Abstract
BackgroundIn 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.ResultsUsing 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.ConclusionsIn 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.
Highlights
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
A separate analysis was performed for which the t* values fitted by PMOD and the weighting scheme used by PMOD were used in an analysis that was carried out using kinfitr, in order to investigate the effect which the differences in these parameters have on the differences between the tools
It was observed that the linearized methods (i.e. Multilinear Analysis 1 (MA1), Multilinear Reference Tissue Model 2 (MRTM2) and both invasive and non-invasive Logan plots) generally exhibited lower agreement than the non-linear models
Summary
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. It is important that analysis tools be adapted to the specific circumstances, and that analyses be documented in a transparent manner. Written in the opensource 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. Positron emission tomography (PET) is an imaging modality with high sensitivity and specificity for biochemical markers and metabolic processes in vivo [1]. In PET imaging, study participants receive an intravenous injection of a radioligand, which binds to a target molecule [5]. The sheer number of options available for kinetic modelling, in addition to those in prior pre-processing
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