Prognostic value of spinal cord lesion measures in early relapsing-remitting multiple sclerosis

BACKGROUND

Spinal cord (SC) lesions have been associated with unfavourable clinical outcomes in multiple sclerosis (MS). However, the relation of whole SC lesion number (SCLN) and volume (SCLV) to the future occurrence and type of confirmed disability accumulation (CDA) remains largely unexplored.

METHODS

In this monocentric retrospective study, SC lesions were manually delineated. Inclusion criteria were: age between 18 and 60 years, relapsing-remitting MS, disease duration under 2 years and clinical follow-up of 5 years. The first CDA event after baseline, determined by a sustained increase in the Expanded Disability Status Scale over 6 months, was classified as either progression independent of relapse activity (PIRA) or relapse-associated worsening (RAW). SCLN and SCLV were compared between different (sub)groups to assess their prospective value.

RESULTS

204 patients were included, 148 of which had at least one SC lesion and 59 experienced CDA. Patients without any SC lesions experienced significantly less CDA (OR 5.8, 95% CI 2.1 to 19.8). SCLN and SCLV were closely correlated (rs=0.91, p<0.001) and were both significantly associated with CDA on follow-up (p<0.001). Subgroup analyses confirmed this association for patients with PIRA on CDA (34 events, p<0.001 for both SC lesion measures) but not for RAW (25 events, p=0.077 and p=0.22).

CONCLUSION

Patients without any SC lesions are notably less likely to experience CDA. Both the number and volume of SC lesions on MRI are associated with future accumulation of disability largely independent of relapses.

Early spinal cord pseudoatrophy in interferon-beta-treated multiple sclerosis

BACKGROUND AND PURPOSE

Brain pseudoatrophy has been shown to play a pivotal role in the interpretation of brain atrophy measures during the first year of disease-modifying therapy in multiple sclerosis. Whether pseudoatrophy also affects the spinal cord remains unclear. The aim of this study was to analyze the extent of pseudoatrophy in the upper spinal cord during the first 2 years after therapy initiation and compare this to the brain.

METHODS

A total of 129 patients from a prospective longitudinal multicentric national cohort study for whom magnetic resonance imaging scans at baseline, 12 months, and 24 months were available were selected for brain and spinal cord volume quantification. Annual percentage brain volume and cord area change were calculated using SIENA (Structural Image Evaluation of Normalized Atrophy) and NeuroQLab, respectively. Linear mixed model analyses were performed to compare patients on interferon-beta therapy (n = 84) and untreated patients (n = 45).

RESULTS

Patients treated with interferon-beta demonstrated accelerated annual percentage brain volume and cervical cord area change in the first year after treatment initiation, whereas atrophy rates stabilized to a similar and not significantly different level compared to untreated patients during the second year.

CONCLUSIONS

These results suggest that pseudoatrophy occurs not only in the brain, but also in the spinal cord during the first year of interferon-beta treatment.

Somatosensory evoked potentials and magnetic resonance imaging of the central nervous system in early multiple sclerosis

BACKGROUND

Somatosensory evoked potentials (SSEP) are still broadly used, although not explicitly recommended, for the diagnostic work-up of suspected multiple sclerosis (MS).

OBJECTIVE

To relate disability, SSEP, and lesions on T2-weighted magnetic resonance imaging (MRI) in patients with early MS.

METHODS

In this monocentric retrospective study, we analyzed a cohort of patients with relapsing-remitting MS or clinically isolated syndrome, with a maximum disease duration of two years, as well as with available data on the score at the expanded disability status scale (EDSS), on SSEP, on whole spinal cord (SC) MRI, and on brain MRI.

RESULTS

Complete data of 161 patients were available. Tibial nerve SSEP (tSSEP) were less frequently abnormal than SC MRI (22% vs. 68%, p < 0.001). However, higher EDSS scores were significantly associated with abnormal tSSEP (median, 2.0 vs. 1.0; p = 0.001) but not with abnormal SC MRI (i.e., at least one lesion; median, 1.5 vs. 1.5; p = 0.7). Of the 35 patients with abnormal tSSEP, 32 had lesions on SC MRI, and 2 had corresponding lesions on brain MRI.

CONCLUSION

Compared to tSSEP, SC MRI is the more sensitive diagnostic biomarker regarding SC involvement. In early MS, lesions as detectable by T2-weighted MRI are the main driver of abnormal tSSEP. However, tSSEP were more closely associated with disability, which is compatible with a potential role of tSSEP as prognostic biomarker in complementation of MRI.

Lesion location across diagnostic regions in multiple sclerosis

BACKGROUND

Lesions in the periventricular, (juxta)cortical, and infratentorial region, as visible on brain MRI, are part of the diagnostic criteria for Multiple sclerosis (MS) whereas lesions in the subcortical region are currently only a marker of disease activity. It is unknown whether MS lesions follow individual spatial patterns or whether they occur in a random manner across diagnostic regions.

AIM

First, to describe cross-sectionally the spatial lesion patterns in patients with MS. Second, to investigate the spatial association of new lesions and lesions at baseline across diagnostic regions.

METHODS

Experienced neuroradiologists analyzed brain MRI (3D, 3T) in a cohort of 330 early MS patients. Lesions at baseline and new solitary lesions after two years were segmented (manually and by consensus) and classified as periventricular, (juxta)cortical, or infratentorial (diagnostic regions) or subcortical-with or without Gadolinium-enhancement. Gadolinium enhancement of lesions in the different regions was compared by Chi square test. New lesions in the four regions served as dependent variable in four zero-inflated Poisson models each with the six independent variables of lesions in the four regions at baseline, age and gender.

RESULTS

At baseline, lesions were most often observed in the subcortical region (mean 13.0 lesions/patient), while lesion volume was highest in the periventricular region (mean 2287 µl/patient). Subcortical lesions were less likely to show gadolinium enhancement (3.1 %) than juxtacortical (4.3 %), periventricular (5.3 %) or infratentorial lesions (7.2 %). Age was inversely correlated with new periventricular, juxtacortical and subcortical lesions. New lesions in the periventricular, juxtacortical and infratentorial region showed a significant autocorrelative behavior being positively related to the number of lesions in the respective regions at baseline. New lesions in the subcortical region showed a different behavior with a positive association with baseline periventricular lesions and a negative association with baseline infratentorial lesions.

CONCLUSION

Across regions, new lesions do not occur randomly; instead, new lesions in the periventricular, juxtacortical and infratentorial diagnostic region are associated with that at baseline. Lesions in the subcortical regions are more closely related to periventricular lesions. Moreover, subcortical lesions substantially contribute to lesion burden in MS but are less likely to show gadolinium enhancement (than lesions in the diagnostic regions).

Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains

The myelin concentration and the degree of myelination of nerve fibers can provide valuable information on the integrity of human brain tissue. Magnetic resonance imaging (MRI) of myelin-sensitive parameters can help to non-invasively evaluate demyelinating diseases such as multiple sclerosis (MS). Several different myelin-sensitive MRI methods have been proposed to determine measures of the degree of myelination, in particular the g-ratio. However, variability in underlying physical principles and different biological models influence measured myelin concentrations, and consequently g-ratio values. We therefore investigated similarities and differences between five different myelin-sensitive MRI measures and their effects on g-ratio mapping in the brains of both MS patients and healthy volunteers. We compared two different estimates of the myelin water fraction (MWF) as well as the inhomogeneous magnetization transfer ratio (ihMTR), magnetization transfer saturation (MTsat), and macromolecular tissue volume (MTV) in 13 patients with MS and 14 healthy controls. In combination with diffusion-weighted imaging, we derived g-ratio parameter maps for each of the five different myelin measures. The g-ratio values calculated from different myelin measures varied strongly, especially in MS lesions. While, compared to normal-appearing white matter, MTsat and one estimate of the MWF resulted in higher g-ratio values within lesions, ihMTR, MTV, and the second MWF estimate resulted in lower lesion g-ratio values. As myelin-sensitive measures provide rough estimates of myelin content rather than absolute myelin concentrations, resulting g-ratio values strongly depend on the utilized myelin measure and model used for g-ratio mapping. When comparing g-ratio values, it is, thus, important to utilize the same MRI methods and models or to consider methodological differences. Particular caution is necessary in pathological tissue such as MS lesions.

Percentage brain volume change in multiple sclerosis mainly reflects white matter and cortical volume

Brain atrophy in multiple sclerosis (MS), as measured by percentage brain volume change (PBVC) from brain magnetic resonance imaging (MRI), has been established as an outcome parameter in clinical trials. It is unknown to what extent volume changes within different brain tissue compartments contribute to PBVC. We analyzed pairs of MRI scans (at least 6 months apart) in 600 patients with relapsing-remitting MS. Multiple regression revealed that PBVC mainly reflects volume loss of white and cortical gray matter, while deep gray matter and white matter lesions were less represented. Our findings aid the interpretation of PBVC changes in MS.

Multiple sclerosis lesions and atrophy in the spinal cord: Distribution across vertebral levels and correlation with disability

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In multiple sclerosis, spinal cord lesions and atrophy are measurable by whole spinal cord MRI with axial and sagittal coverage in a large patient cohort and in healthy control subjects.

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Spinal cord lesions and atrophy are accentuated in the cervical enlargement.

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They have already developed at the stage of RRMS and continue developing in a clinically meaningful way at later stages.

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Yet they remain largely independent.

Background

The vast majority of magnetic resonance imaging (MRI) studies on multiple sclerosis (MS) covered the spinal cord (SC), if at all, incompletely.

Objective

To assess SC involvement in MS, as detectable by whole SC MRI, with regard to distribution across vertebral levels and relation to clinical phenotypes and disability.

Methods

We investigated SC MRI with sagittal and axial coverage. Analyzed were brain and SC MRI scans of 17 healthy controls (HC) and of 370 patients with either clinically isolated syndrome (CIS, 27), relapsing remitting MS (RRMS, 303) or progressive MS (PMS, 40). Across vertebral levels, cross-sectional areas were semiautomatically segmented, and lesions manually delineated.

Results

The frequency of SC lesions was highest at the level C3-4. The volume of SC lesions increased from CIS to RRMS, and from RRMS to PMS whereas lesion distribution across SC levels did not differ. SC atrophy was demonstrated in RRMS and, to a higher degree, in PMS; apart from an accentuation at the level C3-4, it was evenly distributed across SC levels. SC lesions and atrophy volume were not correlated with each other and were independently associated with disability.

Conclusion

SC lesions and atrophy already exist at the stage of RRMS in the whole SC with an accentuation in the cervical enlargement; SC lesions and atrophy are more pronounced in the stage of PMS. Both contribute to the clinical picture but are largely independent.

Gray matter atrophy in relapsing-remitting multiple sclerosis is associated with white matter lesions in connecting fibers

Background:

Lesions of brain white matter (WM) and atrophy of brain gray matter (GM) are well-established surrogate parameters in multiple sclerosis (MS), but it is unclear how closely these parameters relate to each other.

Objective:

To assess across the whole cerebrum whether GM atrophy can be explained by lesions in connecting WM tracts.

Methods:

GM images of 600 patients with relapsing-remitting MS (women = 68%; median age = 33.0 years, median expanded disability status scale score = 1.5) were converted to atrophy maps by data from a healthy control cohort. An atlas of WM tracts from the Human Connectome Project and individual lesion maps were merged to identify potentially disconnected GM regions, leading to individual disconnectome maps. Across the whole cerebrum, GM atrophy and potentially disconnected GM were tested for association both cross-sectionally and longitudinally.

Results:

We found highly significant correlations between disconnection and atrophy across most of the cerebrum. Longitudinal analysis demonstrated a close temporal relation of WM lesion formation and GM atrophy in connecting fibers.

Conclusion:

GM atrophy is associated with WM lesions in connecting fibers. Caution is warranted when interpreting group differences in GM atrophy exclusively as differences in early neurodegeneration independent of WM lesion formation.

Cognitive impairment in early MS: contribution of white matter lesions, deep grey matter atrophy, and cortical atrophy

Background

Cognitive impairment (CI) is a frequent and debilitating symptom in MS. To better understand the neural bases of CI in MS, this magnetic resonance imaging (MRI) study aimed to identify and quantify related structural brain changes and to investigate their relation to each other.

Methods

We studied 51 patients with CI and 391 patients with cognitive preservation (CP). We analyzed three-dimensional T1-weighted and FLAIR scans at 3 Tesla. We determined mean cortical thickness as well as volumes of cortical grey matter (GM), deep GM including thalamus, cerebellar cortex, white matter, corpus callosum, and white matter lesions (WML). We also analyzed GM across the whole brain by voxel-wise and surface-based techniques.

Results

Mean disease duration was 5 years. Comparing MS patients with CI and CP, we found higher volumes of WML, lower volumes of deep and cortical GM structures, and lower volumes of the corpus callosum (all corrected p values < 0.05). Effect sizes were largest for WML and thalamic volume (standardized ß values 0.25 and − 0.25). By logistic regression analysis including both WML and thalamic volume, we found a significant effect only for WML volume. Inclusion of the interaction term of WML and thalamic volume increased the model fit and revealed a highly significant interaction of WML and thalamic volume. Moreover, voxel-wise and surface-based comparisons of MS patients with CI and CP showed regional atrophy of both deep and cortical GM independent of WML volume and overall disability, but effect sizes were lower.

Conclusion

Although several mechanisms contribute to CI already in the early stage of MS, WML seem to be the main driver with thalamic atrophy primarily intensifying this effect.

T1-Weighted Intensity Increase After a Single Administration of a Linear Gadolinium-Based Contrast Agent in Multiple Sclerosis

Purpose

Through analysis of T1-weighted (T1w) images this study investigated gadolinium (Gd) deposition in the brain after administration of a linear (gadopentetic acid) and a cyclic (gadoteric acid) gadolinium-based contrast agent (GBCA) in patients with multiple sclerosis (MS), a disorder frequently requiring magnetic resonance imaging (MRI) scans over years.

Methods

A total of 3233 T1w images (unenhanced with respect to the same scanning session) of 881 MS patients were retrospectively analyzed. After spatial normalization and intensity scaling using a sphere within the pons, differences of all pairs of subsequent scans were calculated and attributed to either linear (n = 2718) or cyclic (n = 385) or no GBCA (n = 130) according to the first scan. Regional analyses were performed, focusing on the dentate nucleus, and whole brain analyses. By 1‑sample t‑tests, signal intensity increases within conditions were searched for; conditions were compared by 2‑sample t‑tests. Furthermore, recent hypotheses on the reversibility of GBCA deposition were tested.

Results

In the dentate nucleus, a significant increase was observed only after administration of linear GBCA even after a single GBCA administration. This increase differed significantly (p < 0.001) from the other conditions (cyclic and no GBCA). Whole brain analyses revealed T1w signal increases only after administration of linear GBCA within two regions, the dentate nucleus and globus pallidus. Additional analyses did not indicate any decline of Gd deposition in the brain.

Conclusion

The data point towards Gd deposition in the brain after administration of linear GBCA even after a single administration.

Prognostic value of white matter lesion shrinking in early multiple sclerosis: An intuitive or naïve notion?

BACKGROUND AND PURPOSE

New or enlarging T2-hyperintense white matter lesions (WML) are associated with clinical disease progression in multiple sclerosis (MS). The prognostic value of WML shrinking is unclear. Assuming that waning of acute inflammation and repair processes would be the main drivers of WML shrinking, we aimed to assess the prognostic value of WML shrinking in early MS.

METHODS

We retrospectively analyzed a cohort of 144 early MS patients with three brain MRI scans at baseline and after 1 and 3 years available. All patients were therapy naïve at baseline and 70.5% of them treated with disease modifying drugs at year 1. We determined the volume of WML shrinking between MRI scans, total WML volumes, number of gadolinium-enhancing and new WML, white matter (WM) and gray matter volumes at each MRI scan. Clinical disability was measured by Expanded Disability Status Scale. We performed the correlation analyses of WML shrinking with other MRI parameters and clinical outcome.

RESULTS

White matter lesions shrinking was highly variable between patients and correlated with the initial number of gadolinium-enhancing WML and with WM volume decrease. WML shrinking was not associated with clinical outcome.

CONCLUSION

We found no indication of a prognostic value of WML shrinking in early MS patients. WML shrinking seems to be related to waning of acute inflammation.

CSF parameters associated with early MRI activity in patients with MS

Objective

To identify CSF parameters at diagnosis of clinically isolated syndrome (CIS) and MS that are associated with early inflammatory disease activity as measured by standardized cerebral MRI (cMRI).

Methods

One hundred forty-nine patients with newly diagnosed CIS and MS were included in the retrospective study. cMRI at onset and after 12 months was analyzed for T2 and gadolinium-enhancing lesions. CSF was tested for oligoclonal bands and intrathecal synthesis of immunoglobulin G (IgG), A (IgA), and M (IgM) before initiation of disease-modifying therapy (DMT). In a subgroup of patients, CSF and serum samples were analyzed for sCD27, neurofilament light chain, and IgG subclasses 1 and 3. Association between CSF parameters and cMRI activity was investigated by univariable and multivariable regression analysis in all patients, DMT-treated patients, and untreated patients.

Results

IgG index, sCD27 levels in CSF, and to a lesser extent IgM index were associated with the occurrence of new cMRI lesions. IgG index and sCD27 levels in CSF were highly correlated. In a multivariable analysis, IgG index and to a lesser extent IgM index together with DMT treatment status and gender were strongest predictors of future cMRI activity.

Conclusions

CSF parameters such as IgG and IgM index are independently associated with future MRI activity and thus might be helpful to support early treatment decisions in patients newly diagnosed with CIS and MS.

CSF Protein Concentration Shows No Correlation With Brain Volume Measures

Background: CSF protein concentrations vary greatly among individuals. Accounting for brain volume may lower the variance and increase the diagnostic value of CSF protein concentrations.

Objective: To determine the relation between CSF protein concentrations and brain volume.

Methods: Brain volumes (total intracranial, gray matter, white matter volumes) derived from brain MRI and CSF protein concentrations (total protein, albumin, albumin CSF/serum ratio) of 29 control patients and 497 patients with clinically isolated syndrome or multiple sclerosis were studied.

Finding: We found significant positive correlations of CSF protein concentrations with intracranial, gray matter, and white matter volumes. None of the correlations remained significant after correction for age and sex.

Conclusion: Accounting for brain volume derived from brain MRI is unlikely to improve the diagnostic value of protein concentrations in CSF.

Automated segmentation of changes in FLAIR-hyperintense white matter lesions in multiple sclerosis on serial magnetic resonance imaging

Longitudinal analysis of white matter lesion changes on serial MRI has become an important parameter to study diseases with white-matter lesions. Here, we build on earlier work on cross-sectional lesion segmentation; we present a fully automatic pipeline for serial analysis of FLAIR-hyperintense white matter lesions. Our algorithm requires three-dimensional gradient echo T1- and FLAIR- weighted images at 3 Tesla as well as available cross-sectional lesion segmentations of both time points. Preprocessing steps include lesion filling and intrasubject registration. For segmentation of lesion changes, initial lesion maps of different time points are fused; herein changes in intensity are analyzed at the voxel level. Significance of lesion change is estimated by comparison with the difference distribution of FLAIR intensities within normal appearing white matter. The method is validated on MRI data of two time points from 40 subjects with multiple sclerosis derived from two different scanners (20 subjects per scanner). Manual segmentation of lesion increases served as gold standard. Across all lesion increases, voxel-wise Dice coefficient (0.7) as well as lesion-wise detection rate (0.8) and false-discovery rate (0.2) indicate good overall performance. Analysis of scans from a repositioning experiment in a single patient with multiple sclerosis did not yield a single false positive lesion. We also introduce the lesion change plot as a descriptive tool for the lesion change of individual patients with regard to both number and volume. An open source implementation of the algorithm is available at http://www.statistical-modeling.de/lst.html.

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Quantification of white matter lesion changes is important in multiple sclerosis.

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We developed and validated an algorithm for automated detection of lesion changes.

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Our algorithm requires T1-weighted and FLAIR images derived at 3 T as well as available cross-sectional lesion segmentations.

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With data from 2 different scanners, the tool showed good agreement with manual tracing.

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An open-source application is available.

Accuracy of Unenhanced MRI in the Detection of New Brain Lesions in Multiple Sclerosis

Background Administration of a gadolinium-based contrast material is widely considered obligatory for follow-up imaging of patients with multiple sclerosis (MS). However, advances in MRI have substantially improved the sensitivity for detecting new or enlarged lesions in MS. Purpose To investigate whether the use of contrast material has an effect on the detection of new or enlarged MS lesions and, consequently, the assessment of interval progression. Materials and Methods In this retrospective study based on a local prospective observational cohort, 507 follow-up MR images obtained in 359 patients with MS (mean age, 38.2 years ± 10.3; 246 women, 113 men) were evaluated. With use of subtraction maps, nonenhanced images (double inversion recovery [DIR], fluid-attenuated inversion recovery [FLAIR]) and contrast material-enhanced (gadoterate meglumine, 0.1 mmol/kg) T1-weighted images were separately assessed for new or enlarged lesions in independent readings by two readers blinded to each other's findings and to clinical information. Primary outcome was the percentage of new or enlarged lesions detected only on contrast-enhanced T1-weighted images and the assessment of interval progression. Interval progression was defined as at least one new or unequivocally enlarged lesion on follow-up MR images. Results Of 507 follow-up images, 264 showed interval progression, with a total of 1992 new or enlarged and 207 contrast-enhancing lesions. Four of these lesions (on three MR images) were retrospectively detected on only the nonenhanced images, corresponding to 1.9% (four of 207) of the enhancing and 0.2% (four of 1992) of all new or enlarged lesions. Nine enhancing lesions were not detected on FLAIR-based subtraction maps (nine of 1442, 0.6%). In none of the 507 images did the contrast-enhanced sequences reveal interval progression that was missed in the readouts of the nonenhanced sequences, with use of either DIR- or FLAIR-based subtraction maps. Interrater agreement was high for all three measures, with intraclass correlation coefficients of 0.91 with FLAIR, 0.94 with DIR, and 0.99 with contrast-enhanced T1-weighted imaging. Conclusion At 3.0 T, use of a gadolinium-based contrast agent at follow-up MRI did not change the diagnosis of interval disease progression in patients with multiple sclerosis. © RSNA, 2019 See also the editorial by Saindane in this issue.

Evidence for a white matter lesion size threshold to support the diagnosis of relapsing remitting multiple sclerosis

BACKGROUND

The number of white matter lesions (WML) in brain MRI is the most established paraclinical tool to support the diagnosis of multiple sclerosis (MS) and to monitor its course. Diagnostic criteria have stipulated a minimum detectable diameter of 3 mm per WML, although this threshold is not evidence-based. We aimed to provide a rationale for a WML size threshold for three-dimensional MRI sequences at 3 T by comparing patients with relapsing-remitting MS (RRMS) to control subjects (CS).

METHODS

We analyzed MR images from two cohorts, obtained at scanners from two different vendors, each comprising patients with RRMS and CS. Both cohorts were examined with FLAIR and T1w sequences. In total, 232 patients with RRMS (Expanded Disability Status Scale: mean = 1.6 ± 1.2; age: mean = 36 ± 10) as well as 116 age- and sex-matched CS were studied. We calculated odds ratios across WML volumes. The WML size threshold, which discriminated best between patients and CS, was estimated with receiver operating characteristic curve analysis.

RESULTS

In both cohorts, odds ratios increased continuously with increasing WML volumes, and discriminative power was highest at a WML size threshold corresponding to a diameter of about 3 mm.

CONCLUSION

The stipulated WML size threshold of 3 mm in diameter for the diagnostic criteria of MS seems a reasonable choice for three-dimensional MRI sequences at 3 T.

Geostatistical Analysis of White Matter Lesions in Multiple Sclerosis Identifies Gender Differences in Lesion Evolution

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system with presumed autoimmune origin. The development of lesions within the gray matter and white matter, which are highly variable with respect to number, total volume, morphology and spatial evolution and which only show a limited correlation with clinical disability, is a hallmark of the disease. Population-based studies indicate a distinct outcome depending on gender. Here, we studied gender-related differences in the evolution of white matter MS-lesions (MS-WML) in early MS by using geostatistical methods. Within a 3 years observation period, a female and a male MS patient group received disease modifying drugs and underwent standardized annual brain magnetic resonance imaging, accompanied by neurological examination. MS-WML were automatically extracted and the derived binary lesion masks were subject to geostatistical analysis, yielding quantitative spatial-statistics metrics on MS-WML pattern morphology and total lesion volume (TLV). Through the MS-lesion pattern discrimination plot, the following differences were disclosed: corresponding to gender and MS-WML pattern morphology at baseline, two female subgroups (F1, F2) and two male subgroups (M1, M2) are discerned that follow a distinct MS-WML pattern evolution in space and time. F1 and M1 start with medium-level MS-WML pattern smoothness and TLV, both behave longitudinally quasi-static. By contrast, F2 and M2 start with high-level MS-WML pattern smoothness and medium-level TLV. F2 and M2 longitudinal development is characterized by strongly diminishing MS-WML pattern smoothness and TLV, i.e., continued shrinking and break-up of MS-WML. As compared to the male subgroup M2, the female subgroup F2 shows continued, increased MS-WML pattern smoothness and TLV. Data from neurological examination suggest a correlation of MS-WML pattern morphology metrics and EDSS. Our results justify detailed studies on gender-related differences.

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

Predicting conversion from clinically isolated syndrome to multiple sclerosis-An imaging-based machine learning approach

Magnetic resonance imaging (MRI) scans play a pivotal role in the evaluation of patients presenting with a clinically isolated syndrome (CIS), as these may depict brain lesions suggestive of an inflammatory cause. We hypothesized that it is possible to predict the conversion from CIS to multiple sclerosis (MS) based on the baseline MRI scan by studying image features of these lesions.

We analyzed 84 patients diagnosed with CIS from a prospective observational single center cohort. The patients were followed up for at least three years. Conversion to MS was defined according to the 2010 McDonald criteria. Brain lesions were segmented based on 3D FLAIR and 3D T1 images. We generated brain lesion masks by a computer assisted manual segmentation. We also generated a set of automated segmentations using the Lesion Segmentation Toolbox for SPM to assess the influence of different segmentation methods. Shape and brightness features were automatically calculated from the segmented masks and used as input data to train an oblique random forest classifier. Prediction accuracies of the resulting model were validated through a three-fold cross-validation.

Conversion from CIS to MS occurred in 66 of 84 patients (79%). The conversion or non-conversion was predicted correctly in 71 patients based on shape features derived from the computer assisted manual segmentation masks (84.5% accuracy). This predictor was more accurate than predicting conversion using dissemination in space at baseline according to the 2010 McDonald criteria (75% accuracy). While shape features strongly contributed to the accuracy of the predictor, including intensity features did not further improve performance.

As patients who convert to definite MS benefit from early treatment, an early classification model is highly desirable. Our study shows that shape parameters of lesions can contribute to predicting the future course of CIS patients more accurately.

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A random forest tool can help to identify patients who convert from clinical isolated syndrome into multiple sclerosis (MS).

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The classifier is driven by shape features of lesions in the first MR scan.

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The found shape features reflect the typical ovoid growth of MS lesions.