Comparative Systematic Analysis of Gray Matter Biophysical Models on a Public Dataset

Biophysical models of diffusion tailored to characterize gray matter (GM) microstructure are gaining traction in the neuroimaging community. NEXI, SMEX, SANDI, and SANDIX represent recent efforts to account for different microstructural features, such as soma contributions and inter-compartment exchange, in the diffusion MRI (dMRI) signal. The purpose of this work is to provide a comparative evaluation of these four GM diffusion models.

A comparative analysis of NEXI, SMEX, SANDI, and SANDIX was performed using a single, publicly available in vivo human dataset, the Connectome Diffusion Microstructure Dataset (CDMD), acquired with two diffusion times. Cortical microstructure metrics were estimated in 26 healthy subjects using the open-source Gray Matter Swiss Knife toolbox, and goodness of fit, anatomical patterns, and consistency with previous studies were evaluated.

CDMD data yielded GM parameter estimates consistent with values reported in previous studies across all four models. NEXI and SMEX produced similar cortical anatomical patterns, with consistent regional distributions across diffusion times. Goodness of fit varied across models, with NEXI showing the best fit, followed by SMEX, and finally SANDIX. SANDI parameter estimates showed strong dependence on diffusion-time selection and fitting algorithm.

This retrospective cross-model analysis establishes the feasibility of estimating exchange models from only two diffusion times and highlights trade-offs in biological specificity, model complexity, and fitting robustness, which are critical considerations when selecting a model for future clinical and research applications.