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Abstract #3471

Axonal fraction imaging on clinical and preclinical dMRI PGSE data

Thina Lundsgaard Thøgersen1,2, Tim B. Dyrby1,2, and Marco Pizzolato1,2
1Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark, 2Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark

Synopsis

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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