Magnetic Resonance Imaging In Multiple Sclerosis Research Articles

Perceptual super-resolution in multiple sclerosis MRI.

Magnetic resonance imaging (MRI) is crucial for diagnosing and monitoring of multiple sclerosis (MS) as it is used to assess lesions in the brain and spinal cord. However, in real-world clinical settings, MRI scans are often acquired with thick slices, limiting their utility for automated quantitative analyses. This work presents a single-image super-resolution (SR) reconstruction framework that leverages SR convolutional neural networks (CNN) to enhance the through-plane resolution of structural MRI in people with MS (PwMS). Our strategy involves the supervised fine-tuning of CNN architectures, guided by a content loss function that promotes perceptual quality, as well as reconstruction accuracy, to recover high-level image features. Extensive evaluation with MRI data of PwMS shows that our SR strategy leads to more accurate MRI reconstructions than competing methods. Furthermore, it improves lesion segmentation on low-resolution MRI, approaching the performance achievable with high-resolution images. Results demonstrate the potential of our SR framework to facilitate the use of low-resolution retrospective MRI from real-world clinical settings to investigate quantitative image-based biomarkers of MS.

Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis.

Slowly expanding lesions (SELs) are thought to represent a subset of chronic active lesions and have been associated with clinical disability, severity, and disease progression. The purpose of this study was to characterize SELs using advanced magnetic resonance imaging (MRI) measures related to myelin and neurite density on 7Tesla (T) MRI. The study design was retrospective, longitudinal, observational cohort with multiple sclerosis (n=15). Magnetom 7T scanner was used to acquire magnetization-prepared 2 rapid acquisition gradient echo and advanced MRI including visualization of short transverse relaxation time component (ViSTa) for myelin, quantitative magnetization transfer (qMT) for myelin, and neurite orientation dispersion density imaging (NODDI). SELs were defined as lesions showing ≥12% of growth over 12months on serial MRI. Comparisons of quantitative measures in SELs and non-SELs were performed at baseline and over time. Statistical analyses included two-sample t-test, analysis of variance, and mixed-effects linear model for MRI metrics between lesion types. A total of 1075 lesions were evaluated. Two hundred twenty-four lesions (21%) were SELs, and 216 (96%) of the SELs were black holes. At baseline, compared to non-SELs, SELs showed significantly lower ViSTa (1.38vs. 1.53, p<.001) and qMT (2.47vs. 2.97, p<.001) but not in NODDI measures (p>.27). Longitudinally, only ViSTa showed a greater loss when comparing SEL and non-SEL (p=.03). SELs have a lower myelin content relative to non-SELs without a difference in neurite measures. SELs showed a longitudinal decrease in apparent myelin water fraction reflecting greater tissue injury.

Differentiating multiple sclerosis from non-specific white matter changes using a convolutional neural network image classification model

BackgroundThe diagnosis of multiple sclerosis (MS) relies heavily on neuroimaging with magnetic resonance imaging (MRI) and exclusion of mimics. This can be a challenging task due to radiological overlap in several disorders and may require ancillary testing or longitudinal follow up. One of the most common radiological MS mimickers is non-specific white matter disease (NSWMD). We aimed to develop and evaluate models leveraging machine learning algorithms to help distinguish MS and NSWMD. MethodsAll adult patients who underwent MRI brain using a demyelinating protocol with available electronic medical records between 2015 and 2019 at Cleveland Clinic affiliated facilities were included. Diagnosis of MS and NSWMD were assessed from clinical documentation. Those with a diagnosis of MS and NSWMD were matched using total T2 lesion volume (T2LV) and used to train models with logistic regression and convolutional neural networks (CNN). Performance metrices were reported for each model. ResultsA total of 250 NSWMD MRI scans were identified, and 250 unique MS MRI scans were matched on T2LV. Cross validated logistic regression model was able to use 20 variables (including spinal cord area, regional volumes, and fractions) to predict MS compared to NSWMD with 68.0% accuracy while the CNN model was able to classify MS compared to NSWMD in two independent validation and testing cohorts with 77% and 78% accuracy on average. ConclusionAutomated methods can be used to differentiate MS compared to NSWMD. These methods can be used to supplement currently available diagnostic tools for patients being evaluated for MS.

Consensus recommendations on regional interdisciplinary standardization of MRI diagnostics for multiple sclerosis in the metropolitan area of Essen

Magnetic resonance imaging (MRI) is of exceptional importance in the diagnostics and monitoring of multiple sclerosis (MS); however, a close interdisciplinary cooperation between neurologists in private practice, (neuro)radiological practices, hospitals or specialized MS centers is only rarely established. In particular, there is a lack of standardized MRI protocols for image acquisition as well as established quality parameters, which guarantee the comparability of MRI records; however, this is a fundamental prerequisite for an effective application of MRI in the treatment of MS patients, e.g., for making the diagnosis or treatment monitoring. To address these challenges a group of neurologists and (neuro)radiologists developed a consensus proposal for standardization of image acquisition, interpretation and transmission of results and for improvement in interdisciplinary cooperation. This pilot project in the metropolitan area of Essen used a modified Delphi process and was based on the most up to date scientific knowledge. The recommendation takes the medical, economic, temporal and practical aspects of MRI in MS into consideration. The model of interdisciplinary cooperation between radiologists and neurologists with the aim of a regional standardization of MRI could serve as an example for other regions of Germany in order to optimize MRI for MS.

Clinical evaluation of white matter lesions on 3D inversion recovery ultrashort echo time MRI in multiple sclerosis.

We clinically evaluated the quality of white matter lesions (WML) of the cerebrum on 3D inversion recovery ultrashort echo time (IR-UTE) magnetic resonance imaging (MRI) in multiple sclerosis (MS) patients. Forty-nine patients with MS were included in this study. A 3T MRI scanner was used. Two radiologists (readers) evaluated the quality of WML on IR-UTE images using a three-point Likert scale (1-good quality, 2-moderate quality, 3-insufficient quality). They also rated other WML-related factors potentially influencing WML quality using another three-point Likert scale (1-no/minor impact, 2-moderate impact, 3-high impact). Another reader rated the presence of WML on IR-UTE to evaluate the diagnostic value (right/false positive and false negative) of IR-UTE in detecting WML. Signal intensity ratios (SIRs) derived from WML signal intensities and WML sizes were also determined and analyzed. Two hundred and seventy-five MS lesions were evaluated. 87% of the lesions were rated Likert 1 on IR-UTE (P<0.01). WML rated Likert 2 and 3 presented near the grey matter (GM) in 58% of the cases (n=21), with 14 lesions being ≤2 mm (P=0.03). 62.5% of the WML rated Likert 2/3 were in the temporal lobe (P=0.02). The mean SIR of WML on IR-UTE was 1.14±0.22, while the mean SIR on fluid-attenuated inversion recovery (FLAIR) was 6.97±1.88. There was no significant correlation of SIRs between IR-UTE and FLAIR (R=0.14, P=0.245). 92.4% of the WML were correctly detected on IR-UTE (n=254). 19 out of the 21 false positive/negative rated WML were located near the GM or in the temporal lobe. WML presented 7.7% smaller in mean on IR-UTE compared to FLAIR. Factors affecting WML quality with a moderate or high impact (Likert 2 and 3) were not found. Most WML are clearly detectable on IR-UTE sequences. The main limitations are WML in the temporal lobe and near the GM.

Multiple sclerosis imaging in clinical practice: a European-wide survey of 428 centers and conclusions by the ESNR Working Group.

To evaluate compliance with the available recommendations, we assessed the current clinical practice of imaging in the evaluation of multiple sclerosis (MS). An online questionnaire was emailed to all members and affiliates. Information was gathered on applied MR imaging protocols, gadolinium-based contrast agents (GBCA) use and image analysis. We compared the survey results with the Magnetic Resonance Imaging in MS (MAGNIMS) recommendations considered as the reference standard. A total of 428 entries were received from 44 countries. Of these, 82% of responders were neuroradiologists. 55% performed more than ten scans per week for MS imaging. The systematic use of 3T is rare (18%). Over 90% follow specific protocol recommendations with 3D FLAIR, T2-weighted and DWI being the most frequently used sequences. Over 50% use SWI at initial diagnosis and 3D gradient-echo T1-weighted imaging is the most used MRI sequence for pre- and post-contrast imaging. Mismatches with recommendations were identified including the use of only one sagittal T2-weighted sequence for spinal cord imaging, the systematic use of GBCA at follow-up (over 30% of institutions), a delay time shorter than 5min after GBCA administration (25%) and an inadequate follow-up duration in pediatric acute disseminated encephalomyelitis (80%). There is scarce use of automated software to compare images or to assess atrophy (13% and 7%). The proportions do not differ significantly between academic and non-academic institutions. While current practice in MS imaging is rather homogeneous across Europe, our survey suggests that recommendations are only partially followed. Hurdles were identified, mainly in the areas of GBCA use, spinal cord imaging, underuse of specific MRI sequences and monitoring strategies. This work will help radiologists to identify the mismatches between their own practices and the recommendations and act upon them. • While current practice in MS imaging is rather homogeneous across Europe, our survey suggests that available recommendations are only partially followed. • Several hurdles have been identified through the survey that mainly lies in the areas of GBCA use, spinal cord imaging, underuse of specific MRI sequences and monitoring strategies.

Image Segmentation with Priority Based Apposite Feature Extraction Model for Detection of Multiple Sclerosis in MR Images Using Deep Learning Technique

Multiple Sclerosis (MS) is a degenerative neurological disease caused by damage to the central nervous system's axons and myelin sheaths. MS lesions alter shape, position, and size over time in patients, therefore radiologists must be vigilant in detecting and evaluating MS lesions appropriately. Magnetic resonance imaging (MRI) has gotten a lot of attention from doctors for diagnosing MS, but there are other ways as well. The information provided by MRI modalities to doctors about the brain's anatomy and function is critical for making an MS diagnosis quickly. For automatic extraction of MS lesions from three-dimensional (3D) MR images, this work introduces a new feature selection approach. The approach described here can be used to treat a variety of MS lesions. MS MRI diagnosis takes a long time, is difficult, and is prone to human mistake. The design of a Computer-Aided Diagnosis System (CADS) based on Artificial Intelligence (AI) to diagnose MS incorporates standard machine learning and deep learning approaches. Traditional machine learning uses trial and error to extract, select, and classify features. Deep learning, on the other hand, uses deep layers with values that are automatically learned. In this research work, a Priority based Apposite Feature Extraction Model with Image Segmentation (PAFEM-IS) is proposed for segmentation and feature extraction. With proposed method, a large number of image attributes can be learned with little effort and bias on the part of the user. Apart from that, by using unlabelled data for feature learning, the classifier training can benefit from the significantly larger amount of generally available unlabelled data. The proposed model is compared with the traditional models and the proposed model exhibits better performance levels.

Uncertainty-Aware and Lesion-Specific Image Synthesis in Multiple Sclerosis Magnetic Resonance Imaging: A Multicentric Validation Study.

Generative adversarial networks (GANs) can synthesize high-contrast MRI from lower-contrast input. Targeted translation of parenchymal lesions in multiple sclerosis (MS), as well as visualization of model confidence further augment their utility, provided that the GAN generalizes reliably across different scanners. We here investigate the generalizability of a refined GAN for synthesizing high-contrast double inversion recovery (DIR) images and propose the use of uncertainty maps to further enhance its clinical utility and trustworthiness. A GAN was trained to synthesize DIR from input fluid-attenuated inversion recovery (FLAIR) and T1w of 50 MS patients (training data). In another 50 patients (test data), two blinded readers (R1 and R2) independently quantified lesions in synthetic DIR (synthDIR), acquired DIR (trueDIR) and FLAIR. Of the 50 test patients, 20 were acquired on the same scanner as training data (internal data), while 30 were scanned at different scanners with heterogeneous field strengths and protocols (external data). Lesion-to-Background ratios (LBR) for MS-lesions vs. normal appearing white matter, as well as image quality parameters were calculated. Uncertainty maps were generated to visualize model confidence. Significantly more MS-specific lesions were found in synthDIR compared to FLAIR (R1: 26.7 ± 2.6 vs. 22.5 ± 2.2 p < 0.0001; R2: 22.8 ± 2.2 vs. 19.9 ± 2.0, p = 0.0005). While trueDIR remained superior to synthDIR in R1 [28.6 ± 2.9 vs. 26.7 ± 2.6 (p = 0.0021)], both sequences showed comparable lesion conspicuity in R2 [23.3 ± 2.4 vs. 22.8 ± 2.2 (p = 0.98)]. Importantly, improvements in lesion counts were similar in internal and external data. Measurements of LBR confirmed that lesion-focused GAN training significantly improved lesion conspicuity. The use of uncertainty maps furthermore helped discriminate between MS lesions and artifacts. In conclusion, this multicentric study confirms the external validity of a lesion-focused Deep-Learning tool aimed at MS imaging. When implemented, uncertainty maps are promising to increase the trustworthiness of synthetic MRI.

Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions

Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS.We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field.This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.

Impact of comorbid post traumatic stress disorder on multiple sclerosis in military veterans: A population-based cohort study

Background: Very little is known regarding the impact of post traumatic stress disorder (PTSD) on the course of multiple sclerosis (MS). Objectives: To explore the impact of pre-existing PTSD on MS relapses, magnetic resonance imaging (MRI) activity, and disability in a large population-based cohort. Methods: Military Veterans with MS and PTSD prior to symptom onset (MSPTSD, n = 96) were identified using the Department of Veterans Affairs MS databases. MSPTSD cases were matched to MS controls without PTSD (n = 95). Number of relapses, number of new T2 lesions and new gadolinium lesions on brain MRI, and neurological disability were abstracted between 2015 and 2019. Results: The mean annualized relapse rate was greater in the MSPTSD group versus controls (0.23 vs 0.06, respectively; p < 0.05), as was the annualized mean number of new T2 and gadolinium-enhancing lesions on brain MRI (0.52 vs 0.16 and 0.29 vs 0.08, respectively; p < 0.05). Disability accrual (time to Disability Status Scale 6.0) was more rapid (23.7 vs 29.5 years, p < 0.05) in relapsing MS patients with PTSD. Conclusion: Patients with MSPTSD have higher disease activity and reach disability endpoints more rapidly than controls. This is the first study to show PTSD as a potentially modifiable risk factor for MS relapses, MRI activity, and disability.

Central vein sign: A putative diagnostic marker for multiple sclerosis.

The presence of a "central vein sign" (CVS) has been introduced as a biomarker for the diagnosis of multiple sclerosis (MS) and shown to have the ability to accurately differentiate MS from other white matter diseases (MS mimics). Following the development of susceptibility-based magnetic resonance venography that allowed the in vivo detection of CVS, a standard CVS definition was established by introducing the "40% rule" that assesses the number of MS lesions with CVS as a fraction of the total number of lesions to differentiate MS lesions from other types of lesions. The "50% rule," the "three-lesion criteria," and the "six-lesion criteria" were later introduced and defined. Each of these rules had high levels of sensitivity, specificity, and accuracy in differentiating MS from other diseases, which has been recognized by the Magnetic Resonance Imaging in MS (MAGNIMS) group and the Consortium of MS Centers task force. The North American Imaging in Multiple Sclerosis Cooperative even provided statements and recommendations aiming to refine, standardize and evaluate the CVS in MS. Herein, we review the existing literature on CVS and evaluate its added value in the diagnosis of MS and usefulness in differentiating it from other vasculopathies. We also review the histopathology of CVS and identify available automated CVS assessment methods as well as define the role of vascular comorbidities in the diagnosis of MS.

P.048 International MAGNIMS-CMSC-NAIMS consensus recommendations on the use of standardized MRI in MS

Background: Standardized magnetic resonance imaging (MRI) guidelines published in 2015 by the Europoean MAGNIMS group and in 2016 by the CMSC are important for the diagnosis and monitoring of patients with multiple sclerosis (MS) and for the appropriate use of MRI in routine clinical practice. Methods: Two panels of experts convened to update existing guidelines for a standardized MRI protocol. The MAGNIMS panel convened in Graz, Austria in April 2019. The CMSC NAIMS panel met separately and independently in Newark, USA in October 2019. Subsequently, the MAGNIMS, NAIMS, and CMSC working groups combined their efforts to reach an international consensus Results: The revised guidelines on MRI in MS merges recommendations from MAGNIMS, CMSC, and NAIMS to improve the use of MRI for diagnosis, prognosis and monitoring of individuals with MS. 3D acquisitions are emphasized for optimal comparison over time. Core brain sequences include a 3D-T2wFLAIR for lesion identification and monitoring treatment effectiveness. Gadolinium-based contrast is recommended for diagnostic studies and judicious use for routine monitoring of MS patients. DWI sequences are recommended for PML safety monitoring. Conclusions: The international consensus guidelines strive for global acceptance of a useful and usable standard of care for patients with MS.

A Novel Digital Care Management Platform to Monitor Clinical and Subclinical Disease Activity in Multiple Sclerosis.

In multiple sclerosis (MS), the early detection of disease activity or progression is key to inform treatment changes and could be supported by digital tools. We present a novel CE-marked and FDA-cleared digital care management platform consisting of (1) a patient phone/web application and healthcare professional portal (icompanion) including validated symptom, disability, cognition, and fatigue patient-reported outcomes; and (2) clinical brain magnetic resonance imaging (MRI) quantifications (icobrain ms). We validate both tools using their ability to detect (sub)clinical disease activity (known-groups validity) and real-world data insights. Surveys showed that 95.6% of people with MS (PwMS) were interested in using an MS app, and 98.2% were interested in knowing about MRI changes. The icompanion measures of disability (p < 0.001) and symptoms (p = 0.005) and icobrain ms MRI parameters were sensitive to (sub)clinical differences between MS subtypes. icobrain ms also decreased intra- and inter-rater lesion count variability and increased sensitivity for detecting disease activity/progression from 24% to 76% compared to standard radiological reading. This evidence shows PwMS’ interest, the digital care platform’s potential to improve the detection of (sub)clinical disease activity and care management, and the feasibility of linking different digital tools into one overarching MS care pathway.

Resonancia Magnética en Esclerosis Múltiple: un repaso de los principios básicos de imagenología y guías prácticas de uso

Resumen La imagenología por resonancia magnética (IRM), representa una ventana in vivo de la fisiopatología de la esclerosis múltiple (EM) y nos ha llevado a considerarla como una herramienta clave para el diagnóstico, manejo y toma de decisiones al iniciar o cambiar fármacos modificadores de la enfermedad (FARME). Resulta esencial estar familiarizado con las técnicas de imagen y los protocolos recomendados que pueden mejorar la detección de la actividad para poder proveer del mejor manejo posible1-2. Muchas veces existe un desacoplamiento entre clínicos y radiólogos en cuanto a los requisitos solicitados al ordenar un estudio de imagen, lo cual se puede traducir en un subóptimo manejo. Esto puede suceder por mala comunicación, desconocimiento de técnicas imagenológicas por parte de los clínicos o, por otra parte, porque los radiólogos muchas veces no son conscientes de la importancia que pueden tener las características específicas de IRM en el proceso de toma de decisiones del neurólogo tratante. De ahí la importancia de los protocolos estandarizados de resonancia magnética para que los médicos y radiólogos se familiaricen con ellos, a fin de mejorar la calidad de la imagen, la detección de lesiones y el informe radiológico. Esta revisión resume los principios básicos de la IRM en EM y compara las recomendaciones relevantes del Consorcio de Centros de EM (CMSC) y el consenso europeo de imagenología por resonancia magnética (MAGNIMS); presentando la información de una manera simple y profesional, fácil de seguir por expertos y no expertos en el campo. Palabras clave: imágenes de resonancia magnética en la red de esclerosis múltiple, imágenes de resonancia magnética, esclerosis múltiple

LesionQuant for Assessment of MRI in Multiple Sclerosis-A Promising Supplement to the Visual Scan Inspection.

Background and Goals: Multiple sclerosis (MS) is a central nervous system inflammatory disease where magnetic resonance imaging (MRI) is an important tool for diagnosis and disease monitoring. Quantitative measurements of lesion volume, lesion count, distribution of lesions, and brain atrophy have a potentially significant value for evaluating disease progression. We hypothesize that utilizing software designed for evaluating MRI data in MS will provide more accurate and detailed analyses compared to the visual neuro-radiological evaluation.Methods: A group of 56 MS patients (mean age 35 years, 70% females and 96% relapsing-remitting MS) was examined with brain MRI one and 5 years after diagnosis. The T1 and FLAIR brain MRI sequences for all patients were analyzed using the LesionQuant (LQ) software. These data were compared with data from structured visual evaluations of the MRI scans performed by neuro-radiologists, including assessments of atrophy, and lesion count. The data from LQ were also compared with data from other validated research methods for brain segmentation, including assessments of whole brain volume and lesion volume. Correlations with clinical tests like the timed 25-foot walk test (T25FT) were performed to explore additional value of LQ analyses.Results: Lesion count assessments by LQ and by the neuro-radiologist were significantly correlated one year (cor = 0.92, p = 2.2 × 10−16) and 5 years (cor = 0.84, p = 2.7 × 10−16) after diagnosis. Analyzes of the intra- and interrater variability also correlated significantly (cor = 0.96, p < 0.001, cor = 0.97, p < 0.001). Significant positive correlation was found between lesion volume measured by LQ and by the software Cascade (cor = 0.7, p < 0.001. LQ detected a reduction in whole brain percentile >10 in 10 patients across the time-points, whereas the neuro-radiologist assessment identified six of these. The neuro-radiologist additionally identified five patients with increased atrophy in the follow-up period, all of them displayed decreasing low whole brain percentiles (median 11, range 8–28) in the LQ analysis. Significant positive correlation was identified between lesion volume measured by LQ and test performance on the T25FT both at 1 and 5 years after diagnosis.Conclusion: For the number of MS lesions at both time-points, we demonstrated strong correlations between the assessments done by LQ and the neuro-radiologist. Lesion volume evaluated with LQ correlated with T25FT performance. LQ-analyses classified more patients to have brain atrophy than the visual neuro-radiological evaluation. In conclusion, LQ seems like a promising supplement to the evaluation performed by neuro-radiologists, providing an automated tool for evaluating lesions in MS patients and also detecting early signs of atrophy in both a longitudinal and cross-sectional setting.

P.285 Association of whole-brain perfusion and major depressive disorder diagnosis and severity measured by arterial spin labelling

Multiple sclerosis (MS) is a central nervous system disorder that may eventually affect its function. The clinical standard for MS severity is based on a clinical scale, which lacks lesion specific information. Magnetic resonance imaging of MS faces the challenge of myelin specificity, and in this work a new method inhomogeneous magnetization transfer (ihMT) is investigated as new biomarker of demyelination in MS.Local ethics committee approved this study and written informed consents were obtained. Between Oct 2017 to May 2018, eighteen patients with relapsing-remitting MS (RRMS) (6 males, 12 females, mean age 31.2) and sixteen healthy volunteers (6 males, 10 females, mean age 30.4 years) were enrolled in this prospective study. All subjects underwent MRI exams including MT and ihMT imaging as well as the Expanded Disability Status Scale (EDSS) assessments. Independent sample t-test were used to compare the difference of ihMT parameters between healthy white matter (HWM) and normal appearing white matter (NAWM) and between HWM and MS lesions, respectively. Spearman correlation were used to analyze the correlation between ihMT parameters of MS lesions and EDSS score.The ihMTR and qihMT demonstrate significant differences between WHM and NAWM groups, while no significant differences are observed for MTR and qMT. All parameters show significant differences between HWM and MS groups (p < 0.05). There was moderate negative correlation between MTR, qMT and EDSS score (−0.440 and −0.572), while there was a strong negative correlation between ihMTR and qihMT and EDSS score (−0.704 and −0.739).Based on whole brain analysis at 3.0 T, ihMT showed better correlation with EDSS compared to magnetization transfer imaging, and may be a potentially valuable biomarker for demyelination in MS.

Cerebrospinal Fluid IgM Levels in Association With Inflammatory Pathways in Multiple Sclerosis Patients

BackgroundIntrathecal immunoglobulin M (IgM) synthesis has been demonstrated in the early disease stages of multiple sclerosis (MS) as a predictor factor of a worsening disease course. Similarly, increased cerebrospinal fluid (CSF) molecules related to B-cell intrathecal activity have been associated with a more severe MS progression. However, whether CSF levels of IgM are linked to specific inflammatory and clinical profile in MS patients at the time of diagnosis remains to be elucidated.MethodsUsing customized Bio-Plex assay, the protein levels of IgG, IgA, IgM, and of 34 other inflammatory molecules, related to B-cell, T-cell, and monocyte/macrophage activity, were analyzed in the CSF of 103 newly diagnosed relapsing–remitting MS patients and 36 patients with other neurological disorders. CSF IgM levels were also correlated with clinical and neuroradiological measures [advanced 3-T magnetic resonance imaging (MRI) parameters], at diagnosis and after 2 years of follow-up.ResultsA 45.6% increase in CSF IgM levels was found in MS patients compared to controls (p = 0.013). CSF IgM levels correlated with higher CSF levels of CXCL13 (p = 0.039), CCL21 (p = 0.023), interleukin 10 (IL-10) (p = 0.025), IL-12p70 (p = 0.020), CX3CL1 (p = 0.036), and CHI3L1 (p = 0.048) and were associated with earlier age of patients at diagnosis (p = 0.008), white matter lesion (WML) number (p = 0.039) and disease activity (p = 0.033) after 2 years of follow-up.ConclusionIgMs are the immunoglobulins mostly expressed in the CSF of naive MS patients compared to other neurological conditions at the time of diagnosis. The association between increased CSF IgM levels and molecules related to both B-cell immunity (IL-10) and recruitment (CXCL13 and CCL21) and to macrophage/microglia activity (IL-12p70, CX3CL1, and CHI3L1) suggests possible correlation between humoral and innate intrathecal immunity in early disease stage. Furthermore, the association of IgM levels with WMLs and MS clinical and MRI activity after 2 years supports the idea of key role of IgM in the disease course.

An International Standardized Magnetic Resonance Imaging Protocol for Diagnosis and Follow-up of Patients with Multiple Sclerosis: Advocacy, Dissemination, and Implementation Strategies.

Standardized magnetic resonance imaging (MRI) protocols are important for the diagnosis and monitoring of patients with multiple sclerosis (MS). The Consortium of Multiple Sclerosis Centers (CMSC) convened an international panel of MRI experts to review and update the current guidelines. The objective was to update the standardized MRI protocol and clinical guidelines for diagnosis and follow-up of MS and develop strategies for advocacy, dissemination, and implementation. Conference attendees included neurologists, radiologists, technologists, and imaging scientists with expertise in MS. Representatives from the CMSC, Magnetic Resonance Imaging in MS (MAGNIMS), North American Imaging in Multiple Sclerosis Cooperative, US Department of Veteran Affairs, National Multiple Sclerosis Society, Multiple Sclerosis Association of America, MRI manufacturers, and commercial image analysis companies were present. Before the meeting, CMSC members were surveyed about standardized MRI protocols, gadolinium use, need for diffusion-weighted imaging, and the central vein sign. The panel worked to make the CMSC and MAGNIMS MRI protocols similar so that the updated guidelines could ultimately be accepted by international consensus. Advocacy efforts will promote the importance of standardized MS MRI protocols. Dissemination will include publications, meeting abstracts, educational programming, webinars, "meet the expert" teleconferences, and examination cards. Implementation will require comprehensive and coordinated efforts to make the protocol easy to access and use. The ultimate vision, and goal, is for the guidelines to be universally useful, usable, and used as the standard of care for patients with MS.

Structured Reporting in Multiple Sclerosis Reduces Interpretation Time

Previous studies have reported mixed results regarding whether the use of structured reporting (SR) leads to a change in interpretation times. The objective of this study was to quantify any change in interpretation times after the implementation of SR for multiple sclerosis (MS) follow-up magnetic resonance imaging (MRI) of the brain. Interpretation times before and after the transition to MS MRI SR were compared over a 5-year period. To control for changing practice patterns, a control group of non-MS (intracranial masses) reports not using SR was also assessed. In a secondary analysis, interpretation times for 2D and 3D MRI MS protocols after the initiation of SR were compared to determine whether increased image number with the 3D protocol affected interpretation times. Mean and median interpretation times before the initiation of SR for MS MRI were 11.0 and 8.0 minutes versus 8.5 and 6.0 minutes after the implementation of SR (p < 0.001). Although non-MS MRI interpretation times also decreased, an interaction analysis demonstrated that the decrease in MS interpretation times was significantly higher (p < 0.001). Mean and median interpretation times using 3D protocols were slighter increased compared to interpretation times with 2D protocols (p = 0.036). After the implementation of SR for MS follow-up MRI at our institution, interpretation times significantly decreased despite the increased number of images with some of the examinations due to the adoption of 3D protocols. The adoption of SR for MS MRI follow-up scans may improve radiologist efficiency.

Prediction of on-treatment disability worsening in RRMS with the MAGNIMS score

Background: The magnetic resonance imaging in multiple sclerosis (MAGNIMS) score combines relapses and magnetic resonance imaging (MRI) lesions to predict disability outcomes in relapsing–remitting multiple sclerosis (RRMS) treated with interferon-β. Objective: To validate the MAGNIMS score and extend to other disease-modifying therapies (DMTs). To examine the prognostic value of gadolinium contrast-enhancing (Gd+) lesions. Methods: This RRMS MSBase cohort study (n = 2293) used a Cox model to examine the prognostic value of relapses, MRI activity and the MAGNIMS score for disability worsening during treatment with interferon-β and three other DMTs. Results: Three new T2 lesions (hazard ratio (HR) = 1.60, p = 0.028) or two relapses (HR = 2.24, p = 0.002) on interferon-β (for 12 months) were predictive of disability worsening over 4 years. MAGNIMS score = 2 (1 relapse and ⩾3 T2 lesions or ⩾2 relapses) was associated with a greater risk of disability worsening on interferon-β (HR = 2.0, p = 0.001). In pooled cohort of four DMTs, similar associations were seen (MAGNIMS score = 2: HR = 1.72, p = 0.001). Secondary analyses demonstrated that the addition of Gd+ to the MAGNIMS did not materially improve its prediction of disability worsening. Conclusion: We have validated the MAGNIMS score in RRMS and extended its application to three other DMTs: 1 relapse and ⩾3 T2 lesions or ⩾2 relapses predicted worsening of disability. Contrast-enhancing lesions did not substantially improve the prognostic score.