Diffusion orientation transform revisited.
Diffusion orientation transform (DOT) is a powerful imaging technique that allows the reconstruction of the microgeometry of fibrous tissues based on diffusion MRI data. The three main error sources involving this methodology are the finite sampling of the q-space, the practical truncation of the series of spherical harmonics and the use of a mono-exponential model for the attenuation of the measured signal. In this work, a detailed mathematical description that provides an extension to the DOT methodology is presented. In particular, the limitations implied by the use of measurements with a finite support in q-space are investigated and clarified as well as the impact of the harmonic series truncation. Near- and far-field analytical patterns for the diffusion propagator are examined. The near-field pattern makes available the direct computation of the probability of return to the origin. The far-field pattern allows probing the limitations of the mono-exponential model, which suggests the existence of a limit of validity for DOT. In the regimen from moderate to large displacement lengths the isosurfaces of the diffusion propagator reveal aberrations in form of artifactual peaks. Finally, the major contribution of this work is the derivation of analytical equations that facilitate the accurate reconstruction of some orientational distribution functions (ODFs) and skewness ODFs that are relatively immune to these artifacts. The new formalism was tested using synthetic and real data from a phantom of intersecting capillaries. The results support the hypothesis that the revisited DOT methodology could enhance the estimation of the microgeometry of fiber tissues.
Canales-Rodríguez
Erick Jorge
EJ
Benito Menni Complex Assistencial en Salut Mental, Barcelona, Spain.
Lin
Ching-Po
CP
Iturria-Medina
Yasser
Y
Yeh
Chun-Hung
CH
Cho
Kuan-Hung
KH
Melie-García
Lester
L
D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005583:Fourier Analysis; D008962:Models, Theoretical; D019047:Phantoms, Imaging