Accelerating CEST MRI through complementary undersampling and multi-offset transformer reconstruction

Chemical exchange saturation transfer (CEST) is a promising magnetic resonance imaging (MRI) technique that provides molecular-level information in vivo. To obtain this unique contrast, repeated acquisition at multiple frequency offsets is needed, resulting a long scanning time. In this study, we propose a hybrid strategy at k-space and image domain to accelerate CEST MRI to facilitate its wider application. In k-space, we developed a complementary undersampling strategy which enforces adjacent frequency offsets by acquiring different subregions of k-space. Both Cartesian and spiral k-space trajectories were applied to validate its effectiveness. In the image domain, we developed a multi-offset transformer reconstruction network that uses complementary information from adjacent frequency offsets to improve reconstruction performance. Additionally, we introduced a data consistency layer to preserve undersampled k-space and a differentiable coil combination layer to leverage multi-coil information. The proposed method was evaluated on rodent brain and multi-coil human brain CEST images from both pre-clinical and clinical 3 T MRI scanners. Compared to fully-sampled images, our method outperforms a number of state-of-the-art CEST MRI reconstruction methods in both accuracy and image fidelity. CEST maps, including amide proton transfer (APT) and relayed nuclear Overhauser enhancement (rNOE), were calculated. The results also showed close agreement with fully-sampled ones.