Introduction
P-glycoprotein (P-gp) mediated transport across the blood-brain barrier (BBB) may play an important role in several neurological disorders. Although racemic [11C]verapamil has been used for assessing P-gp function 1 , potential difference in kinetics between both isomers dictates the use of an optically pure tracer for quantitative studies. Verapamil can be metabolised through N-demethylation and N-dealkylation, with labelled metabolites amounting to ∼70% of total plasma activity one hour p.i. in rats 2 . N-dealkylated metabolites, which have high lipophilicity and are similar to verapamil itself, probably undergo rapid brain uptake and, unlike N-demethylated metabolites, probably also show affinity for P-gp. The aim of the present work was to study the kinetics of (R)-[11C]verapamil in humans and to develop a pharmacokinetic model for the analysis of P-gp mediated transport of (R)-[11C]verapamil, incorporating the contribution of its radioactive metabolites.
Methods
Dynamic PET scans (60 minutes) were acquired in ten healthy volunteers (mean age 43, range 21–68) following intravenous injection of ∼370 MBq (R)-[11C]verapamil. Six volunteers were scanned twice on the same day for test-retest analysis. During the scan arterial blood was monitored continuously and additional samples were taken for metabolite analysis. Total plasma, parent verapamil, HPLC (N-dealkylation) metabolite and polar (N-demethylation) metabolite input curves were determined. PET images were segmented based on co-registered MRI data. Whole brain grey matter data were analysed with various reversible one or two tissue compartment models, with separate metabolite compartments, assuming that either only verapamil or verapamil and any combination of metabolites cross the BBB, and using Logan analysis with a single input function either corrected or not corrected for one or both of the metabolites.
Results
Metabolites due to N-dealkylation and N-demethylation each represented 20 to 30% of total plasma radioactivity at 1 h p.i. Fit results are given in the table 1. Most models fitted the data well and the Akaike criterion did not point to a definite ‘best’ model, with differences in optimal model between subjects. The lowest mean test-retest variability (2.9 %) was found for a single tissue model without any metabolite correction. There was good agreement between the results of the Logan analysis and those of the corresponding compartment models.
V = verapami
M1 = N-dealkylation metabolites (HPLC)
M2 = N-demethylation metabolites (polar fraction)
xT = number of tissure compartments
Conclusion
Based on rat data, metabolites of (R)-[11C]verapamil are likely to cross the BBB. However, a compartment model including separate metabolite compartments leads to high test-retest variability. This is probably due to the statistical uncertainty of the parent fraction and HPLC metabolite data, as well as the increased number of model parameters. Assuming similar kinetics for (R)-[11C] verapamil and HPLC metabolites, a one input, one tissue model with correction for polar metabolites only leads to a good compromise between fit quality and test-retest variability. Further studies into the kinetics of the radioactive metabolites of (R)-[11C]verapamil are necessary to define the biologically most correct model.