Optimizing the NEXI acquisition protocol for quantifying human gray matter microstructure on a clinical MRI scanner using Explainable AI

We optimized the acquisition protocol for parameter estimation of the NEXI model, suited to characterize gray matter microstructure, using concepts from Explainable AI. The improvement over a “naïve” protocol was only marginal. The limit on NEXI parameter estimation precision and accuracy is largely driven by the model and the type of measurements available (linear diffusion encoding, in a combination of (b,t) pairs) and is likely already reached as can be estimated from CRLB. The silver lining is that a clinical acquisition protocol feasible on a 3T system with 80 mT/m gradients yields reasonable NEXI microstructure maps in the human brain.