Literature DB >> 12210909

Orientational diffusion reflects fiber structure within a voxel.

Elisabeth A H von dem Hagen1, R Mark Henkelman.   

Abstract

Several new MR techniques have been introduced to infer direction through diffusion in multiple nerve fiber bundles within a voxel. To date, however, there has been no physical model reported to evaluate these methodologies and their ability to determine fiber orientation. In this article a model of diffusion analogous to nerve fibers is presented. Diffusion measurements at multiple closely spaced angles of 15 degrees in samples with different fiber orientations are compared with theoretical calculations for restricted diffusion in cylindrical geometry. Orientational diffusion measurements are shown to reflect fiber geometry and theoretical predictions to within 10%. Simulations of fiber crossings within a voxel suggest fiber orientation does not correspond to the direction of the largest measured diffusion coefficient, but theoretical knowledge of signal decay curves can predict the shape of these diffusion coefficient contours for given fiber orientation probabilities. Copyright 2002 Wiley-Liss, Inc.

Mesh:

Year:  2002        PMID: 12210909     DOI: 10.1002/mrm.10250

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  17 in total

1.  Deviations from the diffusion tensor model as revealed by contour plot visualization using high angular resolution diffusion-weighted imaging (HARDI).

Authors:  Jochen G Hirsch; Stefanie M Schwenk; Christina Rossmanith; Michael G Hennerici; Achim Gass
Journal:  MAGMA       Date:  2003-06-12       Impact factor: 2.310

2.  Flexible ex vivo phantoms for validation of diffusion tensor tractography on a clinical scanner.

Authors:  Makoto Watanabe; Shigeki Aoki; Yoshitaka Masutani; Osamu Abe; Naoto Hayashi; Tomohiko Masumoto; Harushi Mori; Hiroyuki Kabasawa; Kuni Ohtomo
Journal:  Radiat Med       Date:  2006-11-24

3.  A novel tensor distribution model for the diffusion-weighted MR signal.

Authors:  Bing Jian; Baba C Vemuri; Evren Ozarslan; Paul R Carney; Thomas H Mareci
Journal:  Neuroimage       Date:  2007-05-03       Impact factor: 6.556

Review 4.  Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook.

Authors:  Els Fieremans; Hong-Hsi Lee
Journal:  Neuroimage       Date:  2018-06-18       Impact factor: 6.556

5.  Diffeomorphic image registration of diffusion MRI using spherical harmonics.

Authors:  Xiujuan Geng; Thomas J Ross; Hong Gu; Wanyong Shin; Wang Zhan; Yi-Ping Chao; Ching-Po Lin; Norbert Schuff; Yihong Yang
Journal:  IEEE Trans Med Imaging       Date:  2010-12-03       Impact factor: 10.048

6.  Optimum b value for resolving crossing fibers: a study with standard clinical b value using 1.5-T MR.

Authors:  Kentaro Akazawa; Kei Yamada; Shigenori Matsushima; Mariko Goto; Sachiko Yuen; Tsunehiko Nishimura
Journal:  Neuroradiology       Date:  2010-03-23       Impact factor: 2.804

7.  Uncertainty Visualization in HARDI based on Ensembles of ODFs.

Authors:  Fangxiang Jiao; Jeff M Phillips; Yaniv Gur; Chris R Johnson
Journal:  IEEE Pac Vis Symp       Date:  2012-12-31

8.  Adaptive kernels for multi-fiber reconstruction.

Authors:  Angelos Barmpoutis; Bing Jian; Baba C Vemuri
Journal:  Inf Process Med Imaging       Date:  2009

9.  Hand preference and sex shape the architecture of language networks.

Authors:  Patric Hagmann; Leila Cammoun; Roberto Martuzzi; Philippe Maeder; Stephanie Clarke; Jean-Philippe Thiran; Reto Meuli
Journal:  Hum Brain Mapp       Date:  2006-10       Impact factor: 5.038

10.  Anisotropic phantom to calibrate high-q diffusion MRI methods.

Authors:  M E Komlosh; D Benjamini; A S Barnett; V Schram; F Horkay; A V Avram; P J Basser
Journal:  J Magn Reson       Date:  2016-11-30       Impact factor: 2.229

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.