LAUSR

Dual-VENC strategies have been proposed to improve the velocity-to-noise ratio in phase-contrast MRI. However, they are based on aliasing-free high-VENC data. The aim of this paper is to propose a dual-VENC velocity estimation method allowing high-VENC aliased data. For this purpose, we reformulate the phase-contrast velocity as a least squares estimator, providing a natural framework for including multiple encoding gradient measurements. By analyzing the mathematical properties of both single- and dual-VENC problems, we can justify theoretically high/low-VENC ratios such that the aliasing velocity can be minimized. The resulting reconstruction algorithm was assessed using three types of data: numerical, experimental, and volunteers. In clinical practice, this method would allow shorter examination times by avoiding tedious adaptation of VENC values by repeated scans.