LAUSR

PURPOSE To propose an acceleration method for 3D variable flip-angle (VFA) T1 mapping based on a technique called shift undersampling improves parametric mapping efficiency and resolution (SUPER). METHODS The proposed method incorporates strategies of SUPER, controlled aliasing in volumetric parallel imaging (CAIPIRINHA), and total variation-based regularization to accelerate 3D VFA T1 mapping. The k-space sampling grid of CAIPIRINHA is internally undersampled with SUPER along the contrast dimension. A proximal algorithm was developed to preserve the computational efficiency of SUPER in the presence of regularization. The regularized SUPER-CAIPIRINHA (rSUPER-CAIPIRINHA) was compared with low rank plus sparsity (L + S), reconstruction of principal component coefficient maps (REPCOM), and other SUPER-based methods via simulations and in vivo brain T1 mapping. The results were assessed quantitatively with NRMSE and structural similarity index measure (SSIM), and qualitatively by two experienced reviewers. RESULTS rSUPER-CAIPIRINHA achieved a lower NRMSE and higher SSIM than L + S (0.11 ± 0.01 vs. 0.19 ± 0.03, p < 0.001; 0.66 ± 0.05 vs. 0.37 ± 0.03, p < 0.001) and REPCOM (0.16 ± 0.02, p < 0.001; 0.46 ± 0.04, p < 0.001). The reconstruction time of rSUPER-CAIPIRINHA was 6% of L + S and 2% of REPCOM. For the qualitative comparison, rSUPER-CAIPIRINHA showed improvement of overall image quality and reductions of artifacts and blurring, although with a lower apparent SNR. Compared with 2D SUPER-SENSE, rSUPER-CAIPIRINHA significantly reduced NRMSE (0.11 ± 0.01 vs. 0.23 ± 0.04, p < 0.001) and generated less noisy reconstructions. CONCLUSION By incorporating SUPER, CAIPIRINHA, and regularization, rSUPER-CAIPIRINHA mitigated noise amplification, reduced artifacts and blurring, and achieved faster reconstructions compared with L + S and REPCOM. These advantages render 3D rSUPER-CAIPIRINHA VFA T1 mapping potentially useful for clinical applications.