Estimation and removal of spurious echo artifacts in single-voxel MRS using sensitivity encoding

In localized MRS, spurious echo artifacts commonly occur when unsuppressed signal outside the volume of interest is excited and refocused. In the spectral domain, these signals often overlap with metabolite resonances and hinder accurate quantification. Because the artifacts originate from regions separate from the target MRS voxel, this work proposes that sensitivity encoding based on receive-coil sensitivity profiles may be used to separate these signal contributions.

Numerical simulations were performed to explore the effect of sensitivity-encoded separation for unknown artifact regions. An imaging-based approach was developed to identify regions that may contribute to spurious echo artifacts, and tested for sensitivity-based unfolding of signal on six data sets from three brain regions. Spectral data reconstructed using the proposed method ("ERASE") were compared with the standard coil combination.

The method was able to fully unfold artifact signals if regions were known a priori. Mismatch between estimated and true artifact regions reduced the efficiency of removal, yet metabolite signals were unaffected. Water suppression imaging was able to identify regions of unsuppressed signal, and ERASE (from up to eight regions) led to visible removal of artifacts relative to standard reconstruction. Fitting errors across major metabolites were also lower; for example, Cramér-Rao lower bounds of myo-inositol were 13.7% versus 17.5% for ERASE versus standard reconstruction, respectively.

The ERASE reconstruction tool was demonstrated to reduce spurious echo artifacts in single-voxel MRS. This tool may be incorporated into standard workflows to improve spectral quality when hardware limitations or other factors result in out-of-voxel signal contamination.