Quantifying human gray matter microstructure using neurite exchange imaging (NEXI) and 300 mT/m gradients

Author:

Uhl Quentin12,Pavan Tommaso12,Molendowska Malwina3,Jones Derek K.3,Palombo Marco34,Jelescu Ileana Ozana12

Affiliation:

1. Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland

2. School of Biology and Medicine, University of Lausanne, Lausanne, Switzerland

3. Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom

4. School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom

Abstract

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 magnetic resonance imaging (MRI) set-up. In this work, the translation of NEXI to the human cortex in vivo was achieved using a 3 T Connectom MRI system with 300 mT/m gradients, that enables the acquisition of a broad range of b-values (0 – 7.5 ms/µm²) with a window covering short to intermediate diffusion times (20 – 49 ms) suitable for the characteristic exchange times (10 – 50 ms). Microstructure estimates of four model variants: NEXI, NEXIdot (its extension with the addition of a dot compartment), and their respective versions that correct for the Rician noise floor (NEXIRM and NEXIdot,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) versus between-subjects variability of microstructure estimates was compared in the cortex. The better performance of NEXIRM 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 application of NEXI in humans represents a significant step, unlocking new avenues for studying neurodevelopment, aging, and various neurodegenerative disorders.

Publisher

MIT Press

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