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¹³C NMR: ¹H–¹³C Decoupling01:04

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Updated: Jun 27, 2025

Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging
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Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI.

Ernesto Diaz1, Renuka Sriram1, Jeremy W Gordon1

  • 1Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA.

Journal of Imaging Informatics in Medicine
|May 6, 2024
PubMed
Summary

Standardizing data storage for hyperpolarized (HP) 13C MRI is crucial for comparing results across research sites. This study proposes a minimum data set and demonstrates using the DICOM standard for HP 13C MRI data storage.

Keywords:
DICOM formatExperiment metadataHyperpolarized 13C MRIMetabolic imaging

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Area of Science:

  • Medical Imaging
  • Metabolic Imaging
  • Magnetic Resonance Imaging

Background:

  • Hyperpolarized (HP) 13C MRI is a promising technique for in vivo metabolic measurements.
  • Currently undergoing human trials at multiple global research sites, necessitating standardized data practices.
  • Meaningful data comparison across sites requires consistent data storage protocols.

Purpose of the Study:

  • To define a minimum data set for HP 13C MRI studies.
  • To demonstrate the utilization of the Digital Imaging and Communications in Medicine (DICOM) standard for HP 13C MRI data.
  • To propose best practices for HP 13C MRI data storage to support multi-site collaborations and technical advancements.

Main Methods:

  • Describing essential data elements for HP 13C MRI.
  • Adapting existing DICOM attributes, particularly the "Contrast/Bolus" module, to accommodate HP 13C MRI specific information.
  • Developing and demonstrating pipelines for creating DICOM objects for both human and animal HP 13C MRI studies using various pulse sequences.
  • Utilizing a Python-based method to modify DICOM objects for unique HP 13C MRI data not covered by standard pipelines.

Main Results:

  • A proposed minimum information set tailored for HP 13C MRI studies.
  • Demonstrated feasibility of integrating HP 13C MRI data, including agent information and spectroscopic/metabolite dimensions, into the DICOM standard.
  • Successful implementation of pipelines for DICOM object creation and modification for diverse HP 13C MRI imaging scenarios.
  • Validation of Python-based methods for efficient DICOM object enhancement.

Conclusions:

  • The DICOM standard offers the flexibility to store unique HP 13C MRI data, including metabolic and spectroscopic information.
  • Standardized data storage using DICOM is achievable and essential for the growth and comparability of multi-site HP 13C MRI research.
  • The proposed methods and best practices will facilitate future multi-site trials, research endeavors, and technological development in HP 13C MRI.