Coprime dual-VENC for extended velocity dynamic range in 4D Flow MRI.

Abstract

Background: In the field of cardiovascular imaging, 4D flow MRI provides non-invasive assessment of blood flow. Dual velocity encoding (dual-VENC) strategies have emerged to obtain quantitative information on both low and high blood flow velocities simultaneously. However, these strategies often encounter difficulties in coping with large velocity ranges. This work presents a dual-VENC 4D flow MRI sequence that utilizes the coprime rule to define the VENC ratio.

Methods: A dual-VENC 4D flow MRI sequence and reconstruction algorithm were developed and validated in vitro at two different field strengths, using a flow phantom generating realistic complex flow patterns. A digital twin of the phantom allowed comparison of the MRI measurements with computational fluid dynamics (CFD) simulations. Three patients with different cardiac pathologies were scanned in order to evaluate the in vivo feasibility of the proposed method.

Results: The results of the in vitro acquisitions demonstrated significant improvement in velocity-to-noise ratio (VNR) with respect to single-VENC acquisitions (110  ±  3%) and conventional dual-VENC de-aliasing approach (75  ±  3%). Furthermore, the effectiveness of aliasing correction was demonstrated even when both sets of images from the dual-VENC acquisition presented velocity aliasing artifacts. We observed a high degree of agreement between the measured and simulated velocity fields.

Conclusion: The strength of this approach lies in the fact that, unlike the conventional de-aliasing method, no data is discarded. The final image is obtained by a weighted average of the VENC_low and VENC_high datasets. Consequently, setting the value of the VENC_high to prevent aliasing is no longer necessary, and higher VNR gains are possible.