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      Multispectral brain morphometry in Tourette syndrome persisting into adulthood

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          Abstract

          Tourette syndrome is a childhood-onset neuropsychiatric disorder with a high prevalence of attention deficit hyperactivity and obsessive-compulsive disorder co-morbidities. Structural changes have been found in frontal cortex and striatum in children and adolescents. A limited number of morphometric studies in Tourette syndrome persisting into adulthood suggest ongoing structural alterations affecting frontostriatal circuits. Using cortical thickness estimation and voxel-based analysis of T1- and diffusion-weighted structural magnetic resonance images, we examined 40 adults with Tourette syndrome in comparison with 40 age- and gender-matched healthy controls. Patients with Tourette syndrome showed relative grey matter volume reduction in orbitofrontal, anterior cingulate and ventrolateral prefrontal cortices bilaterally. Cortical thinning extended into the limbic mesial temporal lobe. The grey matter changes were modulated additionally by the presence of co-morbidities and symptom severity. Prefrontal cortical thickness reduction correlated negatively with tic severity, while volume increase in primary somatosensory cortex depended on the intensity of premonitory sensations. Orbitofrontal cortex volume changes were further associated with abnormal water diffusivity within grey matter. White matter analysis revealed changes in fibre coherence in patients with Tourette syndrome within anterior parts of the corpus callosum. The severity of motor tics and premonitory urges had an impact on the integrity of tracts corresponding to cortico-cortical and cortico-subcortical connections. Our results provide empirical support for a patho-aetiological model of Tourette syndrome based on developmental abnormalities, with perturbation of compensatory systems marking persistence of symptoms into adulthood. We interpret the symptom severity related grey matter volume increase in distinct functional brain areas as evidence of ongoing structural plasticity. The convergence of evidence from volume and water diffusivity imaging strengthens the validity of our findings and attests to the value of a novel multimodal combination of volume and cortical thickness estimations that provides unique and complementary information by exploiting their differential sensitivity to structural change.

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          Most cited references55

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          Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies.

          Choosing the appropriate neuroimaging phenotype is critical to successfully identify genes that influence brain structure or function. While neuroimaging methods provide numerous potential phenotypes, their role for imaging genetics studies is unclear. Here we examine the relationship between brain volume, grey matter volume, cortical thickness and surface area, from a genetic standpoint. Four hundred and eighty-six individuals from randomly ascertained extended pedigrees with high-quality T1-weighted neuroanatomic MRI images participated in the study. Surface-based and voxel-based representations of brain structure were derived, using automated methods, and these measurements were analysed using a variance-components method to identify the heritability of these traits and their genetic correlations. All neuroanatomic traits were significantly influenced by genetic factors. Cortical thickness and surface area measurements were found to be genetically and phenotypically independent. While both thickness and area influenced volume measurements of cortical grey matter, volume was more closely related to surface area than cortical thickness. This trend was observed for both the volume-based and surface-based techniques. The results suggest that surface area and cortical thickness measurements should be considered separately and preferred over gray matter volumes for imaging genetic studies. Copyright 2009 Elsevier Inc. All rights reserved.
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            A unified statistical approach for determining significant signals in images of cerebral activation.

            We present a unified statistical theory for assessing the significance of apparent signal observed in noisy difference images. The results are usable in a wide range of applications, including fMRI, but are discussed with particular reference to PET images which represent changes in cerebral blood flow elicited by a specific cognitive or sensorimotor task. Our main result is an estimate of the P-value for local maxima of Gaussian, t, chi(2) and F fields over search regions of any shape or size in any number of dimensions. This unifies the P-values for large search areas in 2-D (Friston et al. [1991]: J Cereb Blood Flow Metab 11:690-699) large search regions in 3-D (Worsley et al. [1992]: J Cereb Blood Flow Metab 12:900-918) and the usual uncorrected P-value at a single pixel or voxel. Copyright (c) 1996 Wiley-Liss, Inc.
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              Unified segmentation

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                Author and article information

                Journal
                Brain
                brain
                brain
                Brain
                Oxford University Press
                0006-8950
                1460-2156
                December 2010
                10 November 2010
                10 November 2010
                : 133
                : 12
                : 3661-3675
                Affiliations
                 1 Département des neurosciences cliniques, CHUV, University of Lausanne, CH-1011 Lausanne, Switzerland
                 2 Wellcome Trust Centre for Neuroimaging, University College London, Institute of Neurology, WC1N 3BG London, UK
                 3 Max Planck Institute for Human Cognitive and Brain Sciences, D-04103 Leipzig, Germany
                 4 Mind Brain Institute, Charité and Humboldt University, D-10099 Berlin, Germany
                 5 Department of Neurological and Psychiatric Sciences, University of Bari, I-70124 Bari, Italy
                 6 Department of Neuropsychiatry, University of Birmingham and BSMHFT, B15 2TT Birmingham, UK
                 7 Department of Mental Health Sciences, University College London, W1W 7EY London, UK
                 8 Department of Neurology, University Ulm, D-89081 Ulm, Germany
                 9 Psychiatry and Clinical Imaging Sciences Centre, Brighton & Sussex Medical School, University of Sussex Campus, BN1 9PX Brighton, UK
                10 Neurobehavioural Clinic, Sussex Partnership NHS Foundation Trust, BN13 3EP Brighton, UK
                11 Neuroimaging Laboratory, IRCCS Fondazione Santa Lucia, I-00179 Rome, Italy
                Author notes
                Correspondence to: Bogdan Draganski, Département des Neurosciences Cliniques, CHUV, University of Lausanne, Switzerland E-mail: bogdan.draganski@ 123456gmail.com
                Article
                awq300
                10.1093/brain/awq300
                2995885
                21071387
                3f033a1f-383e-467a-83eb-95ef6b34bb9f
                © The Author(s) 2010. Published by Oxford University Press on behalf of Brain.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 4 May 2010
                : 27 August 2010
                : 6 September 2010
                Categories
                Original Articles

                Neurosciences
                tourette syndrome,fractional anisotropy,voxel-based morphometry,mean diffusivity,voxel-based cortical thickness

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