Synopsis

Microstructure imaging aims to infer brain tissue quantities using diffusion MRI. However, conventional diffusion MRI yields only a few observables with limited specificity. Multi-dimensional methods use additional acquisition dimensions to obtain new observables with higher specificity. Data acquired using multiple b-tensor shapes separate the effects of structural shape and variation in size. Data acquired using multiple echo times may separate the densities and T2 properties of tissue components. Microstructure modeling aims to increase specificity by interpreting the available data through a tissue model. Although modeling may complement multi-dimensional acquisitions, the approach stresses rather than replaces the need for independent data.