Axonal T₂ estimation using the spherical variance of the strongly diffusion-weighted MRI signal

Abstract

In magnetic resonance imaging, the application of a strong diffusion weighting suppresses the signal contributions from the less diffusion-restricted constituents of the brain’s white matter, thus enabling the estimation of the transverse relaxation time T2 that arises from the more diffusion-restricted constituents such as the axons. However, the presence of cell nuclei and vacuoles can confound the estimation of the axonal T2, as diffusion within those structures is also restricted, causing the corresponding signal to survive the strong diffusion weighting. We devise an estimator of the axonal T2 based on the directional spherical variance of the strongly diffusion-weighted signal. The spherical variance T2 estimates are insensitive to the presence of isotropic contributions to the signal like those provided by cell nuclei and vacuoles. We show that with a strong diffusion weighting these estimates differ from those obtained using the directional spherical mean of the signal which contains both axonal and isotropically-restricted contributions. Our findings hint at the presence of an MRI-visible isotropically-restricted contribution to the signal in the white matter ex vivo fixed tissue (monkey) at 7T, and do not allow us to discard such a possibility also for in vivo human data collected with a clinical 3T system.

Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology

“…Hence, most axon radii are below the lower bound for detection (Edgar and Griffiths, 2014;Dyrby et al, 2018). For an overview of the different strategies that have been employed to measure axon radius with dMRI, the reader is referred to Assaf and Basser (2005), Assaf et al (2008Assaf et al ( , 2013, Alexander et al (2010Alexander et al ( , 2019 Dyrby et al (2013Dyrby et al ( , 2018, Novikov et al (2019), Fan et al (2020), Jelescu et al (2020), Veraart et al (2020), Barakovic et al (2021a), Pizzolato et al (2023).…”