Validation of parametric methods for [11C]PE2I positron emission tomography

OBJECTIVES The radioligand [(11)C]PE2I is highly selective for dopamine transporter (DAT) and can be used in vivo for investigation of changes in DAT concentration, progression of disease and validation of treatment using positron emission tomography (PET). DAT is an important protein for regulation of central dopamine concentration and DAT deficiency has been associated with several neurodegenerative and neuropsychiatric disorders. Accurate parametric images are a prerequisite for clinical application of [(11)C]PE2I. The purpose of this study was to evaluate different methods for producing [(11)C]PE2I parametric images, showing binding potential (BPND) and relative delivery (R1) at the voxel level, using clinical data as well as simulations. METHODS Investigations were made in twelve subjects either with social anxiety disorder (n=6) or parkinsonian syndrome (n=6), each receiving an 80 min dynamic PET scan. All subjects underwent a T1-weighted MRI scan which was co-registered to the PET images and used for definition of regions of interest using a probabilistic template (PVElab). Two basis function implementations (receptor parametric mapping: RPM, RPM2) of the simplified reference tissue model (SRTM) and three multilinear reference tissue models (MRTMo, MRTM and MRTM2) were used for computation of parametric BPND and R1 images. In addition, reference Logan and standard uptake value ratio (SUVr) were investigated. Evaluations of BPND and R1 images were performed using linear regression to compare the parametric methods to region-based analyses with SRTM and cerebellar gray matter as reference region. Accuracy and precision of each method were assessed by simulations. RESULTS Correlation and slope of linear regression between parametric and region-based BPND and R1 values in both striatum and extra-striatal regions were optimal for RPM (R(2)=0.99 for both BPND and R1; slopes 0.99 and 0.98 for BPND and R1, respectively, in striatum). In addition, accuracy and precision were best for RPM and RPM2. CONCLUSION The basis function methods provided more robust estimations of the parameters compared to the other models and performed best in simulations. RPM, a basis function implementation of SRTM, is the preferred method for voxel level analysis of [(11)C]PE2I PET studies.