Pharmacokinetic Modeling
Molecular imaging of neurotransmitter receptors with PET allows to acquiring quantitative data. This is an extremely important option for brain research to measure non-invasively chemical parameters in the living brain. This method is largely dependent on a successful pharmacokinetic modeling. Dynamic imaging data are necessary to model binding processes at receptor levels and to quantify them. In general, pharmacokinetics describes all processes and changes a drug is involved in while being transported and metabolized in an organism (absorption, distribution, metabolism, excretion and its mathematical description).
PET allows to measure the concentration of a radioligand and its radioactive metabolites in the brain. By collecting blood samples at the same time the concentration in blood plasma can be determined and related to the brain concentrations. This allows drawing conclusions about the density of receptors in the human brain in different regions.
Fig. 1: Example of so called time-activity curves (A) from different brain regions reflecting the distribution of the ligand. Activity in blood plasma (B) allows the calibration and quantification of the data. Kinetics of the baseline (filled marks) and a MPEP blockade experiment (open marks) of a representative control rat: (A) Relative time-activity curves of a high binding region (caudate-putamen) and the reference region (cerebellum) normalized by injected dose and body weight. (B) Metabolite-corrected plasma time-activity curves (boxes, left y-axis) and fraction of non-metabolized ligand (circles, right y-axis). The dashed lines represent the respective fits. The small insert shows the plasma peak in the first minutes. Plasma activities are normalized to injected dose and body weight.
Fig. 2: Example of application of the radioligand in a combined bolus plus constant infusion experiment. This method of application leads to a steady state after about 50 min which allows to perform interventional experiments by administering a second drug in high doses that compete for the same receptors without affecting blood flow.
Fig. 3: Example of a linearization model. The slope of the curve corresponds to the distribution volume which is again directly proportional to the receptor density.