Accelerated 4D flow imaging using randomly undersampled echo planer imaging with compressed-sensing reconstruction

Abstract

Background 4D flow imaging using phase contrast CMR (PC CMR) allows visualization and quantification of blood flow. One of the major limitations of 4D flow imaging is its long scan time (in the order of 10-20 min). In this study, we sought to investigate an accelerate 4D flow imaging sequence that combines an efficient data sampling strategy using echo planar imaging (EPI) with randomly undersampled 3D k-space sampling pattern. The randomly undersampled k-space data are then reconstructed using compressed sensing (CS). Methods Figure 1 shows the k-space acquisition strategy. Similar to regular EPI acquisition, the k-space data are divided into multiple segments. For each segment, the profiles are undersampled with the CS rate such that all EPI segments have the same undersampling pattern. The proposed EPI random sampling strategy was implemented. Seven subjects were recruited (26 ± 12 years; 3 males) for 4D flow CMR on a 1.5T Philips Achieva magnet. Images were acquired axially using a GRE sequence (FOV =3 40 ×2 80 ×6 0 mm 3 ,r esolution =2× 2×3m m 3 ,T R/TE/a = 7.4/3.8 ms/20°, EPI factor = 3, Turbo Factor =2 , CS rate =3 ) in av olume covering the ascending and descending aorta, and the aortic bifurcation. Only foot-head flow encoding was used to provide an adequate temporal resolution of 30 ms for the measurements. A single beam navigator placed on the right hemi-diaphragm was used to gate the acquisition with the respiratory cycle. The nominal scan time for this scan was 3:30 minutes at 70 bpm assuming 100% gating efficiency (vs. 8:40 minutes if standard parallel imaging with rate 4 was used). For each subject, the 4D-PC scan was followed by a standard breath-hold 2D-PC scan with the same flow encoding direction (FOV = 340 × 280 mm2, resolution = 2 × 2 mm 2 , slice thickness = 5 mm 3 , SENSE rate = 2.5). The acquired 2D slice is selected from the previously obtained 4D scan and approximately at the aortic bifurcation. Data are then transferred to a separate station where the CS reconstruction was performed using a total variation minimization algorithm. Next, flow quantifications were performed on both the ascending and the descending aorta for all acquisitions and then compared between the 2D scans and the corresponding slices in the 4D scans.