Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI.

Area of Science:

• Biomimetic imaging
• Neuroimaging techniques
• Diffusion-relaxation MRI

Background:

• Accurate fiber radius estimation is crucial for understanding tissue microstructure.
• Biomimetic phantoms mimicking hollow axons are valuable tools for validating MRI methods.
• Existing diffusion-relaxation MRI techniques have limitations in precise radius determination.

Purpose of the Study:

• To evaluate two distinct fiber radius estimation methods: spherical mean power-law and T2-based pore size estimation.
• To assess these techniques using diffusion-relaxation MRI data from microfiber phantoms.
• To compare the performance of these methods against ground truth radii.

Main Methods:

• Developed a general diffusion-relaxation theoretical model for spherical mean signal in cylinders.
• Introduced a novel numerical approach for estimating MRI-visible effective radii.
• Acquired ground truth radii distributions using scanning electron microscopy.

Main Results:

• Both methods demonstrated a linear correlation between estimated and ground truth fiber radii.
• The spherical mean power-law method tended to overestimate fiber radii.
• The T2-based method showed higher sensitivity to smaller radii but had limitations with specific phantoms.

Conclusions:

• Both evaluated techniques are feasible for predicting pore sizes in hollow microfibers.
• The T2-based method offers advantages by not requiring ultra-high diffusion gradients but needs calibration.
• This study advances neuroimaging by evaluating fiber radius estimation methods and providing reproducible datasets.