Pathological cut-offs of global and regional brain volume loss in multiple sclerosis

Brain atrophy assessment in multiple sclerosis: technical- and subject-related barriers for translation to real-world application in individual subjects

INTRODUCTION

Brain atrophy is a well-established MRI outcome for predicting clinical progression and monitoring treatment response in persons with multiple sclerosis (pwMS) at the group level. Despite the important progress made, the translation of brain atrophy assessment into clinical practice faces several challenges.

AREAS COVERED

In this review, the authors discuss technical- and subject-related barriers for implementing brain atrophy assessment as part of the clinical routine at the individual level. Substantial progress has been made to understand and mitigate technical barriers behind MRI acquisition. Numerous research and commercial segmentation techniques for volume estimation are available and technically validated, but their clinical value has not been fully established. A systematic assessment of subject-related barriers, which include genetic, environmental, biological, lifestyle, comorbidity, and aging confounders, is critical for the interpretation of brain atrophy measures at the individual subject level. Educating both medical providers and pwMS will help better clarify the benefits and limitations of assessing brain atrophy for disease monitoring and prognosis.

EXPERT OPINION

Integrating brain atrophy assessment into clinical practice for pwMS requires overcoming technical and subject-related challenges. Advances in MRI standardization, artificial intelligence, and clinician education will facilitate this process, improving disease management and potentially reducing long-term healthcare costs.

Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies

INTRODUCTION

Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS.

METHODS

In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.

RESULTS

A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.

CONCLUSION

This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.

Cortical Thin Patch Fraction Reflects Disease Burden in MS: The Mosaic Approach

BACKGROUND AND PURPOSE

GM pathology plays an essential role in MS disability progression, emphasizing the importance of neuroradiologic biomarkers to capture the heterogeneity of cortical disease burden. This study aimed to assess the validity of a patch-wise, individual interpretation of cortical thickness data to identify GM pathology, the "mosaic approach," which was previously suggested as a biomarker for assessing and localizing atrophy.

MATERIALS AND METHODS

We investigated the mosaic approach in a cohort of 501 patients with MS with respect to 89 internal and 651 external controls. The resulting metric of the mosaic approach is the so-called thin patch fraction, which is an estimate of overall cortical disease burden per patient. We evaluated the mosaic approach with respect to the following: 1) discrimination between patients with MS and controls, 2) classification between different MS phenotypes, and 3) association with established biomarkers reflecting MS disease burden, using general linear modeling.

RESULTS

The thin patch fraction varied significantly between patients with MS and healthy controls and discriminated among MS phenotypes. Furthermore, the thin patch fraction was associated with disease burden, including the Expanded Disability Status Scale, cognitive and fatigue scores, and lesion volume.

CONCLUSIONS

This study demonstrates the validity of the mosaic approach as a neuroradiologic biomarker in MS. The output of the mosaic approach, namely the thin patch fraction, is a candidate biomarker for assessing and localizing cortical GM pathology. The mosaic approach can furthermore enhance the development of a personalized cortical MS biomarker, given that the thin patch fraction provides a feature on which artificial intelligence methods can be trained. Most important, we showed the validity of the mosaic approach when referencing data with respect to external control MR imaging repositories.

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.

Communicating the relevance of neurodegeneration and brain atrophy to multiple sclerosis patients: patient, provider and researcher perspectives

Central nervous system (CNS) atrophy provides valuable additional evidence of an ongoing neurodegeneration independent of lesion accrual in persons with multiple sclerosis (PwMS). However, there are limitations for interpretation of CNS volume changes at individual patient-level. Patients are receiving information on the topic of atrophy through various sources, including media, patient support groups and conferences, and discussions with their providers. Whether or not the topic of CNS atrophy should be proactively discussed with PwMS during office appointments is currently controversial. This commentary/perspective article represents perspectives of PwMS, providers and researchers with recommendations for minimizing confusion and anxiety, and facilitating proactive discussion about brain atrophy, as an upcoming routine measure in evaluating disease progression and treatment response monitoring. The following recommendations were created based on application of patient's and provider's surveys, and various workshops held over a period of 2 years: (1) PwMS should receive basic information on understanding of brain functional anatomy, and explanation of inflammation and neurodegeneration; (2) the expertise for atrophy measurements should be characterized as evolving; (3) quality patient education materials on these topics should be provided; (4) the need for standardization of MRI exams has to be explained and communicated; (5) providers should discuss background on volumetric changes, including references to normal aging; (6) the limitations of brain volume assessments at an individual-level should be explained; (7) the timing and language used to convey this information should be individualized based on the patient's background and disease status; (8) a discussion guide may be a very helpful resource for use by providers/staff to support these discussions; (9) understanding the role of brain atrophy and other MRI metrics may elicit greater patient satisfaction and acceptance of the value of therapies that have proven efficacy around these outcomes; (10) the areas that represent possibilities for positive self-management of MS symptoms that foster hope for improvement should be emphasized, and in particular regarding use of physical and mental exercise that build or maintain brain reserve through increased network efficiency, and (11) an additional time during clinical visits should be allotted to discuss these topics, including creation of specific educational programs.

Multiple sclerosis as a model to investigate SARS-CoV-2 effect on brain atrophy

INTRODUCTION

Data on structural brain changes after infection with SARS-CoV-2 is sparse. We postulate multiple sclerosis as a model to study the effects of SARS-CoV-2 on brain atrophy due to the unique availability of longitudinal imaging data in this patient group, enabling assessment of intraindividual brain atrophy rates.

METHODS

Global and regional cortical gray matter volumes were derived from structural MRIs using FreeSurfer. A linear model was fitted to the measures of the matching pre-SARS-CoV-2 images with age as an explanatory variable. The residuals were used to determine whether the post-SARS-CoV-2 volumes differed significantly from the baseline.

RESULTS

Fourteen RRMS patients with a total of 113 longitudinal magnetic resonance images were retrospectively analyzed. We found no acceleration of brain atrophy after infection with SARS-CoV-2 for global gray matter volume (p = 0.17). However, on the regional level, parahippocampal gyri showed a tendency toward volume reduction (p = 0.0076), suggesting accelerated atrophy during or after infection.

CONCLUSIONS

Our results illustrate the opportunity of using longitudinal MRIs from existing MS registries to study brain changes associated with SARS-CoV-2 infections. We would like to address the global MS community with a call for action to use the available cohorts, reproduce the proposed analysis, and pool the results.

Multisite MRI reproducibility of lateral ventricular volume using the NAIMS cooperative pilot dataset

BACKGROUND AND PURPOSE

The North American Imaging in Multiple Sclerosis (NAIMS) multisite project identified interscanner reproducibility issues with T1-based whole brain volume (WBV). Lateral ventricular volume (LVV) acquired on T2-fluid-attenuated inverse recovery (FLAIR) scans has been proposed as a robust proxy measure. Therefore, we sought to determine the relative magnitude of scanner-induced T2-FLAIR-based LVV and T1-based WBV measurement errors in relation to clinically meaningful changes.

METHODS

This was a post hoc analysis of the NAIMS pilot dataset in which a relapsing-remitting MS patient with no intrastudy clinical or radiological activity was imaged twice on seven different Siemens scanners across the United States. LVV was determined using the automated NeuroSTREAM technique on T2-FLAIR and WBV was determined with SIENAX on high-resolution T1-MPRAGE. Average LVV and WBV were measured, and absolute intrascanner and interscanner coefficients of variation (CoVs) were calculated. The variabilities were compared to previously established annual pathological and clinically meaningful cutoffs of 0.40% for WBV and of 3.51% for LVV.

RESULTS

Mean LVV across all seven scan/rescan pairs was 45.87 ± 1.15 ml. Average LVV intrascanner CoV was 1.42% and interscanner CoV was 1.78%, both smaller than the reported annualized clinically meaningful cutoff of 3.51%. In contrast, intra- and interscanner CoVs for WBV (0.99% and 1.15%) were both higher than the established cutoff of 0.40%. Individually, 1/7 intrasite and 2/7 intersite pair-wise LVV comparisons were above the 3.51% cutoff, whereas 4/7 intrasite and 7/7 intersite WBV comparisons were above the 0.40% cutoff.

CONCLUSION

Fully automated LVV segmentation has higher absolute variability than WBV, but much lower relative variability compared to clinically relevant changes, and may therefore be a meaningful proxy outcome measure of neurodegeneration.

Predicting Long-term Disability in Multiple Sclerosis: A Narrative Review of Current Evidence and Future Directions

The ability to reliably monitor disease progression in patients with multiple sclerosis (MS) is integral to patient care. The Expanded Disability Status Scale (EDSS) is a commonly used tool to assess the disability status of patients with MS; however, it has limited sensitivity in detecting subtle changes in disability levels and, as a result, does not consistently provide clinicians with accurate insight into disease progression. At the 2019 European Committee for Treatment and Research in Multiple Sclerosis meeting in Stockholm, Sweden, a panel of neurologists met to discuss the limitations of the EDSS as a short-term predictor of MS progression. Before this panel discussion, a targeted literature review was conducted to evaluate published evidence on prognostic measures such as fatigue, physical assessments, and measures that are more taxing for patients, all of which may be useful to clinicians at different stages of the course of MS. This article summarizes currently available evidence in support of these measures. In addition, this article highlights the current state of expert clinical consensus regarding the current approaches used to predict and monitor disease progression and offers insight for future studies to assist clinicians in accurately monitoring disease progression in patients with MS.

Longitudinal tracking of axonal loss using diffusion magnetic resonance imaging in multiple sclerosis

Axonal loss in the CNS is a key driver of progressive neurological impairments in people with multiple sclerosis. Currently, there are no established methods for tracking axonal loss clinically. This study aimed to determine the sensitivity of longitudinal diffusion MRI derived fibre specific measures of axonal loss in people with multiple sclerosis. Fibre measures were derived from diffusion MRI acquired as part of a standard radiological MRI protocol and were compared 1) to established measures of neuro-axonal degeneration: brain parenchymal fraction and retinal nerve fibre layer thickness and 2) between different disease stages: clinically isolated syndrome and early/late relapsing-remitting multiple sclerosis. Retrospectively identified data from fifty-nine people with multiple sclerosis (18 clinically isolated syndrome, 22 early and 19 late relapsing-remitting) who underwent diffusion MRI as part of their routine clinical monitoring were collated and analysed. Twenty-six patients had 1-year and 14 patients had 2-year follow-up. Brain parenchymal fraction was calculated from 3D MRI scans, and fibre-specific measures were calculated from diffusion MRI using multi-tissue constrained spherical deconvolution. At each study visit, patients underwent optical coherence tomography to determine retinal nerve fibre layer thickness, and standard neurological assessment expanded disability status scale. We found a significant annual fibre-specific neuro-axonal degeneration (mean ± SD = −3.49 ± 3.32%, p<0.001) that was approximately seven times larger than the annual change of brain parenchymal fraction (−0.53 ± 0.95%, p<0.001), and more than four times larger than annual retinal nerve fibre layer thinning (−0.75 ± 2.50% p=0.036). Only fibre-specific measures showed a significant difference in annual degeneration between the disease stages (p=0.029). Reduced brain parenchymal fraction, retinal nerve fibre layer thickness and fibre-specific measures were moderately related to higher expanded disability status scale (respectively rho=−0.368, rho=−0.408 and rho=−0.365). Fibre-specific measures can be measured from data collected within a standard radiological multiple sclerosis study and are substantially more sensitive to longitudinal change compared to brain atrophy and retinal nerve fibre layer thinning.

Pregnancy-induced brain MRI changes in women with multiple sclerosis

BACKGROUND

The effect of pregnancy on brain changes and radiological disease activity in women with multiple sclerosis (MS) is not well understood.

AIMS

To describe the dynamic of lesion activity and brain volume changes during the pregnancy and postpartum periods.

METHODS

This observational study of 62 women with relapsing-remitting MS included MRI (221 scans) as well as clinical visits at baseline (<24 and >6 months before), prepregnancy (<6 months before), postpartum (<3 months after), and the follow-up (>12 and <24 months after delivery) period.

RESULTS

The majority of women had a mild disability and a short disease duration (median 5.5 years). Eighteen (29.0%) women had a relapse during the year preceding pregnancy onset, 9 (14.5%) during pregnancy, and 20 (32.3%) in the year following delivery. Disability status remained unchanged during follow-up. Women in the postpartum period (n=62) had higher T2 lesion volume (median: 0.94 ml vs. 1.18 ml), greater annualized T2 lesion volume increase (0.0 ml vs. 0.23 ml), lower brain parenchymal fraction (86.4% vs. 85.6%) and greater annualized brain volume loss (-0.16% vs. -1.74%) compared with the prepregnancy period (all p<0.001). At 12-24 months after delivery women (n=41) had higher T2 lesion volume (1.0 ml vs. 1.16 ml) and lower brain parenchymal fraction (86.5% vs. 86.0%) compared to the prepregnancy period (both p<0.001).

CONCLUSIONS

The postpartum period was associated with an increase in T2 lesion volume and accelerated brain volume loss in a considerable proportion of women. This should be considered in treatment decision-making and designing clinical trials.

Brain atrophy rates in patients with multiple sclerosis on long term natalizumab resembles healthy controls

BACKGROUND

Clinically stable multiple sclerosis (MS) patients often have negligible inflammatory MRI changes. Brain atrophy may provide insight into subclinical disease progression. The objective was to compare brain atrophy rates in stable patients on long term natalizumab treatment vs. age and gender matched healthy non-MS controls (HC) prospectively over two-years examining brain volume, cognition, and patient reported outcomes (PROs).

METHODS

MS patients treated with natalizumab for a minimum of 2 years, age 18-60 were recruited and compared with age- and gender-matched healthy controls (HC). Both groups were followed prospectively to obtain two years of consecutive magnetic resonance imaging, clinical and PRO data. Baseline normalized brain volume (NBV), yearly T2 lesion volume (T2LV), and percent brain volume change (PBVC) were measured using SIENAX, JIM 6.0, and SIENA respectively. Neuropsychological tests from the MACFIMS battery were selected to optimize assessments for impairments in the domains of information processing speed and memory. Patient reported outcomes (PROs) for domains of physical, mental and social quality of life were evaluated using the NeuroQol short forms.

RESULTS

Forty-eight natalizumab and 62 HC completed all study visits. At baseline, unadjusted mean NBV (natalizumab=1508.80cm (Popescu et al., 2013) vs. HC=1539.23cm (Popescu et al., 2013); p=0.033) and median baseline T2LV (natalizumab=1724.62mm (Popescu et al., 2013) vs. HC=44.20mm (Popescu et al., 2013); p=<0.0001) were different. The mean PBVC at year 2, adjusted for gender and baseline age was -0.57% (CI: 0.7620, -0.3716) for natalizumab and -0.50% (-0.7208, -0.2831) for HC, but the difference between groups was not statistically significant (0.073%; p=0.62). Over the 2-year period, HC demonstrated mild improvements in some cognitive tests vs. natalizumab subjects. However, PROs were similar between the two groups.

CONCLUSION

Stable MS patients on natalizumab have similar brain volume loss as people who do not have MS, suggesting normalization of brain atrophy.

Retinal layer thinning predicts treatment failure in relapsing multiple sclerosis

Background and purpose

Peripapillary retinal nerve fiber layer (pRNFL) and macular ganglion cell plus inner plexiform layer (GCIPL) thinning are markers of neuroaxonal degeneration in multiple sclerosis (MS), which is reduced by disease‐modifying treatment (DMT). We aimed to investigate the potential of pRNFL and GCIPL thinning for prediction of DMT failure in relapsing MS (RMS).

Methods

In this 4‐year prospective observational study on 113 RMS patients, pRNFL and GCIPL were measured at DMT initiation and after 12 months (M12) and 24 months (M24). Treatment failure was defined as 6‐month confirmed Expanded Disability Status Scale (EDSS) progression and/or Symbol Digit Modalities Test (SDMT) worsening. Optimal cutoff values for predicting treatment failure were determined by receiver operating characteristic analyses and hazard ratios (HRs) by multivariable Cox regression adjusting for age, sex, disease duration, EDSS/SDMT, and DMT class.

Results

Thinning of GCIPL >0.5 μm/year at M24 showed superior value for treatment failure prediction (HR: 4.5, 95% confidence interval [CI]: 1.8–7.6, p < 0.001; specificity 91%, sensitivity 81%), followed by GCIPL >0.5 μm at M12 (odds ratio [OR]: 3.9, 95% CI: 1.4–6.9, p < 0.001; specificity 85%, sensitivity 78%), and pRNFL ≥2 μm/year at M24 (OR: 3.7, 95% CI: 1.1–6.5, p = 0.023; specificity 84%, sensitivity 69%), whereas pRNFL at M12 was not predictive.

Conclusions

GCIPL, and to a lesser degree pRNFL, thinning predicts disability progression after DMT initiation and may be a useful and accessible biomarker of treatment failure in RMS.

Evolution of Brain Volume Loss Rates in Early Stages of Multiple Sclerosis

Objective

To describe the dynamics of brain volume loss (BVL) at different stages of relapsing-remitting multiple sclerosis (RRMS), to describe the association between BVL and clinical measures, and to investigate an effect of treatment escalation on the rate of BVL.

Methods

Together, 1903 patients predominantly with RRMS from the Avonex-Steroids-Azathioprine cohort (N = 166), the study of early IFN-β1a treatment cohort (N = 180), and the quantitative MRI cohort (N = 1,557) with ≥2 MRI scans and ≥1-year of follow-up were included. Brain MRI scans (N = 7,203) were performed using a single 1.5-T machine. Relationships between age or disease duration and global and tissue-specific BVL rates were analyzed using mixed models.

Results

Age was not associated with the rate of BVL (β = −0.003; Cohen f2 = 0.0005; adjusted p = 0.39). Although disease duration was associated with the rate of BVL, its effect on the BVL rate was minimal (β = −0.012; Cohen f2 = 0.004; adjusted p = 4 × 10⁻⁵). Analysis of association between tissue-specific brain volume changes and age (β = −0.019 to −0.011; adjusted p = 0.028–1.00) or disease duration (β = −0.028 to −0.008; adjusted p = 0.16–0.96) confirmed these results. Although increase in the relapse rate (β = 0.10; adjusted p = 9 × 10⁻⁹), Expanded Disability Status Scale (EDSS; β = 0.17; adjusted p = 8 × 10⁻⁵), and EDSS change (β = 0.15; adjusted p = 2 × 10⁻⁵) were associated with accelerated rate of BVL, their effect on the rate of BVL was minimal (all Cohen f2 ≤ 0.007). In 94 patients who escalated therapy, the rate of BVL decreased following treatment escalation by 0.29% (β = −0.29; Cohen f2 = 0.133; p = 5.5 × 10⁻⁸).

Conclusions

The rate of BVL is relatively stable throughout the course of RRMS. The accelerated BVL is weakly associated with concurrent higher disease activity, and timely escalation to high-efficacy immunotherapy helps decrease the rate of BVL.

Factors influencing daily treatment choices in multiple sclerosis: practice guidelines, biomarkers and burden of disease

At two meetings of a Central European board of multiple sclerosis (MS) experts in 2018 and 2019 factors influencing daily treatment choices in MS, especially practice guidelines, biomarkers and burden of disease, were discussed. The heterogeneity of MS and the complexity of the available treatment options call for informed treatment choices. However, evidence from clinical trials is generally lacking, particularly regarding sequencing, switches and escalation of drugs. Also, there is a need to identify patients who require highly efficacious treatment from the onset of their disease to prevent deterioration. The recently published European Committee for the Treatment and Research in Multiple Sclerosis/European Academy of Neurology clinical practice guidelines on pharmacological management of MS cover aspects such as treatment efficacy, response criteria, strategies to address suboptimal response and safety concerns and are based on expert consensus statements. However, the recommendations constitute an excellent framework that should be adapted to local regulations, MS center capacities and infrastructure. Further, available and emerging biomarkers for treatment guidance were discussed. Magnetic resonance imaging parameters are deemed most reliable at present, even though complex assessment including clinical evaluation and laboratory parameters besides imaging is necessary in clinical routine. Neurofilament-light chain levels appear to represent the current most promising non-imaging biomarker. Other immunological data, including issues of immunosenescence, will play an increasingly important role for future treatment algorithms. Cognitive impairment has been recognized as a major contribution to MS disease burden. Regular evaluation of cognitive function is recommended in MS patients, although no specific disease-modifying treatment has been defined to date. Finally, systematic documentation of real-life data is recognized as a great opportunity to tackle unresolved daily routine challenges, such as use of sequential therapies, but requires joint efforts across clinics, governments and pharmaceutical companies.

Interpretation of Brain Volume Increase in Multiple Sclerosis

BACKGROUND AND PURPOSE

A high variability of brain MRI volume change measurement renders challenging its interpretation in multiple sclerosis (MS). Occurrence and clinical relevance of observed apparent brain volume increase (BVI) in MS patients have not been investigated yet. The objective was to quantify the prevalence and factors associated with BVI.

METHODS

We examined 366 MS patients (2,317 scans) and 44 controls (132 scans). Volumetric analysis of brain volume changes was performed by SIENA and ScanView. BVI was defined as brain volume change >0%. We compared characteristics of patients with and without BVI.

RESULTS

BVI was found in 26.3% (from 1,951) longitudinal scans (SIENA). If BVI occurred, a probability that BVI will be repeated consecutively more than or equal to two times was 15.9%. The repeated BVI was associated with clinical disease activity in 50% of cases. BVI was associated with shorter time and lower T2 lesion volume increase between two MRI scans, and higher normalized brain volume (all P < .0001). A proportion of scans with BVI was higher when analyzed by ScanView (35.3%) and in controls (36.4% by SIENA).

CONCLUSIONS

BVI occurs in a great proportion of MR scans over short-term follow-up and is not associated with disease stabilization. Although BVI can be caused by several factors, the results indicate that measurement error may contribute to BVI in the majority of cases. Clinicians should be aware of the frequent occurrence of apparent BVI, interpret brain volume changes in MS patients with great caution, and use methods with precise quantification of brain volume changes.

Exploring the performance of outcome measures in MS for predicting cognitive and clinical progression in the following years

BACKGROUND

The demand for better outcome measures in multiple sclerosis (MS) management has been increasingly recognized. Nevertheless, the prognostic impacts of available outcome measures for long-term clinical and especially cognitive disability have not been thoroughly investigated. We, therefore, aimed to explore the sustainability and long-term predictive value of outcome measures in MS.

METHODS

We studied a cohort of 42 relapsing-remitting MS patients and 30 healthy subjects. Evaluations were performed at baseline and after two (Y2) and six years (Y6), and included neurological and neuropsychological evaluation (BRBN), MRI (3T), and quality of life assessment. Combined clinical and cognitive measures were evaluated, such as minimal and no evidence of disease activity (MEDA and NEDA, respectively). We performed logistic regression with bootstrapping and calculated the diagnostic properties to identify patients who reached six-year clinical and/or cognitive worsening.

RESULTS

NEDA status was observed in up to 30.8% of patients at Y2, but only in 5% at Y6, and did not preclude cognitive decline (SDMT and BRBN). The absence of MRI activity and MEDA status at Y2 were associated with less EDSS worsening in the following years but without impact on cognition. The absence of deterioration on combined clinical/cognitive measures at Y2 (e.g., T25W+ 9HPT + BRBN) was associated with better outcomes in the following years (clinical and cognitive), with moderate to large effect sizes. For the identification of clinical worsening at Y6, best accuracies were found for MEDA (70.6%), and clinical worsening (71.4%), but only MEDA remained in the final model after multivariable logistic regression analysis (OR = 6.81, p = 0.017). For combined clinical and cognitive worsening at Y6, only T25W+ 9HPT + BRBN remained in the final model (OR = 8.5, p = 0.017).

CONCLUSIONS

Early MS inflammatory disease activity is associated with future clinical disability. Nevertheless, NEDA was difficult to sustain in the long-term and did not preclude cognitive deterioration. Clinical and cognitive measures combined predicted outcomes better than each one isolated. Our data suggest that the evaluation of more than one cognitive domain yields a better predictive outcome measure.

Macular ganglion cell-inner plexiform layer thinning as a biomarker of disability progression in relapsing multiple sclerosis

BACKGROUND

Macular ganglion cell-inner plexiform layer (mGCIPL) is an emerging biomarker of neuroaxonal degeneration in multiple sclerosis (MS).

OBJECTIVE

We aimed to determine cut-off values of mGCIPL thinning for discriminating between progressing and stable patients in relapsing multiple sclerosis (RMS).

METHODS

This is a 3-year prospective longitudinal study on 183 RMS patients with annual optical coherence tomography. Best possible cut-off values of baseline mGCIPL and annual loss of macular ganglion cell-inner plexiform layer (aLmGCIPL) for discriminating clinically progressing (physical progression or cognitive decline) from stable patients were defined by receiver operating characteristics analysis and tested using multivariate regression models.

RESULTS

Baseline mGCIPL thickness <77 µm was associated with an increased risk (hazard ratio: 2.7, 95% confidence interval (CI): 1.5-4.7, p < 0.001) of disability progression. An aLmGCIPL cut-off ⩾1 µm accurately identified clinically progressing patients (87% sensitivity at 90% specificity) and was a strong predictor of clinical progression (odds ratio: 18.3, 95% CI: 8.8-50.3).

CONCLUSION

We present evidence that cross-sectionally measured mGCIPL thickness and annualized thinning rates of mGCIPL are able to identify clinically progressing RMS with high accuracy.

Longitudinal Assessment of Multiple Sclerosis with the Brain-Age Paradigm

OBJECTIVE

During the natural course of multiple sclerosis (MS), the brain is exposed to aging as well as disease effects. Brain aging can be modeled statistically; the so-called "brain-age" paradigm. Here, we evaluated whether brain-predicted age difference (brain-PAD) was sensitive to the presence of MS, clinical progression, and future outcomes.

METHODS

In a longitudinal, multicenter sample of 3,565 magnetic resonance imaging (MRI) scans, in 1,204 patients with MS and clinically isolated syndrome (CIS) and 150 healthy controls (mean follow-up time: patients 3.41 years, healthy controls 1.97 years), we measured "brain-predicted age" using T1-weighted MRI. We compared brain-PAD among patients with MS and patients with CIS and healthy controls, and between disease subtypes. Relationships between brain-PAD and Expanded Disability Status Scale (EDSS) were explored.

RESULTS

Patients with MS had markedly higher brain-PAD than healthy controls (mean brain-PAD +10.3 years; 95% confidence interval [CI] = 8.5-12.1] versus 4.3 years; 95% CI = 2.1 to 6.4; p < 0.001). The highest brain-PADs were in secondary-progressive MS (+13.3 years; 95% CI = 11.3-15.3). Brain-PAD at study entry predicted time-to-disability progression (hazard ratio 1.02; 95% CI = 1.01-1.03; p < 0.001); although normalized brain volume was a stronger predictor. Greater annualized brain-PAD increases were associated with greater annualized EDSS score (r = 0.26; p < 0.001).

INTERPRETATION

The brain-age paradigm is sensitive to MS-related atrophy and clinical progression. A higher brain-PAD at baseline was associated with more rapid disability progression and the rate of change in brain-PAD related to worsening disability. Potentially, "brain-age" could be used as a prognostic biomarker in early-stage MS, to track disease progression or stratify patients for clinical trial enrollment. ANN NEUROL 2020 ANN NEUROL 2020;88:93-105.

Brain volume loss in individuals over time: Source of variance and limits of detectability

BACKGROUND

Brain volume loss measured from magnetic resonance imaging (MRI) is a marker of neurodegeneration and predictor of disability progression in MS, and is commonly used to assess drug efficacy at the group level in clinical trials. Whether measures of brain volume loss could be useful to help guide management of individual patients depends on the relative magnitude of the changes over a given interval to physiological and technical sources of variability.

GOAL

To understand the relative contributions of neurodegeneration vs. physiological and technical sources of variability to measurements of brain volume loss in individuals.

MATERIAL AND METHODS

Multiple T1-weighted 3D MPRAGE images were acquired from a healthy volunteer and MS patient over varying time intervals: 7 times on the first day (before breakfast at 7:30AM and then every 2 ​h for 12 ​h), each day for the next 6 working days, and 6 times over the remainder of the year, on 2 ​Siemens MRI scanners: 1.5T Sonata (S1) and 3.0T TIM Trio (S2). Scan-reposition-rescan data were acquired on S2 for daily, monthly and 1-year visits. Percent brain volume change (PBVC) was measured from baseline to each follow-up scan using FSL/SIENA. We estimated the effect of physiologic fluctuations on brain volume using linear regression of the PBVC values over hourly and daily intervals. The magnitude of the physiological effect was estimated by comparing the root-mean-square error (RMSE) of the regression of all the data points relative to the regression line, for the hourly scans vs the daily scans. Variance due to technical sources was assessed as the RMSE of the regression over time using the intracranial volume as a reference.

RESULTS

The RMSE of PBVC over 12 ​h, for both scanners combined, ("Hours", 0.15%), was similar to the day-to-day variation over 1 week ("Days", 0.14%), and both were smaller than the RMS error over the year (0.21%). All of these variations, however, were smaller than the scan-reposition-rescan RMSE (0.32%). The variability of PBVC for the individual scanners followed the same trend. The standard error of the mean (SEM) for PBVC was 0.26 for S1, and 0.22 for S2. From these values, we computed the minimum detectable change (MDC) to be 0.7% on S1 and 0.6% on S2. The location of the brain along the z-axis of the magnet inversely correlated with brain volume change for hourly and daily brain volume fluctuations (p ​< ​0.01).

CONCLUSION

Consistent diurnal brain volume fluctuations attributable to physiological shifts were not detectable in this small study. Technical sources of variation dominate measured changes in brain volume in individuals until the volume loss exceeds around 0.6-0.7%. Reliable interpretation of measured brain volume changes as pathological (greater than normal aging) in individuals over 1 year requires changes in excess of about 1.1% (depending on the scanner). Reliable brain atrophy detection in an individual may be feasible if the rate of brain volume loss is large, or if the measurement interval is sufficiently long.

2D linear measures of ventricular enlargement may be relevant markers of brain atrophy and long-term disability progression in multiple sclerosis

OBJECTIVES

Aim of this study was to investigate the reliability and validity of 2D linear measures of ventricular enlargement as indirect markers of brain atrophy and possible predictors of clinical disability.

METHODS

In this retrospective longitudinal analysis of relapsing-remitting MS patients, brain volumes were computed at baseline and after 2 years. Frontal horn width (FHW), intercaudate distance (ICD), third ventricle width (TVW), and 4th ventricle width were obtained. Two-dimensional measures associated with brain volume at correlation analyses were entered in linear and logistic regression models testing the relationship with baseline clinical disability and 10-year confirmed disability progression (CDP), respectively. Possible cutoff values for clinically relevant atrophy were estimated via receiver operating characteristic (ROC) analyses and probed as 10-year CDP predictors using hierarchical logistic regression.

RESULTS

Eighty-seven patients were available (61/26 = F/M; 34.1 ± 8.5 years). Moderate negative correlations emerged between ICD and TVW and normalized brain volume (NBV; p < 0.001) and percentage brain volume change per year (PBVC/y) and FHW, ICD, and TVW annual changes (p ≤ 0.005). Baseline disability was moderately associated with NBV, ICD, and TVW (p < 0.001), while PBVC/y predicted 10-year CDP (p = 0.01). A cutoff percentage ICD change per year (PICDC/y) value of 4.38%, corresponding to - 0.91% PBVC/y, correlated with 10-year CDP (p = 0.04). These estimated cutoff values provided extra value for predicting 10-year CDP (PBVC/y: p = 0.001; PICDC/y: p = 0.03).

CONCLUSIONS

Two-dimensional measures of ventricular enlargement are reproducible and clinically relevant markers of brain atrophy, with ICD and its increase over time showing the best association with clinical disability. Specifically, a cutoff PICDC/y value of 4.38% could serve as a potential surrogate marker of long-term disability progression.

KEY POINTS

• Assessment of ventricular enlargement as a rapidly accessible indirect marker of brain atrophy may prove useful in cases in which brain volume quantification is not practicable. • Two-dimensional linear measures of ventricular enlargement represent reliable, valid, and clinically relevant markers of brain atrophy. • A cutoff annualized percentage brain volume change of - 0.91% and the corresponding annualized percentage increase of 4.38% for intercaudate distance are able to discriminate patients who will develop long-term disability progression.

Precision medicine for multiple sclerosis promotes preventative medicine

Multiple sclerosis (MS) is a chronic, lifelong disease, currently without a cure that is responsible for significant neurological injury in young adults. Precision medicine for MS aims to provide a more exacting and refined approach toward management by providing recommendations based on disease subtype, clinical status, existing radiological data, para-clinical data, and other biological markers. To achieve better outcomes, the three stages of care-diagnosis, treatment, and management-should be optimized. However, as the temporal profile of disease behavior is highly variable in MS, and unlike outcomes from other chronic conditions (i.e., hypertension, diabetes mellitus, etc.), should precision medicine for MS be one that focuses more on disease prevention and lifestyle modifications beyond recommendations for the use of disease-modifying therapies? As scientific advancements continue within the field of neuroimmunology, and until reliable biomarkers that predict disease outcomes are available, success may be better achieved by focusing on modifiable factors to reduce future disability.

Brain volumetric correlates of dysarthria in multiple sclerosis

Although dysarthria is a common pattern in multiple sclerosis (MS), the contribution of specific brain areas to key factors of dysarthria remains unknown. Speech data were acquired from 123 MS patients with Expanded Disability Status Scale (EDSS) ranging from 1 to 6.5 and 60 matched healthy controls. Results of computerized acoustic analyses of subtests on spastic and ataxic aspects of dysarthria were correlated with MRI-based brain volume measurements. Slow articulation rate during reading was associated with bilateral white and grey matter loss whereas reduced maximum speed during oral diadochokinesis was related to greater cerebellar involvement. Articulation rate showed similar correlation to whole brain atrophy (r = 0.46, p < 0.001) as the standard clinical scales such as EDSS (r = -0.45, p < 0.001). Our results support the critical role of the pyramidal tract and cerebellum in the modification of motor speech timing in MS.

Advances in brain imaging in multiple sclerosis

Brain imaging is increasingly used to support clinicians in diagnosing multiple sclerosis (MS) and monitoring its progression. However, the role of magnetic resonance imaging (MRI) in MS goes far beyond its clinical application. Indeed, advanced imaging techniques have helped to detect different components of MS pathogenesis in vivo, which is now considered a heterogeneous process characterized by widespread damage of the central nervous system, rather than multifocal demyelination of white matter. Recently, MRI biomarkers more sensitive to disease activity than clinical disability outcome measures, have been used to monitor response to anti-inflammatory agents in patients with relapsing-remitting MS. Similarly, MRI markers of neurodegeneration exhibit the potential as primary and secondary outcomes in clinical trials for progressive phenotypes. This review will summarize recent advances in brain neuroimaging in MS from the research setting to clinical applications.

Comparing longitudinal brain atrophy measurement techniques in a real-world multiple sclerosis clinical practice cohort: towards clinical integration?

Background:

Whole brain atrophy (WBA) estimates in multiple sclerosis (MS) correlate more robustly with clinical disability than traditional, lesion-based metrics. We compare Structural Image Evaluation using Normalisation of Atrophy (SIENA) with the icobrain longitudinal pipeline (icobrain long), for assessment of longitudinal WBA in MS patients.

Methods:

Magnetic resonance imaging (MRI) scan pairs [1.05 (±0.15) year separation] from 102 MS patients were acquired on the same 3T scanner. Three-dimensional (3D) T1-weighted and two-dimensional (2D)/3D fluid-attenuated inversion-recovery sequences were analysed. Percentage brain volume change (PBVC) measurements were calculated using SIENA and icobrain long. Statistical correlation, agreement and consistency between methods was evaluated; MRI brain volumetric and clinical data were compared. The proportion of the cohort with annualized brain volume loss (aBVL) rates ⩾ 0.4%, ⩾0.8% and ⩾0.94% were calculated. No evidence of disease activity (NEDA) 3 and NEDA 4 were also determined.

Results:

Mean annualized PBVC was −0.59 (±0.65)% and −0.64 (±0.73)% as measured by icobrain long and SIENA. icobrain long and SIENA-measured annualized PBVC correlated strongly, r = 0.805 (p < 0.001), and the agreement [intraclass correlation coefficient (ICC) 0.800] and consistency (ICC 0.801) were excellent. Weak correlations were found between MRI metrics and Expanded Disability Status Scale scores. Over half the cohort had aBVL ⩾ 0.4%, approximately a third ⩾0.8%, and aBVL was ⩾0.94% in 28.43% and 23.53% using SIENA and icobrain long, respectively. NEDA 3 was achieved in 35.29%, and NEDA 4 in 15.69% and 16.67% of the cohort, using SIENA and icobrain long to derive PBVC, respectively.

Discussion:

icobrain long quantified longitudinal WBA with a strong level of statistical agreement and consistency compared to SIENA in this real-world MS population. Utility of WBA measures in individuals remains challenging, but show promise as biomarkers of neurodegeneration in MS clinical practice. Optimization of MRI analysis algorithms/techniques are needed to allow reliable use in individuals. Increased levels of automation will enable more rapid clinical translation.

MRI Markers and Functional Performance in Patients With CIS and MS: A Cross-Sectional Study

Introduction: Brain atrophy is a widely accepted marker of disease severity with association to clinical disability in multiple sclerosis (MS). It is unclear to which extent this association reflects common age effects on both atrophy and function. Objective: To explore how functional performance in gait, upper extremities and cognition is associated with brain atrophy in patients with Clinically Isolated Syndrome (CIS) and relapsing-remitting MS (RRMS), controlling for effects of age and sex. Methods: In 27 patients with CIS, 59 with RRMS (EDSS ≤3) and 63 healthy controls (HC), 3T MRI were analyzed for T2 lesion count (T2C), volume (T2V) and brain volumes [normalized brain volume (NBV), gray matter volume (NGMV), white matter volume (NWMV), thalamic volume (NThalV)]. Functional performance was measured with short maximum walking speed (SMSW speed), 9-hole peg test (9HPT) and symbol digit modalities test (SDMT). Linear regression models were created for functional variables with stepwise inclusion of age, sex and MR imaging markers. Results: CIS differed from HC only in T2C and T2V. RRMS differed from HC in NBV, NGMV and NThalV, T2C and T2V, but not in NWMV. A strong association with age was seen in HC, CIS and RRMS groups for NBV (r = -0.5 to -0.6) and NGMV (r = -0.6 to -0.8). Associations with age were seen in HC and RRMS but not CIS for NThalV (r = -0.3; r = -0.5), T2C (rs = 0.3; rs = 0.2) and T2V (rs = 0.3; rs = 0.3). No effect of age was seen on NWMV. Correlations of functional performance with age in RRMS were seen for SMSW speed, 9HPTand SDMT (r = -0.27 to -0.46). Regression analyses yielded significant models only in the RRMS group for 9HPT, SMSW speed and EDSS. These included NBV, NGMV, NThalV, NWMV, logT2V, age and sex as predictors. NThalV was the only MRI variable predicting a functional measure (9HPTr) with a higher standardized beta than age and sex (R2 = 0.36, p < 1e-04). Conclusion: Thalamic atrophy was a stronger predictor of hand function (9HPT) in RRMS, than age and sex. This underlines the clinical relevance of thalamic atrophy and the relevance of hand function as a clinical marker even in mildly disabled patients.

The Role of High-Frequency MRI Monitoring in the Detection of Brain Atrophy in Multiple Sclerosis

BACKGROUND AND PURPOSE

A relatively high intraindividual variability of longitudinal magnetic resonance imaging (MRI) of brain volume loss (BVL) measurements over time renders challenging its application to individual multiple sclerosis (MS) patients. Objective of this study was to investigate if high-frequency brain MRI monitoring affects identification of pathological BVL in an individual patient.

METHODS

One hundred fifty-seven relapsing-remitting MS patients had seven MRI scans over 12 months follow-up. All 1,585 MRI scans were performed on the same 1.5T scanner using an identical scanning protocol. Volumetric analysis was performed by ScanView and SIENA software. Linear regression analysis was used for estimation of annualized BVL, with a cutoff greater than .4% defined as pathological. We compared proportions of patients with pathological BVL obtained by analysis of different number of MRI time-points.

RESULTS

An analysis of seven MRI scans (months 0, 2, 4, 6, 8, 10, and 12) showed pathological BVL in 105 (65%) of patients. When three MRI scans were included (months 0, 6, and 12), we found 10 (6.4%) false negative and 9 (5.7%) false positive results compared with the analysis of seven MRI scans, used as a reference for assessment of pathological BVL. Analysis of two MRI time-points (months 0 and 12) showed 10 (6.4%) false negative and 13 (8.3%) false positive results compared with analysis of seven MRI time-points. Change in the accuracy of pathological BVL between results obtained by analysis of seven and two time-points was 14.7%.

CONCLUSIONS

High-frequency MRI monitoring may have a considerable effect on improving the precision of precisely identifying pathological BVL in individual patients. However, limitations in translation to clinical practice remain.

Establishing pathological cut-offs for lateral ventricular volume expansion rates

Background

A percent brain volume change (PBVC) cut-off of −0.4% per year has been proposed to distinguish between pathological and physiological changes in multiple sclerosis (MS). Unfortunately, standardized PBVC measurement is not always feasible on scans acquired outside research studies or academic centers. Percent lateral ventricular volume change (PLVVC) is a strong surrogate measure of PBVC, and may be more feasible for atrophy assessment on real-world scans. However, the PLVVC rate corresponding to the established PBVC cut-off of −0.4% is unknown.

Objective

To establish a pathological PLVVC expansion rate cut-off analogous to −0.4% PBVC.

Methods

We used three complementary approaches. First, the original follow-up-length-weighted receiver operating characteristic (ROC) analysis method establishing whole brain atrophy rates was adapted to a longitudinal ventricular atrophy dataset of 177 relapsing-remitting MS (RRMS) patients and 48 healthy controls. Second, in the same dataset, SIENA PBVCs were used with non-linear regression to directly predict the PLVVC value corresponding to −0.4% PBVC. Third, in an unstandardized, real world dataset of 590 RRMS patients from 33 centers, the cut-off maximizing correspondence to PBVC was found. Finally, correspondences to clinical outcomes were evaluated in both datasets.

Results

ROC analysis suggested a cut-off of 3.09% (AUC = 0.83, p < 0.001). Non-linear regression R² was 0.71 (p < 0.001) and a − 0.4% PBVC corresponded to a PLVVC of 3.51%. A peak in accuracy in the real-world dataset was found at a 3.51% PLVVC cut-off. Accuracy of a 3.5% cut-off in predicting clinical progression was 0.62 (compared to 0.68 for PBVC).

Conclusions

Ventricular expansion of between 3.09% and 3.51% on T2-FLAIR corresponds to the pathological whole brain atrophy rate of 0.4% for RRMS. A conservative cut-off of 3.5% performs comparably to PBVC for clinical outcomes.

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Pathological atrophy in MS can be measured on clinical T2-FLAIR images alone.

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Ventricular enlargement of 3.5% per year separates MS/HC as well as PBVC on T1 images.

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Ventricular cut-offs also correspond to clinical outcome.

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This cut-off can substitute in NEDA-4 when only clinical T2-FLAIR images are available.