Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T...

Relationships between diffusion-weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange?

Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity $$ / $$ , and clinical protocols (single diffusion encoding; maximum b-value: {1000, 1500, 2000} s/mm² ; 5 unique gradient duration/separation pairs; SNR = { $$ , 100, 80, 40, 20}), accounting for heterogeneity in $$ and perfusion contamination. Diffusion ( $$ ) and kurtosis ( $$ ) coefficients were calculated, and relationships between $$ and $$ were visualized. Functions mapping $$ to $$ were computed to predict unseen $$ values, tested for their ability to classify discrete cell-size contrasts, and deployed on 9.4T ex vivo MRI-histology data of fixed mouse livers RESULTS: Relationships between $$ and $$ are complex and depend on the diffusion encoding. Functions mapping $$ to $$ captures salient characteristics of $$ and $$ dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three-class cell-size classification task (for SNR = 20, $$ = 1500 s/mm² , $$ = 20 ms, and $$ = 75 ms). MRI detects cell-size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes.

Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible.