Noninvasive determination of the arterial input function of an anticancer drug from dynamic PET scans using the...

For the application of a kinetic model to PET data, it is generally necessary to obtain the arterial input function (AIF). It was the aim of the present study to introduce a method suitable for the determination of the AIF of a substance that undergoes biochemical transformation from noisy PET data: the population approach. F-18 labeled 5-fluorouracil (5-[18F]FU) was administered i.v. to eight patients suffering from liver metastases of colorectal carcinoma. Radioactivity concentrations in liver and aorta were dynamically measured with PET over 120 min. Pharmacokinetic analysis was carried out by applying a five-compartment model to individual activity-time data for the eight patients or to the mean activity-time data among the eight patients. The mean values of all parameters describing 5-FU transport and catabolism, i.e., volumes of distribution and clearances, as well as interindividual coefficients of variation (CV) were calculated according to both approaches. With our model, we were able to separate the concentration-time course of 5-FU in plasma, i.e., the AIF, from that of its major catabolite alpha-fluoro-beta-alanine (FBAL). As far as the mean parameter estimates are concerned, the differences between both approaches are not significant. For the liver data, the CV's are almost the same for both approaches. For the parameters concerning the aorta, however, there is a decrease in the CV's by using the population approach. For example, the CV of the central distribution volume of 5-FU was 30% for the individual approach and 18% for the population approach. With the population approach, it is possible to determine the AIF of drugs that undergo metabolic conversion, such as anticancer drugs, from the abdominal aorta visualized on PET images. The population approach helps to overcome noise in individual data. Since no measurements are needed in addition to the PET examination, the suggested method helps to reduce risk and pain for the patients as well as cost and thus facilitates large scale patient studies.