Quantifying human gray matter microstructure using NEXI and 300 mT/m gradients

Abstract

Biophysical models of diffusion tailored to quantify gray matter microstructure are gathering increasing interest. The two-compartment Neurite EXchange Imaging ($NEXI$) model has been proposed recently to account for neurites, extra-cellular space and exchange across the cell membrane. $NEXI$ parameter estimation requires multi-shell multi-diffusion time data and has so far only been implemented experimentally on animal data collected on a preclinical MRI set-up. In this work, the first ever translation of $NEXI$ to the human cortex in vivo was achieved using a 3T Connectom MRI system with 300 mT/m gradients, that enables the acquisition of a broad range of b-values (0 - 7.5 ms/$\mu m^{2}$) with a window of diffusion times (20 - 49 ms) suitable for the expected characteristic exchange times (10 - 50 ms). Microstructure estimates of four model variants: $NEXI$, $NEXI_{dot}$ (its extension with the addition of a dot compartment) and their respective versions that correct for the Rician noise floor ($NEXI_{RM}$ and $NEXI_{dot,RM}$) that particularly impacts high b-value signal, were compared. The reliability of estimates in each model variant was evaluated in synthetic and human in vivo data. In the latter, the intra-subject (scan-rescan) vs between-subjects variability of microstructure estimates were compared in the cortex. The better performance of $NEXI_{RM}$ highlights the importance of correcting for Rician bias in the $NEXI$ model to obtain accurate estimates of microstructure parameters in the human cortex, and the sensitivity of the $NEXI$ framework to individual differences in cortical microstructure. This groundbreaking application of $NEXI$ in humans marks a pivotal moment, unlocking new avenues for studying neurodevelopment, ageing, and various neurodegenerative disorders.