Effect of Scatter Coincidences, Partial Volume, Positron Range and Non-Colinearity on the Quantification of FDOPA Patlak Analysis

Introduction: The key characteristics of positron emission tomography (PET) are its quantitative capability and its sensitivity, which allow the in vivo imaging of biochemical interactions with small amounts of tracer concentrations. Therefore, accurate quantification is important. However, it can be sensitive to several physical factors. The aim of this investigation is the assessment of the effect of physical effects, such as: scatter coincidences, partial volume, positron range and non-colinearity on the quantification of FDOPA uptake using PET. Methods: The SimSET Monte Carlo package was employed to simulate acquisitions of the PET/CT Siemens Biograph scanner. The study was performed with a numerical brain model obtained from the CT scan of a commercial striatal phantom. Theoretical pharmacokinetic values were simulated. The simulations were carried out with and without scatter, positron range and non-colinearity effects. The OSEM algorithm from STIR library was used to reconstruct the PET data. Different correction strategies were employed in order to evaluate the effects caused by the different type of degradation on results obtained with Patlak analysis. Results: The FDOPA uptake of Patlak plot increased from 70.4% of the theoretical value to 80.4%, if scatter was perfectly corrected, and it increased to 99% of the theoretical value when the partial volume correction was employed, as well. No significant improvement was found for positron range and non-colinearity effects when the partial volume correction was employed.Conclusions: The results show that the compensation for scatter and partial volume degradations increases accuracy in the uptake calculation.