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In vivo quantification of serotonin transporters using [(11)C]DASB and positron emission tomography in humans: modeling considerations.
Authors:R Todd Ogden  Ashish Ojha  Kjell Erlandsson  Maria A Oquendo  J John Mann  Ramin V Parsey
Institution:Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, New York 10032, USA. ogden@neuron.cpmc.columbia.edu
Abstract:Positron emission tomography (PET) studies of the serotonin transporter (5-HTT) in the human brain are increasingly using the radioligand (11)C]N, N-dimethyl-2-(2-amino-4-cyanophenylthio) benzylamine. A variety of models have been applied to such data in several published articles; however to date, these models have not been validated with test-retest data. We recruited 11 healthy subjects and conducted two identical scans on each subject on the same day. We considered four different models (one- and two-tissue compartment kinetic models, likelihood estimation in graphical analysis (LEGA; a bias-free alternative to the graphical method), and basis pursuit) along with fast noniterative approximations to the kinetic models. We considered four different outcome measures (total volume of distribution (V(T)), binding potential with (BP) and without (BP(1)), free-fraction adjustment, and specific-to-nonspecific equilibrium partition coefficient (BP(2))). To assess the performance of each model, we compared results using six different metrics (percent difference (PD) and within-subject mean sum of squares for reproducibility, interclass coefficient for reliability, variance across subjects, identifiability based on bootstrap resampling of residuals for each method, and time stability analysis to determine minimal required scanning time). We considered analysis of both at the voxel level and at the region of interest (ROI) level and compared results from these two approaches to assess agreement. We determined that 100 mins of scanning time is adequate and that for ROI-level analysis, LEGA gives best results. Average PD is 5.51 for V(T), 20.7 for BP, 17.2 for BP(1), and 16.5 for BP(2) across all regions. For voxel-level analysis we determined that the one-tissue compartment noniterative model is best.
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