Estimation of diffusion properties in crossing fiber bundles.
There is an ongoing debate on how to model diffusivity in fiber crossings. We propose an optimization framework for the selection of a dual tensor model and the set of diffusion weighting parameters b, such that both the diffusion shape and orientation parameters can be precisely as well as accurately estimated. For that, we have adopted the Cramér-Rao lower bound (CRLB) on the variance of the model parameters, and performed Monte Carlo simulations. We have found that the axial diffusion lambda(parallel) needs to be constrained, while an isotropic fraction can be modeled by a single parameter f(iso). Under these circumstances, the Fractional Anisotropy (FA) of both tensors can theoretically be independently estimated with a precision of 9% (at SNR = 25). Levenberg-Marquardt optimization of the Maximum Likelihood function with a Rician noise model approached this precision while the bias was insignificant. A two-element b-vector b = [1.0 3.5] x 10(3) mm(-2)s was found to be sufficient for estimating parameters of heterogeneous tissue with low error. This has allowed us to estimate consistent FA-profiles along crossing tracts. This work defines fundamental limits for comparative studies to correctly analyze crossing white matter structures.
Caan
Matthan W A
MW
Delft University of Technology, Imaging Science and Technology, 2628 CJ Delft, The Netherlands. m.w.a.caan@tudelft.nl
Khedoe
H Ganesh
HG
Poot
Dirk H J
DH
den Dekker
Arjan J
AJ
Olabarriaga
Silvia D
SD
Grimbergen
Kees A
KA
van Vliet
Lucas J
LJ
Vos
Frans M
FM
D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D009010:Monte Carlo Method; D009412:Nerve Fibers / Q000502:physiology*; D016011:Normal Distribution; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted