Design of optimal experimental parameters for diffusion-weighted MRI fibre-tracking protocols

摘要

Abstract. Diffusion-weighted imaging (DWI) has been shown to provide valuable structural information in biological fibrousnsoft tissues, such as the central and peripheral nervous system and skeletal muscle, based on the acquisition of a series ofnimages that sample q-space. Existing q-space sampling schemes have been compared using several metrics based on diffusionntensor imaging (DTI), which models the restricted diffusion inside fibres as anisotropic unrestricted diffusion. Otherwise,nsampling schemes have been optimized using model-independent cost functions. We propose using a model-based frameworknthat connects the experimental noise, the uncertainty in the estimation of the model parameters, and the q-space samplingnschemes together, to obtain model-based optimal sampling schemes for the case when the fibre orientation is known a priori tonbe within a finite region. We apply and validate this framework for the recently proposed quantitative analysis of q-space MRIndata (QUAQ) model.