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      Reduced Ventral Cingulum Integrity and Increased Behavioral Problems in Children with Isolated Optic Nerve Hypoplasia and Mild to Moderate or No Visual Impairment

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          To assess the prevalence of behavioral problems in children with isolated optic nerve hypoplasia, mild to moderate or no visual impairment, and no developmental delay. To identify white matter abnormalities that may provide neural correlates for any behavioral abnormalities identified.

          Patients and Methods

          Eleven children with isolated optic nerve hypoplasia (mean age 5.9 years) underwent behavioral assessment and brain diffusion tensor imaging, Twenty four controls with isolated short stature (mean age 6.4 years) underwent MRI, 11 of whom also completed behavioral assessments. Fractional anisotropy images were processed using tract-based spatial statistics. Partial correlation between ventral cingulum, corpus callosum and optic radiation fractional anisotropy, and child behavioral checklist scores (controlled for age at scan and sex) was performed.


          Children with optic nerve hypoplasia had significantly higher scores on the child behavioral checklist (p<0.05) than controls (4 had scores in the clinically significant range). Ventral cingulum, corpus callosum and optic radiation fractional anisotropy were significantly reduced in children with optic nerve hypoplasia. Right ventral cingulum fractional anisotropy correlated with total and externalising child behavioral checklist scores (r = −0.52, p<0.02, r = −0.46, p<0.049 respectively). There were no significant correlations between left ventral cingulum, corpus callosum or optic radiation fractional anisotropy and behavioral scores.


          Our findings suggest that children with optic nerve hypoplasia and mild to moderate or no visual impairment require behavioral assessment to determine the presence of clinically significant behavioral problems. Reduced structural integrity of the ventral cingulum correlated with behavioral scores, suggesting that these white matter abnormalities may be clinically significant. The presence of reduced fractional anisotropy in the optic radiations of children with mild to moderate or no visual impairment raises questions as to the pathogenesis of these changes which will need to be addressed by future studies.

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          Most cited references 19

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          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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            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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              The diagonal and off-diagonal elements of the effective self-diffusion tensor, Deff, are related to the echo intensity in an NMR spin-echo experiment. This relationship is used to design experiments from which Deff is estimated. This estimate is validated using isotropic and anisotropic media, i.e., water and skeletal muscle. It is shown that significant errors are made in diffusion NMR spectroscopy and imaging of anisotropic skeletal muscle when off-diagonal elements of Deff are ignored, most notably the loss of information needed to determine fiber orientation. Estimation of Deff provides the theoretical basis for a new MRI modality, diffusion tensor imaging, which provides information about tissue microstructure and its physiologic state not contained in scalar quantities such as T1, T2, proton density, or the scalar apparent diffusion constant.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                12 March 2013
                : 8
                : 3
                [1 ]Developmental Endocrinology Research Group, Clinical and Molecular Genetics Unit, University College London Institute of Child Health, London, United Kingdom
                [2 ]Neurosciences Unit, UCL Institute of Child Health and Developmental Vision Clinic, Great Ormond Street Children’s Hospital, London, United Kingdom
                [3 ]Imaging and Biophysics Unit, University College London Institute of Child Health, London, United Kingdom
                University of Maryland, College Park, United States of America
                Author notes

                Competing Interests: This study was sponsored by The Child Growth Foundation and an unrestricted educational grant from Novo Nordisk Ltd. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

                Involved in reviewing the manuscript: EAW MO JC KS ND AS CC MTD. Approved the final version of the manuscript: EAW MO JC KS ND AS CC MTD. Conceived and designed the experiments: EAW MO JC ND AS CC MTD. Performed the experiments: EAW MO JC KS. Analyzed the data: EAW MO. Contributed reagents/materials/analysis tools: JC CC. Wrote the paper: EAW.

                ¶ These authors also contributed equally to this work.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 8
                This study was sponsored by The Child Growth Foundation and an unrestricted educational grant from Novo Nordisk Ltd. EAW and MOR are sponsored by The Child Growth Foundation and an unrestricted educational grant from Novo Nordisk Ltd. MTD is funded by Great Ormond Street Children’s Charity. JC, KS, AS, ND and CC have nothing to declare. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Pediatric Endocrinology
                Developmental and Pediatric Neurology
                Pediatric Ophthalmology
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Social and Behavioral Sciences



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