Abstract
PURPOSE: To develop an effective method for correcting head motion in high-resolution, non-water-suppressed MRSI. METHODS: MRSI scans are susceptible to subject motion due to the long data acquisition time required for sufficient spatial-spectral encodings. The problem is more serious in non-water-suppressed MRSI experiments since motion artifacts in the water and lipid signals make their removal even more challenging. To address this problem, we propose a novel motion correction method that detects and discards motion-corrupted k-space data using TR-wise linear navigators. The discarded data are replaced with reconstructed data obtained by reformulating motion correction as a missing data reconstruction problem using sensitivity encodings. Extrinsic priors for water and lipid signals and intrinsic priors for metabolite signals are incorporated in the motion correction process. We evaluated its performance on a spectroscopic phantom and three human groups: (1) five healthy adults performing three different voluntary motion patterns; (2) a healthy child; and (3) a cerebral hemorrhage patient with involuntary movements. RESULTS: In phantom and healthy subjects, the proposed method produced high-quality water images and metabolite maps that closely matched motion-free references, with 10%-20% quantitative gains in image/map quality (higher PSNR/SSIM, lower NRMSE). In the child and patient data, motion artifacts were noticeably reduced, with 20%-30% reductions in NAA linewidth and fitting error in the child, and ˜50% reductions in coefficient-of-variation in the patient. CONCLUSION: An effective motion-correction technique has been developed for high-resolution non-water-suppressed MRSI. This method has the potential to significantly enhance the robustness and clinical applicability of non-water-suppressed MRSI.