Background

In early multiple sclerosis, a clearer understanding of normal-brain tissue microstructural and metabolic abnormalities will provide valuable insights into its pathophysiology. Here, we studied the brain of patients with their first demyelinating episode using neurite orientation dispersion and density imaging (NODDI), for information about neuro-axonal density and spatial distribution, and ²³Na MRI, for total sodium concentration reflecting neuro-axonal metabolic dysfunction and loss.

Objectives

To detect, using a multi-parametric quantitative MRI approach, clinically relevant alterations in the brain of early patients not captured by conventional MRI.

Methods

We enrolled 42 patients with clinically isolated syndrome or multiple sclerosis within 3 months from the onset and 16 healthy controls. We assessed physical and cognitive scales. On a 3T scanner, we acquired brain and spinal cord structural scans, and brain NODDI. Thirty-two patients and 13 healthy controls also underwent brain ²³Na MRI. In the brain normal-appearing white matter, white matter lesions, and grey matter, we measured, from NODDI, the neurite density index (NDI), a marker of neuro-axonal density, and the orientation dispersion index (ODI), reflecting the fanning and crossing of neurites, and, from ²³Na MRI, the TSC. We used linear regression models, adjusted for brain parenchymal fraction and lesion load, and Spearman correlation tests. For robust regression estimates, we used a p≤0.01.

Results

Patients showed higher ODI in normal-appearing white matter, including the corpus callosum, where they also showed lower NDI and higher TSC, compared with controls. In grey matter, compared with controls, patients had lower ODI in frontal, parietal and temporal cortex; lower NDI in parietal, temporal and occipital cortex; and higher TSC in limbic and frontal cortex. Brain volumes did not differ between patients and controls. In patients, higher ODI in corpus callosum was associated with worse performance on timed walk test (p=0.009, B=0.01, 99% Confidence Interval=0.0001-0.02), independent of brain and lesion volumes. Higher TSC in left frontal middle gyrus was associated with higher disability on Expanded Disability Status Scale (r_s=0.5, p=0.005).

Conclusions

We found increased axonal dispersion in normal-appearing white matter, particularly corpus callosum, where we found also reduced axonal density and total sodium accumulation suggesting that this structure can be early affected by neurodegeneration. The association between increased axonal dispersion in the corpus callosum and worse walking performance implies that morphological and metabolic alterations in this structure may contribute to disability in multiple sclerosis. Brain volumes were neither altered nor related to disability in patients, so these two advanced MRI techniques can be more sensitive at detecting clinically relevant pathology in very early multiple sclerosis.

Background

In multiple sclerosis (MS), MRI measures at a whole and regional brain level have proven able to predict future disability, albeit to a limited degree. Their modest prognostic ability may reflect how cognitive and neurological functions are served by distributed networks rather than by single brain regions.

Objectives

We aimed to identify data-driven MRI network-based measures of covarying gray matter (GM) volumes that can predict disability progression.

Methods

We used baseline MRI and longitudinal clinical data from 988 patients with secondary progressive MS (SPMS) from a randomized, double-blind, placebo-controlled, multicenter trial (ASCEND). We applied spatial-ICA to baseline structural GM probability maps to identify co-varying GM regions. We computed correlations between the loading of our ICA components and expanded disability status scale (EDSS), 9 hole peg test (9HPT), and symbol digit modalities test (SDMT) scores. We estimated the progression of the EDSS confirmed at 3 months, 6 months, and 1 year, and respectively the 20% and 10% worsening of 9HPT and SDMT. We used Cox proportional hazard models to determine the prognostic value of our ICA-components and conventional MRI measures (whole and deep GM volumes, and white matter lesion load).

Results

We identified 15 networks of co-varying GM patterns that were clinically relevant. At baseline, SDMT and 9HPT scores correlated more strongly with ICA-components than the conventional MRI measures. The highest correlations were with a mainly basal ganglia component (encompassing the thalamus, caudate, putamen, frontal and temporal lobe). EDSS correlated more closely with an ICA-component involving cerebellum, brainstem, temporal and parietal lobes (r= -0.11, p<0.001). Prognostically, the baseline volume of caudate predicted EDSS progression confirmed at 3 months (HR= 0.81, 95%CI [0.68: 0.98], p<0.05), while some GM network-based measures outperformed conventional MRI measures in predicting SDMT and 9HPT worsening. SDMT progression was predicted by 6 ICA-components (component 8 (HR= 1.26, 95% CI [1.08-1.48], p< 0.005, and component 13 (HR= 1.25, 95% CI [1.07:1.46], p<0.005)). Two ICA-components were predictors of 9HPT worsening (HR=1.30, 95% CI [1.06:1.60], p<0.01; and HR= 1.21, 95%CI [1.01:1.45], p<0.05).

Conclusions

Data-driven MRI network-based measures of covarying GM volumes predict disability progression better than volumetric measures of GM and white matter lesion loads. ICA of MRI shows promise as a method that could enrich clinical MS studies with patients more likely to show a treatment response.

Background

In the constantly evolving field of MS, personalized medicine is still one of the most important unmet need that requires further attention

Objectives

We aimed to develop a dynamic risk calculator to predict the long-term prognosis of MS in the context of a large MS Centre in Catalonia

Methods

This is an observational study based on data prospectively acquired from a deeply phenotyped CIS cohort from Barcelona. We first built a natural history baseline risk score (BRS) for predicting moderate disability, integrating baseline prognostic factors: Sex, age at CIS, CIS topography, number of T2 lesions, contrast-enhancing lesions (CEL) and oligoclonal bands. This BRS was designed as follows: For untreated patients, we built a Weibull model to estimate the median time to confirmed EDSS 3.0 and with these estimates we identified risk groups based on the median of the cut-offs of 2000 survival trees. Then we obtained the BRS of the full cohort. In patients with more than ten years of follow-up, we performed an inverse probability weighting to balance patients during their follow up for the propensity of being treated or lost to follow-up. The weights were estimated via a proportional hazards (PH) Cox model considering both baseline information (CIS year, BRS) and time-dependent (diagnosis status, new T2 lesions, CEL and cumulative number of relapses). Finally, a weighted PH Cox model was built to estimate the time to confirmed EDSS 3.0 considering the BRS and time-dependent events (new T2 lesions, cumulative number of relapses and first or second-line treatment use). Sensitivity analyses using other disability outcomes and different follow-ups were conducted.

Results

Of 956 patients, 577 (60.4%) were untreated before confirmed EDSS 3.0. Two BRS were obtained: low and high-BRS. Of 400 patients followed for more than ten years, 226 (56.5%) were low-BRS and 174 (43.5%) were high-BRS. High-BRS showed a HR=2.16 95%CI (1.16,4.02). Each new T2 lesion presented HR=1.04 95%CI (1.00,1.08) and each new relapse HR=1.46 95%CI (1.23,1.74). Being on second-line treatment showed a protective effect (HR=0.23 95%CI (0.06,0.94)) but no association was found for first-line treatments (HR=1.32 95%CI (0.67,2.60). Sensitivity analyses confirmed the association between BRS, new T2 lesions and the accumulation of relapses with the prognosis. However, treatment results were inconclusive.

Conclusions

Presenting a high-BRS doubles the risk of reaching moderate disability. Each new lesion and new relapse increses the risk by 4% and 46%, respectively; and second-line treatments seem to be protective. If validated, this risk calculator could be a crucial step to personalized medicine.

Background

There is to our knowledge few validated electronic tool in MS that measures the distance walked by a person with MS (PwMS). Utilising global positioning systems (GPS), WI-FI positioning and an in-built smartphone accelerometer to measure distance walked by a PwMS outdoors or indoors, could alleviate the uncertainty around using pedometers in those with gait disturbances, and is an attractive option.

Objectives

To pilot an accurate measure of distance walked using a smartphone application (mSteps) to facilitate Expanded Disability Status Scale (EDSS) measurement, indoors and outdoors, using both an MS and a control cohort.

Methods

The pilot study recruited 25 PwMS and 10 controls. mSteps utilised the iPhone’s inbuilt accelerometer and GPS functionalities to calculate the distance walked and time taken, indoors and outdoors. Due to unpredictable weather the physician monitored walk took place indoors which was fitted with location beacons to allow for WI-FI indoor positioning. The control cohort did the same walk indoors and outdoors to validate the use of the GPS functionality.

The participant was instructed to walk 25 feet, without rest, whilst the study phone was attached to their arm using a runner’s arm band and study personnel walked alongside them with a trundle wheel. Measurements were taken at 3 separate time points within a 3-month period.

95% levels of agreement between app and trundle wheel (gold standard) were calculated using the Bland-Altman repeated measures analysis. Levels of agreement, app vs trundle, were calculated for indoor measurements on both PwMS and controls with additional app vs trundle outdoor measurements for controls only. The a priori defined clinically acceptable difference was 1.52m.

Results

The 95% levels of agreement for indoor measurements on PwMS were -2.46 to 2.27m; and for controls were -2.02 to 2.71m. The 95% levels of agreement for outdoor measurements on controls were -0.45 to 0.43m.

Conclusions

The outdoor GPS functionality of mSteps is very accurate as shown by the 95% levels of agreements compared to the a priori clinically determined difference. The indoor WI-FI positioning function of mSteps however, was not accurate enough and shows that it is not reliable enough for further use. The control cohort showed the same inaccuracy indoors which eliminates the possibility that an uneven gait pattern in the MS cohort contributed to the error margin. A further validity study is being carried out, looking at a cohort of PwMS walking outdoors using mSteps and a trundle wheel.

Background

Inflammatory demyelination in the anterior optic pathway, including the optic chiasm (OC), occurs frequently in relapsing-remitting multiple sclerosis (RRMS), aquaporin4 (AQP4) antibody (Ab) positive neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein-Ab associated-disease (MOGAD).

Objectives

To evaluate the involvement of the OC in RRMS, AQP4-NMOSD and MOGAD using Magnetization Transfer Ratio (MTR) and explore its relationship with prior optic neuritis (ON).

Methods

We recruited 25 patients with RRMS (16 F, mean age: 44.6 yrs ±11.8, median EDSS: 2.0 [range: 1.0-7.5], mean number of previous episodes of ON: 0.44±0.58, 9 unilateral, 1 bilateral), 13 with AQP4-NMOSD (10 F, mean age: 45.3 yrs ±11.2, median EDSS: 3.0 [1.0-6.5], mean number of ON episodes: 1.54±1.13, 4 unilateral, 6 bilateral), 20 with MOGAD (13 F, mean age: 33.9 yrs ±16.4, median EDSS: 2.0 [0.0-6.5], mean number of ON episodes: 2.85±2.80, 6 unilateral, 11 bilateral) and 29 healthy controls (HC) (23 F, mean age: 35.9 yrs ±12.8). We used T2-weighted, MTon and MToff images to obtain MTR maps of the OC. Age-, sex-, and disease duration-adjusted linear regression models were used to compare the measures between disease and healthy groups (p<0.05).

Results

Chiasmal MTR values in patients with previous ON were lower in AQP4-NMOSD (p=0.040) and MOGAD (p=0.001) than HC but not when compared to patients without previous ON. In patients with RRMS and previous ON, MTR values were lower than patients without prior ON (p=0.003). No differences were found either between patients without ON and HC or between the disease groups.

When considering all patients with demyelinating diseases, patients with previous ON had lower chiasmal MTR values when compared to HC (unilateral: p=0.037; bilateral: p=0.002) and to patients without ON (unilateral: p=0.019; bilateral: p<0.001). This difference persisted when comparing both monophasic and relapsing ON patients to HC (p=0.044; p<0.001) and to patients without ON (p=0.019; p<0.001). No differences were found between patients without history of ON and HC. A correlation was found between MTR values and number of ON episodes (rho=-0.55, p<0.001).

Conclusions

Microstructural damage in the OC correlated with the number of ON episodes across inflammatory demyelinating diseases. A higher number of episodes is associated with lower chiasmal MTR, supporting its role as an accessible target for the assessment of the visual pathway in inflammatory diseases.

Background

Cognitive dysfunction is common in multiple sclerosis (MS) and is particularly prevalent in patients with progressive forms of the disease [1]. Exploring neurofilament associations has clear value in trying to develop treatments for cognition.

Objectives

To perform a post-hoc analysis of the MS-STAT trial [2], assessing serum neurofilament light (sNFL) and heavy (sNFH) as predictive biomarkers of future cognitive performance.

Methods

Serum samples were analysed for sNFL and sNFH using Single Molecule Array (Simoa). Cognition was assessed at months 0, 12 and 24 with a detailed neuropsychometric battery including the Wechsler Abbreviated Scale of Intelligence (WASI) and Brain Injury Rehabilitation Trust Memory and Information Processing Battery (BMIPB), as previously described [3]. Multivariate regression models were used for cross-sectional analysis, and linear mixed models were used to assess the predictive value of dichotomised baseline sNFL and sNFH on changes in cognition. All analyses controlled for the established MRI variables of whole brain volume (WBV) and T2 lesion volume (T2LV) in order to assess the extent to which sNFL and sNFH provided additional prognostic value.

Results

Cross-sectional analyses:

After adjusting for demographics, T2LV and WBV, neither sNFL nor sNFH demonstrated cross-sectional associations with current cognitive performance.

Longitudinal analyses:

Patients with high baseline sNFL experienced significantly greater cognitive decline from 0 to 24 months in WASI full-scale IQ (95% CI of coefficient -0.238 to -0.024), WASI Verbal IQ (-0.281 to -0.011), and in both immediate and delayed BMIPB figure recall (-0.489 to -0.046 and -0.399 to -0.025, respectively). sNFH was not associated with changes in cognitive performance.

Conclusions

Our results demonstrate the prognostic value of sNFL on future changes in cognitive performance in SPMS, assessed through a detailed neuropsychometric battery. sNFL remained significantly associated with future cognitive decline whilst controlling for established MRI biomarkers, suggesting that it may provide additional utility in identifying those who may benefit most from interventions aimed at preventing cognitive decline.

1. Sumowski JF et al (2018) Cognition in multiple sclerosis: State of the field and priorities for the future. Neurology

2. Chataway J et al (2014) Effect of high-dose simvastatin on brain atrophy and disability in secondary progressive multiple sclerosis (MS-STAT): a randomised, placebo-controlled, phase 2 trial. Lancet

3. Chan D et al (2017) Effect of high-dose simvastatin on cognitive, neuropsychiatric, and health-related quality-of-life measures in secondary progressive multiple sclerosis: secondary analyses from the MS-STAT randomised, placebo-controlled trial. Lancet Neurol