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Abstract #2853

A Novel Parallel Sparse MRSI Reconstruction Scheme

Ramin Eslami1, Mathews Jacob

1Biomedical Engineering, University of Rochester, Rochester, NY, United States

Recently, we proposed an efficient MRSI sparse reconstruction technique where we modeled the system using priors such as inhomogeneity, and brain and lipid masks estimated from a companion MR scan for the EPSI sequence using a single channel coil. Here, we propose a fast parallel MRSI acquisition scheme designed on a spiral trajectory. Using a 12-channel head coil, we acquire the in vivo MRSI data at spatial resolution of 4444 with a single average. We extend our sparse reconstruction scheme to parallel MRSI data on the spiral trajectory. This way, we efficiently reduce measurement noise and other artifacts such as field inhomogeneity and spectral leakage in our proposed reconstruction while we have a fast MRSI acquisition (~1"min" for a slice). We show that the proposed scheme could recover the spectral data and outperforms Tikhonov-regularized SENSE reconstruction. We also demonstrate a two-fold acceleration of the acquisition that leads to a comparable reconstruction.