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Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI
Erick J Canales-Rodríguez1,2, Marco Pizzolato2,3, Feng-Lei Zhou4,5
1Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Purpose:
This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique.
Theory And Methods:
A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images.
Results:
Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes.
Conclusion:
The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.
Insights
Two MRI techniques accurately estimate fiber radii in biomimetic phantoms. The T2-based method is sensitive to smaller radii but requires calibration, while the power-law method overestimates sizes.
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.
