Unifying b-tensor encoding with compartmental-exchange: A novel analysis framework applied to double diffusion encoding

Motivation: Microstructure imaging with diffusion MRI is substantially improved by going beyond single diffusion encoding, but the methods using such data are divergent. In particular, theories unifying b-tensor encoding and water exchange are lacking. Goal(s): To develop and validate a theory applicable for detecting microscopic anisotropy and diffusional exchange with encoding strategies going beyond conventional diffusion MRI. Approach: Theoretical predictions were compared with results from Monte Carlo simulations of diffusion in exchanging Gaussian environments. Results: Theory and simulations agreed well, except when violating the assumptions of the theory. We show when and why the diffusional kurtosis decrease and when it increases due to exchange. Impact: We identified a key condition in which exchange leads to increased signal. This condition is similar to that incorporated in neurite exchange models. Our work thus offers new experimental designs of relevance for microstructure imaging of gray matter.