Keywords: Microstructure, Microstructure, Diffusion
Motivation: We wish to quantify the amount of axons in the brain using clinically-feasible in vivo human diffusion MRI.
Goal(s): We want to estimate the axonal signal fraction using the conventional pulsed gradient spin echo (PGSE) sequence while reducing model degeneracy and minimizing modeling assumptions.
Approach: We model spherical harmonic (SH) coefficients across two high b-value PGSE shells. We calculate ratios between SH l-band power spectra across the shells, relate them analytically to the axonal diffusivities - estimated using machine learning - and with these we calculate the axonal signal fraction.
Results: We report comparable results across preclinical and clinical data and demonstrate methodological feasibility.
Impact: The axonal signal fraction is proportional to the total volume of axons within a voxel and can be used to characterize pathology. This work proposes its estimation with clinically-feasible b-values and with conventional diffusion MRI data while minimizing modeling assumptions.
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