Hyperpolarized carbon (13C) MRI of the Kidneys: Basic Concept

Cornelius von Morze, Galen D. Reed, Zhen J. Wang, Michael A. Ohliger, Christoffer Laustsen

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

Existing clinical markers for renal disease are limited. Hyperpolarized (HP) 13C MRI is based on the technology of dissolution dynamic nuclear polarization (DNP) and provides new avenues for imaging kidney structure, function, and most notably, renal metabolism, addressing some of these prior limitations. Changes in kidney structure and function associated with kidney disease can be evaluated using [13C]urea, a metabolically inert tracer. Metabolic changes can be assessed using [1-13C]pyruvate and a range of other rapidly metabolized small molecules, which mainly probe central carbon metabolism. Results from numerous preclinical studies using a variety of these probes demonstrated that this approach holds great potential for monitoring renal disease, although more work is needed to bridge intelligently into clinical studies. Here we introduce the general concept of HP 13C MRI and review the most relevant probes and applications to renal disease, including kidney cancer, diabetic nephropathy and ischemic kidney injury. This chapter is based upon work from the PARENCHIMA COST Action, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages267-278
Number of pages12
DOIs
StatePublished - 2021

Publication series

NameMethods in Molecular Biology
Volume2216
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Carbon-13
  • Dynamic nuclear polarization
  • Kidney
  • Preclinical models

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