Thalamic Atrophy Without Whole Brain Atrophy Is Associated With Absence of 2-Year NEDA in Multiple Sclerosis

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.

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.

Reduced alpha2 power is associated with slowed information processing speed in multiple sclerosis

OBJECTIVE

Cognitive impairment is common in multiple sclerosis (MS), significantly impacts daily functioning, is time-consuming to assess, and is prone to practice effects. We examined whether the alpha band power measured with magnetoencephalography (MEG) is associated with the different cognitive domains affected by MS.

METHODS

Sixty-eight MS patients and 47 healthy controls underwent MEG, T1- and FLAIR-weighted magnetic resonance imaging (MRI), and neuropsychological testing. Alpha power in the occipital cortex was quantified in the alpha1 (8-10 Hz) and alpha2 (10-12 Hz) bands. Next, we performed best subset regression to assess the added value of neurophysiological measures to commonly available MRI measures.

RESULTS

Alpha2 power significantly correlated with information processing speed (p < 0.001) and was always retained in all multilinear models, whereas thalamic volume was retained in 80% of all models. Alpha1 power was correlated with visual memory (p < 0.001) but only retained in 38% of all models.

CONCLUSIONS

Alpha2 (10-12 Hz) power in rest is associated with IPS, independent of standard MRI parameters. This study stresses that a multimodal assessment, including structural and functional biomarkers, is likely required to characterize cognitive impairment in MS. Resting-state neurophysiology is thus a promising tool to understand and follow up changes in IPS.

Thalamic asymmetry in Multiple Sclerosis

BACKGROUND

Multiple Sclerosis (MS) is a chronic neuroinflammatory disease that affects the central nervous system. Asymmetry is one of the finding in brain MRI of these patients, which is related to the debilitating symptoms of the disease. This study aimed to investigate and compare the thalamic asymmetry in MS patients and its relationship with other MRI and clinical findings of these patients.

METHODS

This cross-sectional study conducted on 83 patients with relapse-remitting MS (RRMS), 43 patients with secondary progressive MS (SPMS), and 89 healthy controls. The volumes of total intracranial, total gray matter, total white matter, lesions, thalamus, and also the thalamic asymmetry indices were calculated. The 9-hole peg test (9-HPT) and Expanded Disability Status Scale (EDSS) were assessed as clinical findings.

RESULTS

We showed that the normalized whole thalamic volume in healthy subjects was higher than MS patients (both RRMS and SPMS). Thalamic asymmetry index (TAI) was significantly different between RRMS patients and SPMS patients (p = 0.011). The absolute value of TAI was significantly lower in healthy subjects than in RRMS (p < 0.001) and SPMS patients (p < 0.001), and SPMS patients had a higher absolute TAI compared to RRMS patients (p = 0.037).

CONCLUSIONS

In this cross-sectional study we showed a relationship between normalized whole thalamic volume and MS subtype. Also, we showed that the asymmetric indices of the thalamus can be related to the progression of the disease. Eventually, we showed that thalamic asymmetry can be related to the disease progression and subtype changes in MS.

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

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

Neurodegeneration in multiple sclerosis

Axonal loss in multiple sclerosis (MS) is a key component of disease progression and permanent neurologic disability. MS is a heterogeneous demyelinating and neurodegenerative disease of the central nervous system (CNS) with varying presentation, disease courses, and prognosis. Immunomodulatory therapies reduce the frequency and severity of inflammatory demyelinating events that are a hallmark of MS, but there is minimal therapy to treat progressive disease and there is no cure. Data from patients with MS, post-mortem histological analysis, and animal models of demyelinating disease have elucidated patterns of MS pathogenesis and underlying mechanisms of neurodegeneration. MRI and molecular biomarkers have been proposed to identify predictors of neurodegeneration and risk factors for disease progression. Early signs of axonal dysfunction have come to light including impaired mitochondrial trafficking, structural axonal changes, and synaptic alterations. With sustained inflammation as well as impaired remyelination, axons succumb to degeneration contributing to CNS atrophy and worsening of disease. These studies highlight the role of chronic demyelination in the CNS in perpetuating axonal loss, and the difficulty in promoting remyelination and repair amidst persistent inflammatory insult. Regenerative and neuroprotective strategies are essential to overcome this barrier, with early intervention being critical to rescue axonal integrity and function. The clinical and basic research studies discussed in this review have set the stage for identifying key propagators of neurodegeneration in MS, leading the way for neuroprotective therapeutic development. This article is categorized under: Immune System Diseases > Molecular and Cellular Physiology Neurological Diseases > Molecular and Cellular Physiology.

Sex bias in multiple sclerosis and neuromyelitis optica spectrum disorders: How it influences clinical course, MRI parameters and prognosis

This review is a condensed summary of representative articles addressing the sex/gender bias in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD). The strong effects of sex on the incidence and possibly also the activity and progression of these disorders should be implemented in the evaluation of any phase of clinical research and also in treatment choice consideration in clinical practice and evaluation of MRI parameters. Some relationships between clinical variables and gender still remain elusive but with further understanding of sex/gender-related differences, we should be able to provide appropriate patient-centered care and research.

Grey matter atrophy in patients with benign multiple sclerosis

BACKGROUND

Brain atrophy appears during the progression of multiple sclerosis (MS) and is associated with the disability caused by the disease.

METHODS

We investigated global and regional grey matter (GM) and white matter (WM) volumes, WM lesion load, and corpus callosum index (CCI), in benign relapsing-remitting MS (BRRMS, n = 35) with and without any treatment and compared those to aggressive relapsing-remitting MS (ARRMS, n = 46). Structures were analyzed by using an automated MRI quantification tool (cNeuro®).

RESULTS

The total brain and cerebral WM volumes were larger in BRRMS than in ARRMS (p = .014, p = .017 respectively). In BRRMS, total brain volumes, regional GM volumes, and CCI were found similar whether or not disease-modifying treatment (DMT) was used. The total (p = .033), as well as subcortical (p = .046) and deep WM (p = .041) lesion load volumes were larger in BRRMS patients without DMT. Cortical GM volumes did not differ between BRRMS and ARRMS, but the volumes of total brain tissue (p = .014) and thalami (p = .003) were larger in patients with BRRMS compared to ARRMS. A positive correlation was found between CCI and whole-brain volume in both BRRMS (r = .73, p < .001) and ARRMS (r = .80, p < .01).

CONCLUSIONS

Thalamic volume is the most prominent measure to differentiate BRRMS and ARRMS. Validation of automated quantification of CCI provides an additional applicable MRI biomarker to detect brain atrophy in MS.

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.

MRI-based thalamic volumetry in multiple sclerosis using FSL-FIRST: Systematic assessment of common error modes

BACKGROUND AND PURPOSE

FSL's FMRIB's Integrated Registration and Segmentation Tool (FSL-FIRST) is a widely used and well-validated tool. Automated thalamic segmentation is a common application and an important longitudinal measure for multiple sclerosis (MS). However, FSL-FIRST's algorithm is based on shape models derived from non-MS groups. As such, the present study sought to systematically assess common thalamic segmentation errors made by FSL-FIRST on MRIs from people with multiple sclerosis (PwMS).

METHODS

FSL-FIRST was applied to generate thalamic segmentation masks for 890 MR images in PwMS. Images and masks were reviewed systematically to classify and quantify errors, as well as associated anatomical variations and MRI abnormalities. For cases with overt errors (n = 362), thalamic masks were corrected and quantitative volumetric differences were calculated.

RESULTS

In the entire quantitative volumetric group, the mean volumetric error of FSL-FIRST was 2.74% (0.360 ml): among only corrected cases, the mean volumetric error was 6.79% (0.894 ml). The average percent volumetric error associated with seven error types, two anatomical variants, and motions artifacts are reported. Additional analyses showed that the presence of motion artifacts or anatomical variations significantly increased the probability of error (χ²  = 18.14, p < .01 and χ²  = 64.89, p < .001, respectively). Finally, thalamus volume error was negatively associated with degree of atrophy, such that smaller thalami were systematically overestimated (r = -.28, p < .001).

CONCLUSIONS

In PwMS, FSL-FIRST thalamic segmentation miscalculates thalamic volumetry in a predictable fashion, and may be biased to overestimate highly atrophic thalami. As such, it is recommended that segmentations be reviewed and corrected manually when appropriate for specific studies.

Clinical and Paraclinical Biomarkers and the Hitches to Assess Conversion to Secondary Progressive Multiple Sclerosis: A Systematic Review

Conversion to secondary progressive (SP) course is the decisive factor for long-term prognosis in relapsing multiple sclerosis (MS), generally considered the clinical equivalent of progressive MS-associated neuroaxonal degeneration. Evidence is accumulating that both inflammation and neurodegeneration are present along a continuum of pathologic processes in all phases of MS. While inflammation is the prominent feature in early stages, its quality changes and relative importance to disease course decreases while neurodegenerative processes prevail with ongoing disease. Consequently, anti-inflammatory disease-modifying therapies successfully used in relapsing MS are ineffective in SPMS, whereas specific treatment for the latter is increasingly a focus of MS research. Therefore, the prevention, but also the (anticipatory) diagnosis of SPMS, is of crucial importance. The problem is that currently SPMS diagnosis is exclusively based on retrospectively assessing the increase of overt physical disability usually over the past 6–12 months. This inevitably results in a delay of diagnosis of up to 3 years resulting in periods of uncertainty and, thus, making early therapy adaptation to prevent SPMS conversion impossible. Hence, there is an urgent need for reliable and objective biomarkers to prospectively predict and define SPMS conversion. Here, we review current evidence on clinical parameters, magnetic resonance imaging and optical coherence tomography measures, and serum and cerebrospinal fluid biomarkers in the context of MS-associated neurodegeneration and SPMS conversion. Ultimately, we discuss the necessity of multimodal approaches in order to approach objective definition and prediction of conversion to SPMS.

In vivo gradients of thalamic damage in paediatric multiple sclerosis: a window into pathology

The thalamus represents one of the first structures affected by neurodegenerative processes in multiple sclerosis. A greater thalamic volume reduction over time, on its CSF side, has been described in paediatric multiple sclerosis patients. However, its determinants and the underlying pathological changes, likely occurring before this phenomenon becomes measurable, have never been explored. Using a multiparametric magnetic resonance approach, we quantified, in vivo, the different processes that can involve the thalamus in terms of focal lesions, microstructural damage and atrophy in paediatric multiple sclerosis patients and their distribution according to the distance from CSF/thalamus interface and thalamus/white matter interface. In 70 paediatric multiple sclerosis patients and 26 age- and sex-matched healthy controls, we tested for differences in thalamic volume and quantitative MRI metrics-including fractional anisotropy, mean diffusivity and T1/T2-weighted ratio-in the whole thalamus and in thalamic white matter, globally and within concentric bands originating from CSF/thalamus interface. In paediatric multiple sclerosis patients, the relationship of thalamic abnormalities with cortical thickness and white matter lesions was also investigated. Compared to healthy controls, patients had significantly increased fractional anisotropy in whole thalamus (f2 = 0.145; P = 0.03), reduced fractional anisotropy (f2 = 0.219; P = 0.006) and increased mean diffusivity (f2 = 0.178; P = 0.009) in thalamic white matter and a trend towards a reduced thalamic volume (f2 = 0.027; P = 0.058). By segmenting the whole thalamus and thalamic white matter into concentric bands, in paediatric multiple sclerosis we detected significant fractional anisotropy abnormalities in bands nearest to CSF (f2 = 0.208; P = 0.002) and in those closest to white matter (f2 range = 0.183-0.369; P range = 0.010-0.046), while we found significant mean diffusivity (f2 range = 0.101-0.369; P range = 0.018-0.042) and T1/T2-weighted ratio (f2 = 0.773; P = 0.001) abnormalities in thalamic bands closest to CSF. The increase in fractional anisotropy and decrease in mean diffusivity detected at the CSF/thalamus interface correlated with cortical thickness reduction (r range = -0.27-0.34; P range = 0.004-0.028), whereas the increase in fractional anisotropy detected at the thalamus/white matter interface correlated with white matter lesion volumes (r range = 0.24-0.27; P range = 0.006-0.050). Globally, our results support the hypothesis of heterogeneous pathological processes, including retrograde degeneration from white matter lesions and CSF-mediated damage, leading to thalamic microstructural abnormalities, likely preceding macroscopic tissue loss. Assessing thalamic microstructural changes using a multiparametric magnetic resonance approach may represent a target to monitor the efficacy of neuroprotective strategies early in the disease course.

Predicting disability worsening in relapsing and progressive multiple sclerosis

PURPOSE OF REVIEW

Multiple sclerosis (MS) is a clinically heterogeneous disease, which complicates expectant management as well as treatment decisions. This review provides an overview of both well established and emerging predictors of disability worsening, including clinical factors, imaging factors, biomarkers and treatment strategies.

RECENT FINDINGS

In addition to well known clinical predictors (age, male sex, clinical presentation, relapse behaviour), smoking, obesity, vascular and psychiatric comorbidities are associated with subsequent disability worsening in persons with MS. A number of imaging features are predictive of disability worsening and are present to varying degrees in relapsing and progressive forms of MS. These include brain volumes, spinal cord atrophy, lesion volumes and optical coherence tomography features. Cerebrospinal and more recently blood biomarkers including neurofilament light show promise as more easily attainable biomarkers of future disability accumulation. Importantly, recent observational studies suggest that initiation of early-intensive therapy, as opposed to escalation based on breakthrough disease, is associated with decreased accumulation of disability overall, although randomized controlled trials investigating this question are underway.

SUMMARY

Understanding risk factors associated with disability progression can help to both counsel patients and enhance the clinician's availability to provide evidence-based treatment recommendations.

Identifying Early Neuropsychological Indicators of Cognitive Involvement in Multiple Sclerosis

Multiple sclerosis (MS) is a debilitating disease of the central nervous system that is most commonly seen in early to middle adulthood, although it can be diagnosed during childhood or later in life. While cognitive impairment can become more prevalent and severe as the disease progresses, signs of cognitive involvement can be apparent in the early stages of the disease. In this review, we discuss the prevalence and types of cognitive impairment seen in early MS, including the specific measures used to identify them, as well as the challenges in characterizing their frequency and progression. In addition to examining the progression of early cognitive involvement over time, we explore the clinical factors associated with early cognitive involvement, including demographics, level of physical disability, disease modifying therapy use, vocational status, and psychological and physical symptoms. Given the prevalence and functional impact these impairments can have for persons with MS, considerations for clinicians are provided, such as the role of early cognitive screenings and the importance of comprehensive neuropsychological assessments.

Age-dependent cut-offs for pathological deep gray matter and thalamic volume loss using Jacobian integration

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Longitudinal MRI data of 189 healthy controls and 127 MS patients were analyzed.

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Deep gray matter (deep GMVL) thalamic volume loss (ThalaVL) was assessed.

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Magnitude of measurement error was estimated by means of 162 MRI scan-rescans.

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Age-dependent cut-offs for pathological deep GMVL and ThalaVL are provided.

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Result help interpreting deep GMVL and ThalaVL measurements in individual MS patients.

Introduction

Several recent studies indicate that deep gray matter or thalamic volume loss (VL) might be promising surrogate markers of disease activity in multiple sclerosis (MS) patients. To allow applying these markers to individual MS patients in clinical routine, age-dependent cut-offs distinguishing physiological from pathological VL and an estimation of the measurement error, which provides the confidence of the result, are to be defined.

Methods

Longitudinal MRI scans of the following cohorts were analyzed in this study: 189 healthy controls (HC) (mean age 54 years, 22% female), 98 MS patients from Zurich university hospital (mean age 34 years, 62% female), 33 MS patients from Dresden university hospital (mean age 38 years, 60% female), and publicly available reliability data sets consisting of 162 short-term MRI scan-rescan pairs with scan intervals of days or few weeks. Percentage annualized whole brain volume loss (BVL), gray matter (GM) volume loss (GMVL), deep gray matter volume loss (deep GMVL), and thalamic volume loss (ThalaVL) were computed deploying the Jacobian integration (JI) method. BVL was additionally computed using Siena, an established method used in many Phase III drug trials. A linear mixed effect model was used to estimate the measurement error as the standard deviation (SD) of model residuals of all 162 scan-rescan pairs For estimation of age-dependent cut-offs, a quadratic regression function between age and the corresponding annualized VL values of the HC was computed. The 5th percentile was defined as the threshold for pathological VL per year since 95% of HC subjects exhibit a less pronounced VL for a given age. For the MS patients BVL, GMVL, deep GMVL, and ThalaVL were mutually compared and a paired t-test was used to test whether there are systematic differences in VL between these brain regions.

Results

Siena and JI showed a high agreement for BVL measures, with a median absolute difference of 0.1% and a correlation coefficient of r = 0.78. Siena and GMVL showed a similar standard deviation (SD) of the scan-rescan error of 0.28% and 0.29%, respectively. For deep GMVL, ThalaVL the SD of the scan-rescan error was slightly higher (0.43% and 0.5%, respectively). Among the HC the thalamus showed the highest mean VL (−0.16%, −0.39%, and −0.59% at ages 35, 55, and 75, respectively). Corresponding cut-offs for a pathological VL/year were −0.68%, −0.91%, and −1.11%. The MS cohorts did not differ in BVL and GMVL. However, both MS cohorts showed a significantly (p = 0.05) stronger deep GMVL than BVL per year.

Conclusion

It might be methodologically feasible to assess deep GMVL using JI in individual MS patients. However, age and the measurement error need to be taken into account. Furthermore, deep GMVL may be used as a complementary marker to BVL since MS patients exhibit a significantly stronger deep GMVL than BVL.

Assessment of Racial/Ethnic Disparities in Volumetric MRI Correlates of Clinical Disability in Multiple Sclerosis: A Preliminary Study

BACKGROUND AND PURPOSE

Although global and regional brain volume has been established as a relevant measure to define and predict multiple sclerosis (MS) severity, characterization of specific trends by race/ethnicity is currently lacking. We aim to (1) characterize racial disparities in disability-specific patterns of brain MRI volumetric measures between Hispanic and Caucasian individuals with MS and (2) explore the relevance of these measures as predictors of clinical disability progression.

METHODS

Brain MRI scans from 94 Hispanic and 94 age- and gender-matched Caucasian MS patients were analyzed using automatic and manual segmentation techniques. Select global and regional volume measures were correlated to Expanded Disability Status Scale (EDSS) scores at baseline and subsequent follow-up visits.

RESULTS

Hispanic patients had a higher baseline median EDSS score (interquartile range [IQR], 2.0; [1.0-3.5]) compared to Caucasians (median [IQR], 1.0 [.0-2.0]) and an increased risk of requiring ambulatory assistance (hazard ratio [HR], 9.7; 95% confidence interval [CI], 2.8-32.5). Normalized thalamic volume was moderately associated with EDSS scores (r_s   = -.42,  P < .001 in Hispanics; r_s   = -.32, P  = .002 in Caucasians) and was the best predictor of sustained disability worsening in both racial groups in a time-to-event analysis.

CONCLUSIONS

The confounding impact of race on quantitative brain volume measures may affect the interpretation of outcome measures in MS clinical trials.

Thalamic Atrophy Predicts 5-Year Disability Progression in Multiple Sclerosis

Purpose: Thalamus is among the first brain regions to become atrophic in multiple sclerosis (MS). We studied whether thalamic atrophy predicts disability progression at 5 years in a cohort of Finnish MS patients.

Methods: Global and regional brain volumes were measured from 24 newly diagnosed relapsing MS (RMS) patients 6 months after initiation of therapy and from 36 secondary progressive MS (SPMS) patients. The patients were divided into groups based on baseline whole brain parenchymal (BP) and thalamic atrophy. Standard scores (z scores) were computed by comparing individual brain volumes with healthy controls. A z score cutoff of −1.96 was applied to separate atrophic from normal brain volumes. The Expanded Disability Status Scale (EDSS), brain magnetic resonance imaging (MRI) findings, and relapses were assessed at baseline and at 2 years and EDSS progression at 5 years.

Results: Baseline thalamus volume predicted disability in 5 years in a logistic regression model (p = 0.031). At 5 years, EDSS was same or better in 12 of 18 patients with no brain atrophy at baseline but only in 5 of 18 patients with isolated thalamic atrophy [odds ratio (OR) (95% CI) = 5.2 (1.25, 21.57)]. The patients with isolated thalamic atrophy had more escalations of disease-modifying therapies during follow-up.

Conclusion: Patients with thalamic atrophy at baseline were at a higher risk for 5-year EDSS increase than patients with no identified brain atrophy. Brain volume measurement at a single time point could help predict disability progression in MS and complement clinical and routine MRI evaluation in therapeutic decision-making.

Characterization of thalamic lesions and their correlates in multiple sclerosis by ultra-high-field MRI

BACKGROUND

Thalamic pathology is a marker for neurodegeneration and multiple sclerosis (MS) disease progression.

OBJECTIVE

To characterize (1) the morphology of thalamic lesions, (2) their relation to cortical and white matter (WM) lesions, and (3) clinical measures, and to assess (4) the imaging correlates of thalamic atrophy.

METHODS

A total of 90 MS patients and 44 healthy controls underwent acquisition of 7 Tesla images for lesion segmentation and 3 Tesla scans for atrophy evaluation. Thalamic lesions were classified according to the shape and the presence of a central venule. Regression analysis identified the predictors of (1) thalamic atrophy, (2) neurological disability, and (3) information processing speed.

RESULTS

Thalamic lesions were mostly ovoid than periventricular, and for the great majority (78%) displayed a central venule. Lesion volume in the thalamus, cortex, and WM did not correlate with each other. Thalamic atrophy was only associated with WM lesion volume (p = 0.002); subpial and WM lesion volumes were associated with neurological disability (p = 0.016; p < 0.001); and WM and thalamic lesion volumes were related with cognitive impairment (p < 0.001; p = 0.03).

CONCLUSION

Thalamic lesions are unrelated to those in the cortex and WM, suggesting that they may not share common pathogenic mechanisms and do not contribute to thalamic atrophy. Combined WM, subpial, and thalamic lesion volumes at 7 Tesla contribute to the disease severity.

Aggressive multiple sclerosis (1): Towards a definition of the phenotype

While the major phenotypes of multiple sclerosis (MS) and relapsing-remitting, primary and secondary progressive MS have been well characterized, a subgroup of patients with an active, aggressive disease course and rapid disability accumulation remains difficult to define and there is no consensus about their management and treatment. The current lack of an accepted definition and treatment guidelines for aggressive MS triggered a 2018 focused workshop of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) on aggressive MS. The aim of the workshop was to discuss approaches on how to describe and define the disease phenotype and its treatments. Unfortunately, it was not possible to come to consensus on a definition because of unavailable data correlating severe disease with imaging and molecular biomarkers. However, the workshop highlighted the need for future research needed to define this disease subtype while also focusing on its treatment and management. Here, we review previous attempts to define aggressive MS and present characteristics that might, with additional research, eventually help characterize it. A companion paper summarizes data regarding treatment and management.

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

INTRODUCTION

Conventional imaging measures remain a key clinical tool for the diagnosis multiple sclerosis (MS) and monitoring of patients. However, most measures used in the clinic show unsatisfactory performance in predicting disease progression and conversion to secondary progressive MS.

AREAS COVERED

Sophisticated imaging techniques have facilitated the identification of imaging biomarkers associated with disease progression, such as global and regional brain volume measures, and with conversion to secondary progressive MS, such as leptomeningeal contrast enhancement and chronic inflammation. The relevance of emerging imaging approaches partially overcoming intrinsic limitations of traditional techniques is also discussed.

EXPERT OPINION

Imaging biomarkers capable of detecting tissue damage early on in the disease, with the potential to be applied in multicenter trials and at an individual level in clinical settings, are strongly needed. Several measures have been proposed, which exploit advanced imaging acquisitions and/or incorporate sophisticated post-processing, can quantify irreversible tissue damage. The progressively wider use of high-strength field MRI and the development of more advanced imaging techniques will help capture the missing pieces of the MS puzzle. The ability to more reliably identify those at risk for disability progression will allow for earlier intervention with the aim to favorably alter the disease course.

Intrinsic and Extrinsic Mechanisms of Thalamic Pathology in Multiple Sclerosis

OBJECTIVE

Thalamic atrophy is among the earliest brain changes detected in patients with multiple sclerosis (MS) and the degree of thalamic atrophy is a strong predictor of disability progression. The causes of thalamic atrophy are not fully understood. Here, we investigate the contributions of thalamic demyelinated lesions, thalamic neuronal loss, and cerebral white matter (WM) lesions to thalamic volume.

METHODS

We used postmortem in situ magnetic resonance imaging (MRI) scans of 95 subjects with MS to correlate thalamic lesion volumes with global MRI metrics. We histologically characterized thalamic demyelination patterns and compared neuronal loss and neuritic pathology in the thalami with the extremes of volume.

RESULTS

Grossly apparent thalamic discolorations in cm-thick brain slices were T2/fluid-attenuated inversion recovery (FLAIR) hyperintense, T1-hypointense, and appeared as perivascular demyelinated lesions with dystrophic neurons/axons. Subependymal demyelinated lesions with axonal loss and microglial/macrophage activation were also observed. The 12 subjects with the least thalamic volume had a 17.6% reduction of median neuronal density in the dorsomedial/ventrolateral and pulvinar nuclei compared with the 14 subjects with the greatest thalamic volume (p = 0.03). After correcting for age, disease duration, sex, and T2 lesion volume, the total (p = 0.20), ovoid (p = 0.31), or subependymal (p = 0.44) MRI thalamic lesion volumes correlated with thalamic volume. Thalamic volume correlated with cerebral T2 lesion volume (Spearman's rho = -0.65, p < 0.001; p < 0.0001 after correcting for age, disease duration, and sex).

INTERPRETATION

Our findings suggest the degeneration of efferent/afferent thalamic projections and/or a neurodegenerative process as greater contributors to thalamic atrophy than thalamic demyelinating lesions. ANN NEUROL 2020 ANN NEUROL 2020;88:81-92.