Background: In positron emission tomography (PET) imaging, binding is typically estimated by fitting pharmacokinetic models to the series of measurements of radioactivity in the target tissue following intravenous injection of a radioligand. However, there are multiple different models to choose from and numerous analytical decisions that must be made when modelling PET data. Therefore, it is important that analysis tools be adapted to the specific circumstances, and that analyses be documented in a transparent manner. Kinfitr, written in the open-source programming language R, is a tool developed for flexible and reproducible kinetic modelling of PET data, i.e. performing all steps using code which can be publicly shared in analysis notebooks. In this study, we compared outcomes obtained using kinfitr with those obtained using PMOD: a widely used commercial tool.
Results: Using previously collected test-retest data obtained with four different radioligands, a total of six different kinetic models were fitted to time-activity curves derived from different brain regions. We observed good correspondence between the two kinetic modelling tools both for binding estimates and for microparameters. Likewise, no substantial differences were observed in the test-retest reliability estimates between the two tools.
Conclusions: In summary, we showed excellent agreement between the open-source R package kinfitr, and the widely used commercial application PMOD. We, therefore, conclude that kinfitr is a valid and reliable tool for kinetic modelling of PET data.
Keywords: Kinetic modelling; Positron emission tomography; R; Reproducible research.