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Radiology Research and Practice
Volume 2014, Article ID 871619, 10 pages
http://dx.doi.org/10.1155/2014/871619
Research Article

Multisite Kinetic Modeling of 13C Metabolic MR Using [1-13C]Pyruvate

1GE Global Research, 85748 Garching bei München, Germany
2Medical Engineering, Tecnológico de Monterrey, 64849 Monterrey, NL, Mexico
3Medical Engineering, Technische Universität München, 85748 Garching bei München, Germany
4Nuclear Medicine, Technische Universität München, 81675 Munich, Germany
5Chemistry, Technische Universität München, 85748 Garching bei München, Germany

Received 30 August 2014; Revised 6 November 2014; Accepted 13 November 2014; Published 8 December 2014

Academic Editor: David Maintz

Copyright © 2014 Pedro A. Gómez Damián et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Hyperpolarized 13C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1-13C]pyruvate and downstream metabolites [1-13C]alanine, [1-13C]lactate, and [13C]bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multisite, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multisite model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multisite model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues.