110
views
0
recommends
+1 Recommend
1 collections
    7
    shares
      • Record: found
      • Abstract: found
      • Article: found

      Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ)

      research-article
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Normal ageing is associated with characteristic changes in brain microstructure. Although in vivo neuroimaging captures spatial and temporal patterns of age-related changes of anatomy at the macroscopic scale, our knowledge of the underlying (patho)physiological processes at cellular and molecular levels is still limited. The aim of this study is to explore brain tissue properties in normal ageing using quantitative magnetic resonance imaging (MRI) alongside conventional morphological assessment. Using a whole-brain approach in a cohort of 26 adults, aged 18–85 years, we performed voxel-based morphometric (VBM) analysis and voxel-based quantification (VBQ) of diffusion tensor, magnetization transfer (MT), R1, and R2* relaxation parameters. We found age-related reductions in cortical and subcortical grey matter volume paralleled by changes in fractional anisotropy (FA), mean diffusivity (MD), MT and R2*. The latter were regionally specific depending on their differential sensitivity to microscopic tissue properties. VBQ of white matter revealed distinct anatomical patterns of age-related change in microstructure. Widespread and profound reduction in MT contrasted with local FA decreases paralleled by MD increases. R1 reductions and R2* increases were observed to a smaller extent in overlapping occipito-parietal white matter regions. We interpret our findings, based on current biophysical models, as a fingerprint of age-dependent brain atrophy and underlying microstructural changes in myelin, iron deposits and water. The VBQ approach we present allows for systematic unbiased exploration of the interaction between imaging parameters and extends current methods for detection of neurodegenerative processes in the brain. The demonstrated parameter-specific distribution patterns offer insights into age-related brain structure changes in vivo and provide essential baseline data for studying disease against a background of healthy ageing.

          Research highlights

          ►High-resolution FLASH-based parameter mapping is suitable for clinical purposes. ►Patterns of age-dependent parameter changes reflect specificity to tissue properties. ►Combining VBM and VBQ offers complementary information about brain architecture.

          Related collections

          Most cited references90

          • Record: found
          • Abstract: found
          • Article: not found

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging.

              Diffusion tensor imaging is often performed by acquiring a series of diffusion-weighted spin-echo echo-planar images with different direction diffusion gradients. A problem of echo-planar images is the geometrical distortions that obtain near junctions between tissues of differing magnetic susceptibility. This results in distorted diffusion-tensor maps. To resolve this we suggest acquiring two images for each diffusion gradient; one with bottom-up and one with top-down traversal of k-space in the phase-encode direction. This achieves the simultaneous goals of providing information on the underlying displacement field and intensity maps with adequate spatial sampling density even in distorted areas. The resulting DT maps exhibit considerably higher geometric fidelity, as assessed by comparison to an image volume acquired using a conventional 3D MR technique.
                Bookmark

                Author and article information

                Journal
                Neuroimage
                Neuroimage
                Neuroimage
                Academic Press
                1053-8119
                1095-9572
                15 April 2011
                15 April 2011
                : 55
                : 4
                : 1423-1434
                Affiliations
                [a ]LREN, Département des Neurosciences Cliniques, CHUV, Université de Lausanne, Lausanne, Switzerland
                [b ]Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
                [c ]Mind Brain Institute, Charité and Humboldt University, Berlin, Germany
                [d ]Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, UCL, London, UK
                [e ]Neuroimaging Laboratory, IRCCS Fondazione Santa Lucia, Rome, Italy
                [f ]MR-Research in Neurology and Psychiatry, University Medical Centre, Göttingen, Germany
                Author notes
                [* ]Corresponding author at: LREN, Département des Neurosciences Cliniques, CHUV, Université de Lausanne, Lausanne, Switzerland. Fax: + 41 21 314 1220. bogdan.draganski@ 123456gmail.com
                [1]

                Both authors contributed equally to the study.

                Article
                YNIMG8020
                10.1016/j.neuroimage.2011.01.052
                3093621
                21277375
                a4d38e65-f8f3-4a39-b553-a3e3a45e068f
                © 2011 Elsevier Inc.

                This document may be redistributed and reused, subject to certain conditions.

                History
                : 8 July 2010
                : 17 January 2011
                : 20 January 2011
                Categories
                Article

                Neurosciences
                dti,magnetization transfer,r1,mean diffusivity,fractional anisotropy,voxel-based quantification,voxel-based morphometry,r2*

                Comments

                Comment on this article