Local field of view imaging for alias-free undersampling with nonlinear spatial encoding magnetic fields

Abstract

Purpose: Nonlinear spatial encoding magnetic fields result in an inhomogeneous image resolution. Within this study, this characteristic property of nonlinear encoding is investigated with regard to its potential to accelerate MRI acquisitions.

Theory: A dependency between k-space coverage and local resolvability of the image causes k-space samples to have a spatially localized contribution to the reconstruction of the spin density. On the basis of this observation, a concept for alias-free data undersampling is developed, which is referred to as the local field of view concept.

Methods: On the basis of this concept, a fast sampling trajectory is developed. It is evaluated with simulations and experiments (both using a phantom and in vivo) for MRI with, as an example, pure quadrupolar encoding fields. To demonstrate that the concept is only applicable to (spatially) nonlinear encoding, a comparison with linear encoding is provided.

Results: Application of the local field of view concept results in a localized adaptation of the image resolution by undersampling higher frequency k-space samples without introducing aliasing.

Conclusions: A new effect of nonlinear spatial encoding magnetic fields was found, which allows more efficient data sampling and at the same time counterbalancing the natural variation in image resolution.