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Purpose: This study aims to evaluate two distinct approaches for fibre radiusestimation using diffusion-relaxation MRI data acquired in biomimeticmicrofibre phantoms that mimic hollow axons. The methods considered are thespherical mean power-law approach and a T2-based pore size estimationtechnique. Theory and Methods: A general diffusion-relaxation theoretical modelfor the spherical mean signal from water molecules within a distribution ofcylinders with varying radii was introduced, encompassing the evaluated modelsas particular cases. Additionally, a new numerical approach was presented forestimating effective radii (i.e., MRI-visible mean radii) from the ground truthradii distributions, not reliant on previous theoretical approximations andadaptable to various acquisition sequences. The ground truth radii wereobtained from Scanning Electron Microscope images. Results: Both methods show alinear relationship between effective radii estimated from MRI data andground-truth radii distributions, though some discrepancies were observed. Thespherical mean power-law method overestimated fibre radii. Conversely, theT2-based method exhibited higher sensitivity to smaller fibre radii but facedlimitations in accurately estimating the radius in one particular phantom,possibly due to material-specific relaxation changes. Conclusion: The studydemonstrates the feasibility of both techniques to predict pore sizes of hollowmicrofibres. The T2-based technique, unlike the spherical mean power-lawmethod, does not demand ultra-high diffusion gradients but requires calibrationwith known radius distributions. This research contributes to the ongoingdevelopment and evaluation of neuroimaging techniques for fibre radiusestimation, highlights the advantages and limitations of both methods andprovides datasets for reproducible research.

Pore size estimation in axon-mimicking microfibres with diffusion-relaxation MRI