (assessed by the Paced Auditory Serial Addition Test [PASAT]). Relative reductions were used to quantify the treatment effect on MRI markers (lesions and atrophy), whereas the standardized mean difference (Hedges g) between baseline and follow-up cognitive assessment was used to quantify the treatment effects on cognition. A linear regression, weighted for trial size, was used to assess the relationship between the treatment effects on MRI markers and cognition.

RESULTS

Fourteen trials including more than 8,813 patients with MS were included in the meta-regression. Treatment effect on cognition was strongly associated with the treatment effect on brain atrophy (R2  = 0.79, p < 0.001), but was not correlated with the treatment effect on active MRI lesions (R2  = 0.16, p = 0.14).

INTERPRETATION

Results reported here suggest that brain atrophy, a well-established MRI marker in MS clinical trials, can be used as a main outcome for clinical trials with drugs targeting cognitive impairment and neurodegeneration. ANN NEUROL 2023;94:925-932.

Association of MRI leptomeningeal enhancement with disability worsening in progressive multiple sclerosis: A clinical and post-mortem study

BACKGROUND

Leptomeningeal enhancement (LME) has been described as a biomarker of meningeal inflammation in multiple sclerosis (MS).

OBJECTIVE

The aim of this study was to (1) assess if LME is predictive of disability worsening in progressive MS (pMS) patients and (2) investigate the pathological substrates of LME in an independent post-mortem MS series.

METHODS

In total, 115 pMS patients were imaged yearly with 1.5T MRI, using post-contrast CUBE 3D FLAIR for LME detection. Endpoint: to identify the baseline variables predictive of confirmed disability worsening (CDW) at 24 months follow-up. Post-mortem, inflammation, and structural changes of the leptomeninges were assessed in 12 MS/8 control brains.

RESULTS

LME (27% of patients at baseline) was associated with higher EDSS and lower brain volume (nBV). LME was unchanged in most patients over follow-up. LME at baseline MRI was independently associated with higher risk of 24 months CDW (HR 3.05, 95% CI 1.36-6.84, p = 0.007) in a Cox regression, including age, nBV, T2 lesion volume, high-efficacy treatments, and MRI disease activity. Post-mortem, focal structural changes (fibrosis) of the leptomeninges were observed in MS, usually associated with inflammation (Kendall's Tau 0.315, p < 0.0001).

CONCLUSIONS

LME is frequently detected in pMS patients using 1.5T MRI and is independently predictive of disability progression. LME could result from both focal leptomeningeal post-inflammatory fibrosis and inflammation.

Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR

BACKGROUND AND OBJECTIVES

Disability and cognitive impairment are known to be related to brain atrophy in multiple sclerosis (MS), but 3D-T1 imaging required for brain volumetrics is often unavailable in clinical protocols, unlike 3D-FLAIR. Here our aim was to investigate whether brain volumes derived from 3D-FLAIR images result in similar associations with disability and cognition in MS as do those derived from 3D-T1 images.

METHODS

3T-MRI scans of 329 MS patients and 76 healthy controls were included in this cross-sectional study. Brain volumes were derived using FreeSurfer on 3D-T1 and compared with brain volumes derived with SynthSeg and SAMSEG on 3D-FLAIR. Relative agreement was evaluated by calculating the intraclass correlation coefficient (ICC) of the 3D-T1 and 3D-FLAIR volumes. Consistency of relations with disability and average cognition was assessed using linear regression, while correcting for age and sex. The findings were corroborated in an independent validation cohort of 125 MS patients.

RESULTS

The ICC between volume measured with FreeSurfer and those measured on 3D-FLAIR for brain, ventricle, cortex, total deep gray matter and thalamus was above 0.74 for SAMSEG and above 0.91 for SynthSeg. Worse disability and lower average cognition were similarly associated with brain (adj. R2 = 0.24-0.27, p < 0.01; adj. R2 = 0.26-0.29, p < 0.001) ventricle (adj. R2 = 0.27-0.28, p < 0.001; adj. R2 = 0.19-0.20, p < 0.001) and deep gray matter volumes (adj. R2 = 0.24-0.28, p < 0.001; adj. R2 = 0.27-0.28, p < 0.001) determined with all methods, except for cortical volumes derived from 3D-FLAIR.

DISCUSSION

In this cross-sectional study, brain volumes derived from 3D-FLAIR and 3D-T1 show similar relationships to disability and cognitive dysfunction in MS, highlighting the potential of these techniques in clinical datasets.

Reliability of brain atrophy measurements in multiple sclerosis using MRI: an assessment of six freely available software packages for cross-sectional analyses

PURPOSE

Volume measurement using MRI is important to assess brain atrophy in multiple sclerosis (MS). However, differences between scanners, acquisition protocols, and analysis software introduce unwanted variability of volumes. To quantify theses effects, we compared within-scanner repeatability and between-scanner reproducibility of three different MR scanners for six brain segmentation methods.

METHODS

Twenty-one people with MS underwent scanning and rescanning on three 3 T MR scanners (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) to obtain 3D T1-weighted images. FreeSurfer, FSL, SAMSEG, FastSurfer, CAT-12, and SynthSeg were used to quantify brain, white matter and (deep) gray matter volumes both from lesion-filled and non-lesion-filled 3D T1-weighted images. We used intra-class correlation coefficient (ICC) to quantify agreement; repeated-measures ANOVA to analyze systematic differences; and variance component analysis to quantify the standard error of measurement (SEM) and smallest detectable change (SDC).

RESULTS

For all six software, both between-scanner agreement (ICCs ranging 0.4-1) and within-scanner agreement (ICC range: 0.6-1) were typically good, and good to excellent (ICC > 0.7) for large structures. No clear differences were found between filled and non-filled images. However, gray and white matter volumes did differ systematically between scanners for all software (p < 0.05). Variance component analysis yielded within-scanner SDC ranging from 1.02% (SAMSEG, whole-brain) to 14.55% (FreeSurfer, CSF); and between-scanner SDC ranging from 4.83% (SynthSeg, thalamus) to 29.25% (CAT12, thalamus).

CONCLUSION

Volume measurements of brain, GM and WM showed high repeatability, and high reproducibility despite substantial differences between scanners. Smallest detectable change was high, especially between different scanners, which hampers the clinical implementation of atrophy measurements.

Methods for Brain Atrophy MR Quantification in Multiple Sclerosis: Application to the Multicenter INNI Dataset

BACKGROUND

Current therapeutic strategies in multiple sclerosis (MS) target neurodegeneration. However, the integration of atrophy measures into the clinical scenario is still an unmet need.

PURPOSE

To compare methods for whole-brain and gray matter (GM) atrophy measurements using the Italian Neuroimaging Network Initiative (INNI) dataset.

STUDY TYPE

Retrospective (data available from INNI).

POPULATION

A total of 466 patients with relapsing-remitting MS (mean age = 37.3 ± 10 years, 323 women) and 279 healthy controls (HC; mean age = 38.2 ± 13 years, 164 women).

FIELD STRENGTH/SEQUENCE

A 3.0-T, T1-weighted (spin echo and gradient echo without gadolinium injection) and T2-weighted spin echo scans at baseline and after 1 year (170 MS, 48 HC).

ASSESSMENT

Structural Image Evaluation using Normalization of Atrophy (SIENA-X/XL; version 5.0.9), Statistical Parametric Mapping (SPM-v12); and Jim-v8 (Xinapse Systems, Colchester, UK) software were applied to all subjects.

STATISTICAL TESTS

In MS and HC, we evaluated the intraclass correlation coefficient (ICC) among FSL-SIENA(XL), SPM-v12, and Jim-v8 for cross-sectional whole-brain and GM tissue volumes and their longitudinal changes, the effect size according to the Cohen's d at baseline and the sample size requirement for whole-brain and GM atrophy progression at different power levels (lowest = 0.7, 0.05 alpha level). False discovery rate (Benjamini-Hochberg procedure) correction was applied. A P value <0.05 was considered statistically significant.

RESULTS

SPM-v12 and Jim-v8 showed significant agreement for cross-sectional whole-brain (ICC = 0.93 for HC and ICC = 0.84 for MS) and GM volumes (ICC = 0.66 for HC and ICC = 0.90) and longitudinal assessment of GM atrophy (ICC = 0.35 for HC and ICC = 0.59 for MS), while no significant agreement was found in the comparisons between whole-brain and GM volumes for SIENA-X/XL and both SPM-v12 (P = 0.19 and P = 0.29, respectively) and Jim-v8 (P = 0.21 and P = 0.32, respectively). SPM-v12 and Jim-v8 showed the highest effect size for cross-sectional GM atrophy (Cohen's d = -0.63 and -0.61). Jim-v8 and SIENA(XL) showed the smallest sample size requirements for whole-brain (58) and GM atrophy (152), at 0.7 power level.

DATA CONCLUSION

The findings obtained in this study should be considered when selecting the appropriate brain atrophy pipeline for MS studies.

EVIDENCE LEVEL

4.

TECHNICAL EFFICACY

Stage 1.

Neurodegeneration and its potential markers in the diagnosing of secondary progressive multiple sclerosis. A review

Approximately 70% of relapsing-remitting multiple sclerosis (RRMS) patients will develop secondary progressive multiple sclerosis (SPMS) within 10-15 years. This progression is characterized by a gradual decline in neurological functionality and increasing limitations of daily activities. Growing evidence suggests that both inflammation and neurodegeneration are associated with various pathological processes throughout the development of MS; therefore, to delay disease progression, it is critical to initiate disease-modifying therapy as soon as it is diagnosed. Currently, a diagnosis of SPMS requires a retrospective assessment of physical disability exacerbation, usually over the previous 6-12 months, which results in a delay of up to 3 years. Hence, there is a need to identify reliable and objective biomarkers for predicting and defining SPMS conversion. This review presents current knowledge of such biomarkers in the context of neurodegeneration associated with MS, and SPMS conversion.

Patterns of brain atrophy in recently-diagnosed relapsing-remitting multiple sclerosis

Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in recently-diagnosed RRMS using volumetry and voxel-based morphometry (VBM). RRMS patients (N = 354) underwent 3T structural MRI <6 months after diagnosis and 1-year follow-up, as part of the Scottish multicentre 'FutureMS' study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish regional patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the brain. Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, cerebellar GM, brainstem, amygdala, basal ganglia, hippocampus, accumbens, thalamus and ventral diencephalon. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 26 regions and 16/26; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe. Widespread GM and NAWM atrophy was observed in this large recently-diagnosed RRMS cohort, particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions; indicative of neurodegeneration across tissue types, and in accord with limited previous studies in early disease. Volumetric and VBM results emphasise different features of longitudinal lobar and loco-regional change, however identify consistent atrophy patterns across individuals. Atrophy measures targeted to specific brain regions may provide improved markers of neurodegeneration, and potential future imaging stratifiers and endpoints for clinical decision making and therapeutic trials.

Scanner agnostic large-scale evaluation of MS lesion delineation tool for clinical MRI

Introduction

Patients with MS are MRI scanned continuously throughout their disease course resulting in a large manual workload for radiologists which includes lesion detection and size estimation. Though many models for automatic lesion segmentation have been published, few are used broadly in clinic today, as there is a lack of testing on clinical datasets. By collecting a large, heterogeneous training dataset directly from our MS clinic we aim to present a model which is robust to different scanner protocols and artefacts and which only uses MRI modalities present in routine clinical examinations.

Methods

We retrospectively included 746 patients from routine examinations at our MS clinic. The inclusion criteria included acquisition at one of seven different scanners and an MRI protocol including 2D or 3D T2-w FLAIR, T2-w and T1-w images. Reference lesion masks on the training (n = 571) and validation (n = 70) datasets were generated using a preliminary segmentation model and subsequent manual correction. The test dataset (n = 100) was manually delineated. Our segmentation model https://github.com/CAAI/AIMS/ was based on the popular nnU-Net, which has won several biomedical segmentation challenges. We tested our model against the published segmentation models HD-MS-Lesions, which is also based on nnU-Net, trained with a more homogenous patient cohort. We furthermore tested model robustness to data from unseen scanners by performing a leave-one-scanner-out experiment.

Results

We found that our model was able to segment MS white matter lesions with a performance comparable to literature: DSC = 0.68, precision = 0.90, recall = 0.70, f1 = 0.78. Furthermore, the model outperformed HD-MS-Lesions in all metrics except precision = 0.96. In the leave-one-scanner-out experiment there was no significant change in performance (p < 0.05) between any of the models which were only trained on part of the dataset and the full segmentation model.

Conclusion

In conclusion we have seen, that by including a large, heterogeneous dataset emulating clinical reality, we have trained a segmentation model which maintains a high segmentation performance while being robust to data from unseen scanners. This broadens the applicability of the model in clinic and paves the way for clinical implementation.

A review on multiple sclerosis prognostic findings from imaging, inflammation, and mental health studies

Magnetic resonance imaging (MRI) of the brain is commonly used to detect where chronic and active lesions are in multiple sclerosis (MS). MRI is also extensively used as a tool to calculate and extrapolate brain health by way of volumetric analysis or advanced imaging techniques. In MS patients, psychiatric symptoms are common comorbidities, with depression being the main one. Even though these symptoms are a major determinant of quality of life in MS, they are often overlooked and undertreated. There has been evidence of bidirectional interactions between the course of MS and comorbid psychiatric symptoms. In order to mitigate disability progression in MS, treating psychiatric comorbidities should be investigated and optimized. New research for the prediction of disease states or phenotypes of disability have advanced, primarily due to new technologies and a better understanding of the aging brain.

Ocrelizumab-treated patients with relapsing multiple sclerosis show volume loss rates similar to healthy aging

BACKGROUND

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system characterized by two major and interconnected hallmarks: inflammation and progressive neurodegeneration.

OBJECTIVE

The aim of this work was to compare neurodegenerative processes, in the form of global and regional brain volume loss rates, in healthy controls (HCs) and in patients with relapsing MS (RMS) treated with ocrelizumab, which suppresses acute inflammation.

METHODS

Whole brain, white matter, cortical gray matter, thalamic, and cerebellar volume loss rates were assessed in 44 HCs that were part of a substudy in the OPERA II randomized controlled trial (NCT01412333) and 59 patients with RMS enrolled in the same substudy as well as age- and sex-matched patients in OPERA I (NCT01247324) and II. Volume loss rates were computed using random coefficients models over a period of 2 years.

RESULTS

Ocrelizumab-treated patients showed global and regional brain volume loss rates that were approaching that of HCs.

CONCLUSION

These findings are consistent with an important role of inflammation on overall tissue loss and the role of ocrelizumab in reducing this phenomenon.

Assessing the Equivalence of Brain-Derived Measures from Two 3D T1-Weighted Acquisitions: One Covering the Brain and One Covering the Brain and Spinal Cord

BACKGROUND AND PURPOSE

In MS, it is common to acquire brain and spinal cord MR imaging sequences separately to assess the extent of the disease. The goal of this study was to see how replacing the traditional brain T1-weighted images (brain-T1) with an acquisition that included both the brain and the cervical spinal cord (cns-T1) affected brain- and spinal cord-derived measures.

MATERIALS AND METHODS

Thirty-six healthy controls (HC) and 42 patients with MS were included. Of those, 18 HC and 35 patients with MS had baseline and follow-up at 1 year acquired on a 3T magnet. Two 3D T1-weighted images (brain-T1 and cns-T1) were acquired at each time point. Regional cortical thickness and volumes were determined with FastSurfer, and the percentage brain volume change per year was obtained with SIENA. The spinal cord area was estimated with the Spinal Cord Toolbox. Intraclass correlation coefficients (ICC) were calculated to check for consistency of measures obtained from brain-T1 and cns-T1.

RESULTS

Cortical thickness measures showed an ICC >0.75 in 94% of regions in healthy controls and 80% in patients with MS. Estimated regional volumes had an ICC >0.88, and the percentage brain volume change had an ICC >0.79 for both groups. The spinal cord area measures had an ICC of 0.68 in healthy controls and 0.92 in patients with MS.

CONCLUSIONS

Brain measurements obtained from 3D cns-T1 are highly equivalent to those obtained from a brain-T1, suggesting that it could be feasible to replace the brain-T1 with cns-T1.

The association between brain volume loss and disability in multiple sclerosis: A systematic review

BACKGROUND

Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating, degenerative disease of the central nervous system that affects approximately 2.8 million people worldwide. Compelling evidence from observational studies and clinical trials indicates a strong association between brain volume loss (BVL) and the accumulation of disability in MS. However, the considerable heterogeneity in study designs and methods of assessment of BVL invites questions concerning the generalizability of the reported findings. Therefore, we conducted this systematic review to characterize the relationship between BVL and physical disability in patients with MS.

METHODS

A systematic literature search of MEDLINE and EMBASE databases was performed supplemented by gray literature searches. The following study designs were included: prospective/retrospective cohort, cross-sectional and case-control. Only English language articles published from 2010 onwards were eligible for final inclusion. There were no restrictions on MS subtype, age, or ethnicity. Of the 1620 citations retrieved by the structured searches, 50 publications met our screening criteria and were included in the final data set.

RESULTS

Across all BVL measures, there was considerable heterogeneity in studies regarding the underlying study population, the definitions of BVL and image analysis methodologies, the physical disability measure used, the measures of association reported and whether the analysis conducted was univariable or multivariable. A total of 36 primary studies providing data on the association between whole BVL and physical disability in MS collectively suggest that whole brain atrophy is associated with greater physical disability progression in MS patients. Similarly, a total of 15 primary studies providing data on the association between ventricular atrophy and physical disability in MS suggest that ventricular atrophy is associated with greater physical disability progression in MS patients. Along similar lines, the existing evidence based on a total of 13 primary studies suggests that gray matter atrophy is associated with greater physical disability progression in MS patients. Four primary studies suggest that corpus callosum atrophy is associated with greater physical disability progression in MS patients. The majority of the existing evidence (6 primary studies) suggests no association between white matter atrophy and physical disability in MS. It is difficult to assign a relationship between basal ganglia volume loss and physical disability as well as medulla oblongata width and physical disability in MS due to very limited data.

CONCLUSION

The evidence gathered from this systematic review, although very heterogeneous, suggests that whole brain atrophy is associated with greater physical disability progression in MS patients. Our review can help define future imaging biomarkers for physical disability progression and treatment monitoring in MS.

Therapy effect on AI-derived thalamic atrophy using clinical routine MRI protocol: A longitudinal, multi-center, propensity-matched multiple sclerosis study

BACKGROUND

The effect of disease modifying therapies (DMTs) on brain atrophy in persons with multiple sclerosis (pwMS) is typically investigated in highly standardized clinical trial settings or single-center academic institutions. We aimed at utilizing artificial intelligence (AI)-based volumetric analysis on routine unstandardized T2-FLAIR scans in determining the effect of DMTs on lateral ventricular volume (LVV) and thalamic volume (TV) changes in pwMS.

METHODS

The DeepGRAI (Deep Gray Rating via Artificial Intelligence) registry is a multi-center, longitudinal, observational, real-word study with a convenience sample of 1002 relapsing-remitting (RR) pwMS from 30 United States sites. Brain MRI exams acquired as part of the routine clinical management were collected at baseline and on average at 2.6-years follow-up. The MRI scans were acquired either on 1.5T or 3T scanners with no prior harmonization. TV was determined using the DeepGRAI tool and lateral ventricular volume LVV was measured using NeuroSTREAM software.

RESULTS

After propensity matching based on baseline age, disability and time of follow-up, untreated pwRRMS had significantly greater TV change when compared to treated pwRRMS (-1.2% vs. -0.3%, p = 0.044). PwRRMS treated with high-efficacy DMTs had significant and two-fold lower% LVV change when compared to pwRRMS treated on moderate-efficacy DMTs (3.5% vs. 7.0%, p = 0.001). PwRRMS who stopped DMT during the follow-up had significantly greater annualized% TV change compared to pwRRMS who remained on their DMT (-0.73% vs. -0.14%, p = 0.012) and significantly greater annualized% LVV change (3.4% vs. 1.7%, p = 0.047). These findings were also observed in a propensity analysis that additionally incorporated matching for scanner model at both baseline and follow-up visits.

CONCLUSIONS

LVV and TV measured on T2-FLAIR scans can detect treatment-induced short-term neurodegenerative changes measured in a real-word unstandardized, multicenter, clinical routine setting.

Optical coherence tomography reflects clinically relevant gray matter damage in patients with multiple sclerosis

BACKGROUND

Retinal degeneration leading to optical coherence tomography (OCT) changes is frequent in patients with multiple sclerosis (PwMS).

OBJECTIVE

To investigate associations among OCT changes, MRI measurements of global and regional brain volume loss, and physical and cognitive impairment in PwMS.

METHODS

95 PwMS and 52 healthy controls underwent OCT and MRI examinations. Mean peripapillary retinal nerve fiber layer (pRNFL) thickness and ganglion cell/inner plexiform layer (GCIPL) volume were measured. In PwMS disability was quantified with the Expanded Disability Status Scale (EDSS) and Symbol Digit Modalities Test (SDMT). Associations between OCT, MRI, and clinical measures were investigated with multivariable regression models.

RESULTS

In PwMS, pRNFL and GCIPL were associated with the volume of whole brain (p < 0.04), total gray matter (p < 0.002), thalamus (p ≤ 0.04), and cerebral cortex (p ≤ 0.003) -both globally and regionally-, but not white matter. pRNFL and GCIPL were also inversely associated with T2-lesion volume (T2LV), especially in the optic radiations (p < 0.0001). The brain volumes associated with EDSS and SDMT significantly overlapped with those correlating with pRNFL and GCIPL.

CONCLUSIONS

In PwMS, pRNFL and GCIPL reflect the integrity of clinically-relevant gray matter structures, underling the value of OCT measures as markers of neurodegeneration and disability in multiple sclerosis.

Adipokines in multiple sclerosis patients are related to clinical and radiological measures

BACKGROUND

An imbalance of adipokines, hormones secreted by white adipose tissue, is suggested to play a role in the immunopathology of multiple sclerosis (MS). In people with MS (PwMS) of the same age, we aimed to determine whether the adipokines adiponectin, leptin, and resistin are associated with MS disease severity. Furthermore, we aimed to investigate whether these adipokines mediate the association between body mass index (BMI) and MS disease severity.

METHODS

Adiponectin, resistin, and leptin were determined in serum using ELISA. 288 PwMS and 125 healthy controls (HC) were included from the Project Y cohort, a population-based cross-sectional study of people with MS born in the Netherlands in 1966, and age and sex-matched HC. Adipokine levels and BMI were related to demographic, clinical and disability measures, and MRI-based brain volumes.

RESULTS

Adiponectin levels were 1.2 fold higher in PwMS vs. HC, especially in secondary progressive MS. Furthermore, we found a sex-specific increase in adiponectin levels in primary progressive (PP) male patients compared to male controls. Leptin and resistin levels did not differ between PwMS and HC, however, leptin levels were associated with higher disability (EDSS) and resistin strongly related to brain volumes in progressive patients, especially in several grey matter regions in PPMS. Importantly, correction for BMI did not significantly change the results.

CONCLUSION

In PwMS of the same age, we found associations between adipokines (adiponectin, leptin, and resistin) and a range of clinical and radiological metrics. These associations were independent of BMI, indicating distinct mechanisms.

A study of linear measurement and clinical correlation of brain atrophy in Wilson's disease

Background

The aim of this study was to explore the clinical relevance of linear measures of Wilson's disease (WD).

Methods

Relative values of brain atrophy in 30 patients with WD and 30 healthy volunteers were measured and compared using a manual measurement method. Linear measurement indicators of brain atrophy in patients with and without mental disorders were also compared. In addition, correlations of patients' age, disease duration, and Unified Wilson's Disease Rating Scale (UWDRS) scores with brain atrophy indicators were determined.

Results

The results showed that the e-value, Huckman number, Evans index, and lateral ventricular body index were higher in the WD group compared with the control group. The age of patients with WD was negatively correlated with the k-value and significantly positively correlated with the brainstem index. WD duration was prominently positively correlated with the d-value and negatively correlated with the j-value. In addition, neurological function scores were significantly positively correlated with the c-value, e-value, caudate nucleus index, Huckman number, Evans index, and lateral ventricular body index. By contrast, patients with psychiatric symptoms had a higher a-value and fourth ventricular index than those without psychiatric symptoms.

Conclusion

Therefore, it can be concluded that patients with WD and those with psychiatric symptoms have more severe brain atrophy compared to normal subjects. The patient's age, disease duration, and neurological function scores were positively correlated with the severity of brain atrophy.

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

Introduction

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

Methods

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

Results and discussion

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

Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI

The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising approach to achieving unprecedented levels of accuracy when predicting the course of neurological conditions, including multiple sclerosis, by means of extracting image features not detectable through conventional methods. Additionally, the study of CNN-derived attention maps, which indicate the most relevant anatomical features for CNN-based decisions, has the potential to uncover key disease mechanisms leading to disability accumulation. From a cohort of patients prospectively followed up after a first demyelinating attack, we selected those with T1-weighted and T2-FLAIR brain MRI sequences available for image analysis and a clinical assessment performed within the following six months (N = 319). Patients were divided into two groups according to expanded disability status scale (EDSS) score: ≥3.0 and < 3.0. A 3D-CNN model predicted the class using whole-brain MRI scans as input. A comparison with a logistic regression (LR) model using volumetric measurements as explanatory variables and a validation of the CNN model on an independent dataset with similar characteristics (N = 440) were also performed. The layer-wise relevance propagation method was used to obtain individual attention maps. The CNN model achieved a mean accuracy of 79% and proved to be superior to the equivalent LR-model (77%). Additionally, the model was successfully validated in the independent external cohort without any re-training (accuracy = 71%). Attention-map analyses revealed the predominant role of frontotemporal cortex and cerebellum for CNN decisions, suggesting that the mechanisms leading to disability accrual exceed the mere presence of brain lesions or atrophy and probably involve how damage is distributed in the central nervous system.

Comparing RNA-sequencing datasets from astrocytes, oligodendrocytes, and microglia in multiple sclerosis identifies novel dysregulated genes relevant to inflammation and myelination

Central nervous system (CNS) inflammation is a key factor in multiple sclerosis (MS). Invasion of peripheral immune cells into the CNS resulting from an unknown signal or combination of signals results in activation of resident immune cells and the hallmark feature of the disease: demyelinating lesions. These lesion sites are an amalgam of reactive peripheral and central immune cells, astrocytes, damaged and dying oligodendrocytes, and injured neurons and axons. Sustained inflammation affects cells directly located within the lesion site and further abnormalities are apparent diffusely throughout normal-appearing white matter and grey matter. It is only relatively recently, using animal models, new tissue sampling techniques, and next-generation sequencing, that molecular changes occurring in CNS resident cells have been broadly captured. Advances in cell isolation through Fluorescence Activated Cell Sorting (FACS) and laser-capture microdissection together with the emergence of single-cell sequencing have enabled researchers to investigate changes in gene expression in astrocytes, microglia, and oligodendrocytes derived from animal models of MS as well as from primary patient tissue. The contribution of some dysregulated pathways has been followed up in individual studies; however, corroborating results often go unreported between sequencing studies. To this end, we have consolidated results from numerous RNA-sequencing studies to identify and review novel patterns of differentially regulated genes and pathways occurring within CNS glial cells in MS. This article is categorized under: Neurological Diseases > Molecular and Cellular Physiology.