Dynamic hyperpolarized 13C MR spectroscopic imaging using SPICE in mouse kidney at 9.4 T #DNPNMR

Song, Jae Eun, Jaewook Shin, Hansol Lee, Young‐Suk Choi, Ho‐Taek Song, and Dong‐Hyun Kim. “Dynamic Hyperpolarized 13C MR Spectroscopic Imaging Using SPICE in Mouse Kidney at 9.4 T.” NMR in Biomedicine, December 19, 2019.


This study aims to investigate the feasibility of dynamic hyperpolarized 13C MR spectroscopic imaging (MRSI) using the SPectroscopic Imaging by exploiting spatiospectral CorrElation (SPICE) technique and an estimation of the spatially resolved conversion constant rate (kpl). An acquisition scheme comprising a single training dataset and several imaging datasets was proposed considering hyperpolarized 13C circumstances. The feasibility and advantage of the scheme were investigated in two parts: (a) consistency of spectral basis over time and (b) accuracy of the estimated kpl. The simulations and in vivo experiments support accurate kpl estimation with consistent spectral bases. The proposed method was implemented in an enzyme phantom and via in vivo experiments. In the enzyme phantom experiments, spatially resolved homogeneous kpl maps were observed. In the in vivo experiments, normal diet (ND) mice and high-fat diet (HFD) mice had kpl (s−1) values of medullar (ND: 0.0119 ± 0.0022, HFD: 0.0195 ± 0.0005) and cortical (ND: 0.0148 ±0.0023, HFD: 0.0224 ±0.0054) regions which were higher than vascular (ND: 0.0087 ±0.0013, HFD: 0.0132 ±0.0050) regions. In particular, the kpl value in the medullar region exhibited a significant difference between the two diet groups. In summary, the feasibility of using modified SPICE for dynamic hyperpolarized 13C MRSI was demonstrated via simulations and in vivo experiments. The consistency of spectral bases over time and the accuracy of the estimated kpl values validate the proposed acquisition scheme, which comprises only a single training dataset. The proposed method improved the spatial resolution of dynamic hyperpolarized 13C MRSI, which could be used for kpl estimation using high signal-to-noise ratio spectral bases.

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