RT info:eu-repo/semantics/article
T1 HYDI-DSI revisited: Constrained non-parametric EAP imaging without q-space re-gridding
A1 Tristán Vega, Antonio
A1 Pieciak, Tomasz
A1 París Bandrés, Guillem
A1 Rodríguez Galván, Justino Rafael
A1 Aja Fernández, Santiago
A1 Tristán-Vega, Antonio
A1 París, Guillem
A1 Rodríguez-Galván, Justino R.
A1 Aja-Fernández, Santiago
K1 Hybrid Diffusion Imaging (HYDI)
K1 Imagen de Difusión Híbrida (HYDI)
K1 Magnetic Resonance Imaging (MRI)
K1 Imagen por Resonancia Magnética (MRI)
AB Hybrid Diffusion Imaging (HYDI) was one of the first attempts to use multi-shell samplings of the q-space to infer diffusion properties beyond Diffusion Tensor Imaging (DTI) or High Angular Resolution Diffusion Imaging (HARDI). HYDI was intended as a flexible protocol embedding both DTI (for lower -values) and HARDI (for higher -values) processing, as well as Diffusion Spectrum Imaging (DSI) when the entire data set was exploited. In the latter case, the spherical sampling of the q-space is re-gridded by interpolation to a Cartesian lattice whose extent covers the range of acquired b-values, hence being acquisition-dependent. The Discrete Fourier Transform (DFT) is afterwards used to compute the corresponding Cartesian sampling of the Ensemble Average Propagator (EAP) in an entirely non-parametric way. From this lattice, diffusion markers such as the Return To Origin Probability (RTOP) or the Mean Squared Displacement (MSD) can be numerically estimated.We aim at re-formulating this scheme by means of a Fourier Transform encoding matrix that eliminates the need for q-space re-gridding at the same time it preserves the non-parametric nature of HYDI-DSI. The encoding matrix is adaptively designed at each voxel according to the underlying DTI approximation, so that an optimal sampling of the EAP can be pursued without being conditioned by the particular acquisition protocol. The estimation of the EAP is afterwards carried out as a regularized Quadratic Programming (QP) problem, which allows to impose positivity constraints that cannot be trivially embedded within the conventional HYDI-DSI. We demonstrate that the definition of the encoding matrix in the adaptive space allows to analytically (as opposed to numerically) compute several popular descriptors of diffusion with the unique source of error being the cropping of high frequency harmonics in the Fourier analysis of the attenuation signal. They include not only RTOP and MSD, but also Return to Axis/Plane Probabilities (RTAP/RTPP), which are defined in terms of specific spatial directions and are not available with the former HYDI-DSI. We report extensive experiments that suggest the benefits of our proposal in terms of accuracy, robustness and computational efficiency, especially when only standard, non-dedicated q-space samplings are available.
PB Elsevier
SN 1361-8415
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/57986
UL https://uvadoc.uva.es/handle/10324/57986
LA eng
NO Medical Image Analysis, 2023,  Volume 84, 102728
NO Producción Científica
DS UVaDOC
RD 30-may-2024