RESUMEN
This study aims to investigate the feasibility of dynamic hyperpolarized 13 C 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 13 C 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 13 C 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 13 C MRSI, which could be used for kpl estimation using high signal-to-noise ratio spectral bases.
Asunto(s)
Algoritmos , Espectroscopía de Resonancia Magnética con Carbono-13 , Riñón/diagnóstico por imagen , Animales , Dieta Alta en Grasa , Enzimas/metabolismo , Ratones , Fantasmas de ImagenRESUMEN
PURPOSE: To improve signal-to-noise ratio (SNR) for high-resolution spectroscopic imaging using a subspace-based technique known as SPectroscopic Imaging by exploiting spatiospectral CorrElation (SPICE). METHODS: The proposed method is based on a union-of-subspaces model of MRSI signals, which exploits the partial separability properties of water, lipid, baseline and metabolite signals. Enabled by this model, a special scheme is used for accelerated data acquisition, which includes a double-echo CSI component used to collect a "training" dataset (for determination of the basis functions) and a short-TE EPSI component used to collect a sparse "imaging" dataset (for determination of the overall spatiospectral distributions). A set of signal processing algorithms are developed to remove the water and lipid signals and jointly reconstruct the metabolite and baseline signals. RESULTS: In vivo 1 H-MRSI results show that the proposed method can effectively remove the remaining water and lipid signals from sparse MRSI data acquired at 20 ms TE. Spatiospectral distributions of metabolite signals at 2 mm in-plane resolution with good SNR were obtained in a 15.5 min scan. CONCLUSIONS: The proposed method can effectively remove nuisance signals and reconstruct high-resolution spatiospectral functions from sparse data to make short-TE SPICE possible. The method should prove useful for high-resolution 1 H-MRSI of the brain. Magn Reson Med 77:467-479, 2017. © 2016 International Society for Magnetic Resonance in Medicine.