Determination of the Input Function at the Entry of the Tissue of Interest and Its Impact on PET Kinetic Modeling Parameters

Brain PET imaging using 11C-flumazenil and 11C-buprenorphine does not support the hypothesis of a mutual interaction between buprenorphine and benzodiazepines at the neuroreceptor level

Among opioids, buprenorphine presents a favorable safety profile with a limited risk of respiratory depression. However, fatalities have been reported when buprenorphine is combined to a benzodiazepine. Potentiation of buprenorphine interaction with opioid receptors (ORs) with benzodiazepines, and/or vice versa, is hypothesized to explain this drug-drug interaction (DDI). The mutual DDI between buprenorphine and benzodiazepines was investigated at the neuroreceptor level in nonhuman primates (n = 4 individuals) using brain PET imaging and kinetic modelling. The binding potential (BPND) of benzodiazepine receptor (BzR) was assessed using 11C-flumazenil PET imaging before and after administration of buprenorphine (0.2 mg, i.v.). Moreover, the brain kinetics and receptor binding of buprenorphine were investigated in the same individuals using 11C-buprenorphine PET imaging before and after administration of diazepam (10 mg, i.v.). Outcome parameters were compared using a two-way ANOVA. Buprenorphine did not impact the plasma nor brain kinetics of 11C-flumazenil. 11C-flumazenil BPND was unchanged following buprenorphine exposure, in any brain region (p > 0.05). Similarly, diazepam did not impact the plasma or brain kinetics of 11C-buprenorphine. 11C-buprenorphine volume of distribution (VT) was unchanged following diazepam exposure, in any brain region (p > 0.05). To conclude, our PET imaging findings do not support a neuropharmacokinetic or neuroreceptor-related mechanism of the buprenorphine/benzodiazepine interaction.

The ultra high sensitivity blood counter: a compact, MRI-compatible, radioactivity counter for pharmacokinetic studies in µL volumes

Quantification of physiological parameters in preclinical pharmacokinetic studies based on nuclear imaging requires the monitoring of arterial radioactivity over time, known as the arterial input function (AIF). Continuous derivation of the AIF in rodent models is very challenging because of the limited blood volume available for sampling. To address this challenge, an Ultra High Sensitivity Blood Counter (UHS-BC) was developed. The device detects beta particles in real-time using silicon photodiodes, custom low-noise electronics, and 3D-printed plastic cartridges to hold standard catheters. Two prototypes were built and characterized in two facilities. Sensitivities up to 39% for¹⁸F and 58% for¹¹C-based positron emission tomography (PET) tracers were demonstrated.^99mTc and¹²⁵I based Single Photon Emission Computed Tomography (SPECT) tracers were detected with greater than 3% and 10% sensitivity, respectively, opening new applications in nuclear imaging and fundamental biology research. Measured energy spectra show all relevant peaks down to a minimum detectable energy of 20 keV. The UHS-BC was shown to be highly reliable, robust towards parasitic background radiation and electromagnetic interference in the PET or MRI environment. The UHS-BC provides reproducible results under various experimental conditions and was demonstrated to be stable over days of continuous operation. Animal experiments showed that the UHS-BC performs accurate AIF measurements using low detection volumes suitable for small animal models in PET, SPECT and PET/MRI investigations. This tool will help to reduce the time and number of animals required for pharmacokinetic studies, thus increasing the throughput of new drug development.

Pharmacokinetic neuroimaging to study the dose-related brain kinetics and target engagement of buprenorphine in vivo

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.

Noninvasive quantification of nonhuman primate dynamic 18F-FDG PET imaging

¹⁸F-FDG uptake rate constant K_i is the main physiology parameter measured in dynamic PET studies. A model-independent graphical analysis using Patlak plot with plasma input function (PIF) is a standard approach used to estimate K_i . The PIF is the ¹⁸F-FDG time activity curve (TAC) in plasma that is obtained by serial arterial blood sampling. The purpose of the study is to evaluate a Patlak plot-based optimization approach with reduced blood samples for noninvasive quantification of dynamic ¹⁸F-FDG PET imaging. Eight 60 min rhesus monkey brain dynamic ¹⁸F-FDG PET scans with arterial blood samples were collected. The measured PIF (mPIF) was determined by arterial blood samples. TACs of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the population-based PIF (pPIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal sampling scheme with given blood sample size was determined by maximizing the correlations between the K_i estimated from pPIF and those obtained by mPIF. A leave-two-out cross-validation method was used for evaluation. The linear correlations between the K_i estimates from pPIF with optimal sampling schemes and those from mPIF were: K_i (pPIF 1 sample at 40 min) = 1.015 K_i (mPIF) - 0.000, R ² = 0.974; K_i (pPIF 2 samples at 35 and 50 min) = 1.052 K_i (mPIF) - 0.001, R ² = 0.976; K_i (pPIF 3 samples at 12, 40, and 50 min) = 1.030 K_i (mPIF) - 0.000, R ² = 0.985; and K_i (pPIF 4 samples at 10, 20, 40, and 50 min) = 1.016 K_i (mPIF)- 0.000, R ² = 0.993. As the sample size became greater or equal to 4, the K_i estimates from pPIF with the optimal protocol were almost identical to those from mPIF. The Patlak plot-based optimization approach is a reliable method to estimate PIF for noninvasive quantification of non-human primate dynamic ¹⁸F-FDG PET imaging and is potentially extendable to further translational human studies.

Hybrid PET/MR Kernelised Expectation Maximisation Reconstruction for Improved Image-Derived Estimation of the Input Function from the Aorta of Rabbits

Positron emission tomography (PET) provides simple noninvasive imaging biomarkers for multiple human diseases which can be used to produce quantitative information from single static images or to monitor dynamic processes. Such kinetic studies often require the tracer input function (IF) to be measured but, in contrast to direct blood sampling, the image-derived input function (IDIF) provides a noninvasive alternative technique to estimate the IF. Accurate estimation can, in general, be challenging due to the partial volume effect (PVE), which is particularly important in preclinical work on small animals. The recently proposed hybrid kernelised ordered subsets expectation maximisation (HKEM) method has been shown to improve accuracy and contrast across a range of different datasets and count levels and can be used on PET/MR or PET/CT data. In this work, we apply the method with the purpose of providing accurate estimates of the aorta IDIF for rabbit PET studies. In addition, we proposed a method for the extraction of the aorta region of interest (ROI) using the MR and the HKEM image, to minimise the PVE within the rabbit aortic region-a method which can be directly transferred to the clinical setting. A realistic simulation study was performed with ten independent noise realisations while two, real data, rabbit datasets, acquired with the Biograph Siemens mMR PET/MR scanner, were also considered. For reference and comparison, the data were reconstructed using OSEM, OSEM with Gaussian postfilter and KEM, as well as HKEM. The results across the simulated datasets and different time frames show reduced PVE and accurate IDIF values for the proposed method, with 5% average bias (0.8% minimum and 16% maximum bias). Consistent results were obtained with the real datasets. The results of this study demonstrate that HKEM can be used to accurately estimate the IDIF in preclinical PET/MR studies, such as rabbit mMR data, as well as in clinical human studies. The proposed algorithm is made available as part of an open software library, and it can be used equally successfully on human or animal data acquired from a variety of PET/MR or PET/CT scanners.

Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with 11C-SB201745

Background

Kinetic analysis of dynamic PET data requires an accurate knowledge of available PET tracer concentration within blood plasma over time, known as the arterial input function (AIF). The gold standard method used to measure the AIF requires serial arterial blood sampling over the course of the PET scan, which is an invasive procedure and makes this method less practical in clinical settings. Traditional image-derived methods are limited to specific tracers and are not accurate if metabolites are present in the plasma.

Results

In this work, we utilise an image-derived whole blood curve measurement to reduce the computational complexity of the simultaneous estimation method (SIME), which is capable of estimating the AIF directly from tissue time activity curves (TACs). This method was applied to data obtained from a serotonin receptor study (¹¹C-SB207145) and estimated parameter results are compared to results obtained using the original SIME and gold standard AIFs derived from arterial samples. Reproducibility of the method was assessed using test-retest data. It was shown that the incorporation of image-derived information increased the accuracy of total volume of distribution (V _T) estimates, averaged across all regions, by 40% and non-displaceable binding potential (BP _ND) estimates by 16% compared to the original SIME. Particular improvements were observed in K₁ parameter estimates. BP _ND estimates, based on the proposed method and the gold standard arterial sample-derived AIF, were not significantly different (P=0.7).

Conclusions

The results of this work indicate that the proposed method with prior AIF information obtained from a partial volume corrected image-derived whole blood curve, and modelled parent fraction, has the potential to be used as an alternative non-invasive method to perform kinetic analysis of tracers with metabolite products.