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Am J Physiol Endocrinol Metab 281: E524-E536, 2001;
0193-1849/01 $5.00
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Vol. 281, Issue 3, E524-E536, September 2001

Kinetic modeling of [18F]FDG in skeletal muscle by PET: a four-compartment five-rate-constant model

A. Bertoldo1, P. Peltoniemi2,3, V. Oikonen2, J. Knuuti2, P. Nuutila2,3, and C. Cobelli1

1 Department of Electronics and Informatics, University of Padova, Padua 35131, Italy; and 2 Turku PET Centre and 3 Department of Medicine, University of Turku, F-20520 Turku, Finland

Various modeling strategies have been developed to convert regional [18F]fluorodeoxyglucose ([18F]FDG) concentration measured by positron emission tomography (PET) to a measurement of physiological parameters. However, all the proposed models have been developed and tested mostly for brain studies. The purpose of the present study is to select the most accurate model for describing [18F]FDG kinetics in human skeletal muscle. The database consists of basal and hyperinsulinemic-euglycemic studies performed in normal subjects. PET data were first analyzed by an input-output modeling technique (often called spectral analysis). These results provided guidelines for developing a compartmental model. A new model with four compartments and five rate constants (5K model) emerged as the best. By accounting for plasma and extracellular and intracellular kinetics, this model allows, for the first time, PET assessment of the individual steps of [18F]FDG kinetics in human skeletal muscle, from plasma to extracellular space to transmembrane transport into the cell to intracellular phosphorylation. Insulin is shown to affect transport and phosphorylation but not extracellular kinetics, with the transport step becoming the main site of control. The 5K model also allows definition of the domain of validity of the classic three-compartment three- or four-rate-constant models. These models are candidates for an investigative tool to quantitatively assess insulin control on individual metabolic steps in human muscle in normal and physiopathological states.

positron emission tomography; parameter estimation; glucose; compartmental model; insulin


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