Clinical Soma and Neurite Density Imaging ( SANDI ): Translational Microstructure Mapping on Clinical 3T MRI Scanners

ABSTRACT Purpose The Soma and Neurite Density Imaging (SANDI) model enables characterization of gray matter (GM) microstructure by estimating soma and neurite signal fractions, but its clinical applicability is limited by the need for multi‐shell acquisitions (at least five b ‐values up to 6000 s/mm 2 ), requiring high‐gradient MRI systems. We developed a clinically feasible SANDI model that reduces data requirements and model complexity while preserving sensitivity to cellular‐level microstructural features. Methods Clinical SANDI incorporates biophysical constraints via fixed intra‐neurite diffusivity and a tortuosity relation from effective medium theory to estimate extracellular diffusivity from intracellular volume fractions, reducing the number of free parameters and data requirements. The model was validated using Monte Carlo diffusion simulations in GM‐like microenvironments and evaluated in vivo on the ultra‐high‐gradient 3 T Connectome 2.0 scanner ( G max = 500 mT/m, five‐shell, ∼19 min) and a clinical 3 T system ( G max = 80 mT/m, two‐shell, ∼7 min). Additional experiments across multiple gradient strengths, diffusion times, and sites assessed model robustness. Results Diffusion simulations showed close agreement (Pearson r = 0.99) between simulated and theoretical extracellular diffusivity across varying intracellular volume fractions. With 500 mT/m gradients, clinical SANDI using two shells demonstrated strong correspondence with five‐shell standard SANDI ( r = 0.97, intraclass correlation coefficient = 0.94). Across reduced gradient strengths, clinical SANDI preserved cortical intra‐soma signal fraction values, whereas standard SANDI exhibited underestimation at gradient strengths below 80 mT/m. Conclusion Clinical SANDI enables reliable cortical GM microstructure estimation on widely available clinical 3T scanners within feasible scan times, facilitating broader translation of advanced diffusion MRI methods for studying aging, neurodegeneration, and neurological disorders.