Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI
Ernesto Diaz, Renuka Sriram, Jeremy W. Gordon, Avantika Sinha, Xiaoxi, Liu, Sule Sahin, Jason Crane, Marram P Olson, Hsin-Yu Chen, Jenna Bernard,, Daniel B. Vigneron, Zhen Jane Wang, Duan Xu, Peder E. Z. Larson

TL;DR
This paper proposes standardized data storage practices and demonstrates DICOM integration for hyperpolarized 13C MRI to facilitate multi-site research and clinical trials.
Contribution
It introduces a set of data standards and pipelines for incorporating HP 13C MRI data into DICOM, enhancing data consistency and sharing.
Findings
Defined minimal data requirements for HP 13C MRI
Developed DICOM pipelines for human and animal studies
Created a Python tool for customizing DICOM objects
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
