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      Network Damage Predicts Clinical Worsening in Multiple Sclerosis : A 6.4-Year Study

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          Abstract

          Objective

          In multiple sclerosis (MS), clinical impairment is likely due to both structural damage and abnormal brain function. We assessed the added value of integrating structural and functional network MRI measures to predict 6.4-year MS clinical disability deterioration.

          Methods

          Baseline 3D T1-weighted and resting-state functional MRI scans were obtained from 233 patients with MS and 77 healthy controls. Patients underwent a neurologic evaluation at baseline and at 6.4-year median follow-up (interquartile range = 5.06–7.51 years). At follow-up, patients were classified as clinically stable/worsened according to disability changes. In relapsing-remitting (RR) MS, secondary progressive (SP) MS conversion was evaluated. Global brain volumetry was obtained. Furthermore, independent component analysis identified the main functional connectivity (FC) and gray matter (GM) network patterns.

          Results

          At follow-up, 105/233 (45%) patients were clinically worsened; 26/157 (16%) patients with RRMS evolved to SPMS. The treatment-adjusted random forest model identified normalized GM and brain volumes, decreased FC between default-mode networks, increased FC of the left precentral gyrus in the sensorimotor network (SMN), and GM atrophy in the fronto-parietal network (false discovery rate [FDR]-corrected p = range 0.01–0.09) as predictors of clinical worsening (out-of-bag [OOB] accuracy = 0.74). An expected contribution of baseline disability was also present (FDR-p = 0.01). Baseline disability, normalized GM volume, and GM atrophy in the SMN (FDR-p = range 0.01–0.09) were independently associated with SPMS conversion (OOB accuracy = 0.84). At receiver operating characteristic analysis, including network MRI variables improved disability worsening ( p = 0.05) and SPMS conversion ( p = 0.02) prediction.

          Conclusions

          Integration of MRI network measures helped determining the relative contributions of global/local GM damage and functional reorganization to clinical deterioration in MS.

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          Most cited references41

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          Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria

          The 2010 McDonald criteria for the diagnosis of multiple sclerosis are widely used in research and clinical practice. Scientific advances in the past 7 years suggest that they might no longer provide the most up-to-date guidance for clinicians and researchers. The International Panel on Diagnosis of Multiple Sclerosis reviewed the 2010 McDonald criteria and recommended revisions. The 2017 McDonald criteria continue to apply primarily to patients experiencing a typical clinically isolated syndrome, define what is needed to fulfil dissemination in time and space of lesions in the CNS, and stress the need for no better explanation for the presentation. The following changes were made: in patients with a typical clinically isolated syndrome and clinical or MRI demonstration of dissemination in space, the presence of CSF-specific oligoclonal bands allows a diagnosis of multiple sclerosis; symptomatic lesions can be used to demonstrate dissemination in space or time in patients with supratentorial, infratentorial, or spinal cord syndrome; and cortical lesions can be used to demonstrate dissemination in space. Research to further refine the criteria should focus on optic nerve involvement, validation in diverse populations, and incorporation of advanced imaging, neurophysiological, and body fluid markers.
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            Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS).

            J. Kurtzke (1983)
            One method of evaluating the degree of neurologic impairment in MS has been the combination of grades (0 = normal to 5 or 6 = maximal impairment) within 8 Functional Systems (FS) and an overall Disability Status Scale (DSS) that had steps from 0 (normal) to 10 (death due to MS). A new Expanded Disability Status Scale (EDSS) is presented, with each of the former steps (1,2,3 . . . 9) now divided into two (1.0, 1.5, 2.0 . . . 9.5). The lower portion is obligatorily defined by Functional System grades. The FS are Pyramidal, Cerebellar, Brain Stem, Sensory, Bowel & Bladder, Visual, Cerebral, and Other; the Sensory and Bowel & Bladder Systems have been revised. Patterns of FS and relations of FS by type and grade to the DSS are demonstrated.
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              Dissociable intrinsic connectivity networks for salience processing and executive control.

              Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a "salience network," anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an "executive-control network" that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.
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                Author and article information

                Contributors
                Journal
                Neurol Neuroimmunol Neuroinflamm
                Neurol Neuroimmunol Neuroinflamm
                nnn
                NEURIMMINFL
                Neurology® Neuroimmunology & Neuroinflammation
                Lippincott Williams & Wilkins (Hagerstown, MD )
                2332-7812
                July 2021
                21 May 2021
                21 May 2021
                : 8
                : 4
                : e1006
                Affiliations
                From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
                Author notes
                Correspondence Prof. Filippi filippi.massimo@ 123456hsr.it

                Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article.

                The Article Processing Charge was funded by the authors.

                Author information
                http://orcid.org/0000-0003-2358-4320
                http://orcid.org/0000-0002-5485-0479
                Article
                NEURIMMINFL2020035055
                10.1212/NXI.0000000000001006
                8143700
                34021055
                d7c44b04-1017-4fdc-b08b-94148a167fba
                Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

                History
                : 26 August 2020
                : 05 March 2021
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