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Gómez Damián PA, Sperl JI, Janich MA, et al. Multisite Kinetic Modeling of (13)C Metabolic MR Using [1-(13)C]Pyruvate. Radiol Res Pract. 2014;2014:871619doi: 10.1155/2014/871619.
Gómez Damián, P. A., Sperl, J. I., Janich, M. A., Khegai, O., Wiesinger, F., Glaser, S. J., Haase, A., Schwaiger, M., Schulte, R. F., & Menzel, M. I. (2014). Multisite Kinetic Modeling of (13)C Metabolic MR Using [1-(13)C]Pyruvate. Radiology research and practice, 2014871619. https://doi.org/10.1155/2014/871619
Gómez Damián, Pedro A, et al. "Multisite Kinetic Modeling of (13)C Metabolic MR Using [1-(13)C]Pyruvate." Radiology research and practice vol. 2014 (2014): 871619. doi: https://doi.org/10.1155/2014/871619
Gómez Damián PA, Sperl JI, Janich MA, Khegai O, Wiesinger F, Glaser SJ, Haase A, Schwaiger M, Schulte RF, Menzel MI. Multisite Kinetic Modeling of (13)C Metabolic MR Using [1-(13)C]Pyruvate. Radiol Res Pract. 2014;2014:871619. doi: 10.1155/2014/871619. Epub 2014 Dec 08. PMID: 25548671; PMCID: PMC4274847.
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Radiol Res Pract. 2014;2014:871619. doi: 10.1155/2014/871619. Epub 2014 Dec 08.

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

Radiology research and practice

Pedro A Gómez Damián, Jonathan I Sperl, Martin A Janich, Oleksandr Khegai, Florian Wiesinger, Steffen J Glaser, Axel Haase, Markus Schwaiger, Rolf F Schulte, Marion I Menzel

Affiliations

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

PMID: 25548671 PMCID: PMC4274847 DOI: 10.1155/2014/871619

Abstract

Hyperpolarized (13)C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1-(13)C]pyruvate and downstream metabolites [1-(13)C]alanine, [1-(13)C]lactate, and [(13)C]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.

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