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dc.contributor.authorShetty, Anil N.
Chiang, Sharon
Maletic-Savatic, Mirjana
Kasprian, Gregor
Vannucci, Marina
Lee, Wesley
dc.date.accessioned 2017-08-17T19:19:42Z
dc.date.available 2017-08-17T19:19:42Z
dc.date.issued 2014
dc.identifier.citation Shetty, Anil N., Chiang, Sharon, Maletic-Savatic, Mirjana, et al.. "Spatial mapping of translational diffusion coefficients using diffusion tensor imaging: A mathematical description." Concepts in Magnetic Resonance Part A, 43, no. 1 (2014) Wiley: 1-27. https://doi.org/10.1002/cmr.a.21288.
dc.identifier.urihttps://hdl.handle.net/1911/97342
dc.description.abstract In this article, we discuss the theoretical background for diffusion weighted imaging and diffusion tensor imaging. Molecular diffusion is a random process involving thermal Brownian motion. In biological tissues, the underlying microstructures restrict the diffusion of water molecules, making diffusion directionally dependent. Water diffusion in tissue is mathematically characterized by the diffusion tensor, the elements of which contain information about the magnitude and direction of diffusion and is a function of the coordinate system. Thus, it is possible to generate contrast in tissue based primarily on diffusion effects. Expressing diffusion in terms of the measured diffusion coefficient (eigenvalue) in any one direction can lead to errors. Nowhere is this more evident than in white matter, due to the preferential orientation of myelin fibers. The directional dependency is removed by diagonalization of the diffusion tensor, which then yields a set of three eigenvalues and eigenvectors, representing the magnitude and direction of the three orthogonal axes of the diffusion ellipsoid, respectively. For example, the eigenvalue corresponding to the eigenvector along the long axis of the fiber corresponds qualitatively to diffusion with least restriction. Determination of the principal values of the diffusion tensor and various anisotropic indices provides structural information. We review the use of diffusion measurements using the modified Stejskal–Tanner diffusion equation. The anisotropy is analyzed by decomposing the diffusion tensor based on symmetrical properties describing the geometry of diffusion tensor. We further describe diffusion tensor properties in visualizing fiber tract organization of the human brain.
dc.language.iso eng
dc.publisher Wiley
dc.rights This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Wiley.
dc.title Spatial mapping of translational diffusion coefficients using diffusion tensor imaging: A mathematical description
dc.type Journal article
dc.citation.journalTitle Concepts in Magnetic Resonance Part A
dc.subject.keyworddiffusion
diffusion anisotropy
diffusion tensor
tractography
dc.citation.volumeNumber 43
dc.citation.issueNumber 1
dc.identifier.digital Spatial_Mapping_Translational_Diffusion_Coefficients
dc.type.dcmi Text
dc.identifier.doihttps://doi.org/10.1002/cmr.a.21288
dc.identifier.pmcid PMC4948124
dc.type.publication post-print
dc.citation.firstpage 1
dc.citation.lastpage 27


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