Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2015
Quantification of 11C-Laniquidar Kinetics in the Brain.
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Froklage Femke E, Boellaard Ronald, Bakker Esther, Hendrikse N Harry, Reijneveld Jaap C, Schuit Robert C, Windhorst Albert D, Schober Patrick, van Berckel Bart N M, Lammertsma Adriaan A, Postnov Andrey
Аннотация
UNLABELLED: Overexpression of the multidrug efflux transport P-glycoprotein may play an important role in pharmacoresistance. (11)C-laniquidar is a newly developed tracer of P-glycoprotein expression. The aim of this study was to develop a pharmacokinetic model for quantification of (11)C-laniquidar uptake and to assess its test-retest variability.
METHODS: Two (test-retest) dynamic (11)C-laniquidar PET scans were obtained in 8 healthy subjects. Plasma input functions were obtained using online arterial blood sampling with metabolite corrections derived from manual samples. Coregistered T1 MR images were used for region-of-interest definition. Time-activity curves were analyzed using various plasma input compartmental models.
RESULTS: (11)C-laniquidar was metabolized rapidly, with a parent plasma fraction of 50% at 10 min after tracer injection. In addition, the first-pass extraction of (11)C-laniquidar was low. (11)C-laniquidar time-activity curves were best fitted to an irreversible single-tissue compartment (1T1K) model using conventional models. Nevertheless, significantly better fits were obtained using 2 parallel single-tissue compartments, one for parent tracer and the other for labeled metabolites (dual-input model). Robust K1 results were also obtained by fitting the first 5 min of PET data to the 1T1K model, at least when 60-min plasma input data were used. For both models, the test-retest variability of (11)C-laniquidar rate constant for transfer from arterial plasma to tissue (K1) was approximately 19%.
CONCLUSION: The accurate quantification of (11)C-laniquidar kinetics in the brain is hampered by its fast metabolism and the likelihood that labeled metabolites enter the brain. Best fits for the entire 60 min of data were obtained using a dual-input model, accounting for uptake of (11)C-laniquidar and its labeled metabolites. Alternatively, K1 could be obtained from a 5-min scan using a standard 1T1K model. In both cases, the test-retest variability of K1 was approximately 19%.
METHODS: Two (test-retest) dynamic (11)C-laniquidar PET scans were obtained in 8 healthy subjects. Plasma input functions were obtained using online arterial blood sampling with metabolite corrections derived from manual samples. Coregistered T1 MR images were used for region-of-interest definition. Time-activity curves were analyzed using various plasma input compartmental models.
RESULTS: (11)C-laniquidar was metabolized rapidly, with a parent plasma fraction of 50% at 10 min after tracer injection. In addition, the first-pass extraction of (11)C-laniquidar was low. (11)C-laniquidar time-activity curves were best fitted to an irreversible single-tissue compartment (1T1K) model using conventional models. Nevertheless, significantly better fits were obtained using 2 parallel single-tissue compartments, one for parent tracer and the other for labeled metabolites (dual-input model). Robust K1 results were also obtained by fitting the first 5 min of PET data to the 1T1K model, at least when 60-min plasma input data were used. For both models, the test-retest variability of (11)C-laniquidar rate constant for transfer from arterial plasma to tissue (K1) was approximately 19%.
CONCLUSION: The accurate quantification of (11)C-laniquidar kinetics in the brain is hampered by its fast metabolism and the likelihood that labeled metabolites enter the brain. Best fits for the entire 60 min of data were obtained using a dual-input model, accounting for uptake of (11)C-laniquidar and its labeled metabolites. Alternatively, K1 could be obtained from a 5-min scan using a standard 1T1K model. In both cases, the test-retest variability of K1 was approximately 19%.