Toward faster inference of micron-scale axon diameters using Monte Carlo simulations

Area of Science:

• Neuroimaging
• Biophysics

Background:

• Oscillating gradient (OG) diffusion MRI advances enable micron-scale axon diameter inference.
• Reducing scan time is crucial for clinical feasibility of these advanced MRI techniques.

Purpose of the Study:

• To investigate the impact of reduced image acquisition on the precision of axon diameter measurements using OG diffusion MRI.
• To determine optimal parameters for efficient and accurate axon diameter estimation.

Main Methods:

• Monte Carlo simulations of cosine OG sequences were performed using a two-compartment model.
• Simulations utilized parallel cylinder geometry with diameters ranging from 1-5 μm.
• Temporal diffusion spectroscopy was employed to infer axon diameters under varying gradient strengths and frequencies.

Main Results:

• Five frequencies were sufficient for accurate diameter inference (3-5 μm) in single-sized and larger effective diameter distributions.
• Increased precision for smaller diameters (1-2 μm) was observed with 10 frequencies.
• Fewer frequencies, particularly at higher gradient strengths, yielded the greatest precision improvements.

Conclusions:

• Axon diameter measurements using OG diffusion MRI can maintain precision with reduced frequencies and gradient strengths.
• Optimizing acquisition parameters can significantly decrease imaging time, enhancing clinical applicability of OG diffusion MRI.