Elsevier

NeuroImage

Volume 90, 15 April 2014, Pages 163-178
NeuroImage

Plausibility Tracking: A method to evaluate anatomical connectivity and microstructural properties along fiber pathways

https://doi.org/10.1016/j.neuroimage.2014.01.002Get rights and content
Under a Creative Commons license
open access

Highlights

  • Framework to compare bundle specific parameters derived from dMRI across subjects

  • Introduction of a new global tractography method called “Plausibility Tracking”

  • Fast and reliable initialization through probabilistic tractography

  • More specific results compared to analysis with indices of diffusion tensor

Abstract

Diffusion MRI is a non-invasive method that potentially gives insight into the brain's white matter structure regarding the pathway of connections and properties of the axons.

Here, we propose a novel global tractography method named Plausibility Tracking that provides the most plausible pathway, modeled as a smooth spline curve, between two locations in the brain. Compared to other tractography methods, plausibility tracking combines the more complete connectivity pattern of probabilistic tractography with smooth tracks that are globally optimized using the fiber orientation density function and hence is relatively robust against local noise and error propagation. It has been tested on phantom and biological data and compared to other methods of tractography. Plausibility tracking provides reliable local directions all along the fiber pathways which makes it especially interesting for tract-based analysis in combination with direction dependent indices of diffusion MRI.

In order to demonstrate this potential of plausibility tracking, we propose a framework for the assessment and comparison of diffusion derived tissue properties. This framework comprises atlas-guided parameterization of tract representation and advanced bundle-specific indices describing fiber density, fiber spread and white matter complexity. We explore the new method using real data and show that it allows for a more specific interpretation of the white matter's microstructure compared to rotationally invariant indices derived from the diffusion tensor.

Abbreviations

MRI
magnetic resonance imaging
dMRI
diffusion magnetic resonance imaging
fODF
fiber orientation density function
FA
fractional anisotropy
MD
mean diffusivity
AD
axial diffusivity
RD
radial diffusivity
SD
spherical deconvolution
CSD
constrained spherical deconvolution
CHARMED
composite hindered and restricted model of diffusion
HARDI
high angular resolution diffusion imaging
FD
fiber density
AFD
angular fiber density
AFDmax
maximal angular fiber density
FS
fiber spread
GRAPPA
generalized auto calibrating partially parallel acquisitions
CC
corpus callosum
PFC
prefrontal cortex
BA45
Brodmann area 45
MC
motor cortex
ILF
inferior longitudinal fasciculus
SLF
superior longitudinal fasciculus
CR
corona radiate
IFOF
inferior fronto-occipital fasciculus
ROI
region of interest
MAD
median absolute deviation
MNI
Montreal Neurological Institute

Keywords

Diffusion MRI
Tract-based analysis
Tractography
Global tractography
Spherical deconvolution
Microstructural metrics
Fiber density

Cited by (0)