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A wide range of buprenorphine doses are used for either pain management or maintenance therapy in opioid addiction. The complex in vitro profile of buprenorphine, with affinity for µ-, δ-, and κ-opioid receptors (OR), makes it difficult to predict its dose-related neuropharmacology in vivo. In rats, microPET imaging and pretreatment by OR antagonists were performed to assess the binding of radiolabeled buprenorphine (microdose 11C-buprenorphine) to OR subtypes in vivo (n= 4 per condition). The µ-selective antagonist naloxonazine (10 mg/kg) and the non-selective OR antagonist naloxone (1 mg/kg) blocked the binding of 11C-buprenorphine, while pretreatment by the δ-selective (naltrindole, 3 mg/kg) or the κ-selective antagonist (norbinaltorphimine, 10 mg/kg) did not. In four macaques, PET imaging and kinetic modeling enabled description of the regional brain kinetics of 11C-buprenorphine, co-injected with increasing doses of unlabeled buprenorphine. No saturation of the brain penetration of buprenorphine was observed for doses up to 0.11 mg/kg. Regional differences in buprenorphine-associated receptor occupancy were observed. Analgesic doses of buprenorphine (0.003 and 0.006 mg/kg), respectively, occupied 20% and 49% of receptors in the thalamus while saturating the low but significant binding observed in cerebellum and occipital cortex. Occupancy >90% was achieved in most brain regions with plasma concentrations >7 µg/L. PET data obtained after co-injection of an analgesic dose of buprenorphine (0.003 mg/kg) predicted the binding potential of microdose 11C-buprenorphine. This strategy could be further combined with pharmacodynamic exploration or pharmacological MRI to investigate the neuropharmacokinetics and neuroreceptor correlate, at least at µ-OR, of the acute effects of buprenorphine in humans.

Small animal image registration is challenging because of its joint structure, and posture and position difference in each acquisition without a standard scan protocol. In this paper, we face the issue of mouse whole-body skeleton registration from CT images. A novel method is developed for analyzing mouse hind-limb and fore-limb postures based on geodesic path descriptor and then registering the major skeletons and fore limb skeletons initially by thin-plate spline (TPS) transform based on the obtained geodesic paths and their enhanced correspondence fields. A target landmark correction method is proposed for improving the registration accuracy of the improved 3D shape context non-rigid registration method we previously proposed. A novel non-rigid registration framework, combining the skeleton posture analysis, geodesic path based initial alignment and 3D shape context model, is proposed for mouse whole-body skeleton registration. The performance of the proposed methods and framework was tested on 12 pairs of mouse whole-body skeletons. The experimental results demonstrated the flexibility, stability and accuracy of the proposed framework for automatic mouse whole body skeleton registration.