Comparison of 3D orientation distribution functions measured with confocal microscopy and diffusion MRI

Neuroimage. 2016 Apr 1:129:185-197. doi: 10.1016/j.neuroimage.2016.01.022. Epub 2016 Jan 21.

Abstract

The ability of diffusion MRI (dMRI) fiber tractography to non-invasively map three-dimensional (3D) anatomical networks in the human brain has made it a valuable tool in both clinical and research settings. However, there are many assumptions inherent to any tractography algorithm that can limit the accuracy of the reconstructed fiber tracts. Among them is the assumption that the diffusion-weighted images accurately reflect the underlying fiber orientation distribution (FOD) in the MRI voxel. Consequently, validating dMRI's ability to assess the underlying fiber orientation in each voxel is critical for its use as a biomedical tool. Here, using post-mortem histology and confocal microscopy, we present a method to perform histological validation of orientation functions in 3D, which has previously been limited to two-dimensional analysis of tissue sections. We demonstrate the ability to extract the 3D FOD from confocal z-stacks, and quantify the agreement between the MRI estimates of orientation information obtained using constrained spherical deconvolution (CSD) and the true geometry of the fibers. We find an orientation error of approximately 6° in voxels containing nearly parallel fibers, and 10-11° in crossing fiber regions, and note that CSD was unable to resolve fibers crossing at angles below 60° in our dataset. This is the first time that the 3D white matter orientation distribution is calculated from histology and compared to dMRI. Thus, this technique serves as a gold standard for dMRI validation studies - providing the ability to determine the extent to which the dMRI signal is consistent with the histological FOD, and to establish how well different dMRI models can predict the ground truth FOD.

Keywords: Crossing fibers; DTI; Diffusion MRI; Fiber orientation distribution; Validation.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Animals
  • Brain / anatomy & histology*
  • Brain Mapping / methods*
  • Diffusion Magnetic Resonance Imaging / methods*
  • Image Processing, Computer-Assisted / methods
  • Imaging, Three-Dimensional / methods*
  • Microscopy, Confocal / methods*
  • Saimiri