Resonance Imaging In Multiple Sclerosis Research Articles

2.5D transfer deep learning model for segmentation of contrast-enhancing lesions on brain magnetic resonance imaging of multiple sclerosis and neuromyelitis optica spectrum disorder.

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are the two mimic autoimmune diseases of the central nervous system, which are rare in East Asia. Quantitative detection of contrast-enhancing lesions (CELs) on contrast-enhancing T1-weighted magnetic resonance (MR) images is of great significance for assessing the disease activity of MS and NMOSD. However, it is challenging to develop automatic segmentation algorithms due to the lack of data. In this work, we present an automatic segmentation model of CELs based on Fully Convolutional with Attention DenseNet (FCA-DenseNet) and transfer learning strategy to address the challenge of CEL quantification in small-scale datasets. A transfer learning approach was employed in this study, whereby pretraining was conducted using 77 MS subjects from the open access datasets (MICCAI 2016, MICCAI 2017, ISBI 2015) for white matter hyperintensity segmentation, followed by fine-tuning using 24 MS and NMOSD subjects from the local dataset for CEL segmentation. The proposed FCA-DenseNet combined the Fully Convolutional DenseNet and Convolutional Block Attention Module in order to improve the learning capability. A 2.5D data slicing strategy was used to process complex 3D MR images. U-Net, ResUNet, TransUNet, and Attention-UNet are used as comparison models to FCA-DenseNet. Dice similarity coefficient (DSC), positive predictive value (PPV), true positive rate (TPR), and volume difference (VD) are used as evaluation metrics to evaluate the performances of different models. FCA-DenseNet outperforms all other models in terms of all evaluation metrics, with a DSC of 0.661±0.187, PPV of 0.719±0.201, TPR of 0.680±0.254, and VD of 0.388±0.334. Transfer learning strategy has achieved success in building segmentation models on a small-scale local dataset where traditional deep learning approaches fail to train effectively. The improved FCA-DenseNet, combined with transfer learning strategy and 2.5D data slicing strategy, has successfully addressed the challenges in constructing deep learning models on small-scale datasets, making it conducive to clinical quantification of brain CELs and diagnosis of MS and NMOSD.

A Real-World Experience of Azathioprine Versus First-Line Disease-Modifying Therapy in Relapsing-Remitting Multiple Sclerosis-A Prospective Cohort Study.

Azathioprine (AZA) has demonstrated efficacy in multiple randomized control trials (RCTs) for Relapsing-Remitting Multiple Sclerosis (RRMS). However, we still need comparative real-world data with other first-line disease-modifying therapies (DMTs). We aimed to assess AZA's effectiveness regarding relapses, disability progression, time to the first relapse, magnetic resonance imaging (MRI) activity, and safety compared with other approved first-line DMTs in an Indian population in a real-world setting. We conducted a single-center prospective study of treatment-naive RRMS patients between 2017 and 2019. We evaluated the effects of AZA and other approved DMTs on clinical and radiological measures. Among 192 eligible patients (F:M ratio 2.84:1), 68 patients (35.4%) were on AZA, 68 patients (35.4%) were on dimethyl fumarate (DMF), 32 patients (16.7%) on interferon (IFN beta-1a), and 16 patients (8.3%) on teriflunomide (TFL). Four treatment groups were comparable: AZA v/s DMF v/s TFL v/s IFN beta-1a. In primary outcomes, there was no significant difference between the groups in terms of change in the Expanded Disability Status Scale (EDSS) score at three months (p-value = 0.169), six months (p-value = 0.303), 12 months (p-value = 0.082), and 24 months (p-value = 0.639), the number of relapses (p-value = 0.229), and time to the first relapse (p-value > 0.05 in all groups). In the secondary outcome, there was no significant difference between the treatment groups on serial MRI parameters used according to "Magnetic Resonance Imaging in Multiple Sclerosis" (MAGNIMS) 2016 criteria (p-value > 0.05). In safety outcomes, leukopenia was significantly more common in the AZA group (p-value = 0.025), flu-like symptoms (p-value = 0.0001), and injection site reactions (p-value = 0.035) were significantly more common in the IFN beta-1a group. Our study suggests AZA is as effective as other approved DMTs and a good alternative as a first-line treatment for multiple sclerosis's clinical and radiological activity in real-world settings on short follow-up. Based on these results, more randomized controlled trials of AZA v/s DMF or other DMTs are needed for more robust outcomes.

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.

Understanding the Pathophysiology and Magnetic Resonance Imaging of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders.

Magnetic resonance imaging (MRI) has been extensively applied in the study of multiple sclerosis (MS), substantially contributing to diagnosis, differential diagnosis, and disease monitoring. MRI studies have significantly contributed to the understanding of MS through the characterization of typical radiological features and their clinical or prognostic implications using conventional MRI pulse sequences and further with the application of advanced imaging techniques sensitive to microstructural damage. Interpretation of results has often been validated by MRI-pathology studies. However, the application of MRI techniques in the study of neuromyelitis optica spectrum disorders (NMOSD) remains an emerging field, and MRI studies have focused on radiological correlates of NMOSD and its pathophysiology to aid in diagnosis, improve monitoring, and identify relevant prognostic factors. In this review, we discuss the main contributions of MRI to the understanding of MS and NMOSD, focusing on the most novel discoveries to clarify differences in the pathophysiology of focal inflammation initiation and perpetuation, involvement of normal-appearing tissue, potential entry routes of pathogenic elements into the CNS, and existence of primary or secondary mechanisms of neurodegeneration.

Understanding Magnetic Resonance Imaging in Multiple Sclerosis (UMIMS): Development and Piloting of an Online Education Program About Magnetic Resonance Imaging for People With Multiple Sclerosis.

BackgroundPeople with multiple sclerosis (pwMS) lack sufficient magnetic resonance imaging (MRI) knowledge to truly participate in frequently occurring MRI-related therapy decisions. An evidence-based patient information (EBPI) about MRI is currently lacking.ObjectiveThe aim of this study was to develop an evidence-based online education program about limitations and benefits of MRI for pwMS. Ultimately, our goal was to improve MRI risk-knowledge, empower pwMS, and promote shared decision-making.MethodsThe program's contents were based on literature research and a previous pilot study. It was revised following 2 evaluation rounds with pwMS, MRI experts and expert patients. In a pilot study, n = 92 pwMS received access to the program for 4 weeks. User experiences and acceptance, MRI knowledge (MRI-RIKNO 2.0 questionnaire) and emotions and attitudes toward MRI (MRI-EMA questionnaire) were assessed. Results were compared to a previous survey population of n = 508 pwMS without access to the program.ResultsParticipants rated the program as easy to understand, interesting, relevant, recommendable, and encouraging. In comparison to pwMS without access to the program, MRI risk-knowledge and perceived MRI competence were higher.ConclusionSatisfaction with the program and good MRI-risk knowledge after usage demonstrates the need and applicability of EBPI about MRI in MS.

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.

New Prospects for Ultra-High-Field Magnetic Resonance Imaging in Multiple Sclerosis.

There is growing interest in imaging multiple sclerosis (MS) through the ultra-high-field (UHF) lens, which currently means a static magnetic field strength of 7 T or higher. Because of higher signal-to-noise ratio and enhanced susceptibility effects, UHF magnetic resonance imaging improves conspicuity of MS pathological hallmarks, among them cortical demyelination and the central vein sign. This could, in turn, improve confidence in MS diagnosis and might also facilitate therapeutic monitoring of MS patients. Furthermore, UHF imaging offers unique insight into iron-related pathology, leptomeningeal inflammation, and spinal cord pathologies in neuroinflammation. Yet, limitations such as the longer scanning times to achieve improved resolution and incipient safety data on implanted medical devices need to be considered. In this review, we discuss applications of UHF imaging in MS, its advantages and limitations, and practical aspects of UHF in the clinical setting.

Signal quality as Achilles\u2019 heel of graph theory in functional magnetic resonance imaging in multiple sclerosis

Graph-theoretical analysis is a novel tool to understand the organisation of the brain.We assessed whether altered graph theoretical parameters, as observed in multiple sclerosis (MS), reflect pathology-induced restructuring of the brain's functioning or result from a reduced signal quality in functional MRI (fMRI). In a cohort of 49 people with MS and a matched group of 25 healthy subjects (HS), we performed a cognitive evaluation and acquired fMRI. From the fMRI measurement, Pearson correlation-based networks were calculated and graph theoretical parameters reflecting global and local brain organisation were obtained. Additionally, we assessed metrics of scanning quality (signal to noise ratio (SNR)) and fMRI signal quality (temporal SNR and contrast to noise ratio (CNR)). In accordance with the literature, we found that the network parameters were altered in MS compared to HS. However, no significant link was found with cognition. Scanning quality (SNR) did not differ between both cohorts. In contrast, measures of fMRI signal quality were significantly different and explained the observed differences in GTA parameters. Our results suggest that differences in network parameters between MS and HS in fMRI do not reflect a functional reorganisation of the brain, but rather occur due to reduced fMRI signal quality.

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla.

The overall goal of this article is to demonstrate a state-of-the-art ultrahigh field (UHF) magnetic resonance (MR) protocol of the brain at 7.0 Tesla in multiple sclerosis (MS) patients. MS is a chronic inflammatory, demyelinating, neurodegenerative disease that is characterized by white and gray matter lesions. Detection of spatially and temporally disseminated T2-hyperintense lesions by the use of MRI at 1.5 T and 3 T represents a crucial diagnostic tool in clinical practice to establish accurate diagnosis of MS based on the current version of the 2017 McDonald criteria. However, the differentiation of MS lesions from brain white matter lesions of other origins can sometimes be challenging due to their resembling morphology at lower magnetic field strengths (typically 3 T). Ultrahigh field MR (UHF-MR) benefits from increased signal-to-noise ratio and enhanced spatial resolution, both key to superior imaging for more accurate and definitive diagnoses of subtle lesions. Hence, MRI at 7.0 T has shown encouraging results to overcome the challenges of MS differential diagnosis by providing MS-specific neuroimaging markers (e.g., central vein sign, hypointense rim structures and differentiation of MS grey matter lesions). These markers and others can be identified by other MR contrasts other than T1 and T2 (T2*, phase, diffusion) and substantially improve the differentiation of MS lesions from those occurring in other neuroinflammatory conditions such as neuromyelitis optica and Susac syndrome. In this article, we describe our current technical approach to study cerebral white and grey matter lesions in MS patients at 7.0 T using different MR acquisition methods. The up-to-date protocol includes the preparation of the MR setup including the radio-frequency coils customized for UHF-MR, standardized screening, safety and interview procedures with MS patients, patient positioning in the MR scanner and acquisition of dedicated brain scans tailored for examining MS.

Simultaneous lesion and brain segmentation in multiple sclerosis using deep neural networks

Segmentation of white matter lesions and deep grey matter structures is an important task in the quantification of magnetic resonance imaging in multiple sclerosis. In this paper we explore segmentation solutions based on convolutional neural networks (CNNs) for providing fast, reliable segmentations of lesions and grey-matter structures in multi-modal MR imaging, and the performance of these methods when applied to out-of-centre data. We trained two state-of-the-art fully convolutional CNN architectures on the 2016 MSSEG training dataset, which was annotated by seven independent human raters: a reference implementation of a 3D Unet, and a more recently proposed 3D-to-2D architecture (DeepSCAN). We then retrained those methods on a larger dataset from a single centre, with and without labels for other brain structures. We quantified changes in performance owing to dataset shift, and changes in performance by adding the additional brain-structure labels. We also compared performance with freely available reference methods. Both fully-convolutional CNN methods substantially outperform other approaches in the literature when trained and evaluated in cross-validation on the MSSEG dataset, showing agreement with human raters in the range of human inter-rater variability. Both architectures showed drops in performance when trained on single-centre data and tested on the MSSEG dataset. When trained with the addition of weak anatomical labels derived from Freesurfer, the performance of the 3D Unet degraded, while the performance of the DeepSCAN net improved. Overall, the DeepSCAN network predicting both lesion and anatomical labels was the best-performing network examined.

Comparison of Gadovist and Magnevist in brain Magnetic resonance imaging of multiple sclerosis patients with an acute attack

Objective: The use of an appropriate contrast agent performs a major role in brain magnetic resonance imaging (MRI) of multiple sclerosis (MS) patients. The present study aimed to make a comparison between the diagnostic values of Gadovist and Magnevist considering the successive imaging times in contrast-enhanced brain MRI of MS patients. Materials and Methods: A total of 62 relapsing-remitting MS patients (56 females, mean age of 31 years) were enrolled in the present study. All of them underwent two sessions of standard contrast-enhanced brain MRI upon enrollment and 48 h later. The participants were randomly assigned to each contrast agent. T1-weighted (T1W) images were taken 30 sec, as well as 5, 10, 15, and 30 min after the contrast injection. For all of the images, two neuro-radiologists who were blinded to the contrast type counted the number of plaques in the brain. In addition, for the enhanced plaques larger than 10 mm, the signal intensity (SI) was determined using its region of interest. Results: The mean plaque number significantly increased from 30 sec to 15 min for both contrasts separately (P<0.001). Nonetheless, the slight increases in the mean plaque number from 15-30 min for both Gadovist and Magnevist were not statistically significant (both P-Values>0.25). The mean plaque number in the Gadovist group was higher, compared to that in the Magnevist group at both 15 and 30 min, and the differences were statistically on the borderline (both P-Values=0.07). The mean SI of enhanced plaques gradually increased in the course of imaging in both contrast groups. Except for 30 sec, in all other time sessions, the mean SI was higher in Gadovist-enhanced MR images, compared to Magnevist-enhanced MR images (P<0.01). Conclusion: As evidenced by the obtained results, Gadovist showed a relatively better diagnostic value for brain MRI of MS patients. Furthermore, the findings suggested that it is cost-effective to take MRI only up to 15 min (instead of 30 min) after contrast injection in both agents.

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

Assessing the effect of an evidence-based patient online educational tool for people with multiple sclerosis called UMIMS\u2014understanding magnetic resonance imaging in multiple sclerosis: study protocol for a double-blind, randomized controlled trial

BackgroundWhile magnetic resonance imaging (MRI) plays a major role in the lives of people with multiple sclerosis (pwMS), studies have shown that MRI-specific knowledge in pwMS is limited. Moreover, poor knowledge was associated with negative feelings towards MRI (e.g. anxiety concerning MRI scan). Because information sources about MRI in MS for pwMS are not available, we designed and evaluated an evidence-based online educational platform about MRI in MS called “Understanding MRI in MS” (UMIMS). Based on a pilot study in n= 79 subjects, an educational intervention was found to be feasible and effective. We hypothesize that MRI-specific knowledge can be increased by using UMIMS and that, subsequently, negative feelings towards MRI will be reduced and shared decision-making competences increased.MethodsThis randomized, controlled, double-blinded trial (RCT) will recruit n = 120 pwMS. The intervention group will receive access to UMIMS. The control group will get access to a specifically developed control website, which visually imitates UMIMS and contains the standard information available by several MS self-help organizations. The change in MRI-specific knowledge assessed via the MRI-risk knowledge questionnaire (MRI-RIKNO) after the intervention is the primary endpoint at 2 weeks. Several secondary endpoints will be assessed at different timepoints throughout the study, e.g. emotions towards MRI, autonomy preferences, threat by MS and shared decision-making competences. The study includes a process evaluation.DiscussionThe aim of this RCT is to prove that access to an education tool on MRI in MS will increase pwMS’ MRI-specific knowledge and enhance shared decision-making when discussing decisions involving MRI results during patient-physician encounters.Trial registrationClinicaltrials.gov NCT03872583. Registered on 13 March 2019.

Magnetic resonance imaging of multiple sclerosis

Magnetic resonance imaging of multiple sclerosis

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.

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.

Robustness of Simultaneous Lesion and Neuroanatomy Segmentation in Multiple Sclerosis Using Deep Neural Networks

Background: Segmentation of white matter lesions and deep grey matter structures is an important task in the quantification of magnetic resonance imaging in multiple sclerosis. In this paper we explore segmentation solutions based on convolutional neural networks (CNNs) for providing fast, reliable segmentations of multimodal magnetic resonance images into lesion classes and normal-appearing grey and white-matter structures. We also explore the ability of such methods to transfer between institutions. Methods: We trained two state-of-the-art CNN architectures in cross-validation on the 2016 MSSEG training dataset: a reference implementation of a 3D Unet, and a more recently proposed architecture (DeepSCAN), to set a baseline for MS lesion segmentation performance. We then retrained those methods on a larger dataset from a single centre, with and without labels for other brain structures, and compared performance with the reference methods, and with other reference methods from recent publications. Results: Both CNN methods substantially outperform other approaches in the literature when trained on the MSSEG dataset, showing agreement with human raters in the range of human inter-rater variability. Both showed small drops in performance when trained on single-centre data and tested on the MSSEG dataset instead. When trained with the addition of anatomical labels, the performance of the 3D Unet degraded, while the performance of the DeepSCAN net improved. Overall, the DeepSCAN network predicting both lesion and anatomical labels was the best-performing network. A retrospective study of this classifier found that the classifier successfully identified several lesions missed by human raters. Interpretation: We present a method for simultaneously segmenting MS lesions and neuroanatomical structures, whose performance on lesion segmentation is close to that of human raters. The drop in performance when evaluated on external data is less drastic than reported by other researchers. Performance of 3D Unets, while excellent on datasets with small numbers of structures labelled, may suffer when the number of labels increases. Funding Statement: This research was supported by the Swiss Multiple Sclerosis Society and a grant from the Novartis Forschungsstiftung. Declaration of Interests: Richard McKInley, Rik Wepfer, Fabian Aschwanden, Lorenz Grunder, Raphaela Muri, CHristian Rummel, Rajeev Verma, Christian Weisstanner, Mauricio Reyes, Franca Wagner and Roland Wiest have no interests to declare. Anke Salmen has recieved speaker honoraria and/or travel compensation for activities with Almirall Hermal GmbH, Biogen, Merck, Novartis, Roche, and Sanofi Genzyme, none related to this work. Andrew Chan received honoraria for board and speaker honoraria from Actelion, Bayer, Biogen, Celgene, Merck, Novartis, Sanofi-Genzyme, Roche, Teva, all for hospital/university research funds. He has recieved reserach funds from Research funds: UCB, Biogen, Sanofi-Genzyme, and is an editor for European Journal of Neurology, and Clin Transl Neurosci. Ethics Approval Statement: Ethical approval for the study was granted by the local ethical commission (Cantonal Ethical Commission Bern, ’MS segmentation disease monitoring’, approval number 2016-02035).

Improved Cervical Cord Lesion Detection with 3D-MP2RAGE Sequence in Patients with Multiple Sclerosis.

Spinal cord lesions have a real diagnostic and prognostic role in multiple sclerosis. Thus, optimizing their detection on MR imaging has become a central issue with direct therapeutic impact. In this study, we compared the 3D-MP2RAGE sequence with the conventional Magnetic Resonance Imaging in Multiple Sclerosis (MAGNIMS) set for cervical cord lesion detection in 28 patients with multiple sclerosis. 3D-MP2RAGE allowed better detection of cervical lesions (+62%) in this population, with better confidence, due to optimized contrast and high spatial resolution.

Choroid plexus changes on magnetic resonance imaging in multiple sclerosis and neuromyelitis optica spectrum disorder

ObjectiveTo investigate alterations in the choroid plexus in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) using brain magnetic resonance imaging (MRI). MethodsWe prospectively recruited consecutive patients with MS or NMOSD from July 2018 to February 2019. The inclusion criterion was brain MRI within three months from onset of acute neurological symptoms. The thickness and enhancement ratio of the choroid plexus on gadolinium-enhanced T1-weighted images of patients with MS (n = 51), patients with NMOSD (n = 32), and healthy controls (HCs, n = 28) were compared. ResultsMRI in patients with MS or NMOSD showed a comparably thick but more enhanced choroid plexus compared with that of HCs. In the axial view, enhancement ratios of the lateral ventricle of MS and NMOSD patients and HCs were 1.64 ± 0.34, 1.65 ± 0.25, and 1.39 ± 0.17, respectively (P > .999 for MS vs. NMOSD; P = .001 for MS vs. HCs; P = .001 for NMOSD vs. HCs). ConclusionsThe choroid plexus was significantly more enhanced on brain MRI of patients with MS or NMOSD than on that of HCs, suggesting the involvement of the choroid plexus in the autoimmune inflammatory processes in MS and NMOSD.