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      Quantification of Global Cerebral Atrophy in Multiple Sclerosis from 3T MRI Using SPM: The Role of Misclassification Errors

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          Abstract

          Purpose

          We tested the validity of a freely available segmentation pipeline to measure compartmental brain volumes from 3T MRI in patients with multiple sclerosis (MS). Our primary focus was methodological to explore the effect of segmentation corrections on the clinical relevance of the output metrics.

          Methods

          Three-dimensional T1-weighted images were acquired to compare 61 MS patients to 30 age- and gender-matched normal controls (NC). We also tested the within patient MRI relationship to disability (eg, expanded disability status scale [EDSS] score) and cognition. Statistical parametric mapping v. 8 (SPM8)-derived gray matter (GMF), white matter (WMF), and total brain parenchyma fractions (BPF) were derived before and after correcting errors from T1 hypointense MS lesions and/or ineffective deep GM contouring.

          Results

          MS patients had lower GMF and BPF as compared to NC ( P<.05). Cognitively impaired patients had lower BPF than cognitively preserved patients ( P<.05). BPF was related to EDSS; BPF and GMF were related to disease duration (all P<.05). Errors caused bias in GMFs and WMFs but had no discernable influence on BPFs or any MRI-clinical associations.

          Conclusions

          We report the validity of a segmentation pipeline for the detection of MS-related brain atrophy with 3T MRI. Longitudinal studies are warranted to extend these results.

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          Most cited references 50

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          Unified segmentation.

          A probabilistic framework is presented that enables image registration, tissue classification, and bias correction to be combined within the same generative model. A derivation of a log-likelihood objective function for the unified model is provided. The model is based on a mixture of Gaussians and is extended to incorporate a smooth intensity variation and nonlinear registration with tissue probability maps. A strategy for optimising the model parameters is described, along with the requisite partial derivatives of the objective function.
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            The Family of Ln2Ti2S2O5 Compounds (Ln=Nd Sm Gd Tb Dy Ho Er and Y) Optical Properties

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              Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald Criteria".

              New diagnostic criteria for multiple sclerosis integrating magnetic resonance image assessment with clinical and other paraclinical methods were introduced in 2001. The "McDonald Criteria" have been extensively assessed and used since 2001. New evidence and consensus now strengthen the role of these criteria in the multiple sclerosis diagnostic workup to demonstrate dissemination of lesions in time, to clarify the use of spinal cord lesions, and to simplify diagnosis of primary progressive disease. The 2005 Revisions to the McDonald Diagnostic Criteria for MS should simplify and speed diagnosis, whereas maintaining adequate sensitivity and specificity.
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                Author and article information

                Journal
                J Neuroimaging
                J Neuroimaging
                jon
                Journal of Neuroimaging
                BlackWell Publishing Ltd (Oxford, UK )
                1051-2284
                1552-6569
                March 2015
                18 December 2014
                : 25
                : 2
                : 191-199
                Affiliations
                Department of Neurology, Brigham and Women's Hospital, Laboratory for Neuroimaging Research, Partners MS Center, Harvard Medical School Boston, MA
                Department of Neurology, State University of New York Buffalo, NY
                Author notes
                Correspondence: Address correspondence to Rohit Bakshi, MD, MA, Laboratory for Neuroimaging Research, One Brookline Place, Brookline, MA 02445. E-mail: rbakshi@ 123456bwh.harvard.edu .
                [*]

                Both authors contributed equally to the paper.

                Article
                10.1111/jon.12194
                4409073
                25523616
                © 2014 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of the American Society of Neuroimaging

                This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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                Original Research

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