Metabolite-Specific Echo Planar Imaging for Preclinical Studies with Hyperpolarized 13 C-Pyruvate MRI.
Sule I SahinXiao JiShubhangi AgarwalAvantika SinhaIvina MaliJeremy W GordonMark MattinglySukumar SubramaniamJohn KurhanewiczPeder Eric Zufall LarsonRenuka SriramPublished in: Tomography (Ann Arbor, Mich.) (2023)
Metabolite-specific echo-planar imaging (EPI) sequences with spectral-spatial (spsp) excitation are commonly used in clinical hyperpolarized [1- 13 C]pyruvate studies because of their speed, efficiency, and flexibility. In contrast, preclinical systems typically rely on slower spectroscopic methods, such as chemical shift imaging (CSI). In this study, a 2D spspEPI sequence was developed for use on a preclinical 3T Bruker system and tested on in vivo mice experiments with patient-derived xenograft renal cell carcinoma (RCC) or prostate cancer tissues implanted in the kidney or liver. Compared to spspEPI sequences, CSI were found to have a broader point spread function via simulations and exhibited signal bleeding between vasculature and tumors in vivo. Parameters for the spspEPI sequence were optimized using simulations and verified with in vivo data. The expected lactate SNR and pharmacokinetic modeling accuracy increased with lower pyruvate flip angles (less than 15°), intermediate lactate flip angles (25° to 40°), and temporal resolution of 3 s. Overall SNR was also higher with coarser spatial resolution (4 mm isotropic vs. 2 mm isotropic). Pharmacokinetic modelling used to fit k PL maps showed results consistent with the previous literature and across different sequences and tumor xenografts. This work describes and justifies the pulse design and parameter choices for preclinical spspEPI hyperpolarized 13 C-pyruvate studies and shows superior image quality to CSI.
Keyphrases
- prostate cancer
- high resolution
- renal cell carcinoma
- contrast enhanced
- magnetic resonance
- image quality
- cell therapy
- systematic review
- magnetic resonance imaging
- computed tomography
- diffusion weighted imaging
- case control
- molecular dynamics
- gene expression
- single molecule
- big data
- metabolic syndrome
- deep learning
- dual energy
- adipose tissue
- amino acid
- radical prostatectomy
- mesenchymal stem cells
- type diabetes
- bone marrow