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Research ArticleBasic Science Investigations

Quantification of Brain Glucose Metabolism by 18F-FDG PET with Real-Time Arterial and Image-Derived Input Function in Mice

Malte F. Alf, Matthias T. Wyss, Alfred Buck, Bruno Weber, Roger Schibli and Stefanie D. Krämer
Journal of Nuclear Medicine January 2013, 54 (1) 132-138; DOI: https://doi.org/10.2967/jnumed.112.107474
Malte F. Alf
1Center for Radiopharmaceutical Sciences of ETH, PSI, and USZ, Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
2Laboratory of Functional and Metabolic Imaging, Institute of Physics of Biological Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Matthias T. Wyss
3Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
4Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland; and
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Alfred Buck
3Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
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Bruno Weber
4Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland; and
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Roger Schibli
1Center for Radiopharmaceutical Sciences of ETH, PSI, and USZ, Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
5Center for Radiopharmaceutical Sciences of ETH, PSI, and USZ, Paul Scherrer Institute PSI, Villigen, Switzerland
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Stefanie D. Krämer
1Center for Radiopharmaceutical Sciences of ETH, PSI, and USZ, Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
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Abstract

Kinetic modeling of PET data derived from mouse models remains hampered by the technical inaccessibility of an accurate input function (IF). In this work, we tested the feasibility of IF measurement with an arteriovenous shunt and a coincidence counter in mice and compared the method with an image-derived IF (IDIF) obtained by ensemble-learning independent component analysis of the heart region. Methods: 18F-FDG brain kinetics were quantified in 2 mouse strains, CD1 and C57BL/6, using the standard 2-tissue-compartment model. Fits obtained with the 2 IFs were compared regarding their goodness of fit as assessed by the residuals, fit parameter SD, and Bland–Altman analysis. Results: On average, cerebral glucose metabolic rate was 10% higher for IDIF-based quantification. The precision of model parameter fitting was significantly higher using the shunt-based IF, rendering the quantification of single process rate constants feasible. Conclusion: We demonstrated that the arterial IF can be measured in mice with a femoral arteriovenous shunt. This technique resulted in higher precision for kinetic modeling parameters than did use of the IDIF. However, for longitudinal or high-throughput studies, the use of a minimally invasive IDIF based on ensemble-learning independent component analysis represents a suitable alternative.

  • energy metabolism
  • PET
  • molecular imaging
  • glucose
  • kinetic modeling

Footnotes

  • Published online Nov. 15, 2012.

  • © 2013 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
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Journal of Nuclear Medicine: 54 (1)
Journal of Nuclear Medicine
Vol. 54, Issue 1
January 1, 2013
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Quantification of Brain Glucose Metabolism by 18F-FDG PET with Real-Time Arterial and Image-Derived Input Function in Mice
Malte F. Alf, Matthias T. Wyss, Alfred Buck, Bruno Weber, Roger Schibli, Stefanie D. Krämer
Journal of Nuclear Medicine Jan 2013, 54 (1) 132-138; DOI: 10.2967/jnumed.112.107474

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Quantification of Brain Glucose Metabolism by 18F-FDG PET with Real-Time Arterial and Image-Derived Input Function in Mice
Malte F. Alf, Matthias T. Wyss, Alfred Buck, Bruno Weber, Roger Schibli, Stefanie D. Krämer
Journal of Nuclear Medicine Jan 2013, 54 (1) 132-138; DOI: 10.2967/jnumed.112.107474
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Keywords

  • energy metabolism
  • PET
  • Molecular Imaging
  • glucose
  • kinetic modeling
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