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      Quantitative multi-parameter mapping of R1, PD *, MT, and R2 * at 3T: a multi-center validation

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          Abstract

          Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD *), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2 * = 1/T2 *). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2 * (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

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          A fast diffeomorphic image registration algorithm.

          This paper describes DARTEL, which is an algorithm for diffeomorphic image registration. It is implemented for both 2D and 3D image registration and has been formulated to include an option for estimating inverse consistent deformations. Nonlinear registration is considered as a local optimisation problem, which is solved using a Levenberg-Marquardt strategy. The necessary matrix solutions are obtained in reasonable time using a multigrid method. A constant Eulerian velocity framework is used, which allows a rapid scaling and squaring method to be used in the computations. DARTEL has been applied to intersubject registration of 471 whole brain images, and the resulting deformations were evaluated in terms of how well they encode the shape information necessary to separate male and female subjects and to predict the ages of the subjects.
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            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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              SENSE: Sensitivity encoding for fast MRI

              New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two-coil array in brain imaging. With an array of five coils double-oblique heart images were obtained in one-third of conventional scan time. Magn Reson Med 42:952-962, 1999. Copyright 1999 Wiley-Liss, Inc.
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                Author and article information

                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                25 March 2013
                10 June 2013
                2013
                : 7
                : 95
                Affiliations
                [1] 1Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London London, UK
                [2] 2Department of Psychiatry, University of Cambridge Cambridge, UK
                [3] 3Behavioural and Clinical Neuroscience Institute, University of Cambridge Cambridge, UK
                [4] 4Cambridgeshire and Peterborough NHS Foundation Trust Cambridge, UK
                [5] 5Department of Clinical Neuroscience, Wolfson Brain Imaging Centre, University of Cambridge Cambridge, UK
                [6] 6MRC Cognition and Brain Sciences Unit Cambridge, UK
                [7] 7GlaxoSmithKline, Clinical Unit Cambridge, Addenbrooke's Hospital Cambridge, UK
                [8] 8Laboratoire de recherche en neuroimagerie, Département des neurosciences cliniques, CHUV, University of Lausanne Lausanne, Switzerland
                Author notes

                Edited by: Ching-Po Lin, National Yang-Ming University, Taiwan

                Reviewed by: Pierre Bellec, University of Montreal, Canada; Chao Yi-Ping, Chang Gung University, Taiwan

                *Correspondence: Nikolaus Weiskopf, Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK e-mail: n.weiskopf@ 123456ucl.ac.uk

                This article was submitted to Frontiers in Brain Imaging Methods, a specialty of Frontiers in Neuroscience.

                Article
                10.3389/fnins.2013.00095
                3677134
                23772204
                39b6aaa5-ccfb-41d0-b08d-8c79d7ca49f7
                Copyright © 2013 Weiskopf, Suckling, Williams, Correia, Inkster, Tait, Ooi, Bullmore and Lutti.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 04 February 2013
                : 18 May 2013
                Page count
                Figures: 6, Tables: 3, Equations: 1, References: 59, Pages: 11, Words: 8664
                Categories
                Neuroscience
                Original Research Article

                Neurosciences
                multi-center,t1,pd,mt,t2*,3t,mpm,qmri
                Neurosciences
                multi-center, t1, pd, mt, t2*, 3t, mpm, qmri

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