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      Spinal Cord Imaging in Amyotrophic Lateral Sclerosis: Historical Concepts—Novel Techniques

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          Abstract

          Amyotrophic lateral sclerosis (ALS) is the most common adult onset motor neuron disease with no effective disease modifying therapies at present. Spinal cord degeneration is a hallmark feature of ALS, highlighted in the earliest descriptions of the disease by Lockhart Clarke and Jean-Martin Charcot. The anterior horns and corticospinal tracts are invariably affected in ALS, but up to recently it has been notoriously challenging to detect and characterize spinal pathology in vivo. With recent technological advances, spinal imaging now offers unique opportunities to appraise lower motor neuron degeneration, sensory involvement, metabolic alterations, and interneuron pathology in ALS. Quantitative spinal imaging in ALS has now been used in cross-sectional and longitudinal study designs, applied to presymptomatic mutation carriers, and utilized in machine learning applications. Despite its enormous clinical and academic potential, a number of physiological, technological, and methodological challenges limit the routine use of computational spinal imaging in ALS. In this review, we provide a comprehensive overview of emerging spinal cord imaging methods and discuss their advantages, drawbacks, and biomarker potential in clinical applications, clinical trial settings, monitoring, and prognostic roles.

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          Most cited references116

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          Demyelination increases radial diffusivity in corpus callosum of mouse brain.

          Myelin damage, as seen in multiple sclerosis (MS) and other demyelinating diseases, impairs axonal conduction and can also be associated with axonal degeneration. Accurate assessments of these conditions may be highly beneficial in evaluating and selecting therapeutic strategies for patient management. Recently, an analytical approach examining diffusion tensor imaging (DTI) derived parameters has been proposed to assess the extent of axonal damage, demyelination, or both. The current study uses the well-characterized cuprizone model of experimental demyelination and remyelination of corpus callosum in mouse brain to evaluate the ability of DTI parameters to detect the progression of myelin degeneration and regeneration. Our results demonstrate that the extent of increased radial diffusivity reflects the severity of demyelination in corpus callosum of mouse brain affected by cuprizone treatment. Subsequently, radial diffusivity decreases with the progression of remyelination. Furthermore, radial diffusivity changes were specific to the time course of changes in myelin integrity as distinct from axonal injury, which was detected by betaAPP immunostaining and shown to be most extensive prior to demyelination. Radial diffusivity offers a specific assessment of demyelination and remyelination, as distinct from acute axonal damage.
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            Prognostic factors in ALS: A critical review.

            We have performed a systematic review to summarize current knowledge concerning factors related to survival in ALS and to evaluate the implications of these data for clinical trials design. The median survival time from onset to death ranges from 20 to 48 months, but 10-20% of ALS patients have a survival longer than 10 years. Older age and bulbar onset are consistently reported to have a worse outcome. There are conflicting data on gender, diagnostic delay and El Escorial criteria. The rate of symptom progression was revealed to be an independent prognostic factor. Psychosocial factors, FTD, nutritional status, and respiratory function are also related to ALS outcome. The effect of enteral nutrition on survival is still unclear, while NIPPV has been found to improve survival. There are no well established biological markers of progression, although some are likely to emerge in the near future. These findings have relevant implications for the design of future trials. Randomization, besides the type of onset, should take into account age, respiratory status at entry, and a measure of disease progression pre-entry. Alternative trial designs can include the use of natural history controls, the so-called minimization method for treatment allocation, and the futility approach.
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              Global Epidemiology of Amyotrophic Lateral Sclerosis: A Systematic Review of the Published Literature

              Background: Amyotrophic lateral sclerosis (ALS) is relatively rare, yet the economic and social burden is substantial. Having accurate incidence and prevalence estimates would facilitate efficient allocation of healthcare resources. Objective: To provide a comprehensive and critical review of the epidemiological literature on ALS. Methods: MEDLINE and EMBASE (1995-2011) databases of population-based studies on ALS incidence and prevalence reporting quantitative data were analyzed. Data extracted included study location and time, design and data sources, case ascertainment methods and incidence and/or prevalence rates. Medians and interquartile ranges (IQRs) were calculated, and ALS case estimates were derived using 2010 population estimates. Results: In all, 37 articles met the inclusion criteria. In Europe, the median incidence rate (/100,000 population) was 2.08 (IQR 1.47-2.43), corresponding to an estimated 15,355 (10,852-17,938) cases. Median prevalence (/100,000 population) was 5.40 (IQR 4.06-7.89), or 39,863 (29,971-58,244) prevalent cases. Conclusions: Disparity in rates among ALS incidence and prevalence studies may be due to differences in study design or true variations in population demographics such as age and geography, including environmental factors and genetic predisposition. Additional large-scale studies that use standardized case ascertainment methods are needed to more accurately assess the true global burden of ALS.
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                12 April 2019
                2019
                : 10
                : 350
                Affiliations
                [1] 1Department of Neurology, Icahn School of Medicine at Mount Sinai , New York, NY, United States
                [2] 2Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM , Paris, France
                [3] 3Department of Neurology, Pitié-Salpêtrière University Hospital (APHP) , Paris, France
                [4] 4Computational Neuroimaging Group, Trinity College Dublin , Dublin, Ireland
                Author notes

                Edited by: Justin John Yerbury, University of Wollongong, Australia

                Reviewed by: Virginie Callot, Centre National de la Recherche Scientifique (CNRS), France; David Devos, Université de Lille, France

                *Correspondence: Pierre-François Pradat pierre-francois.pradat@ 123456psl.aphp.fr

                This article was submitted to Neurodegeneration, a section of the journal Frontiers in Neurology

                †These authors have contributed equally as co-senior authors

                Article
                10.3389/fneur.2019.00350
                6474186
                31031688
                a16aaaa0-3afd-4074-ab14-22dac717498c
                Copyright © 2019 El Mendili, Querin, Bede and Pradat.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 December 2018
                : 21 March 2019
                Page count
                Figures: 0, Tables: 2, Equations: 0, References: 136, Pages: 12, Words: 9322
                Funding
                Funded by: Health Research Board 10.13039/100010414
                Funded by: Irish Institute of Clinical Neuroscience 10.13039/501100003840
                Funded by: AFM-Téléthon 10.13039/501100004923
                Funded by: Institut pour la Recherche sur la Moelle épiniére et l'Encéphale 10.13039/501100010299
                Funded by: Association pour la Recherche sur la Sclérose Latérale Amyotrophique et autres Maladies du Motoneurone 10.13039/501100006510
                Funded by: Target ALS 10.13039/100013013
                Categories
                Neurology
                Mini Review

                Neurology
                als (amyotrophic lateral sclerosis),mri—magnetic resonance imaging,mnd,spinal cord,neuroimaging

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