Identification of multiple sclerosis patients at highest risk of cognitive impairment using an integrated brain magnetic resonance imaging assessment approach

Brain MRI disease burden and sex differences in cognitive performance of patients with multiple sclerosis

BACKGROUND

Although there is evidence that shows worse cognitive functioning in male patients with multiple sclerosis (MS), the role of brain pathology in this context is under-investigated.

OBJECTIVE

To investigate sex differences in cognitive performance of MS patients, in the context of brain pathology and disease burden.

METHODS

Brain MRI, neurological examination, neuropsychological assessment (Brief International Cognitive Assessment in MS-BICAMS, and Paced Auditory Verbal Learning Test-PASAT), and patient-reported outcome questionnaires were performed/administered in 1052 MS patients.

RESULTS

Females had higher raw scores in the Symbol Digit Modalities Test (SDMT) (57.0 vs. 54.0; p < 0.001) and Categorical Verbal Learning Test (CVLT) (63.0 vs. 57.0; p < 0.001), but paradoxically, females evaluated their cognitive performance by MS Neuropsychological Questionnaire as being worse (16.6 vs 14.5, p = 0.004). Females had a trend for a weaker negative correlation between T2 lesion volume and SDMT ([Formula: see text] = - 0.37 in females vs. - 0.46 in men; interaction p = 0.038). On the other hand, women had a trend for a stronger correlation between Brain Parenchymal Fraction (BPF) and a visual memory test (Spearman's [Formula: see text] = 0.31 vs. 0.21; interaction p = 0.016). All these trends were not significant after correction for false discovery rate.

CONCLUSIONS

Although, females consider their cognition as worse, males had at a group level slightly worse verbal memory and information processing speed. However, the sex differences in cognitive performance were smaller than the variability of scores within the same sex group. Brain MRI measures did not explain the sex differences in cognitive performance among MS patients.

T1 and T2 weighted lesions and cognition in multiple Sclerosis: A systematic review and meta-analysis

BACKGROUND

Considering the different results regarding the correlation between Magnetic Resonance Imaging (MRI) structural measures and cognitive dysfunction in patients with MS, we aimed to perform a systematic review and meta-analysis study to investigate the correlation between T1 and T2 weighted lesions and cognitive scores to find the most robust MRI markers for cognitive function in MS population.

METHODS

The literature of this paper was identified through a comprehensive search of electronic datasets including PubMed, Scopus, Web of Science, and Embase in February 2022. Studies that reported the correlation between cognitive status and T1 and T2 weighted lesions in MS patients were selected.

RESULTS

21 studies with a total of 3771 MS patients with mean ages ranging from 30 to 57 years were entered into our study. Our analysis revealed that the volume of T1 lesions was significantly correlated with Symbol Digit Modality test (SDMT) (r: -0.30, 95 %CI: -0.59, -0.01) and Paced Auditory Serial-Addition Task (PASAT) scores (r: -0.23, 95 %CI: -0.36, -0.10). We investigated the correlation between T2 lesions and cognitive scores. The pooled estimates of z scores were significant for SDMT (r: -0.27, 95 %CI: -0.51, -0.03) and PASAT (r: -0.27, 95 %CI: -0.41, -0.13).

CONCLUSION

In conclusion, our systematic review and meta-analysis study provides strong evidence of the correlation between T1 and T2 lesions and cognitive function in MS patients. Further research is needed to explore the potential mechanisms underlying this relationship and to develop targeted interventions to improve cognitive outcomes in MS patients.

Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that affects millions of people worldwide. The disease course varies greatly across individuals and many disease-modifying treatments with different safety and efficacy profiles have been developed recently. Prognostic models evaluated and shown to be valid in different settings have the potential to support people with MS and their physicians during the decision-making process for treatment or disease/life management, allow stratified and more precise interpretation of interventional trials, and provide insights into disease mechanisms. Many researchers have turned to prognostic models to help predict clinical outcomes in people with MS; however, to our knowledge, no widely accepted prognostic model for MS is being used in clinical practice yet.

OBJECTIVES

To identify and summarise multivariable prognostic models, and their validation studies for quantifying the risk of clinical disease progression, worsening, and activity in adults with MS.

SEARCH METHODS

We searched MEDLINE, Embase, and the Cochrane Database of Systematic Reviews from January 1996 until July 2021. We also screened the reference lists of included studies and relevant reviews, and references citing the included studies.

SELECTION CRITERIA

We included all statistically developed multivariable prognostic models aiming to predict clinical disease progression, worsening, and activity, as measured by disability, relapse, conversion to definite MS, conversion to progressive MS, or a composite of these in adult individuals with MS. We also included any studies evaluating the performance of (i.e. validating) these models. There were no restrictions based on language, data source, timing of prognostication, or timing of outcome.

DATA COLLECTION AND ANALYSIS

Pairs of review authors independently screened titles/abstracts and full texts, extracted data using a piloted form based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), assessed risk of bias using the Prediction Model Risk Of Bias Assessment Tool (PROBAST), and assessed reporting deficiencies based on the checklist items in Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD). The characteristics of the included models and their validations are described narratively. We planned to meta-analyse the discrimination and calibration of models with at least three external validations outside the model development study but no model met this criterion. We summarised between-study heterogeneity narratively but again could not perform the planned meta-regression.

MAIN RESULTS

We included 57 studies, from which we identified 75 model developments, 15 external validations corresponding to only 12 (16%) of the models, and six author-reported validations. Only two models were externally validated multiple times. None of the identified external validations were performed by researchers independent of those that developed the model. The outcome was related to disease progression in 39 (41%), relapses in 8 (8%), conversion to definite MS in 17 (18%), and conversion to progressive MS in 27 (28%) of the 96 models or validations. The disease and treatment-related characteristics of included participants, and definitions of considered predictors and outcome, were highly heterogeneous amongst the studies. Based on the publication year, we observed an increase in the percent of participants on treatment, diversification of the diagnostic criteria used, an increase in consideration of biomarkers or treatment as predictors, and increased use of machine learning methods over time. Usability and reproducibility All identified models contained at least one predictor requiring the skills of a medical specialist for measurement or assessment. Most of the models (44; 59%) contained predictors that require specialist equipment likely to be absent from primary care or standard hospital settings. Over half (52%) of the developed models were not accompanied by model coefficients, tools, or instructions, which hinders their application, independent validation or reproduction. The data used in model developments were made publicly available or reported to be available on request only in a few studies (two and six, respectively). Risk of bias We rated all but one of the model developments or validations as having high overall risk of bias. The main reason for this was the statistical methods used for the development or evaluation of prognostic models; we rated all but two of the included model developments or validations as having high risk of bias in the analysis domain. None of the model developments that were externally validated or these models' external validations had low risk of bias. There were concerns related to applicability of the models to our research question in over one-third (38%) of the models or their validations. Reporting deficiencies Reporting was poor overall and there was no observable increase in the quality of reporting over time. The items that were unclearly reported or not reported at all for most of the included models or validations were related to sample size justification, blinding of outcome assessors, details of the full model or how to obtain predictions from it, amount of missing data, and treatments received by the participants. Reporting of preferred model performance measures of discrimination and calibration was suboptimal.

AUTHORS' CONCLUSIONS

The current evidence is not sufficient for recommending the use of any of the published prognostic prediction models for people with MS in clinical routine today due to lack of independent external validations. The MS prognostic research community should adhere to the current reporting and methodological guidelines and conduct many more state-of-the-art external validation studies for the existing or newly developed models.

The impact of disease modifying therapies on cognitive functions typically impaired in multiple sclerosis patients: a clinician's review

Objective

Over the last few decades clinicians have become aware that cognitive impairment might be a major cause of disability, loss of employment and poor quality of life in patients suffering from multiple sclerosis [MS].The impact of disease modifying therapies [DMTs] on cognition is still a matter of debate. Theoretically, DMTs could exert a substantial beneficial effect by means of reducing neuroinflammation and brain atrophy, which are established correlates of cognitive dysfunction. The aim of the study was to review the evidence concerning the effect of DMTs on cognitive functions.

Methods

PubMed, Scopus, and the European Committee for Treatment and Research in Multiple Sclerosis [ECTRIMS] Library were searched for articles concerning the pediatric and adult populations of patients with multiple sclerosis, including clinical trials and RWD, where psychometric results were analyzed as secondary or exploratory endpoints.

Results

We reviewed a total of 44 studies that were found by our search strategy, analyzed the psychological tests that were applied, the length of the follow-up, and possible limitations. We pointed out the difficulties associated with assessing of DMTs' effects on cognitive functions, and pitfalls in cognitive tools used for evaluating of MS patients.

Conclusion

There is a need to highlight this aspect of MS therapies, and to collect adequate data to make informed therapeutic decisions, to improve our understanding of MS-related cognitive dysfunction and provide new therapeutic targets.

Lexical and syntactic deficits analyzed via automated natural language processing: the new monitoring tool in multiple sclerosis

Background

Impairment of higher language functions associated with natural spontaneous speech in multiple sclerosis (MS) remains underexplored.

Objectives

We presented a fully automated method for discriminating MS patients from healthy controls based on lexical and syntactic linguistic features.

Methods

We enrolled 120 MS individuals with Expanded Disability Status Scale ranging from 1 to 6.5 and 120 age-, sex-, and education-matched healthy controls. Linguistic analysis was performed with fully automated methods based on automatic speech recognition and natural language processing techniques using eight lexical and syntactic features acquired from the spontaneous discourse. Fully automated annotations were compared with human annotations.

Results

Compared with healthy controls, lexical impairment in MS consisted of an increase in content words (p = 0.037), a decrease in function words (p = 0.007), and overuse of verbs at the expense of noun (p = 0.047), while syntactic impairment manifested as shorter utterance length (p = 0.002), and low number of coordinate clause (p < 0.001). A fully automated language analysis approach enabled discrimination between MS and controls with an area under the curve of 0.70. A significant relationship was detected between shorter utterance length and lower symbol digit modalities test score (r = 0.25, p = 0.008). Strong associations between a majority of automatically and manually computed features were observed (r > 0.88, p < 0.001).

Conclusion

Automated discourse analysis has the potential to provide an easy-to-implement and low-cost language-based biomarker of cognitive decline in MS for future clinical trials.

Instruments measuring change in cognitive function in multiple sclerosis: A systematic review

BACKGROUND

Multiple sclerosis (MS) is a chronic demyelinating/neurodegenerative disease associated with change in cognitive function (CF) over time. This systematic review aims to describe the instruments used to measure change in CF over time in people with MS (PwMS).

METHODS

PubMed, OVID, Web of Science, and Scopus databases were searched in English until May 2021. Articles were included if they had at least 100 participants and at least a 1-year interval between baseline and last follow-up measurement of CF. Results were quantitatively synthesized, presented in tables and risk of bias was assessed with the Newcastle-Ottawa Scale.

RESULTS

Fifty-seven articles met the inclusion criteria (41,623 PwMS and 1105 controls). An intervention (drug/rehabilitation) was assessed in 22 articles. In the studies that used a test battery, Visual and verbal learning and memory were the most frequently measured domains, but when studies that used test battery or a single test are combined, Information processing speed was the most measured. The Symbol Digit Modalities Test (SDMT) was the most frequently used test as a single test and in a test battery combined. Most studied assessed "change in CF" as cognitive decline defined as 1 or more tests measured as ≥ 1.5 SD from the study control or normative mean in a test battery at baseline and follow-up. Meta-analysis of change in SDMT scores with seven articles indicated a nonstatistically significant -0.03 (95% CI -0.14, 0.09) decrease in mean SDMT score per year.

CONCLUSION

This study highlights the slow rate of measured change in cognition in PwMS and emphasizes the lack of a gold standard test and consistency in measuring cognitive change at the population level. More sensitive testing utilizing multiple domains and longer follow-up may define subgroups where CF change follows different trajectories thus allowing targeted interventions to directly support those where CF is at greatest risk of becoming a clinically meaningful issue.

Brief international cognitive assessment for MS (BICAMS) and global brain volumes in early stages of MS - A longitudinal correlation study

BACKGROUND

Cognitive impairment is common in patients with multiple sclerosis, even in the early stages of the disease. The Brief International Cognitive Assessment for multiple sclerosis (BICAMS) is a short screening tool developed to assess cognitive function in everyday clinical practice.

OBJECTIVE

To investigate associations between volumetric brain measures derived from a magnetic resonance imaging (MRI) examination and performance on BICAMS subtests in early stages of multiple sclerosis (MS).

METHODS

BICAMS was used to assess cognitive function in 49 MS patients at baseline and after one and two years. The patients were separated into two groups (with or without cognitive impairment) based on their performances on BICAMSs subtests. MRI data were analysed by a software tool (MSMetrix), yielding normalized measures of global brain volumes and lesion volumes. Associations between cognitive tests and brain MRI measures were analysed by running correlation analyses, and differences between subgroups and changes over time with independent and paired samples tests, respectively.

RESULTS

The strongest baseline correlations were found between the BICAMS subtests and normalized whole brain volume (NBV) and grey matter volume (NGV); processing speed r = 0.54/r = 0.48, verbal memory r = 0.49/ r = 0.42, visual memory r = 0.48 /r = 0.39. Only the verbal memory test had significant correlations with T2 and T1 lesion volumes (LV) at both time points; T2LV r = 0.39, T1LV r = 0.38. There were significant loss of grey matter and white matter volume overall (NGV p<0.001, NWV p = 0.003), as well as an increase in T1LV (p = 0.013). The longitudinally defined confirmed cognitively impaired (CCI) and preserved (CCP) patients showed significant group differences on all MRI volume measures at both time points, except for NWV. Only the CCI subgroup showed significant white matter atrophy (p = 0.006) and increase in T2LV (p = 0.029).

CONCLUSIONS

The present study found strong correlations between whole brain and grey matter volumes and performance on the BICAMS subtests as well as significant changes in global volumes from baseline to follow-up with clear differences between patients defined as cognitively impaired and preserved at both baseline and follow-up.

Improved prediction of early cognitive impairment in multiple sclerosis combining blood and imaging biomarkers

Disability in multiple sclerosis is generally classified by sensory and motor symptoms, yet cognitive impairment has been identified as a frequent manifestation already in the early disease stages. Imaging- and more recently blood-based biomarkers have become increasingly important for understanding cognitive decline associated with multiple sclerosis. Thus, we sought to determine the prognostic utility of serum neurofilament light chain levels alone and in combination with MRI markers by examining their ability to predict cognitive impairment in early multiple sclerosis. A comprehensive and detailed assessment of 152 early multiple sclerosis patients (Expanded Disability Status Scale: 1.3 ± 1.2, mean age: 33.0 ± 10.0 years) was performed, which included serum neurofilament light chain measurement, MRI markers (i.e. T₂-hyperintense lesion volume and grey matter volume) acquisition and completion of a set of cognitive tests (Symbol Digits Modalities Test, Paced Auditory Serial Addition Test, Verbal Learning and Memory Test) and mood questionnaires (Hospital Anxiety and Depression scale, Fatigue Scale for Motor and Cognitive Functions). Support vector regression, a branch of unsupervised machine learning, was applied to test serum neurofilament light chain and combination models of biomarkers for the prediction of neuropsychological test performance. The support vector regression results were validated in a replication cohort of 101 early multiple sclerosis patients (Expanded Disability Status Scale: 1.1 ± 1.2, mean age: 34.4 ± 10.6 years). Higher serum neurofilament light chain levels were associated with worse Symbol Digits Modalities Test scores after adjusting for age, sex Expanded Disability Status Scale, disease duration and disease-modifying therapy (B = −0.561; SE = 0.192; P = 0.004; 95% CI = −0.940 to −0.182). Besides this association, serum neurofilament light chain levels were not linked to any other cognitive or mood measures (all P-values > 0.05). The tripartite combination of serum neurofilament light chain levels, lesion volume and grey matter volume showed a cross-validated accuracy of 88.7% (90.8% in the replication cohort) in predicting Symbol Digits Modalities Test performance in the support vector regression approach, and outperformed each single biomarker (accuracy range: 68.6–75.6% and 68.9–77.8% in the replication cohort), as well as the dual biomarker combinations (accuracy range: 71.8–82.3% and 72.6–85.6% in the replication cohort). Taken together, early neuro-axonal loss reflects worse information processing speed, the key deficit underlying cognitive dysfunction in multiple sclerosis. Our findings demonstrate that combining blood and imaging measures improves the accuracy of predicting cognitive impairment, highlighting the clinical utility of cross-modal biomarkers in multiple sclerosis.

Brain age as a surrogate marker for cognitive performance in multiple sclerosis

Background and purpose

Data from neuro‐imaging techniques allow us to estimate a brain's age. Brain age is easily interpretable as ‘how old the brain looks’ and could therefore be an attractive communication tool for brain health in clinical practice. This study aimed to investigate its clinical utility by investigating the relationship between brain age and cognitive performance in multiple sclerosis (MS).

Methods

A linear regression model was trained to predict age from brain magnetic resonance imaging volumetric features and sex in a healthy control dataset (HC_train, n = 1673). This model was used to predict brain age in two test sets: HC_test (n = 50) and MS_test (n = 201). Brain‐predicted age difference (BPAD) was calculated as BPAD = brain age minus chronological age. Cognitive performance was assessed by the Symbol Digit Modalities Test (SDMT).

Results

Brain age was significantly related to SDMT scores in the MS_test dataset (r = −0.46, p < 0.001) and contributed uniquely to variance in SDMT beyond chronological age, reflected by a significant correlation between BPAD and SDMT (r = −0.24, p < 0.001) and a significant weight (−0.25, p = 0.002) in a multivariate regression equation with age.

Conclusions

Brain age is a candidate biomarker for cognitive dysfunction in MS and an easy to grasp metric for brain health.

Interrogating large multiple sclerosis registries and databases: what information can be gained?

PURPOSE OF REVIEW

Although substantial progress has been made in understanding the natural history of multiple sclerosis (MS) and the development of new therapies, many questions concerning disease behavior and therapeutics remain to be answered. Data generated from real-world observational studies, based on large MS registries and databases and analyzed with advanced statistical methods, are offering the scientific community answers to some of these questions that are otherwise difficult or impossible to address. This review focuses on observational studies published in the last 2 years designed to compare the effectiveness of escalation vs. induction treatment strategies, to assess the effectiveness of treatment in pediatric-onset and late-onset MS, and to identify the clinical phenotype of secondary progressive (SP)MS.

RECENT FINDINGS

The main findings originating from real-world studies suggest that MS patients who will qualify for high-efficacy disease-modifying therapies (DMTs) should be offered these as early as possible to prevent irreversible accumulation of neurological disability. Especially pediatric patients derive substantial benefits from early treatment. In patients with late-onset MS, sustained exposure to DMTs may result in more favorable outcomes. Data-driven definitions are more accurate in defining transition to SPMS than diagnosis based solely on neurologists' judgment.

SUMMARY

Patients, physicians, industry, and policy-makers have all benefited from real-world evidence based on registry data, in answering questions of diagnostics, choice of treatment, and timing of treatment decisions.

Relationship between optical coherence tomography angiography and visual evoked potential in patients with multiple sclerosis

Purpose:

This study aimed to identify an easy-to-apply biomarker by correlating visual evoked potential (VEP) with optical coherence tomography angiography (OCTA) results in multiple sclerosis (MS).

Methods:

Our study was planned prospectively. Patients with MS were divided into two groups, VEP prolonged group 1 and VEP normal group 2. Age-matched and gender-matched healthy individuals (group 3) were included as the control group. Vascular density (VD) of the optic nerve head (ONH) and radial peripapillary capillaries (RPCs) were measured and recorded by OCTA. The optic nerve damage of patients was measured and recorded with a VEP device.

Results:

Thirty-two eyes were included in group 1, 50 eyes were included in group 2, and 51 healthy eyes were included in group 3. In terms of visual acuity, group 1 was significantly lower than the other groups (P < 0.001). Regardless of the prolongation of p100 latency in patients with MS, whole image, inside disc ONH VD and in the same sectors in RPC VD were found to be significantly lower than the control group (P < 0.05). Retinal nerve fiber layer thickness was found to be significantly lower in group 1 than in group 2 and group 3 (P < 0.05). There was a significant correlation between low ONH VD and RPC VD and prolonged VEP P100 (P < 0.05).

Conclusion:

VEP measurements can be correlated with OCTA measurements in patients with MS and can be used as a biomarker to determine the degree of optic nerve damage.

Information processing speed as a prognostic marker of physical impairment and progression in patients with multiple sclerosis

BACKGROUND

Prediction of disability progression in patients with MS (pwMS) is challenging. So far, scarce evidence exists suggesting knowledge about how cognitive performance may potentially improve prediction of physical impairment and disability progression in MS. Therefore, we wanted to assess the prognostic value of cognitive performance regarding physical impairment and disability progression in pwMS.

METHODS

85 patients (64% female; 60% relapse-remitting MS; mean age=36.78 ± 9.63 years) underwent clinical, neuropsychological (Brief Repeatable Battery for Neuropsychological Test (BRB-N)) and brain MRI (T1-weighted and T2-weighted FLAIR images) assessment at baseline and after an average of 7 years (SD=3.75) at follow-up. We assessed physical impairment and annualized disability progression (disability progression divided by follow-up duration) using the Expanded Disability Status Scale (EDSS). To compare patients with no or mild physical impairment (EDSS≤2.5) and patients with moderate to severe physical impairment (EDSS≥3.0), we used an EDSS score ≥3.0 as cut-off. Silent progression was defined by an EDSS worsening of at least 0.5 in the absence of relapses and inflammation in relapsing-remitting MS.

RESULTS

In hierarchical regression models (method "STEPWISE", forward) performance in information processing speed was a significant and independent predictor of physical impairment (EDSS≥3.0) at follow-up (model R²=0.671, b=-1.46, OR=0.23, p=0.001) and annualized disability progression (adjusted model R²=0.257, β=-0.26, 95% CI: -0.066, -0.008, p=0.012), in addition to demographics (age, education, individual follow-up time), clinical (EDSS, disease duration, clinical phenotype, annualized-relapse-rate) and MRI measures (brain volumes and T2-lesion load). In a MANCOVA controlled for age, disease duration and individual follow-up time, worse baseline performance in information processing speed was found in patients with higher EDSS at follow-up (m=-1.91, SD=1.18, p<0.001) and silent progression (m=-2.19, SD=1.01, p=0.038).

CONCLUSION

Performance in information processing speed might help to identify patients at risk for physical impairment. Therefore, neuropsychological assessment should be integrated in clinical standard care to support disease management in pwMS.

The clinical and paraclinical correlates of employment status in multiple sclerosis

PURPOSE

To identify the clinical and paraclinical markers of employment status in multiple sclerosis (MS).

METHODS

This was a cross-sectional sub-study investigating 1226 MS patients. To minimalized confounding effect, two groups of patients, matched by sex, age, and education, were selected: 307 patients with full time employment and 153 unemployed patients receiving disability pension. We explored associations between employment status and Expanded Disability Status Scale (EDSS), 25 Foot Walk Test (25FWT), Nine Hole Peg Test (9HPT), Brief International Cognitive Assessment for MS (BICAMS), Paced Auditory Serial Addition Test (PASAT), Beck Depression Inventory (BDI), SLOAN charts (SLOAN), and brain volumetric MRI measures.

RESULTS

Both groups differed significantly on all variables of interest (p < 0.001). In the univariate analyses, EDSS, SDMT (Symbol Digit Modalities Test) adjusted for BDI, 25FWT, and 9HPT best explained variability in vocational status. In multivariate analyses, the combination of EDSS, 25FWT, SDMT, BDI, and corpus callosum fraction (CCF) explained the greatest variability. As a next step, after patients were matched by EDSS, differences in SDMT, 25FWT (both p < 0.001), 9HPT, CCF, and T2 lesion volume were still present (all p < 0.005) between both groups. The best multivariate model consisted of SDMT, BDI, and T2 lesion volume.

CONCLUSIONS

EDSS, walking ability, cognitive performance, and MRI volumetric parameters are independently associated with employment status.

Outcome measures assisting treatment optimization in multiple sclerosis

Objective

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

Methods

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

Results

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

Conclusions

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

Isolated Cognitive Decline in Neurologically Stable Patients with Multiple Sclerosis

(1) Background: Cognitive deterioration is an important marker of disease activity in multiple sclerosis (MS). It is vital to detect cognitive decline as soon as possible. Cognitive deterioration can take the form of isolated cognitive decline (ICD) with no other clinical signs of disease progression present. (2) Methods: We investigated 1091 MS patients from the longitudinal GQ (Grant Quantitative) study, assessing their radiological, neurological, and neuropsychological data. Additionally, the confirmatory analysis was conducted. Clinical disease activity was defined as the presence of new relapse or disability worsening. MRI activity was defined as the presence of new or enlarged T2 lesions on brain MRI. (3) Results: Overall, 6.4% of patients experienced cognitive decline and 4.0% experienced ICD without corresponding clinical activity. The vast majority of cognitively worsening patients showed concomitant progression in other neurological and radiologic measures. There were no differences in disease severity between completely stable patients and cognitively worsening patients but with normal cognition at baseline. (4) Conclusions: Only a small proportion of MS patients experience ICD over short-term follow-up. Patients with severe MS are more prone to cognitive decline; however, patients with normal cognitive performance and mild MS might benefit from the early detection of cognitive decline the most.

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.

Cognitive processing speed in multiple sclerosis clinical practice: association with patient-reported outcomes, employment and magnetic resonance imaging metrics

BACKGROUND AND PURPOSE

To analyze the relationship between cognitive processing speed, patient-reported outcome measures (PROMs), employment and magnetic resonance imaging (MRI) metrics in a large multiple sclerosis cohort.

METHODS

Cross-sectional clinical data, PROMs, employment and MRI studies within 90 days of completion of the Processing Speed Test (PST), a technology-enabled adaptation of the Symbol Digit Modalities Test, were collected. MRI was analyzed using semi-automated methods. Correlations of PST score with PROMs and MRI metrics were examined using Spearman's rho. Wilcoxon rank sum testing compared MRI metrics across PST score quartiles and linear regression models identified predictors of PST performance. Effects of employment and depression were also investigated.

RESULTS

In 721 patients (mean age 47.6 ± 11.4 years), PST scores were significantly correlated with all MRI metrics, including cord atrophy and deep gray matter volumes. Linear regression demonstrated self-reported physical disability, cognitive function, fatigue and social domains (adjusted R²  = 0.44, P < 0.001) as the strongest clinical predictors of PST score, whereas that of MRI variables included T2 lesion volume, whole-brain fraction and cord atrophy (adjusted R²  = 0.42, P < 0.001). An inclusive model identified T2 lesion volume, whole-brain fraction, self-reported upper extremity function, cognition and social participation as the strongest predictors of PST score (adjusted R²  = 0.51, P < 0.001). There was significant effect modification by depression on the relationship between self-reported cognition and PST performance. Employment status was associated with PST scores independent of age and physical disability.

CONCLUSION

The PST score correlates with PROMs, MRI measures of focal and diffuse brain injury, and employment. The PST score is a feasible and meaningful measure for routine multiple sclerosis care.

Morphological MRI phenotypes of multiple sclerosis differ in resting-state brain function

We aimed to assess differences in resting-state functional connectivity (FC) between distinct morphological MRI-phenotypes in multiple sclerosis (MS). Out of 180 MS patients, we identified those with high T2-hyperintense lesion load (T2-LL) and high normalized brain volume (NBV; a predominately white matter damage group, WMD; N = 37) and patients with low T2-LL and low NBV (N = 37; a predominately grey matter damage group; GMD). Independent component analysis of resting-state fMRI was used to test for differences in the sensorimotor network (SMN) between MS MRI-phenotypes and compared to 37 age-matched healthy controls (HC). The two MS groups did not differ regarding EDSS scores, disease duration and distribution of clinical phenotypes. WMD compared to GMD patients showed increased FC in all sub-units of the SMN (sex- and age-corrected). WMD patients had increased FC compared to HC and GMD patients in the central SMN (leg area). Only in the WMD group, higher EDSS scores and T2-LL correlated with decreased connectivity in SMN sub-units. MS patients with distinct morphological MRI-phenotypes also differ in brain function. The amount of focal white matter pathology but not global brain atrophy affects connectivity in the central SMN (leg area) of the SMN, consistent with the notion of a disconnection syndrome.

Additive Effect of Spinal Cord Volume, Diffuse and Focal Cord Pathology on Disability in Multiple Sclerosis

Introduction: Spinal cord (SC) pathology is strongly associated with disability in multiple sclerosis (MS). We aimed to evaluate the association between focal and diffuse SC abnormalities and spinal cord volume and to assess their contribution to physical disability in MS patients. Methods: This large sample-size cross-sectional study investigated 1,249 patients with heterogeneous MS phenotypes. Upper cervical-cord cross-sectional area (MUCCA) was calculated on an axial 3D-T2w-FatSat sequence acquired at 3T using a novel semiautomatic edge-finding tool. SC images were scored for the presence of sharply demarcated hyperintense areas (focal lesions) and homogenously increased signal intensity (diffuse changes). Patients were dichotomized according EDSS in groups with mild (EDSS up to 3.0) and moderate (EDSS ≥ 3.5) physical disability. Analysis of covariance was used to identify factors associated with dichotomized MUCCA. In binary logistic regression, the SC imaging parameters were entered in blocks to assess their individual contribution to risk of moderate disability. In order to assess the risk of combined SC damage in terms of atrophy and lesional pathology on disability, secondary analysis was carried out where patients were divided into four categories (SC phenotypes) according to median dichotomized MUCCA and presence/absence of focal and/or diffuse changes. Results: MUCCA was strongly associated with total intracranial volume, followed by presence of diffuse SC pathology, and disease duration. Compared to the reference group (normally appearing SC, MUCCA>median), patients with the most severe SC changes (SC affected with focal and/or diffuse lesions, MUCCA Collapse

Key Words

• diffuse abnormalities
• focal lesions
• magnetic resonance imaging
• spinal cord
• spinal cord reserve

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Affiliation(s)

Michaela Andelova Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Tomas Uher Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Jan Krasensky Department of Radiology, Charles University in Prague, 1st Faculty of Medicine and General University Hospital, Prague, Czechia
Lukas Sobisek Endowment Fund IMPULS, Prague, Czechia
Eliska Kusova Department of Radiology, Charles University in Prague, 1st Faculty of Medicine and General University Hospital, Prague, Czechia
Barbora Srpova Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Karolina Vodehnalova Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Lucie Friedova Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Jiri Motyl Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Jana Lizrova Preiningerova Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Eva Kubala Havrdova Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Dana Horakova Department of Neurology, First Faculty of Medicine, Center of Clinical Neuroscience, Charles University and General University Hospital in Prague, Prague, Czechia
Manuela Vaneckova Department of Radiology, Charles University in Prague, 1st Faculty of Medicine and General University Hospital, Prague, Czechia

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Slowed articulation rate is associated with information processing speed decline in multiple sclerosis: A pilot study

BACKGROUND

Impairment of cognition and speech are common in multiple sclerosis (MS) patients, but their relationship is not well understood.

OBJECTIVE

To describe the relationship between articulation rate characteristics and processing speed and to investigate the potential role of objective speech analysis for the detection of cognitive decline in MS.

METHODS

A total of 122 patients with clinically definite MS were included in this cross-sectional pilot study. Patients underwent three speaking tasks (oral diadochokinesis, reading text and monologue) and assessment of processing speed (Symbol Digit Modalities Test [SDMT], Paced Auditory Serial Addition Test-3 s [PASAT-3]). Association between articulation rate and cognition was analyzed using linear regression analysis. We estimated the area under the receiver operating characteristics curves (AUC) to evaluate the predictive accuracy of articulation rate measures for the detection of abnormal processing speed.

RESULTS

We observed an association between articulation rate and cognitive measures (rho = 0.45-0.58; p < 0.001). Faster reading speed by one word per second was associated with an 18.7 point (95% confidence interval [CI] 14.9-22.5) increase of the SDMT score and 14.7 (95% CI 8.9-20.4) point increase of PASAT-3 score (both p < 0.001). AUC values of articulation rate characteristics for the identification of processing speed impairment ranged between 0.67 and 0.79. Using a cutoff of 3.10 in reading speed, we were able to identify impairment in both the SDMT and PASAT-3 with 91% sensitivity and 54% specificity.

CONCLUSION

Slowed articulation rate is strongly associated with processing speed decline. Objective quantitative speech analysis identified patients with abnormal cognitive performance.

Identification of Cortical and Subcortical Correlates of Cognitive Performance in Multiple Sclerosis Using Voxel-Based Morphometry

Objective: Cognitive impairment is an important feature in multiple sclerosis (MS) and has been associated to several Magnetic Resonance Imaging (MRI) markers, but especially brain atrophy. However, the relationship between specific neuropsychological tests examining several cognitive functions and brain volumes has been little explored. Furthermore, because MS frequently damage subcortical regions, it may be an interesting model to examine the role of subcortical areas in cognitive functioning. Our aim was to identify correlations between specific brain regions and performance in neuropsychological tests evaluating different cognitive functions in a large series of patients with MS.

Methods: A total of 375 patients were evaluated with a comprehensive neuropsychological battery and with MRI. Voxel-based morphometry was conducted to analyse the correlation between cognitive performance and gray matter damage, using Statistical Parametric Mapping with the toolboxes VBM8 and Lesion Segmentation Tool.

Results: The following correlations were found: Corsi block-tapping test with right insula; Trail Making Test with caudate nucleus, thalamus, and several cortical regions including the posterior cingulate and inferior frontal gyrus; Symbol Digit Modalities Test with caudate nucleus, thalamus, posterior cingulate, several frontal regions, insula, and cerebellum; Stroop Color and Word Test with caudate nucleus and putamen; Free and Cued Selective Reminding Test and Rey-Osterrieth Complex Figure with thalamus, precuneus, and parahippocampal gyrus; Boston Naming Test with thalamus, caudate nucleus, and hippocampus; semantic verbal fluency with thalamus and phonological verbal fluency with caudate nucleus; and Tower of London test with frontal lobe, caudate nucleus, and posterior cingulate.

Conclusion: Our study provides valuable data on the cortical and subcortical basis of cognitive function in MS. Neuropsychological tests mainly assessing attention and executive function showed a stronger association with caudate volume, while tests primarily evaluating memory were more strongly correlated with the thalamus. Other relevant regions were the posterior cingulate/precuneus, which were associated with attentional tasks, and several frontal regions, which were found to be correlated with planning and higher order executive functioning. Furthermore, our study supports the brain vertical organization of cognitive functioning, with the participation of the cortex, thalamus, basal ganglia, and cerebellum.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

The Rationale for Monitoring Cognitive Function in Multiple Sclerosis: Practical Issues for Clinicians

About half of patients with multiple sclerosis exhibit cognitive impairment which negatively affects their quality of life. The assessment of cognitive function in routine clinical practice is still undervalued, although various tools have been proposed for this reason. In this article, we describe the potential benefits of implementing cognitive assessment tools in routine follow -ups of MS patients. Early detection of changes in cognitive performance may provide evidence of disease activity, could unmask depression or medication side-effects and provide suitable candidates for cognitive rehabilitation. Since apathy and cognitive deficiencies are common presenting symptoms in Progressive Multifocal Leukoencephalopathy, we discuss the utility of frequent monitoring of mental status in multiple sclerosis patients at increased risk. In addition, we propose a relevant algorithm aiming to incorporate a systematic evaluation of cognitive function in every day clinical practice in multiple sclerosis.

Optic radiations are thinner and show signs of iron deposition in patients with long-standing remitting-relapsing multiple sclerosis: an enhanced T2*-weighted angiography imaging study

Objective

This study aimed to investigate iron deposition and thickness and signal changes in optic radiation (OR) by enhanced T₂^*-weighted angiography imaging (ESWAN) in patients with relapsing-remitting multiple sclerosis (RRMS) with unilateral and bilateral lesions or no lesions.

Methods

Fifty-one RRMS patients (42 patients with a disease duration [DD] ≥ 2 years [group Mor], nine patients with a DD < 2 years [group Les]) and 51 healthy controls (group Con) underwent conventional magnetic resonance imaging (MRI) and ESWAN at 3.0 T. The mean phase value (MPV) of the OR was measured on the phase image, and thickness and signal changes of the OR were observed on the magnitude image.

Results

The average MPVs for the OR were 1,981.55 ± 7.75 in group Mor, 1,998.45 ± 2.01 in group Les, and 2,000.48 ± 5.53 in group Con. In group Mor, 28 patients with bilateral OR lesions showed bilateral OR thinning with a heterogeneous signal, and 14 patients with unilateral OR lesions showed ipsilateral OR thinning with a heterogeneous signal. In the remaining nine patients without OR lesions and in group Con, the bilateral OR had a normal appearance. In the patients, a negative correlation was found between DD and OR thickness and a positive correlation was found between MPV and OR thickness.

Conclusions

We confirmed iron deposition in the OR in the RRMS patients, and the OR thickness was lower in the patients than in the controls.

Key Points

• Enhanced T₂^*-weighted magnetic resonance angiography (ESWAN) provides new insights into multiple sclerosis (MS).

• Focal destruction of the optic radiation (OR) is detectable by ESWAN.

• Iron deposition in OR can be measured on ESWAN phase image in MS patients.

• OR thickness was lower in the patients than in the controls.

• Iron deposition and thickness changes of the OR are associated with disease duration.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5461-8) contains supplementary material, which is available to authorized users.

Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year employment status in multiple sclerosis patients

BACKGROUND

Multiple sclerosis (MS) is frequently diagnosed in the most productive years of adulthood and is often associated with worsening employment status. However, reliable predictors of employment status change are lacking.

OBJECTIVE

To identify early clinical and brain magnetic resonance imaging (MRI) markers of employment status worsening in MS patients at 12-year follow-up.

METHODS

A total of 145 patients with early relapsing-remitting MS from the original Avonex-Steroids-Azathioprine (ASA) study were included in this prospective, longitudinal, observational cohort study. Cox models were conducted to identify MRI and clinical predictors (at baseline and during the first 12 months) of worsening employment status (patients either (1) working full-time or part-time with no limitations due to MS and retaining this status during the course of the study, or (2) patients working full-time or part-time with no limitations due to MS and switching to being unemployed or working part-time due to MS).

RESULTS

In univariate analysis, brain parenchymal fraction, T1 and T2 lesion volume were the best MRI predictors of worsening employment status over the 12-year follow-up period. MS duration at baseline (hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.03-1.18; p = 0.040) was the only significant clinical predictor. Having one extra milliliter of T1 lesion volume was associated with a 53% greater risk of worsening employment status (HR = 1.53, 95% CI 1.16-2.02; p = 0.018). A brain parenchymal fraction decrease of 1% increased the risk of worsening employment status by 22% (HR = 0.78, 95% CI 0.65-0.95; p = 0.034).

CONCLUSION

Brain atrophy and lesion load were significant predictors of worsening employment status in MS patients. Using a combination of clinical and MRI markers may improve the early prediction of an employment status change over long-term follow-up.

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.

Cognitive clinico-radiological paradox in early stages of multiple sclerosis

Objective

To investigate whether the strength of the association between magnetic resonance imaging (MRI) metrics and cognitive outcomes differs between various multiple sclerosis subpopulations.

Methods

A total of 1052 patients were included in this large cross‐sectional study. Brain MRI (T1 and T2 lesion volume and brain parenchymal fraction) and neuropsychological assessment (Brief International Cognitive Assessment for Multiple Sclerosis and Paced Auditory Serial Addition Test) were performed.

Results

Weak correlations between cognitive domains and MRI measures were observed in younger patients (age≤30 years; absolute Spearman's rho = 0.05–0.21), with short disease duration (<2 years; rho = 0.01–0.21), low Expanded Disability Status Scale [EDSS] (≤1.5; rho = 0.08–0.18), low T2 lesion volume (lowest quartile; <0.59 mL; rho = 0.01–0.20), and high brain parenchymal fraction (highest quartile; >86.66; rho = 0.01–0.16). Stronger correlations between cognitive domains and MRI measures were observed in older patients (age>50 years; rho = 0.24–0.50), with longer disease duration (>15 years; rho = 0.26–0.53), higher EDSS (≥5.0; rho = 0.23–0.39), greater T2 lesion volume (highest quartile; >5.33 mL; rho = 0.16–0.32), and lower brain parenchymal fraction (lowest quartile; <83.71; rho = 0.13–0.46). The majority of these observed results were confirmed by significant interactions (P ≤ 0.01) using continuous variables.

Interpretation

The association between structural brain damage and functional cognitive impairment is substantially weaker in multiple sclerosis patients with a low disease burden. Therefore, disease stage should be taken into consideration when interpreting associations between structural and cognitive measures in clinical trials, research studies, and clinical practice.

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

BACKGROUND

Volumetric MRI surrogate markers of disease progression are lacking.

OBJECTIVE

To establish cut-off values of brain volume loss able to discriminate between healthy controls and MS patients.

METHODS

In total, 386 patients after first demyelinating event suggestive of MS (CIS), 964 relapsing-remitting MS (RRMS) patients, 63 secondary-progressive MS (SPMS) patients and 58 healthy controls were included in this longitudinal study. A total of 11,438 MRI scans performed on the same MRI scanner with the same protocol were analysed. Annualised percentage changes of whole brain, grey matter, thalamus and corpus callosum volumes were estimated. We investigated cut-offs able to discriminate between healthy controls and MS patients.

RESULTS

At a predefined specificity of 90%, the annualised percentage change cut-off of corpus callosum volume (-0.57%) was able to distinguish between healthy controls and patients with the highest sensitivity (51% in CIS, 48% in RRMS and 42% in SPMS patients). Lower sensitivities (22%-49%) were found for cut-offs of whole brain, grey matter and thalamic volume loss. Among CIS and RRMS patients, cut-offs were associated with greater accumulation of disability.

CONCLUSION

We identified cut-offs of annualised global and regional brain volume loss rates able to discriminate between healthy controls and MS patients.

Gray matter atrophy patterns in multiple sclerosis: A 10-year source-based morphometry study

Objectives

To investigate spatial patterns of gray matter (GM) atrophy and their association with disability progression in patients with early relapsing-remitting multiple sclerosis (MS) in a longitudinal setting.

Methods

Brain MRI and clinical neurological assessments were obtained in 152 MS patients at baseline and after 10 years of follow-up. Patients were classified into those with confirmed disability progression (CDP) (n = 85) and those without CDP (n = 67) at the end of the study. An optimized, longitudinal source-based morphometry (SBM) pipeline, which utilizes independent component analysis, was used to identify eight spatial patterns of common GM volume co-variation in a data-driven manner. GM volume at baseline and rates of change were compared between patients with CDP and those without CDP.

Results

The identified patterns generally included structurally or functionally related GM regions. No significant differences were detected at baseline GM volume between the sub-groups. Over the follow-up, patients with CDP experienced a significantly greater rate of GM atrophy within two of the eight patterns, after correction for multiple comparisons (corrected p-values of 0.001 and 0.007). The patterns of GM atrophy associated with the development of CDP included areas involved in motor functioning and cognitive domains such as learning and memory.

Conclusion

SBM analysis offers a novel way to study the temporal evolution of regional GM atrophy. Over 10 years of follow-up, disability progression in MS is related to GM atrophy in areas associated with motor and cognitive functioning.

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We present a longitudinal source-based morphometry (SBM) pipeline for detecting gray matter atrophy in multiple sclerosis.

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We report a significantly greater rate of atrophy in patients developing disability progression over 10 years of follow-up.

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We show that longitudinal SBM is potentially more sensitive than voxel-based morphometry in detecting gray matter atrophy.