Kinetic modelling of [11C]flumazenil using data-driven methods
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[11C]Flumazenil (FMZ) is a benzodiazepine receptor antagonist that binds reversibly to central-type gamma-aminobutyric acid (GABA-A) sites. A validated approach for analysis of [11C]FMZ is the invasive one-tissue (1T) compartmental model. However, it would be advantageous to analyse FMZ binding with whole-brain pixel-based methods that do not require a-priori hypotheses regarding preselected regions. Therefore, in this study we compared invasive and noninvasive data-driven methods (Logan graphical analysis, LGA; multilinear reference tissue model, MRTM2; spectral analysis, SA; basis pursuit denoising, BPD) with the 1T model.
We focused on two aspects: (1) replacing the arterial input function analyses with a reference tissue method using the pons as the reference tissue, and (2) shortening the scan protocol from 90 min to 60 min. Dynamic PET scans were conducted in seven healthy volunteers with arterial blood sampling. Distribution volume ratios (DVRs) were selected as the common outcome measure.
The SA, LGA with and without arterial input, and MRTM2 agreed best with the 1T model DVR values. The invasive and noninvasive BPD were slightly less well correlated. The full protocol of a 90-min emission data performed better than the 60-min protocol, but the 60-min protocol still delivered useful data, as assessed by the coefficient of variation, and the correlation and bias analyses.
This study showed that the SA, LGA and MRTM2 are valid methods for the quantification of benzodiazepine receptor binding with [11C]FMZ using an invasive or noninvasive protocol, and therefore have the potential to reduce the invasiveness of the procedure.
Keywords[11C]Flumazenil Benzodiazepine receptors Parametric images PET Reference tissue methods Pharmacokinetics 18F-labelled
We would like to acknowledge the work of our colleagues Brigitte Dzewas and Choletta Kruschke for their excellent technical assistance in data acquisition. We would also like to thank Vin Cunningham and Roger Gunn for provision of software for spectral analysis and basis pursuit and for helpful discussion. This work was supported by the Kommission für Klinische Forschung.
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