Background and Objectives Magnetic resonance imaging (MRI) can be used to measure structural changes in the brain of people with multiple sclerosis (MS), and is essential for diagnosis, longitudinal monitoring, and therapy evaluation. The North American Imaging in Multiple Sclerosis Cooperative (NAIMS) steering committee developed a uniform high-resolution 3T MRI protocol relevant to the quantification of cerebral lesions and atrophy and implemented it at seven sites across the United States. To assess inter-site variability in scan data, a volunteer with relapsing-remitting MS was imaged with a scan-rescan at each site. Materials and Methods All imaging was acquired on Siemens scanners (4 Skyra, 2 TIM Trio, and 1 Verio). Expert segmentations were manually obtained for T1-hypointense and T2 (FLAIR)-hyperintense lesions. Several automated lesion detection and whole-brain, cortical, and deep gray matter volumetric pipelines were applied. Statistical analyses were conducted to assess variability across sites, as well as systematic biases in the volumetric measurements that were site-related. Results Systematic biases due to site differences in expert-traced lesion measurements were significant (p<0.01 for both T1 and T2 lesion volumes), with site explaining over 90% of the variation (range = 13.0–16.4ml in T1 and 15.9–20.1ml in T2) in lesion volumes. Site also explained more than 80% of the variation in most automated volumetric measurements. Output measures clustered according to scanner models, with similar results from the Skyra vs. the other two units. Conclusions Even in multi-center studies with consistent scanner field strength and manufacturer, after protocol harmonization, systematic differences can lead to severe biases in volumetric analyses.

IMPORTANCE MicroRNAs (miRNAs) are promising multiple sclerosis (MS) biomarkers. Establishing the association between miRNAs and magnetic resonance imaging (MRI) measures of disease severity will help define their significance and potential impact. OBJECTIVE To correlate circulating miRNAs in the serum of patients with MS to brain and spinal MRI. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional study comparing serum miRNA samples with MRI metrics was conducted at a tertiary MS referral center. Two independent cohorts (41 and 79 patients) were retrospectively identified from the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital. Expression of miRNA was determined by locked nucleic acid-based quantitative real-time polymerase chain reaction. Spearman correlation coefficients were used to test the association between miRNA and brain lesions (T2 hyperintense lesion volume [T2LV]), the ratio of T1 hypointense lesion volume [T1LV] to T2LV [T1:T2]), brain atrophy (whole brain and gray matter), and cervical spinal cord lesions (T2LV) and atrophy. The study was conducted from December 2013 to April 2016. MAIN OUTCOMES AND MEASURES miRNA expression. RESULTSOf the 120 patients included in the study, cohort 1 included 41 participants (7 [17.1%] men), with mean (SD) age of 47.7 (9.5) years; cohort 2 had 79 participants (26 [32.9%] men) with a mean (SD) age of 43.0 (7.5) years. Associations between miRNAs and MRIs were both protective and pathogenic. Regarding miRNA signatures, a topographic specificity differed for the brain vs the spinal cord, and the signature differed between T2LV and atrophy/destructive measures. Four miRNAs showed similar significant protective correlations with T1:T2 in both cohorts, with the highest for hsa.miR.143.3p

Our results raise awareness of the significant impact that GNL can have on quantitative UCCA studies, and point the way to prospectively and retrospectively managing GNL distortions in a variety of settings, including clinical environments. Magn Reson Med 79:1595-1601, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

BACKGROUND AND PURPOSEA pipeline for fully automated segmentation of 3T brain MRI scans in multiple sclerosis (MS) is presented. This 3T morphometry (3TM) pipeline provides indicators of MS disease progression from multichannel datasets with high‐resolution 3‐dimensional T1‐weighted, T2‐weighted, and fluid‐attenuated inversion‐recovery (FLAIR) contrast. 3TM segments white (WM) and gray matter (GM) and cerebrospinal fluid (CSF) to assess atrophy and provides WM lesion (WML) volume.METHODSTo address nonuniform distribution of noise/contrast (eg, posterior fossa in 3D‐FLAIR) of 3T magnetic resonance imaging, the method employs dual sensitivity (different sensitivities for lesion detection in predefined regions). We tested this approach by assigning different sensitivities to supratentorial and infratentorial regions, and validated the segmentation for accuracy against manual delineation, and for precision in scan‐rescans.RESULTSIntraclass correlation coefficients of .95, .91, and .86 were observed for WML and CSF segmentation accuracy and brain parenchymal fraction (BPF). Dual sensitivity significantly reduced infratentorial false‐positive WMLs, affording increases in global sensitivity without decreasing specificity. Scan‐rescan yielded coefficients of variation (COVs) of 8% and .4% for WMLs and BPF and COVs of .8%, 1%, and 2% for GM, WM, and CSF volumes. WML volume difference/precision was .49 ± .72 mL over a range of 0–24 mL. Correlation between BPF and age was r = .62 (P = .0004), and effect size for detecting brain atrophy was Cohen's d = 1.26 (standardized mean difference vs. healthy controls).CONCLUSIONSThis pipeline produces probability maps for brain lesions and tissue classes, facilitating expert review/correction and may provide high throughput, efficient characterization of MS in large datasets.