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      Brain structure in children with congenital visual disorders and visual impairment

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          Abstract

          Aim

          To examine if congenital visual impairment is associated with differences in brain anatomy in children.

          Method

          Ten children (8–12y) with congenital disorders of the peripheral visual system with severe visual impairment ( SVI; >0.8 log MAR) or mild‐to‐moderate visual impairment ( MVI; 0.6–0.8 log MAR) were compared to 21 typically sighted comparison ( TSC) children. Thalamus volume, grey matter density, white matter microstructure, and integrity of visual tracts were investigated in SVI, MVI, and TSC groups with anatomical and diffusion‐weighted magnetic resonance imaging.

          Results

          Compared to the TSC group, the SVI group had lower white matter integrity in tracts of the visual system (optic radiations: SVI 0.35±0.015, TSC 0.39±0.007 [ p=0.022]; posterior corpus callosum: SVI 0.37±0.019; TSC 0.42±0.009 [ p=0.033]) and lower left thalamus volume ( SVI 4.37±0.087; TSC 4.99±0.339 [ p=0.015]). Neuroanatomical differences were greater in the SVI group, while no consistent differences between the MVI and TSC group were observed.

          Interpretation

          Posterior tracts of the visual system are compromised in children with congenital visual impairment versus those who are typically sighted. The severity of visual input appears to have affected neuroanatomical development as significant reductions were only found in the SVI group.

          What this paper adds

          • Severe visual impairment in mid‐childhood is associated with reduced integrity of visual pathways and reduced thalamus volume.

          What this paper adds

          • Severe visual impairment in mid‐childhood is associated with reduced integrity of visual pathways and reduced thalamus volume.

          This article is commented on by Bauer on page https://doi.org/10.1111/dmcn.14339 of this issue.

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          Most cited references26

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          Advances in functional and structural MR image analysis and implementation as FSL.

          The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right. In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB's Software Library (FSL).
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            Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.

            There has been much recent interest in using magnetic resonance diffusion imaging to provide information about anatomical connectivity in the brain, by measuring the anisotropic diffusion of water in white matter tracts. One of the measures most commonly derived from diffusion data is fractional anisotropy (FA), which quantifies how strongly directional the local tract structure is. Many imaging studies are starting to use FA images in voxelwise statistical analyses, in order to localise brain changes related to development, degeneration and disease. However, optimal analysis is compromised by the use of standard registration algorithms; there has not to date been a satisfactory solution to the question of how to align FA images from multiple subjects in a way that allows for valid conclusions to be drawn from the subsequent voxelwise analysis. Furthermore, the arbitrariness of the choice of spatial smoothing extent has not yet been resolved. In this paper, we present a new method that aims to solve these issues via (a) carefully tuned non-linear registration, followed by (b) projection onto an alignment-invariant tract representation (the "mean FA skeleton"). We refer to this new approach as Tract-Based Spatial Statistics (TBSS). TBSS aims to improve the sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies. We describe TBSS in detail and present example TBSS results from several diffusion imaging studies.
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              MRtrix: Diffusion tractography in crossing fiber regions

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                Author and article information

                Contributors
                j.m.c.bathelt@uva.nl
                Journal
                Dev Med Child Neurol
                Dev Med Child Neurol
                10.1111/(ISSN)1469-8749
                DMCN
                Developmental Medicine and Child Neurology
                John Wiley and Sons Inc. (Hoboken )
                0012-1622
                1469-8749
                08 August 2019
                January 2020
                : 62
                : 1 ( doiID: 10.1111/dmcn.v62.1 )
                : 125-131
                Affiliations
                [ 1 ] Department of Psychology University of Amsterdam Amsterdam the Netherlands
                [ 2 ] UCL Great Ormond Street Hospital Institute of Child Health University College London London UK
                [ 3 ] Great Ormond Street Hospital for Children NHS Foundation Trust London UK
                Author notes
                [*] [* ]Correspondence to Joe Bathelt at Department of Psychology, Nieuwe Achtergracht 129‐B, 1018 WS Amsterdam, the Netherlands. E‐mail: j.m.c.bathelt@ 123456uva.nl
                Author information
                https://orcid.org/0000-0001-5195-956X
                https://orcid.org/0000-0003-2195-1430
                Article
                DMCN14322
                10.1111/dmcn.14322
                6916268
                31393613
                b3d40cfa-2474-4a34-9587-ab44b0f278ad
                © 2019 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 June 2019
                Page count
                Figures: 2, Tables: 4, Pages: 7, Words: 5357
                Funding
                Funded by: Great Ormond Street Hospital Children's Charity , open-funder-registry 10.13039/501100001279;
                Funded by: UCL Impact
                Funded by: UCL Grand Challenges
                Funded by: Royal National Institute of Blind People
                Funded by: Children NHS Foundation Trust and University College London
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                January 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.3 mode:remove_FC converted:17.12.2019

                Neurology
                Neurology

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