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Background: Diagnosis of multiple sclerosis (MS) frequently relies on MRI dissemination in time (DIT) and space (DIS), as codified in 2017 McDonald criteria (McD 2017). The central vein sign (CVS) is a proposed MS diagnostic biomarker, but its optimal incorporation into McD 2017 has not been extensively studied., Objective: Evaluate the diagnostic performance of several methods incorporating CVS into McD 2017 radiological DIS criteria., Methods: Data were obtained from the CAVS-MS Pilot, a cross-sectional, international multi-center study conducted by the North American Imaging in MS Cooperative (NAIMS) that recruited adults referred for suspicion/diagnosis of demyelinating disease. Diagnostic performance of methods incorporating CVS into McD 2017 radiological DIS were evaluated by comparing sensitivity, specificity, and accuracy., Results: 78 participants (37 MS, 41 others) were included. For MS diagnosis, sensitivity, specificity, and accuracy of DIS based on brain imaging (DIS-B) alone was 92 %, 69 %, and 78 %. Requiring at least one lesion with CVS in any brain location in addition to DIS-B increased specificity (sensitivity 92 %, specificity 81 %, accuracy 86 %). Presence of 2 deep white matter lesions with CVS as an additional topography for DIS-B had higher sensitivity (sensitivity 97 %, specificity 59 %, accuracy 77 %)., Conclusions: Incorporation of CVS in McD 2017 DIS criteria can be used to improve diagnostic accuracy. Validation in additional prospective studies is needed., Competing Interests: Declaration of competing interest MA: Received Novartis fellowship award NGC4474. KN: Received licensing fee from Biogen; received Research Support from Department of Defense, National Institutes of Health, Patient Centered Outcomes Research Institute, and Biogen. LD: None CMO: None QC: None PR: Employed by and holds stocks in QMENTA JD: None CA: Has received grant support from the National Multiple Sclerosis Society and the NIH. Has received consulting fees from Horizon Therapeutics, Genentech, Sanofi Genzyme, TG Therapeutics, and EMD Serono. Has received honoraria for serving on grant review committees for the Department of Defense and the NIH and for participation in unbranded CME activities from the American Academy of Neurology, Efficient LLC, Spire Learning, and Catamount Medical Education AB: Consulting and/or advisory board fees from Accure, Atara Biotherapeutics, Biogen, BMS/Celgene/Receptos, GlaxoSmithKline, Gossamer, Janssen/Actelion, Medimmune, Merck/EMD Serono, Novartis, Roche/Genentech, Sanofi-Genzyme. Grant support to the University of Pennsylvania from Biogen Idec, Roche/Genentech, Merck/EMD Serono and Novartis. Research funding from the National Institutes of Health (NIH), The National MS Society (NMSS), the Juvenile Diabetes Research Foundation (JDRF), the Canadian Institutes of Health Research, Multiple Sclerosis Society of Canada. EC: None PAC: PI on grants to JHU from Genentech. Serves on scientific advisory boards for Lilly, Novartis, Idorsia, and Project Efflux. BACC: Compensation for consulting from: Alexion, Atara, Autobahn, Avotres, Biogen, Boston Pharma, EMD Serono, Gossamer Bio, Hexal/Sandoz, Horizon, Immunic AG, Kyverna, Neuron23, Novartis, Sanofi, and TG Therapeutics and research support from Genentech. LF: Received fees for consultancy and/or advisory board participation from Genentech, Novartis, Celgene/Bristol Myers Squibb, EMD Serono, and TG Therapeutics; Received fees for educational activities from Medscape, LLC, and the MS Association of America; program sponsorship to UT from EMD Serono; and grant support to UT from NIH/NINDS, PCORI, Genentech, and EMD Serono. RGH: Research support from Roche, Genentech, Atara, Medday. Consulting for Novartis, Sanofi/Genzyme, Roche/Genentech, QIA, and Neurona. EEL: Grants: Genentech, Biogen. Consulting: EMD Serono, BMS, Genentech, Genzyme, Bristol Myers Squibb, TG Therapeutics, Janssen, NGM Bio JO: Research support from Biogen-Idec, Roche, and EMD-Serono; consulting compensation from EMD-Serono, Sanofi-Genzyme, Biogen-Idec, Roche, Celgene, and Novartis NP: Reports research support from the Race to Erase MS Foundation and from the National Center for Advancing Translational Sciences, National Institutes of Health, through a UCSF-CTSI grant DP: Consulting compensation from EMD-Serono, Sanofi Genzyme, Roche, and Novartis VP: Employed by and holds stocks in QMENTA PR: None MR: Employed by and holds stock options in QMENTA RDS: Advisory board participation (Biogen, EMD Serono, Sanofi Genzyme); Consulting (EMD Serono, Biogen) MKS: None ESS: Consulting for scientific advisory boards from Viela Bio and Genentech, Speaker honoraria from Viela Bio NLS: Research support from the National Institutes of Health, National Multiple Sclerosis Society, Patient Centered Outcomes Research Institute, Race to Erase MS Foundation and Biogen-Idec AJS: Consulting: EMD Serono, Biogen, Alexion, Celgene, Greenwich Biosciences, Octave Bioscience, TG Therapeutics, Sanofi; Non-promotional speaking: EMD Serono; Research Funding: Biogen, Bristol Myers Squibb; Contracted Research: Biogen, Novartis, Actelion, Genentech/Roche RTS: Supported NIH R01NS112274, R01MH112847, R01MH123550. Consulting income from Octave Bioscience. DSR: Research support from Sanofi-Genzyme and Abata Therapeutics, unrelated to the current study. PS: Research support from the National Institutes of Health, National Multiple Sclerosis Society, Department of Defense, Erwin Rautenberg fondation. DO: Received research support from the National Institutes of Health, National Multiple Sclerosis Society, Patient Centered Outcomes Research Institute, Race to Erase MS Foundation, Genentech, Genzyme, and Novartis. Consulting fees from Biogen Idec, Genentech/Roche, Genzyme, Novartis, and Merck., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background and Objectives: Certain demographic and clinical characteristics, including the use of some disease-modifying therapies (DMTs), are associated with severe acute respiratory syndrome coronavirus 2 infection severity in people with multiple sclerosis (MS). Comprehensive exploration of these relationships in large international samples is needed., Methods: Clinician-reported demographic/clinical data from 27 countries were aggregated into a data set of 5,648 patients with suspected/confirmed coronavirus disease 2019 (COVID-19). COVID-19 severity outcomes (hospitalization, admission to intensive care unit [ICU], requiring artificial ventilation, and death) were assessed using multilevel mixed-effects ordered probit and logistic regression, adjusted for age, sex, disability, and MS phenotype. DMTs were individually compared with glatiramer acetate, and anti-CD20 DMTs with pooled other DMTs and with natalizumab., Results: Of 5,648 patients, 922 (16.6%) with suspected and 4,646 (83.4%) with confirmed COVID-19 were included. Male sex, older age, progressive MS, and higher disability were associated with more severe COVID-19. Compared with glatiramer acetate, ocrelizumab and rituximab were associated with higher probabilities of hospitalization (4% [95% CI 1-7] and 7% [95% CI 4-11]), ICU/artificial ventilation (2% [95% CI 0-4] and 4% [95% CI 2-6]), and death (1% [95% CI 0-2] and 2% [95% CI 1-4]) (predicted marginal effects). Untreated patients had 5% (95% CI 2-8), 3% (95% CI 1-5), and 1% (95% CI 0-3) higher probabilities of the 3 respective levels of COVID-19 severity than glatiramer acetate. Compared with pooled other DMTs and with natalizumab, the associations of ocrelizumab and rituximab with COVID-19 severity were also more pronounced. All associations persisted/enhanced on restriction to confirmed COVID-19., Discussion: Analyzing the largest international real-world data set of people with MS with suspected/confirmed COVID-19 confirms that the use of anti-CD20 medication (both ocrelizumab and rituximab), as well as male sex, older age, progressive MS, and higher disability are associated with more severe course of COVID-19., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Inc.)

Purpose: Repeated injections of linear gadolinium-based contrast agent (GBCA) have shown correlations with increased signal intensities (SI) on unenhanced T1-weighted (T1w) images. Assessment is usually performed manually on a single slice and the SI as an average of a freehand region-of-interest is reported. We aim to develop a fully automated software that segments and computes SI ratio of dentate nucleus (DN) to pons (DN/P) and globus pallidus (GP) to thalamus (GP/T) for the assessment of gadolinium presence in the brain after a serial GBCA administrations. Approach: All patients ( N = 113 ) underwent at least eight GBCA enhanced scans. The modal SI in the DN, GP, pons, and thalamus were measured volumetrically on unenhanced T1w images and corrected based on the reference protocol (measurement 1) and compared to the SI-uncorrected-modal-volume (measurement 2), SI-corrected-mean-volume (measurement 3), as well as SI-corrected-modal-single slice (measurement 4) approaches. Results: Automatic processing worked on all 2119 studies (1150 at 1.5 T and 969 at 3 T). DN/P were 1.085 ± 0.048 (1.5 T) and 0.979 ± 0.061 (3 T). GP/T were 1.084 ± 0.039 (1.5 T) and 1.069 ± 0.042 (3 T). Modal DN/P ratios from volumetric assessment at 1.5 T failed to show a statistical difference with or without SI corrections ( p = 0.71 ). All other t -tests demonstrated significant differences (measurement 2, 3, 4 compared to 1, p < 0.001 ). Conclusion: The fully automatic method is an effective powerful tool to streamline the analysis of SI ratios in the deep brain tissues. Divergent SI ratios using different approaches reinforces the need to standardize the measurement for the research in this field., (© 2021 Society of Photo-Optical Instrumentation Engineers (SPIE).)

Background: Fiber tracking with diffusion-weighted MRI has become an essential tool for estimating in vivo brain white matter architecture. Fiber tracking results are sensitive to the choice of processing method and tracking criteria., Purpose: To assess the variability for an algorithm in group studies reproducibility is of critical context. However, reproducibility does not assess the validity of the brain connections. Phantom studies provide concrete quantitative comparisons of methods relative to absolute ground truths, yet do no capture variabilities because of in vivo physiological factors. The ISMRM 2017 TraCED challenge was created to fulfill the gap., Study Type: A systematic review of algorithms and tract reproducibility studies., Subjects: Single healthy volunteers., Field Strength/sequence: 3.0T, two different scanners by the same manufacturer. The multishell acquisition included b-values of 1000, 2000, and 3000 s/mm 2 with 20, 45, and 64 diffusion gradient directions per shell, respectively., Assessment: Nine international groups submitted 46 tractography algorithm entries each consisting 16 tracts per scan. The algorithms were assessed using intraclass correlation (ICC) and the Dice similarity measure., Statistical Tests: Containment analysis was performed to assess if the submitted algorithms had containment within tracts of larger volume submissions. This also serves the purpose to detect if spurious submissions had been made., Results: The top five submissions had high ICC and Dice >0.88. Reproducibility was high within the top five submissions when assessed across sessions or across scanners: 0.87-0.97. Containment analysis shows that the top five submissions are contained within larger volume submissions. From the total of 16 tracts as an outcome relatively the number of tracts with high, moderate, and low reproducibility were 8, 4, and 4., Data Conclusion: The different methods clearly result in fundamentally different tract structures at the more conservative specificity choices. Data and challenge infrastructure remain available for continued analysis and provide a platform for comparison., Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:234-249., (© 2019 International Society for Magnetic Resonance in Medicine.)

Objectives and Design: Neuronal responses adapt to familiar and repeated sensory stimuli. Enhanced synchrony across wide brain systems has been postulated as a potential mechanism for this adaptation phenomenon. Here, we used recently developed graph theory methods to investigate hidden connectivity features of dynamic synchrony changes during a visual repetition paradigm. Particularly, we focused on strength connectivity changes occurring at local and distant brain neighborhoods., Principal Observations: We found that connectivity reorganization in visual modal cortex-such as local suppressed connectivity in primary visual areas and distant suppressed connectivity in fusiform areas-is accompanied by enhanced local and distant connectivity in higher cognitive processing areas in multimodal and association cortex. Moreover, we found a shift of the dynamic functional connections from primary-visual-fusiform to primary-multimodal/association cortex., Conclusions: These findings suggest that repetition-suppression is made possible by reorganization of functional connectivity that enables communication between low- and high-order areas. Hum Brain Mapp 38:1965-1976, 2017. © 2017 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Analysis of the structural connectomes can lead to powerful insights about the brain's organization and damage. However, the accuracy and reproducibility of constructing the structural connectome done with different acquisition and reconstruction techniques is not well defined. In this work, we evaluated the reproducibility of the structural connectome techniques by performing test-retest (same day) and longitudinal studies (after 1 month) as well as analyzing graph-based measures on the data acquired from 22 healthy volunteers (6 subjects were used for the longitudinal study). We compared connectivity matrices and tract reconstructions obtained with the most typical acquisition schemes used in clinical application: diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI), and diffusion spectrum imaging (DSI). We observed that all techniques showed high reproducibility in the test-retest analysis (correlation >.9). However, HARDI was the only technique with low variability (2%) in the longitudinal assessment (1-month interval). The intraclass coefficient analysis showed the highest reproducibility for the DTI connectome, however, with more sparse connections than HARDI and DSI. Qualitative (neuroanatomical) assessment of selected tracts confirmed the quantitative results showing that HARDI managed to detect most of the analyzed fiber groups and fanning fibers. In conclusion, we found that HARDI acquisition showed the most balanced trade-off between high reproducibility of the connectome, higher rate of path detection and of fanning fibers, and intermediate acquisition times (10-15 minutes), although at the cost of higher appearance of aberrant fibers., (Copyright © 2015 by the American Society of Neuroimaging.)

The optic radiation (OR) is one of the major components of the visual system and a key structure at risk in white matter diseases such as multiple sclerosis (MS). However, it is challenging to perform track reconstruction of the OR using diffusion MRI due to a sharp change of direction in the Meyer's loop and the presence of kissing and crossing fibers along the pathway. As such, we aimed to provide a highly precise and reproducible framework for tracking the OR from thalamic and visual cortex masks. The framework combined the generation of probabilistic streamlines by high order fiber orientation distributions estimated with constrained spherical deconvolution and an automatic post-processing based on anatomical exclusion criteria (AEC) to compensate for the presence of anatomically implausible streamlines. Specifically, those ending in the contralateral hemisphere, cerebrospinal fluid or grey matter outside the visual cortex were automatically excluded. We applied the framework to two distinct high angular resolution diffusion-weighted imaging (HARDI) acquisition protocols on one cohort, comprised of ten healthy volunteers and five MS patients. The OR was successfully delineated in both HARDI acquisitions in the healthy volunteers and MS patients. Quantitative evaluation of the OR position was done by comparing the results with histological reference data. Compared with histological mask, the OR reconstruction into a template (OR-TCT) was highly precise (percentage of voxels within the OR-TCT correctly defined as OR), ranging from 0.71 to 0.83. The sensitivity (percentage of voxels in histological reference mask correctly defined as OR in OR-TCT) ranged from 0.65 to 0.81 and the accuracy (measured by F1 score) was 0.73 to 0.77 in healthy volunteers. When AEC was not applied the precision and accuracy decreased. The absolute agreement between both HARDI datasets measured by the intraclass correlation coefficient was 0.73. This improved framework allowed us to reconstruct the OR with high reliability and accuracy independently of the acquisition parameters. Moreover, the reconstruction was possible even in the presence of tissue damage due to MS. This framework could also be applied to other tracts with complex configuration.

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

High-angular resolution diffusion imaging (HARDI) is a diffusion weighted MRI technique that overcomes some of the decisive limitations of its predecessor, diffusion tensor imaging (DTI), in the areas of composite nerve fiber structure. Despite its advantages, HARDI raises several issues: complex modeling of the data, nonintuitive and computationally demanding visualization, inability to interactively explore and transform the data, etc. To overcome these drawbacks, we present a novel, multifield visualization framework that adopts the benefits of both DTI and HARDI. By applying a classification scheme based on HARDI anisotropy measures, the most suitable model per imaging voxel is automatically chosen. This classification allows simplification of the data in areas with single fiber bundle coherence. To accomplish fast and interactive visualization for both HARDI and DTI modalities, we exploit the capabilities of modern GPUs for glyph rendering and adopt DTI fiber tracking in suitable regions. The resulting framework, allows user-friendly data exploration of fused HARDI and DTI data. Many incorporated features such as sharpening, normalization, maxima enhancement and different types of color coding of the HARDI glyphs, simplify the data and enhance its features. We provide a qualitative user evaluation that shows the potentials of our visualization tools in several HARDI applications., (© 2011 IEEE)