Objective Rates of worsening and evolution to secondary progressive multiple sclerosis (MS) may be substantially lower in actively treated patients compared to natural history studies from the pretreatment era. Nonetheless, in our recently reported prospective cohort, more than half of patients with relapsing MS accumulated significant new disability by the 10th year of follow‐up. Notably, “no evidence of disease activity” at 2 years did not predict long‐term stability. Here, we determined to what extent clinical relapses and radiographic evidence of disease activity contribute to long‐term disability accumulation. Methods Disability progression was defined as an increase in Expanded Disability Status Scale (EDSS) of 1.5, 1.0, or 0.5 (or greater) from baseline EDSS = 0, 1.0–5.0, and 5.5 or higher, respectively, assessed from baseline to year 5 (±1 year) and sustained to year 10 (±1 year). Longitudinal analysis of relative brain volume loss used a linear mixed model with sex, age, disease duration, and HLA‐DRB1*15:01 as covariates. Results Relapses were associated with a transient increase in disability over 1‐year intervals ( p = 0.012) but not with confirmed disability progression ( p = 0.551). Relative brain volume declined at a greater rate among individuals with disability progression compared to those who remained stable ( p < 0.05). Interpretation Long‐term worsening is common in relapsing MS patients, is largely independent of relapse activity, and is associated with accelerated brain atrophy. We propose the term silent progression to describe the insidious disability that accrues in many patients who satisfy traditional criteria for relapsing–remitting MS. Ann Neurol 2019;85:653–666

Objective In multiple sclerosis (MS) cerebral gray matter (GM) atrophy correlates more strongly than white matter (WM) atrophy with disability. The corresponding relationships in the spinal cord (SC) are unknown due to technical limitations in assessing SCGM atrophy. Using phase sensitive inversion recovery (PSIR) MRI, we determined the association of the SCGM and SCWM areas with MS disability and disease type. Methods 113 MS patients and 20 healthy controls were examined at 3T with a PSIR sequence acquired at the C2/C3 disc level. Two independent, clinically-masked readers measured the cord WM and GM areas. Correlations between cord areas and Expanded Disability Status Score (EDSS) were determined. Differences in areas between groups were assessed with age and sex as covariates. Results Relapsing (R) MS patients showed smaller SCGM areas than age and sex matched controls (p=0.008) without significant differences in SCWM areas. Progressive MS patients showed smaller SCGM and SCWM areas compared to RMS patients (all p≤0.004). SCGM, SCWM, and whole cord areas inversely correlated with EDSS (rho: −0.60, −0.32, −0.42, respectively; all p≤0.001). SCGM area was the strongest correlate of disability in multivariate models including brain GM and WM volumes, FLAIR lesion load, T1-lesion load, SCWM area, number of spinal cord T2 lesions, age, sex, disease duration. Brain and spinal GM independently contributed to EDSS. Interpretation SCGM atrophy is detectable in-vivo in absence of WM atrophy in RMS. It is more pronounced in progressive than RMS and contributes more to patient disability than spinal cord WM or brain GM atrophy.

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.

abbreviatioNs AF = arcuate fasciculus; AFTD = altered fiber tractography density; CD = clinical deficit; CRT set = clinically relevant tract set; DTI = diffusion tensor imaging; FA = fractional anisotropy; GTR = gross-total resection; HARDI = high angular resolution diffusion-weighted imaging; HGG = high-grade glioma; IFOF = inferior frontooccipital fasciculus; ILF = inferior longitudinal fasciculus; IR-SPGR = inversion-recovery spoiled gradient echo; ISM = intraoperative stimulation mapping; LGG = low-grade glioma; MdLF = middle longitudinal fasciculus; MNI = Montreal Neurological Institute; MST set = minimally sufficient tract set; ODF = orientation distribution function; ROI = region of interest; SLF = superior longitudinal fasciculus; SLF-tp = temporoparietal component of SLF; SLF-II&III = SLF components II and III; UF = uncinate fasciculus. obJective Diffusion MRI has uniquely enabled in vivo delineation of white matter tracts, which has been applied to the segmentation of eloquent pathways for intraoperative mapping. The last decade has also seen the development from earlier diffusion tensor models to higher-order models, which take advantage of high angular resolution diffusion-weighted imaging (HARDI) techniques. However, these advanced methods have not been widely implemented for routine preoperative and intraoperative mapping. The authors report on the application of residual bootstrap q-ball fiber tracking for routine mapping of potentially functional language pathways, the development of a system for rating tract injury to evaluate the impact on clinically assessed language function, and initial results predicting long-term language deficits following glioma resection. methods The authors have developed methods for the segmentation of 8 putative language pathways including dorsal phonological pathways and ventral semantic streams using residual bootstrap q-ball fiber tracking. Furthermore, they have implemented clinically feasible preoperative acquisition and processing of HARDI data to delineate these pathways for neurosurgical application. They have also developed a rating scale based on the altered fiber tract density to estimate the degree of pathway injury, applying these ratings to a subset of 35 patients with pre- and postoperative fiber tracking. The relationships between specific pathways and clinical language deficits were assessed to determine which pathways are predictive of long-term language deficits following surgery. results This tracking methodology has been routinely implemented for preoperative mapping in patients with brain gliomas who have undergone awake brain tumor resection at the University of California, San Francisco (more than 300 patients to date). In this particular study the authors investigated the white matter structure status and language correlation in a subcohort of 35 subjects both pre- and postsurgery. The rating scales developed for fiber pathway damage were found to be highly reproducible and provided significant correlations with language performance. Preserva...

Background and Purpose-The quantification of spinal cord (SC) atrophy by MRI has assumed an important role in assessment of neuroinflammatory/neurodegenerative diseases and traumatic SC injury. Recent technical advances make possible the quantification of gray matter (GM) and white matter tissues in clinical settings. However, the goal of a reliable diagnostic, prognostic or predictive marker is still elusive, in part due to large inter-subject variability of SC areas. Here, we investigated the sources of this variability and explored effective strategies to reduce it.Methods-129 healthy subjects (mean age: 41.0±15.9) underwent MRI on a Siemens 3T Skyra scanner. 2D PSIR at the C2-C3 vertebral level and a sagittal 1mm 3 3D T1-weighted brain acquisition extended to the upper cervical cord were acquired. Total cross-sectional area and GM area were measured at C2-C3, as well as measures of the vertebra, spinal canal and the skull. Correlations between the different metrics were explored using Pearson product-moment coefficients. The most promising metrics were used to normalize cord areas using multiple regression analyses.Results-The most effective normalization metrics were the V-scale (from SienaX) and the product of the C2-C3 spinal canal diameters. Normalization methods based on these metrics reduced the inter-subject variability of cord areas of up to 17.74%. The measured cord areas had a statistically significant sex difference, while the effect of age was moderate.Conclusions-The present work explored in a large cohort of healthy subjects the source of inter-subject variability of SC areas and proposes effective normalization methods for its reduction.