Variable density sampling based on physically plausible gradient waveform. Application to 3D MRI angiography

TL;DR

This paper introduces a new gradient waveform design method for variable density MRI sampling that respects hardware constraints, enabling efficient implementation of complex trajectories for improved 3D angiography.

Contribution

A novel gradient waveform design approach based on projecting trajectories onto hardware constraints, facilitating practical implementation of variable density sampling in MRI.

Findings

Efficient trajectory traversal with high curvature areas

Implementation of TSP-based trajectories in MRI

Successful application to 3D mouse brain angiography

Abstract

Performing k-space variable density sampling is a popular way of reducing scanning time in Magnetic Resonance Imaging (MRI). Unfortunately, given a sampling trajectory, it is not clear how to traverse it using gradient waveforms. In this paper, we actually show that existing methods [1, 2] can yield large traversal time if the trajectory contains high curvature areas. Therefore, we consider here a new method for gradient waveform design which is based on the projection of unrealistic initial trajectory onto the set of hardware constraints. Next, we show on realistic simulations that this algorithm allows implementing variable density trajectories resulting from the piecewise linear solution of the Travelling Salesman Problem in a reasonable time. Finally, we demonstrate the application of this approach to 2D MRI reconstruction and 3D angiography in the mouse brain.