Hyperpolarized 13C MRI Data Acquisition and Analysis in Prostate and Brain at UCSF

Based on the expanding set of applications for hyperpolarized carbon-13 (HP- 13 C) MRI, this work aims to communicate standardized methodology implemented at our institution (UCSF) as a primer for conducting reproducible metabolic imaging studies of the prostate and brain. Current state-of-the-art HP- 13 C acquisition, data processing/reconstruction, and kinetic modeling approaches utilized in patient studies are presented together with the rationale underpinning their usage. Organized around spectroscopic and imaging-based methods, this guide provides an extensible framework for handling a variety of HP- 13 C applications, which derives from two examples with dynamic acquisitions: 3D echo-planar spectroscopic imaging (EPSI) of the human prostate and frequency-specific 2D multi-slice echo-planar imaging (EPI) of the human brain. Details of sequence-specific parameters and processing techniques contained in these examples should enable investigators to effectively tailor studies around individual use cases. Given the importance of clinical integration in improving the utility of HP exams, practical aspects of standardizing data formats for reconstruction, analysis and visualization are also addressed alongside open-source software packages that enhance institutional interoperability and validation of methodology. To facilitate the adoption and further development of this methodology, example datasets and analysis pipelines have been made available via hyperlinks to the Supplementary Material. This work describes standardized hyperpolarized carbon-13 (HP- 13 C) MRI methodology implemented at UCSF for prostate and brain exams as a primer for conducting reproducible metabolic imaging studies of the prostate and brain. Data processing, reconstruction, and kinetic modeling approaches utilized in patient studies are presented together with the rationale underpinning their usage. Practical aspects of standardizing data formats for analysis and visualization are described and accompanied by supplementary material that includes open-source software packages, example datasets and analysis pipelines.