Fiber estimation and tractography in diffusion MRI: development of simulated brain images and comparison of multi-fiber analysis methods at clinical b-values.

Advances in diffusion-weighted magnetic resonance imaging (DW-MRI) have led to many alternative diffusion sampling strategies and analysis methodologies. A common objective among methods is estimation of white matter fiber orientations within each voxel, as doing so permits in-vivo fiber-tracking and the ability to study brain connectivity and networks. Knowledge of how DW-MRI sampling schemes affect fiber estimation accuracy, tractography and the ability to recover complex white-matter pathways, differences between results due to choice of analysis method, and which method(s) perform optimally for specific data sets, all remain important problems, especially as tractography-based studies become common.

Effect of Data Acquisition and Analysis Method on Fiber Orientation Estimation in Diffusion MRI.

In this paper we investigate the effect of single-shell q-space diffusion sampling strategies and applicable multiple-fiber analysis methods on fiber orientation estimation in Diffusion MRI. Specifically, we develop a simulation based on an in-vivo data set and compare a two-compartment "ball-and-stick" model, a constrained spherical deconvolution approach, a generalized Fourier transform approach, and three related methods based on transforms of Fourier data on the sphere. We evaluate each method for = 20, 30, 40, 60, 90 and 120 angular diffusion-weighted samples, at SNR = 18 and diffusion-weighting = 1000s/mm, common to clinical studies.