  Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in
vivo measurements of metabolism and is currently in human trials at 15 research
sites worldwide. With this growth it is important to adopt standardized data
storage practices as it will allow sites to meaningfully compare data.
  In this paper we (1) describe data that we believe should be stored and (2)
demonstrate pipelines and methods that utilize the Digital Imaging and
Communications in Medicine (DICOM) standard. This includes proposing a set of
minimum set of information that is specific to HP 13C MRI studies. We then show
where the majority of these can be fit into existing DICOM Attributes,
primarily via the "Contrast/Bolus" module.
  We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is
the most common standard for clinical medical image storage and provides the
flexibility to accommodate the unique aspects of HP 13C MRI, including the HP
agent information but also spectroscopic and metabolite dimensions. The
pipelines shown include creating DICOM objects for studies on human and animal
imaging systems with various pulse sequences. We also show a python-based
method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI
information that is not captured by existing pipelines. Moreover, we propose
best practices for HP 13C MRI data storage that will support future multi-site
trials, research studies and technical developments of this imaging technique.
