Exploring the effect of glatiramer acetate on cerebral gray matter atrophy in multiple sclerosis.

BACKGROUND AND PURPOSE: Cerebral gray matter (GM) atrophy is a proposed measure of neuroprotection in multiple sclerosis (MS). Glatiramer acetate (GA) limits clinical relapses, MRI lesions, and whole brain atrophy in relapsing-remitting MS (RRMS). The effect of GA on GM atrophy remains unclear. We assessed GM atrophy in patients with RRMS starting GA therapy in comparison to a cohort of patients with clinically benign RRMS (BMS). DESIGN/METHODS: We studied 14 patients at GA start [age (mean ± SD) 44.2 ± 7.0 years, disease duration (DD) 7.2 ± 6.4 years, Expanded Disability Status Scale score (EDSS) (median,IQR) 1.0,2.0] and 6 patients with BMS [age 43.0 ± 6.1 years, DD 18.1 ± 8.4 years, EDSS 0.5,1.0]. Brain MRI was obtained at baseline and one year later (both groups) and two years later in all patients in the GA group except one who was lost to follow-up. Semi-automated algorithms assessed cerebral T2 hyperintense lesion volume (T2LV), white matter fraction (WMF), GM fraction (GMF), and brain parenchymal fraction (BPF). The exact Wilcoxon-Mann-Whitney test compared the groups. The Wilcoxon signed rank test assessed longitudinal changes within groups. RESULTS: During the first year, MRI changes did not differ significantly between groups (p > 0.15). Within the BMS group, WMF and BPF decreased during the first year (p = 0.03). Within the GA group, there was no significant change in MRI measures during each annual period (p > 0.05). Over two years, the GA group had a significant increase in T2LV and decrease in WMF (p < 0.05), while GMF and BPF remained stable (p > 0.05). MRI changes in brain volumes (GMF or WMF) in the first year in the GA group were not significantly different from those in the BMS group (p > 0.5). CONCLUSIONS: In this pilot study with a small sample size, patients with RRMS started on GA did not show significant GM or whole brain atrophy over 2 years, resembling MS patients with a clinically benign disease course.

Quantifying neurologic disease using biosensor measurements in-clinic and in free-living settings in multiple sclerosis.

Technological advances in passive digital phenotyping present the opportunity to quantify neurological diseases using new approaches that may complement clinical assessments. Here, we studied multiple sclerosis (MS) as a model neurological disease for investigating physiometric and environmental signals. The objective of this study was to assess the feasibility and correlation of wearable biosensors with traditional clinical measures of disability both in clinic and in free-living in MS patients. This is a single site observational cohort study conducted at an academic neurological center specializing in MS. A cohort of 25 MS patients with varying disability scores were recruited. Patients were monitored in clinic while wearing biosensors at nine body locations at three separate visits. Biosensor-derived features including aspects of gait (stance time, turn angle, mean turn velocity) and balance were collected, along with standardized disability scores assessed by a neurologist. Participants also wore up to three sensors on the wrist, ankle, and sternum for 8 weeks as they went about their daily lives. The primary outcomes were feasibility, adherence, as well as correlation of biosensor-derived metrics with traditional neurologist-assessed clinical measures of disability. We used machine-learning algorithms to extract multiple features of motion and dexterity and correlated these measures with more traditional measures of neurological disability, including the expanded disability status scale (EDSS) and the MS functional composite-4 (MSFC-4). In free-living, sleep measures were additionally collected. Twenty-three subjects completed the first two of three in-clinic study visits and the 8-week free-living biosensor period. Several biosensor-derived features significantly correlated with EDSS and MSFC-4 scores derived at visit two, including mobility stance time with MSFC-4 z-score (Spearman correlation -0.546; p = 0.0070), several aspects of turning including turn angle (0.437; p = 0.0372), and maximum angular velocity (0.653; p = 0.0007). Similar correlations were observed at subsequent clinic visits, and in the free-living setting. We also found other passively collected signals, including measures of sleep, that correlated with disease severity. These findings demonstrate the feasibility of applying passive biosensor measurement techniques to monitor disability in MS patients both in clinic and in the free-living setting.

Whole-brain atrophy assessed by proportional- versus registration-based pipelines from 3T MRI in multiple sclerosis.

BACKGROUND AND PURPOSE: Whole-brain atrophy is a standard outcome measure in multiple sclerosis (MS) clinical trials as assessed by various software tools. The effect of processing method on the validity of such data obtained from high-resolution 3T MRI is not known. We compared two commonly used methods of quantifying whole-brain atrophy. METHODS: Three-dimensional T1-weighted and FLAIR images were obtained at 3T in MS (n = 61) and normal control (NC, n = 30) groups. Whole-brain atrophy was assessed by two automated pipelines: (a) SPM8 to derive brain parenchymal fraction (BPF, proportional-based method); (b) SIENAX to derive normalized brain parenchymal volume (BPV, registration method). We assessed agreement between BPF and BPV, as well their relationship to Expanded Disability Status Scale (EDSS) score, timed 25-foot walk (T25FW), cognition, and cerebral T2 (FLAIR) lesion volume (T2LV). RESULTS: Brain parenchymal fraction and BPV showed only partial agreement (r = 0.73) in the MS group, and r = 0.28 in NC. Both methods showed atrophy in MS versus NC (BPF p < 0.01, BPV p < 0.05). Within MS group comparisons, BPF (p < 0.05) but not BPV (p > 0.05) correlated with EDSS score. BPV (p = 0.03) but not BPF (p = 0.08) correlated with T25FW. Both metrics correlated with T2LV (p < 0.05) and cognitive subscales. BPF (p < 0.05) but not BPV (p > 0.05) showed lower brain volume in cognitively impaired (n = 23) versus cognitively preserved (n = 38) patients. However, direct comparisons of BPF and BPV sensitivities to atrophy and clinical correlations were not statistically significant. CONCLUSION: Whole-brain atrophy metrics may not be interchangeable between proportional- and registration-based automated pipelines from 3T MRI in patients with MS.

Gradient nonlinearity effects on upper cervical spinal cord area measurement from 3D T1 -weighted brain MRI acquisitions.

PURPOSE: To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T1 -weighted scans related to gradient nonlinearity (GNL) and subject positioning; (ii) the effect of vendor-implemented GNL corrections; and (iii) easily applicable methods that can be used to retrospectively correct data. METHODS: A multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with the same 3D T1 -weighted protocol without GNL-distortion correction. Two healthy subjects and a phantom were additionally scanned at a single site with varying table positions. The 2D and 3D vendor-implemented GNL-correction algorithms and retrospective methods based on (i) phantom data fit, (ii) normalization with C2 vertebral body diameters, and (iii) the Jacobian determinant of nonlinear registrations to a template were tested. RESULTS: Depending on the positioning of the subject, GNL introduced up to 15% variability in UCCA measurements from volumetric brain T1 -weighted scans when no distortion corrections were used. The 3D vendor-implemented correction methods and the three proposed methods reduced this variability to less than 3%. CONCLUSIONS: 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.

Dual-Sensitivity Multiple Sclerosis Lesion and CSF Segmentation for Multichannel 3T Brain MRI.

BACKGROUND AND PURPOSE: A 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. METHODS: To 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. RESULTS: Intraclass 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). CONCLUSIONS: This 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.

Automatic spinal cord localization, robust to MRI contrasts using global curve optimization.

During the last two decades, MRI has been increasingly used for providing valuable quantitative information about spinal cord morphometry, such as quantification of the spinal cord atrophy in various diseases. However, despite the significant improvement of MR sequences adapted to the spinal cord, automatic image processing tools for spinal cord MRI data are not yet as developed as for the brain. There is nonetheless great interest in fully automatic and fast processing methods to be able to propose quantitative analysis pipelines on large datasets without user bias. The first step of most of these analysis pipelines is to detect the spinal cord, which is challenging to achieve automatically across the broad range of MRI contrasts, field of view, resolutions and pathologies. In this paper, a fully automated, robust and fast method for detecting the spinal cord centerline on MRI volumes is introduced. The algorithm uses a global optimization scheme that attempts to strike a balance between a probabilistic localization map of the spinal cord center point and the overall spatial consistency of the spinal cord centerline (i.e. the rostro-caudal continuity of the spinal cord). Additionally, a new post-processing feature, which aims to automatically split brain and spine regions is introduced, to be able to detect a consistent spinal cord centerline, independently from the field of view. We present data on the validation of the proposed algorithm, known as "OptiC", from a large dataset involving 20 centers, 4 contrasts (T2-weighted n = 287, T1-weighted n = 120, T2∗-weighted n = 307, diffusion-weighted n = 90), 501 subjects including 173 patients with a variety of neurologic diseases. Validation involved the gold-standard centerline coverage, the mean square error between the true and predicted centerlines and the ability to accurately separate brain and spine regions. Overall, OptiC was able to cover 98.77% of the gold-standard centerline, with a mean square error of 1.02 mm. OptiC achieved superior results compared to a state-of-the-art spinal cord localization technique based on the Hough transform, especially on pathological cases with an averaged mean square error of 1.08 mm vs. 13.16 mm (Wilcoxon signed-rank test p-value < .01). Images containing brain regions were identified with a 99% precision, on which brain and spine regions were separated with a distance error of 9.37 mm compared to ground-truth. Validation results on a challenging dataset suggest that OptiC could reliably be used for subsequent quantitative analyses tasks, opening the door to more robust analysis on pathological cases.

A two-year study using cerebral gray matter volume to assess the response to fingolimod therapy in multiple sclerosis.

BACKGROUND: Cerebral gray matter (GM) atrophy has clinical relevance in multiple sclerosis (MS). Fingolimod has known efficacy on clinical and conventional MRI findings in MS; the effect on GM is unknown. OBJECTIVE: To explore fingolimod's treatment effect on cerebral GM atrophy over two years in patients with relapsing forms of MS. DESIGN/METHODS: Patients starting fingolimod [n=24, age (mean±SD) 41.2±11.6years, Expanded Disability Status Scale (EDSS) score 1.1±1.4; 58% women] were compared to untreated patients [n=29, age 45.7±8.4years, EDSS 1.0±1.2; 93% women]. Baseline, one and two year MRI was applied to an SPM12 pipeline to assess brain parenchymal fraction (BPF) and cortical GM fraction (cGMF). T2 lesion volume (T2LV) and gadolinium-enhancing lesions were assessed. Change was modeled using a mixed effects linear regression with a random intercept and fixed effects for time, group, and the time-by-group interaction. The group slope difference was assessed using the interaction term. RESULTS: Over two years, cGMF remained stable in the fingolimod group (p>0.05), but decreased in the untreated group (p<0.001) (group difference p<0.001). BPF change did not differ between groups (all time-points p>0.05). T2LV increased over two years in the untreated group (p<0.001) but not in the fingolimod group (p≥0.44) (group difference p<0.001). CONCLUSION: These results suggest a treatment effect of fingolimod on cerebral GM atrophy in the first two years. GM atrophy is more sensitive to such effects than whole brain atrophy. However, due to the non-randomized, retrospective design, heterogeneous between-group characteristics, and small sample size, these results require confirmation in future studies.

Spinal Cord as an Adjunct to Brain Magnetic Resonance Imaging in Defining "No Evidence of Disease Activity" in Multiple Sclerosis.

Background: Monitoring patients with multiple sclerosis (MS) for "no evidence of disease activity" (NEDA) may help guide disease-modifying therapy (DMT) management decisions. Whereas surveillance brain magnetic resonance imaging (MRI) is common, the role of spinal cord monitoring for NEDA is unknown. Objective: To evaluate the role of brain and spinal cord 3T MRI in the 1-year evaluation of NEDA. Methods: Of 61 study patients (3 clinically isolated syndrome, 56 relapsing-remitting, 2 secondary progressive), 56 (91.8%) were receiving DMT. The MRI included brain fluid-attenuated inversion recovery and cervical/thoracic T2-weighted fast spin echo images. On MRI, NEDA was defined as the absence of new or enlarging T2 lesions at 1 year. Results: Thirty-nine patients (63.9%) achieved NEDA by brain MRI, only one of whom had spinal cord activity. This translates to a false-positive rate for NEDA based on the brain of 2.6% (95% CI, 0.1%­13.5%). Thirty-eight patients (62.3%) had NEDA by brain and spinal cord MRI. Fifty-five patients (90.2%) had NEDA by spinal cord MRI, 17 of whom had brain activity. Of the 22 patients (36.1%) with brain changes, 5 had spinal cord changes. No evidence of disease activity was sustained in 48.3% of patients at 1 year and was the same with the addition of spinal cord MRI. Patients with MRI activity in either the brain or the spinal cord only were more likely to have activity in the brain (P = .0001). Conclusions: Spinal cord MRI had a low diagnostic yield as an adjunct to brain MRI at 3T in monitoring patients with MS for NEDA over 1 year. Studies with larger data sets are needed to confirm these findings.

Association Between Serum MicroRNAs and Magnetic Resonance Imaging Measures of Multiple Sclerosis Severity.

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. Results: Of 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 (cohort 1: Spearman correlation coefficient rs = -0.452, P = .003; cohort 2: rs = -0.225, P = .046); the others included hsa.miR.142.5p (cohort 1: rs = -0.424, P = .006; cohort 2: rs = -0.226, P = .045), hsa.miR.181c.3p (cohort 1: rs = -0.383, P = .01; cohort 2: rs = -0.222, P = .049), and hsa.miR.181c.5p (cohort 1: rs = -0.433, P = .005; cohort 2: rs = -0.231, P = .04). In the 2 cohorts, hsa.miR.486.5p (cohort 1: rs = 0.348, P = .03; cohort 2: rs = 0.254, P = .02) and hsa.miR.92a.3p (cohort 1: rs = 0.392, P = .01; cohort 2: rs = 0.222, P = .049) showed similar significant pathogenic correlations with T1:T2; hsa.miR.375 (cohort 1: rs = -0.345, P = .03; cohort 2: rs = -0.257, P = .022) and hsa.miR.629.5p (cohort 1: rs = -0.350, P = .03; cohort 2: rs = -0.269, P = .02) showed significant pathogenic correlations with brain atrophy. Although we found several miRNAs associated with MRI outcomes, none of these associations remained significant when correcting for multiple comparisons, suggesting that further validation of our findings is needed. Conclusions and Relevance: Serum miRNAs may serve as MS biomarkers for monitoring disease progression and act as surrogate markers to identify underlying disease processes.

The Contribution of Cortical Lesions to a Composite MRI Scale of Disease Severity in Multiple Sclerosis.

OBJECTIVE: To test a new version of the Magnetic Resonance Disease Severity Scale (v.3 = MRDSS3) for multiple sclerosis (MS), incorporating cortical gray matter lesions (CLs) from 3T magnetic resonance imaging (MRI). BACKGROUND: MRDSS1 was a cerebral MRI-defined composite scale of MS disease severity combining T2 lesion volume (T2LV), the ratio of T1 to T2LV (T1/T2), and whole brain atrophy [brain parenchymal fraction (BPF)]. MRDSS2 expanded the scale to include cerebral gray matter fraction (GMF) and upper cervical spinal cord area (UCCA). We tested the contribution of CLs to the scale (MRDSS3) in modeling the MRI relationship to clinical status. METHODS: We studied 51 patients [3 clinically isolated syndrome, 43 relapsing-remitting, 5 progressive forms, age (mean ± SD) 40.7 ± 9.1 years, Expanded Disability Status Scale (EDSS) score 1.6 ± 1.7] and 20 normal controls by high-resolution cerebrospinal MRI. CLs required visibility on both fluid-attenuated inversion-recovery (FLAIR) and modified driven equilibrium Fourier transform sequences. The MACFIMS battery defined cognitively impaired (n = 18) vs. preserved (n = 33) MS subgroups. RESULTS: EDSS significantly correlated with only BPF, UCCA, MRDSS2, and MRDSS3 (all p < 0.05). After adjusting for depressive symptoms, the cognitively impaired group had higher severity of MRI metrics than the cognitively preserved group in regard to only BPF, GMF, T1/T2, MRDSS1, and MRDSS2 (all p < 0.05). CL number was not significantly related to EDSS score or cognition status. CONCLUSION: CLs from 3T MRI did not appear to improve the validity of the MRDSS. Further studies employing advanced sequences or higher field strengths may show more utility for the incorporation of CLs into composite scales.

Serum lipid antibodies are associated with cerebral tissue damage in multiple sclerosis.

OBJECTIVE: To determine whether peripheral immune responses as measured by serum antigen arrays are linked to cerebral MRI measures of disease severity in multiple sclerosis (MS). METHODS: In this cross-sectional study, serum samples were obtained from patients with relapsing-remitting MS (n = 21) and assayed using antigen arrays that contained 420 antigens including CNS-related autoantigens, lipids, and heat shock proteins. Normalized compartment-specific global brain volumes were obtained from 3-tesla MRI as surrogates of atrophy, including gray matter fraction (GMF), white matter fraction (WMF), and total brain parenchymal fraction (BPF). Total brain T2 hyperintense lesion volume (T2LV) was quantified from fluid-attenuated inversion recovery images. RESULTS: We found serum antibody patterns uniquely correlated with BPF, GMF, WMF, and T2LV. Furthermore, we identified immune signatures linked to MRI markers of neurodegeneration (BPF, GMF, WMF) that differentiated those linked to T2LV. Each MRI measure was correlated with a specific set of antibodies. Strikingly, immunoglobulin G (IgG) antibodies to lipids were linked to brain MRI measures. Based on the association between IgG antibody reactivity and each unique MRI measure, we developed a lipid index. This comprised the reactivity directed against all of the lipids associated with each specific MRI measure. We validated these findings in an additional independent set of patients with MS (n = 14) and detected a similar trend for the correlations between BPF, GMF, and T2LV vs their respective lipid indexes. CONCLUSIONS: We propose serum antibody repertoires that are associated with MRI measures of cerebral MS involvement. Such antibodies may serve as biomarkers for monitoring disease pathology and progression.

An MRI-defined measure of cerebral lesion severity to assess therapeutic effects in multiple sclerosis.

Assess the sensitivity of the Magnetic Resonance Disease Severity Scale (MRDSS), based on cerebral lesions and atrophy, for treatment monitoring of glatiramer acetate (GA) in relapsing-remitting multiple sclerosis (MS). This retrospective non-randomized pilot study included patients who started daily GA [n = 23, age (median, range) 41 (26.2, 53.1) years, Expanded Disability Status Scale (EDSS) score 1.0 (0, 3.5)], or received no disease-modifying therapy (noDMT) [n = 21, age 44.8 (28.2, 55.4), EDSS 0 (0, 2.5)] for 2 years. MRDSS was the sum of z-scores (normalized to a reference sample) of T2 hyperintense lesion volume (T2LV), the ratio of T1 hypointense LV to T2LV (T1/T2), and brain parenchymal fraction (BPF) multiplied by negative 1. The two groups were compared by Wilcoxon rank sum tests; within group change was assessed by Wilcoxon signed rank tests. Glatiramer acetate subjects had less progression than noDMT on T1/T2 [(median z-score change (range), 0 (-1.07, 1.20) vs. 0.41 (-0.30, 2.51), p = 0.003)] and MRDSS [0.01 (-1.33, 1.28) vs. 0.46 (-1.57, 2.46), p = 0.01]; however, not on BPF [0.12 (-0.18, 0.58) vs. 0.10 (-1.47,0.50), p = 0.59] and T2LV [-0.03 (-0.90, 0.57) vs. 0.01 (-1.69, 0.34), p = 0.40]. While GA subjects worsened only on BPF [0.12 (-0.18, 0.58), p = 0.001], noDMT worsened on BPF [0.10 (-1.47, 0.50), p = 0.002], T1/T2 [0.41 (-0.30, 2.51), p = 0.0002], and MRDSS [0.46 (-1.57, 2.46), p = 0.0006]. These preliminary findings show the potential of two new cerebral MRI metrics to track MS therapeutic response. The T1/T2, an index of the destructive potential of lesions, may provide particular sensitivity to treatment effects.

MRI detection of hypointense brain lesions in patients with multiple sclerosis: T1 spin-echo vs. gradient-echo.

OBJECTIVE: Compare T1 spin-echo (T1SE) and T1 gradient-echo (T1GE) sequences in detecting hypointense brain lesions in multiple sclerosis (MS). BACKGROUND: Chronic hypointense lesions on T1SE MRI scans are a surrogate of severe demyelination and axonal loss in MS. The role of T1GE images in the detection of such lesions has not been clarified. DESIGN/METHODS: In 45 patients with MS [Expanded Disability Status Scale (EDSS) score (mean±SD) 3.5±2.0; 37 relapsing-remitting (RR); 8 secondary progressive (SP)], cerebral T1SE, T1GE, and T2-weighted fluid-attenuated inversion-recovery (FLAIR) images were acquired on a 1.5T MRI scanner. Images were re-sampled to axial 5mm slices before directly comparing lesion detectability using Jim (v.7, Xinapse Systems). Statistical methods included Wilcoxon signed rank tests to compare sequences and Spearman correlations to test associations. RESULTS: Considering the entire cohort, T1GE detected a higher lesion volume (5.90±6.21 vs. 4.17±4.84ml, p<0.0001) and higher lesion number (27.82±20.66 vs. 25.20±20.43, p<0.05) than T1SE. Lesion volume differences persisted when considering RR and SP patients separately (both p<0.01). A higher lesion number by T1GE was seen only in the RR group (p<0.05). When comparing correlations between lesion volume and overall neurologic disability (EDSS score), T1SE correlated with EDSS (Spearman r=0.29, p<0.05) while T1GE (r=0.23, p=0.13) and FLAIR (r=0.24, p=0.12) did not. CONCLUSION: Our data suggest that hypointense lesions on T1SE and T1GE are not interchangeable in patients with MS. Based on these results, we hypothesize that T1GE shows more sensitivity to lesions at the expense of less pathologic specificity for tissue destruction than T1SE.