BACKGROUND: Equilibrium analysis to quantify dynamic positron emission tomography (PET) with bolus followed by continuous tracer infusion and acute amphetamine challenge assumes that all tissue kinetics attain steady states during pre- and post-challenge phases. Violations of this assumption may result in unreliable estimation of the amphetamine-induced percent change in the binding potential (DeltaBP%). METHOD: We derived an extended simplified reference tissue model (ESRTM) for modeling tracer kinetics in the pre- and post-challenge phases. Ninety-minute [11C]raclopride PET studies with bolus injection followed by continuous tracer infusion were performed on 18 monkeys and 2 baboons. Forty minutes after the bolus injection, a single acute intravenous amphetamine administration was given of 2.0 mg/kg to monkeys and of 0.05, 0.1, 0.5, and 1.5 mg/kg to baboons. Computer simulations further evaluated and characterized the ESRTM. RESULTS: In monkey studies, the DeltaBP% estimated by the ESRTM was 32+/-11, whereas, the DeltaBP% obtained using the equilibrium methods was 32% to 81% lower. In baboon studies, the DeltaBP% values estimated with the ESRTM showed a linear relationship between the DeltaBP% and the natural logarithm of amphetamine dose (R2=0.96), where the DeltaBP%=10.67Ln(dose)+33.79 (0.05<or=dose in mg/kg<or=1.5). At 1.5 mg/kg amphetamine, the DeltaBP% estimates from equilibrium methods were 18% to 40% lower than those estimated by the ESRTM. Results showed that the nonsteady state of tracer kinetics produced an underestimation of the DeltaBP% from the equilibrium analysis. The accuracy of the DeltaBP% estimates from the equilibrium analysis was significantly improved by the ESRTM. The DeltaBP% estimated by the ESRTM in the study was consistent with that from previous [11C] raclopride PET with amphetamine challenge. CONCLUSION: In conclusion, the ESRTM is a robust kinetic modeling approach and is proposed for the quantification of dynamic PET with acute amphetamine stimulation.
BACKGROUND: Equilibrium analysis to quantify dynamic positron emission tomography (PET) with bolus followed by continuous tracer infusion and acute amphetamine challenge assumes that all tissue kinetics attain steady states during pre- and post-challenge phases. Violations of this assumption may result in unreliable estimation of the amphetamine-induced percent change in the binding potential (DeltaBP%). METHOD: We derived an extended simplified reference tissue model (ESRTM) for modeling tracer kinetics in the pre- and post-challenge phases. Ninety-minute [11C]raclopride PET studies with bolus injection followed by continuous tracer infusion were performed on 18 monkeys and 2 baboons. Forty minutes after the bolus injection, a single acute intravenous amphetamine administration was given of 2.0 mg/kg to monkeys and of 0.05, 0.1, 0.5, and 1.5 mg/kg to baboons. Computer simulations further evaluated and characterized the ESRTM. RESULTS: In monkey studies, the DeltaBP% estimated by the ESRTM was 32+/-11, whereas, the DeltaBP% obtained using the equilibrium methods was 32% to 81% lower. In baboon studies, the DeltaBP% values estimated with the ESRTM showed a linear relationship between the DeltaBP% and the natural logarithm of amphetamine dose (R2=0.96), where the DeltaBP%=10.67Ln(dose)+33.79 (0.05<or=dose in mg/kg<or=1.5). At 1.5 mg/kg amphetamine, the DeltaBP% estimates from equilibrium methods were 18% to 40% lower than those estimated by the ESRTM. Results showed that the nonsteady state of tracer kinetics produced an underestimation of the DeltaBP% from the equilibrium analysis. The accuracy of the DeltaBP% estimates from the equilibrium analysis was significantly improved by the ESRTM. The DeltaBP% estimated by the ESRTM in the study was consistent with that from previous [11C] raclopride PET with amphetamine challenge. CONCLUSION: In conclusion, the ESRTM is a robust kinetic modeling approach and is proposed for the quantification of dynamic PET with acute amphetamine stimulation.
Authors: Yun Zhou; Susan M Resnick; Weiguo Ye; Hong Fan; Daniel P Holt; William E Klunk; Chester A Mathis; Robert Dannals; Dean F Wong Journal: Neuroimage Date: 2007-03-16 Impact factor: 6.556
Authors: Tomás R Guilarte; Neal C Burton; Jennifer L McGlothan; Tatyana Verina; Yun Zhou; Mohab Alexander; Luu Pham; Michael Griswold; Dean F Wong; Tore Syversen; Jay S Schneider Journal: J Neurochem Date: 2008-09-20 Impact factor: 5.372
Authors: Paul L Soto; Kristin M Wilcox; Yun Zhou; Anil Kumar; Nancy A Ator; Mark A Riddle; Dean F Wong; Michael R Weed Journal: Neuropsychopharmacology Date: 2012-07-18 Impact factor: 7.853
Authors: Ming-Kai Chen; Hiroto Kuwabara; Yun Zhou; Robert J Adams; James R Brasić; Jennifer L McGlothan; Tatyana Verina; Neal C Burton; Mohab Alexander; Anil Kumar; Dean F Wong; Tomás R Guilarte Journal: J Neurochem Date: 2007-11-05 Impact factor: 5.372