An international group of experts in pharmacokinetic modeling recommends a consensus nomenclature to describe in vivo molecular imaging of reversibly binding radioligands.

Many theories of cognitive aging are based on evidence that dopamine (DA) declines with age. Here we performed a systematic meta-analysis of cross-sectional PET and SPECT studies on the average effects of age on distinct DA targets (receptors, transporters, or relevant enzymes) in healthy adults (N=95 studies including 2,611 subjects). Results revealed significant moderate to large, negative effects of age on DA transporters and receptors. Age had a significantly larger effect on D1- than D2-like receptors. In contrast, there was no significant effect of age on DA synthesis capacity. The average age reductions across the DA system were 3.7–14.0% per decade. A meta-regression found only DA target as a significant moderator of the age effect. This study precisely quantifies prior claims of reduced DA functionality with age. It also identifies presynaptic mechanisms (spared synthesis capacity and reduced DA transporters) that may partially account for previously unexplained phenomena whereby older adults appear to use dopaminergic resources effectively. Recommendations for future studies including minimum required samples sizes are provided.

Microglia play an essential role in many brain diseases. Microglia are activated by local tissue damage or inflammation, but systemic inflammation can also activate microglia. An important clinical question is whether the effects of systemic inflammation on microglia mediates the deleterious effects of systemic inflammation in diseases such as Alzheimer's dementia, multiple sclerosis, and stroke. Positron Emission Tomography (PET) imaging with ligands that bind to Translocator Protein (TSPO) can be used to detect activated microglia. The aim of this study was to evaluate whether the effect of systemic inflammation on microglia could be measured with PET imaging in nonhuman primates, using the TSPO ligand [11C]PBR28. Methods Six female baboons (Papio anubis) were scanned before and at 1 h and/or 4h and/or 22h after intravenous administration of E. coli lipopolysaccharide (LPS; 0.1 mg/kg), which induces systemic inflammation. Regional time-activity data from regions of interest (ROIs) were fitted to the two-tissue compartmental model, using the metabolite-corrected arterial plasma curve as input function. Total volume of distribution (VT) of [11C]PBR28 was used as a measure of total ligand binding. The primary outcome was change in VT from baseline. Serum levels of tumor necrosis factor alpha (TNFα), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), and interleukin-8 (IL-8) were used to assess correlations between systemic inflammation and microglial activation. In one baboon, immunohistochemistry was used to identify cells expressing TSPO. Results LPS administration increased [11C]PBR28 binding (F(3,6)=5.1, p=.043) with a 29±16 % increase at 1h (n = 4) and a 62±34% increase at 4h (n = 3) post-LPS. There was a positive correlation between serum IL-1β and IL-6 levels and the increase in [11C]PBR28 binding. TSPO immunoreactivity occurred almost exclusively in microglia and rarely in astrocytes. Conclusion In the nonhuman-primate brain, LPS-induced systemic inflammation produces a robust increase in the level of TSPO that is readily detected with [11C]PBR28 PET. The effect of LPS on [11C]PBR28 binding is likely mediated by inflammatory cytokines. Activation of microglia may be a mechanism through which systemic inflammatory processes influence the course of diseases such as Alzheimer's, multiple sclerosis, and possibly depression.

Our goal in this paper is the estimation of kinetic model parameters for each voxel corresponding to a dense three-dimensional (3-D) positron emission tomography (PET) image. Typically, the activity images are first reconstructed from PET sinogram frames at each measurement time, and then the kinetic parameters are estimated by fitting a model to the reconstructed time-activity response of each voxel. However, this "indirect" approach to kinetic parameter estimation tends to reduce signal-to-noise ratio (SNR) because of the requirement that the sinogram data be divided into individual time frames. In 1985, Carson and Lange proposed, but did not implement, a method based on the expectation-maximization (EM) algorithm for direct parametric reconstruction. The approach is "direct" because it estimates the optimal kinetic parameters directly from the sinogram data, without an intermediate reconstruction step. However, direct voxel-wise parametric reconstruction remained a challenge due to the unsolved complexities of inversion and spatial regularization. In this paper, we demonstrate and evaluate a new and efficient method for direct voxel-wise reconstruction of kinetic parameter images using all frames of the PET data. The direct parametric image reconstruction is formulated in a Bayesian framework, and uses the parametric iterative coordinate descent (PICD) algorithm to solve the resulting optimization problem. The PICD algorithm is computationally efficient and is implemented with spatial regularization in the domain of the physiologically relevant parameters. Our experimental simulations of a rat head imaged in a working small animal scanner indicate that direct parametric reconstruction can substantially reduce root-mean-squared error (RMSE) in the estimation of kinetic parameters, as compared to indirect methods, without appreciably increasing computation.