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

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

ABSTRACT 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

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 1.5 T MRI scanner. Images were re-sampled to axial 5 mm 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 ± 4.84 ml, 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

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

CME/CNE Information Activity Available Online: To access the article, post-test, and evaluation online, go to http://www.cmscscholar.org. Target Audience: The target audience for this activity is physicians, physician assistants, nursing professionals, and other health-care providers involved in the management of patients with multiple sclerosis (MS). Learning Objectives: Accreditation Statement: This activity has been planned and implemented in accordance with the accreditation requirements and policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint providership of the Consortium of Multiple Sclerosis Centers (CMSC), Nurse Practitioner Alternatives (NPA), and Delaware Media Group. The CMSC is accredited by the ACCME to provide continuing medical education for physicians. The CMSC designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Nurse Practitioner Alternatives (NPA) is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's Commission on Accreditation. NPA designates this enduring material for 1.0 Continuing Nursing Education credit (none in the area of pharmacology). Laurie Scudder, DNP, NP, has served as Nurse Planner for this activity. She has disclosed no relevant financial relationships. Disclosures: Editor in Chief of the International Journal of MS Care (IJMSC), has served as Physician Planner for this activity. He has received royalties from Springer Publishing; has received consulting fees from Acorda Therapeutics, Merz Pharma, and Ipsen; and has performed contracted research for Biogen, Acorda Therapeutics, and Adamas Pharmaceuticals.Francois Bethoux, MD, has served as Nurse Planner for this activity. She has disclosed no relevant financial relationships.Laurie Scudder, DNP, NP, has disclosed no relevant financial relationships.Subhash Tummala, MD, has disclosed no relevant financial relationships.Tarun Singhal, MD, has disclosed no relevant financial relationships.Vinit V. Oommen, MD, has disclosed no relevant financial relationships.Gloria Kim, BA, has disclosed no relevant financial relationships.Fariha Khalid, MD, has received research support from Genzyme, Merck Serono, Novartis, and Verily Life Sciences.Brian C. Healy, PhD, has received consulting fees from AbbVie, Alkermes, Biogen, Novartis, and Questcor; and has received research support from Biogen, Genzyme, Merck Serono, Novartis, and Teva. Dr. Bakshi's spouse owns stock in Biogen.Rohit Bakshi, MD, One anonymous peer reviewer for the IJMSC has received consulting fees or honoraria from Actelion, Bayer HealthCare, Biogen Idec, Chugai, EMD Canada, Genzyme, Merck Serono, Novartis, Hoffman-La Roche, Sanofi-Aventis, and Teva Canada Innovation; has served on a speakers' bureau for Genzyme; has served on an advisory board, a board of directors, or another similar group for Actelion, Bayer HealthCare, Biogen Idec, Hoffman-La Roche, Merck Serono, MedDay, Novartis, and Sanofi-Aventis; and has received research support from Genzyme. The other two reviewers have disclosed no relevant financial relationships. The staff at the IJMSC, CMSC, NPA, and Delaware Media Group who are in a position to influence content have disclosed no relevant financial relationships. Method of Participation: Release Date: May 1, 2017 Valid for Credit Through: May 1, 2018 In order to receive CME/CNE credit, participants must: Statements of Credit are awarded upon successful completion of the post-test with a passing score of >70% and the evaluation. There is no fee to participate in this activity. Disclosure of Unlabeled Use: This CME/CNE activity may contain discussion of published and/or investigational uses of agents that are not approved by the FDA. CMSC, NPA, and Delaware Media Group do not recommend the use of any agent outside of the labeled indications. The opinions expressed in the educational activity are those of the faculty and do not necessarily represent the views of CMSC, NPA, or Delaware Media Group. Disclaimer: Participants have an implied responsibility to use the newly acquired information to enhance patient outcomes and their own professional development. The information presented in this activity is not meant to serve as a guideline for patient management. Any medications, diagnostic procedures, or treatments discussed in this publication should not be used by clinicians or other health-care professionals without first evaluating their patients' conditions, considering possible contraindications or risks, reviewing any applicable manufacturer's product information, and comparing any therapeutic approach with the recommendations of other authorities

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

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

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

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. To explore fingolimod's treatment effect on cerebral GM atrophy over two years in patients with relapsing forms of MS. 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. Over two years, cGMF remained stable in the fingolimod group (p>0.05), but decreased in the untreated group (p0.05). 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). 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. •Cerebral gray matter atrophy has clinical relevance in multiple sclerosis (MS).•Fingolimod has a known efficacy on MRI-defined lesions and whole brain atrophy in MS.•Fingolimod's effect on cerebral gray matter (GM) disease is unknown.•Our findings suggest treatment effect on GM atrophy over 2years.•GM was more sensitive to fingolimod's effects than whole brain atrophy or clinical measures

OptiC: Robust and Automatic Spinal Cord Localization on a Large Variety of MRI Data Using a Distance Transform Based Global Optimization

International audienceLocalizing the center of the spinal cord on MR images is a critical step toward fully automated and robust quantitative analysis, which is essential to achieve clinical utilization. While automatic localization of the spinal cord might appear as a simple task, that has already been addressed extensively, it is much more challenging to achieve this across the large variation in MRI contrasts, field of view, resolutions and pathologies. In this study, we introduce a novel method, called “OptiC”, to automatically and robustly localize the spinal cord on a large variety of MRI data. Starting from a localization map computed by a linear Support Vector Machine trained with Histogram of Oriented Gradient features, the center of the spinal cord is localized by solving an optimization problem, that introduces a trade-off between the localization map and the cord continuity along the superior-inferior axis. The OptiC algorithm features an efficient search (with a linear complexity in the number of voxels) and ensures the global minimum is reached. OptiC was compared to a recently-published method based on the Hough transform using a broad range of MRI data, involving 13 different centers, 3 contrasts (T2-weighted n=278, T1-weighted n=112 and T∗2-weighted n=263), with a total of 441 subjects, including 133 patients with traumatic and neurodegenerative diseases. Overall, OptiC was able to find 98.5% of the gold-standard centerline coverage, with a mean square error of 1.21 mm, suggesting that OptiC could reliably be used for subsequent analyses tasks, such as cord segmentation, opening the door to more robust analysis in patient population