Non-contrast MRA (NC-MRA) is emerging as an alternative test for patients with poor renal function. Compared with contrast-enhanced MRA, NC-MRA has the added advantage of repeat scanning as needed. We have developed the quadruple inversion-recovery (QIR) NC-MRA method to image the aortoiliac arteries using multiple inversion recovery preparations and balanced steady-state of free precession readout (1) and evaluated its performance in patients with peripheral arterial disease (2). The scan time of QIR with respiratory gating, however, is on the order of 10-15 minutes, depending on the patient’s breathing pattern and rate. For clinical translation, we sought to accelerate QIR using 3D radial stack-of-stars k-space sampling with compressed sensing (CS) and compare its performance versus original QIR using parallel imaging.

All imaging was performed on a 3T scanner (Tim Trio, Siemens). To determine limits of acceleration factors (R), we performed a numerical simulation experiment, where a fully sampled data set was retrospectively undersampled according to Figure 1. We tested three different acceleration strategies: (i) radial with R = 5.3, (ii) radial with R = 10.7, and (iii) radial with R = 16. We note that QIR requires a consistent inversion time for each kz plane, so we designed R to be multiples (sans small rounding) of previously published R = 2.7 using parallel imaging. For image reconstruction performed offline in Matlab, for each sampling pattern, coil sensitivity maps were self-calibrated from the densely sampled center of k-space (3). CS reconstruction was performed using non-local means (NLM) (4,5), which is a popular denoising filter that is applicable for CS. Image reconstruction was performed with 50 iterations with normalized NLM weight of 0.7 and normalized fidelity weight of 0.7, where normalization is based on maximum value. These weights were determined empirically based on visual inspection of training data. Based on visual inspection of images shown in Figure 1, prospective acceleration was limited to R=5.3 and 10.6.

For prospective imaging, 6 healthy volunteers (3 male, 3 female, mean age = 39+/-13) and 4 patients (2 male, 2 female, mean age = 63+/-8) with diagnosed aortoiliac disease were imaged after obtaining IRB-approved informed consent, with the original QIR with R = 2.7 and accelerated QIR with R=5.3 and 10.6. Other than the acceleration factors, all QIR NC-MRA pulse sequences used identical parameters: spatial resolution 1.3 x 1.3 x 1.7 mm, TR = 1 respiratory cycle, flip angle = 100°, inversion time = 1600 ms, and respiratory gating. Arterial vessel dimensions were measured at 4 locations as shown in Figure 2 (see arrows). Vessel dimensions were compared using analysis of variance (ANOVA), and with Bonferroni correction to compare each pair with original QIR as control. We also measured normalized signal difference [(vessel-background)/vessel] as a surrogate for contrast-to-noise ratio (CNR) at these locations. Note that true CNR is not easily measurable from GRAPPA and CS reconstructed data.

Mean scan time was 14.6 ± 2.9 minutes, 7.2 ± 1.8 minutes, and 3.7 ± 0.7 minutes for GRAPPA and CS R=5.3 and R=10.6 acquisitions, respectively. Representative maximum intensity projection images are shown in Figure 2. Radial QIR with R=5.3 produced images that are comparable to GRAPPA QIR with R = 2.7, whereas radial QIR with R = 10.6 produced noticeably lower image quality. Normalized signal difference results and vessel dimensions results were not significantly different (p > 0.05) at all levels (see Tables 1 and 2), likely due to low sample size (n=10).We have demonstrated feasibility of 5.3-fold accelerated QIR using 3D radial stack-of-star with CS, enabling 2-fold additional acceleration compared with previously described GRAPPA QIR with R = 2.7. Further study is warranted to determine optimal CS constraints and diagnostic performance in patients with aortic disease.