Estimation of fiber orientation and spin density distribution by diffusion deconvolution

Neuroimage. 2011 Apr 1;55(3):1054-62. doi: 10.1016/j.neuroimage.2010.11.087. Epub 2011 Jan 11.

Abstract

A diffusion deconvolution method is proposed to apply deconvolution to the diffusion orientation distribution function (dODF) and calculate the fiber orientation distribution function (fODF), which is defined as the orientation distribution of the fiber spin density. The dODF can be obtained from q-space imaging methods such as q-ball imaging (QBI), diffusion spectrum imaging (DSI), and generalized q-sampling imaging (GQI), and thus the method can be applied to various diffusion sampling schemes. A phantom study was conducted to compare the angular resolution of the fODF with the dODF, and the in vivo datasets were acquired using single-shell, two-shell, and grid sampling schemes, which were then reconstructed by QBI, GQI, and DSI, respectively. The phantom study showed that the fODF significantly improved the angular resolution over the dODF at 45- and 60-degree crossing angles. The in vivo study showed consistent fODF regardless of the applied sampling schemes and reconstruction methods, and the ability to resolve crossing fibers was improved in reduced sampling condition. The fiber spin density obtained from deconvolution showed a higher contrast-to-noise ratio than the fractional anisotropy (FA) mapping, and further application on tractography showed that the fiber spin density can be used to determine the termination of fiber tracts. In conclusion, the proposed deconvolution method is generally applicable to different q-space imaging methods. The calculated fODF improves the angular resolution and also provides a quantitative index of fiber spin density to refine fiber tracking.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Anisotropy
  • Brain Mapping / methods
  • Diffusion Magnetic Resonance Imaging / methods*
  • Diffusion Tensor Imaging
  • Humans
  • Image Processing, Computer-Assisted
  • Male
  • Models, Neurological
  • Models, Statistical
  • Nerve Fibers / physiology*
  • Phantoms, Imaging