Comparison of HRRT and HR+ scanners for quantitative (R)-[11C]verapamil, [11C]raclopride and [11C]flumazenil brain studies

Systemic inflammation enhances stimulant-induced striatal dopamine elevation in tobacco smokers

Immune-brain interactions influence the pathophysiology of addiction. Lipopolysaccharide (LPS)-induced systemic inflammation produces effects on reward-related brain regions and the dopamine system. We previously showed that LPS amplifies dopamine elevation induced by methylphenidate (MP), compared to placebo (PBO), in eight healthy controls. However, the effects of LPS on the dopamine system of tobacco smokers have not been explored. The goal of Study 1 was to replicate previous findings in an independent cohort of tobacco smokers. The goal of Study 2 was to combine tobacco smokers with the aforementioned eight healthy controls to examine the effect of LPS on dopamine elevation in a heterogenous sample for power and effect size determination. Eight smokers were each scanned with [¹¹C]raclopride positron emission tomography three times-at baseline, after administration of LPS (0.8 ng/kg, intravenously) and MP (40 mg, orally), and after administration of PBO and MP, in a double-blind, randomized order. Dopamine elevation was quantified as change in [¹¹C]raclopride binding potential (ΔBP_ND) from baseline. A repeated-measures ANOVA was conducted to compare LPS and PBO conditions. Smokers and healthy controls were well-matched for demographics, drug dosing, and scanning parameters. In Study 1, MP-induced striatal dopamine elevation was significantly higher following LPS than PBO (p = 0.025, 18 ± 2.9 % vs 13 ± 2.7 %) for smokers. In Study 2, MP-induced striatal dopamine elevation was also significantly higher under LPS than under PBO (p < 0.001, 18 ± 1.6 % vs 11 ± 1.5 %) in the combined sample. Smoking status did not interact with the effect of condition. This is the first study to translate the phenomenon of amplified dopamine elevation after experimental activation of the immune system to an addicted sample which may have implications for drug reinforcement, seeking, and treatment.

Harmonization of [11C]raclopride brain PET images from the HR+ and HRRT: method development and validation in human subjects

BACKGROUND

There has been an ongoing need to compare and combine the results of new PET imaging studies conducted with [¹¹C]raclopride with older data. This typically means harmonizing data across different scanners. Previous harmonization studies have utilized either phantoms or human subjects, but the use of both phantoms and humans in one harmonization study is not common. The purpose herein was (1) to use phantom images to develop an inter-scanner harmonization technique and (2) to test the harmonization technique in human subjects.

METHODS

To develop the harmonization technique (Experiment 1), the Iida brain phantom was filled with F-18 solution and scanned on the two scanners in question (HRRT, HR+, Siemens/CTI). Phantom images were used to determine the optimal isotropic Gaussian filter to harmonize HRRT and HR+ images. To evaluate the harmonization on human images (Experiment 2), inter-scanner variability was calculated using [¹¹C]raclopride scans of 3 human subjects on both the HRRT and HR+ using percent difference (PD) in striatal non-displaceable binding potential (BP_ND) between HR+ and HRRT (with and without Gaussian smoothing). Finally, (Experiment 3), PD_T/RT was calculated for test-retest (T/RT) variability of striatal BP_ND for 8 human subjects scanned twice on the HR+.

RESULTS

Experiment 1 identified the optimal filter as a Gaussian with a 4.5 mm FWHM. Experiment 2 resulted in 13.9% PD for unfiltered HRRT and 3.71% for HRRT filtered with 4.5 mm. Experiment 3 yielded 5.24% PD_T/RT for HR+.

CONCLUSIONS

The PD results show that the variability of harmonized HRRT is less than the T/RT variability of the HR+. The harmonization technique makes it possible for BP_ND estimates from the HRRT to be compared to (and/or combined with) those from the HR+ without adding to overall variability. Our approach is applicable to all pairs of scanners still in service.

Cerebral grey matter density is associated with neuroreceptor and neurotransporter availability: A combined PET and MRI study

Positron emission tomography (PET) can be used for in vivo measurement of specific neuroreceptors and transporters using radioligands, while voxel-based morphometric analysis of magnetic resonance images allows automated estimation of local grey matter densities. However, it is not known how regional neuroreceptor or transporter densities are reflected in grey matter densities. Here, we analyzed brain scans retrospectively from 328 subjects and compared grey matter density estimates with neuroreceptor and transporter availabilities. µ-opioid receptors (MORs) were measured with [¹¹C]carfentanil (162 scans), dopamine D2 receptors with [¹¹C]raclopride (92 scans) and serotonin transporters (SERT) with [¹¹C]MADAM (74 scans). The PET data were modelled with simplified reference tissue model. Voxel-wise correlations between binding potential and grey matter density images were computed. Regional binding of all the used radiotracers was associated with grey matter density in region and ligand-specific manner independently of subjects' age or sex. These data show that grey matter density and MOR and D2R neuroreceptor / SERT availability are correlated, with effect sizes (r²) ranging from 0.04 to 0.69. This suggests that future studies comparing PET outcome measure different groups (such as patients and controls) should also analyze interactive effects of grey matter density and PET outcome measures.

Model selection criteria for dynamic brain PET studies

Background

 Several criteria exist to identify the optimal model for quantification of tracer kinetics. The purpose of this study was to evaluate the correspondence in kinetic model preference identification for brain PET studies among five model selection criteria: Akaike Information Criterion (AIC), AIC unbiased (AIC_C), model selection criterion (MSC), Schwartz Criterion (SC), and F-test.

Materials and Methods

Six tracers were evaluated: [¹¹C]FMZ, [¹¹C]GMOM, [¹¹C]PK11195, [¹¹C]Raclopride, [¹⁸F]FDG, and [¹¹C]PHT, including data from five subjects per tracer. Time activity curves (TACs) were analysed using six plasma input models: reversible single-tissue model (1T2k), irreversible two-tissue model (2T3k), and reversible two-tissue model (2T4k), all with and without blood volume fraction parameter (V_B). For each tracer and criterion, the percentage of TACs preferring a certain model was calculated.

Results

For all radiotracers, strong agreement was seen across the model selection criteria. The F-test was considered as the reference, as it is a frequently used hypothesis test. The F-test confirmed the AIC preferred model in 87% of all cases. The strongest (but minimal) disagreement across regional TACs was found when comparing AIC with AIC_C. Despite these regional discrepancies, same preferred kinetic model was obtained using all criteria, with an exception of one FMZ subject.

Conclusion

In conclusion, all five model selection criteria resulted in similar conclusions with only minor differences that did not affect overall model selection.

Electronic supplementary material

The online version of this article (10.1186/s40658-017-0197-0) contains supplementary material, which is available to authorized users.

Reproducibility of Quantitative Brain Imaging Using a PET-Only and a Combined PET/MR System

The purpose of this study was to test the feasibility of migrating a quantitative brain imaging protocol from a positron emission tomography (PET)-only system to an integrated PET/MR system. Potential differences in both absolute radiotracer concentration as well as in the derived kinetic parameters as a function of PET system choice have been investigated. Five healthy volunteers underwent dynamic (R)-[¹¹C]verapamil imaging on the same day using a GE-Advance (PET-only) and a Siemens Biograph mMR system (PET/MR). PET-emission data were reconstructed using a transmission-based attenuation correction (AC) map (PET-only), whereas a standard MR-DIXON as well as a low-dose CT AC map was applied to PET/MR emission data. Kinetic modeling based on arterial blood sampling was performed using a 1-tissue-2-rate constant compartment model, yielding kinetic parameters (K₁ and k₂) and distribution volume (V _T ). Differences for parametric values obtained in the PET-only and the PET/MR systems were analyzed using a 2-way Analysis of Variance (ANOVA). Comparison of DIXON-based AC (PET/MR) with emission data derived from the PET-only system revealed average inter-system differences of -33 ± 14% (p < 0.05) for the K₁ parameter and -19 ± 9% (p < 0.05) for k₂. Using a CT-based AC for PET/MR resulted in slightly lower systematic differences of -16 ± 18% for K₁ and -9 ± 10% for k₂. The average differences in V _T were -18 ± 10% (p < 0.05) for DIXON- and -8 ± 13% for CT-based AC. Significant systematic differences were observed for kinetic parameters derived from emission data obtained from PET/MR and PET-only imaging due to different standard AC methods employed. Therefore, a transfer of imaging protocols from PET-only to PET/MR systems is not straightforward without application of proper correction methods. Clinical Trial Registration: www.clinicaltrialsregister.eu, identifier 2013-001724-19.

Partial volume correction of brain PET studies using iterative deconvolution in combination with HYPR denoising

Background

Accurate quantification of PET studies depends on the spatial resolution of the PET data. The commonly limited PET resolution results in partial volume effects (PVE). Iterative deconvolution methods (IDM) have been proposed as a means to correct for PVE. IDM improves spatial resolution of PET studies without the need for structural information (e.g. MR scans). On the other hand, deconvolution also increases noise, which results in lower signal-to-noise ratios (SNR). The aim of this study was to implement IDM in combination with HighlY constrained back-PRojection (HYPR) denoising to mitigate poor SNR properties of conventional IDM.

Methods

An anthropomorphic Hoffman brain phantom was filled with an [¹⁸F]FDG solution of ~25 kBq mL⁻¹ and scanned for 30 min on a Philips Ingenuity TF PET/CT scanner (Philips, Cleveland, USA) using a dynamic brain protocol with various frame durations ranging from 10 to 300 s. Van Cittert IDM was used for PVC of the scans. In addition, HYPR was used to improve SNR of the dynamic PET images, applying it both before and/or after IDM. The Hoffman phantom dataset was used to optimise IDM parameters (number of iterations, type of algorithm, with/without HYPR) and the order of HYPR implementation based on the best average agreement of measured and actual activity concentrations in the regions. Next, dynamic [¹¹C]flumazenil (five healthy subjects) and [¹¹C]PIB (four healthy subjects and four patients with Alzheimer’s disease) scans were used to assess the impact of IDM with and without HYPR on plasma input-derived distribution volumes (V_T) across various regions of the brain.

Results

In the case of [¹¹C]flumazenil scans, Hypr-IDM-Hypr showed an increase of 5 to 20% in the regional V_T whereas a 0 to 10% increase or decrease was seen in the case of [¹¹C]PIB depending on the volume of interest or type of subject (healthy or patient). References for these comparisons were the V_Ts from the PVE-uncorrected scans.

Conclusions

IDM improved quantitative accuracy of measured activity concentrations. Moreover, the use of IDM in combination with HYPR (Hypr-IDM-Hypr) was able to correct for PVE without increasing noise.

Electronic supplementary material

The online version of this article (doi:10.1186/s13550-017-0284-1) contains supplementary material, which is available to authorized users.

Impact of New Scatter Correction Strategies on High-Resolution Research Tomograph Brain PET Studies

PURPOSE

The aim of this study is to evaluate the impact of different scatter correction strategies on quantification of high-resolution research tomograph (HRRT) data for three tracers covering a wide range in kinetic profiles.

PROCEDURES

Healthy subjects received dynamic HRRT scans using either (R)-[(11)C]verapamil (n = 5), [(11)C]raclopride (n = 5) or [(11)C]flumazenil (n = 5). To reduce the effects of patient motion on scatter scaling factors, a margin in the attenuation correction factor (ACF) sinogram was applied prior to 2D or 3D single scatter simulation (SSS).

RESULTS

Some (R)-[(11)C]verapamil studies showed prominent artefacts that disappeared with an ACF-margin of 10 mm or more. Use of 3D SSS for (R)-[(11)C]verapamil showed a statistically significant increase in volume of distribution compared with 2D SSS (p < 0.05), but not for [(11)C]raclopride and [(11)C]flumazenil studies (p > 0.05).

CONCLUSIONS

When there is a patient motion-induced mismatch between transmission and emission scans, applying an ACF-margin resulted in more reliable scatter scaling factors but did not change (and/or deteriorate) quantification.

Rosuvastatin Liver Partitioning in Cynomolgus Monkeys: Measurement In Vivo and Prediction Using In Vitro Monkey Hepatocyte Uptake

Unbound plasma concentrations may not reflect those in target tissues, and there is a need for methods to predict tissue partitioning. Here, we investigate the unbound liver partitioning (Kpu,u) of rosuvastatin, a substrate of hepatic organic anion transporting peptides, in cynomolgus monkeys and compare it with that determined using hepatocytes in vitro. Rosuvastatin (3 mg/kg) was administered orally to monkeys and plasma and liver (by ultrasound-guided biopsy) collected over time. Uptake into monkey hepatocytes was evaluated up to steady state. Binding in monkey plasma, liver, and hepatocytes was determined using equilibrium dialysis. Mean in vivo Kpu,u was 118 after correcting total liver partitioning by plasma and liver binding. In vitro uptake data were analyzed by compartmental modeling to determine active uptake clearance, passive diffusion, the intracellular unbound fraction, and Kpu,u. In vitro Kpu,u underpredicted that in vivo, resulting in the need for an empirical in vitro to in vivo scaling factor of 10. Adjusting model parameters using hypothetical scaling factors for transporter expression and surface area or assuming no effect of protein binding on active transport increased partitioning values by 1.1-, 6-, and 9-fold, respectively. In conclusion, in vivo rosuvastatin unbound liver partitioning in monkeys was underpredicted using hepatocytes in vitro. Modeling approaches that allow integrating corrections from passive diffusion or protein binding on active uptake could improve the estimation of in vivo intracellular partitioning of this organic anion transporting peptide substrate. A similar assessment of other active hepatic transport mechanisms could confirm and determine the extent to which limited accumulation in isolated hepatocytes needs to be considered in drug development.

Commentary: an eye on PET quantification

Positron emission tomography (PET) is generally considered to be a quantitative imaging modality, allowing assessment of regional differences in radiotracer accumulation and the derivation of quantitative physiological information. Due to the increasing complexity of PET technology, the quantitative accuracy of PET images has to be continually reassessed if PET is to maintain its quantitative reputation. In this commentary, we discuss the results from a recent inter-scanner study in which the quantitative outcome measures from human studies were compared for three different radiotracers. The approach is a useful complement to standard phantom tests such as those prescribed by NEMA, but the resulting data are more difficult to interpret.

Synthesis of ([(11)C]carbonyl)raclopride and a comparison with ([(11)C]methyl)raclopride in a monkey PET study

INTRODUCTION

The selective dopamine D2 receptor antagonist raclopride is usually labeled with carbon-11 using [(11)C]methyl iodide or [(11)C]methyl triflate for use in the quantification of dopamine D2 receptors in human brain. The aim of this work was to label raclopride at the carbonyl position using [(11)C]carbon monoxide chemistry and to compare ([(11)C]carbonyl)raclopride with ([(11)C]methyl)raclopride in non-human primate (NHP) using PET with regard to quantitative outcome measurement, metabolism of the labeled tracers and protein binding.

METHODS

Palladium-mediated carbonylation using [(11)C]carbon monoxide, 4,6-dichloro-2-iodo-3-methoxyphenol and (S)-(-)-2-aminomethyl-1-ethylpyrrolidine was applied in the synthesis of ([(11)C]carbonyl)raclopride. The reaction was performed at atmospheric pressure using xantphos as supporting phosphine ligand and palladium (π-cinnamyl) chloride dimer as the palladium source. ([(11)C]Methyl)raclopride was prepared by a previously published method. In the PET study, two female cynomolgus monkeys were used under gas anesthesia of sevoflurane. A dynamic PET measurement was performed for 63 min with an HRRT PET camera after intravenous injection of ([(11)C]carbonyl)raclopride and ([(11)C]methyl)raclopride, respectively, during the same day. The order of injection of the two PET radioligands was changed between the two monkeys. The venous blood sample for measurement of protein binding was taken 3 min prior to the PET scan. Binding potential (BPND) of the putamen and caudate was calculated with SRTM using the cerebellum as a reference region.

RESULTS

The target compound ([(11)C]carbonyl)raclopride was obtained with 50 ± 5% decay corrected radiochemical yield and 95% radiochemical purity. The trapping efficiency (TE) of [(11)C]carbon monoxide was 65 ± 5% and the specific radioactivity of the final product was 34 ± 1 GBq/μmol after a 50 min of synthesis time. The radiochemical yield of ([(11)C]methyl)raclopride was in the same range as published previously i. e. 50-60% and specific radioactivity of those two batches which were used in the present PET study were 192 GBq/μmol and 638 GBq/μmol respectively after a synthesis time of 32 min. In monkey PET studies, the percentage difference of BPND in putamen was <3% and that in caudate was <9% for the two radioligands. The plasma protein binding was 86.2 ± 0.3% and 85.7 ± 0.6% for ([(11)C]carbonyl)raclopride and ([(11)C]methyl)raclopride, respectively. The radiometabolite pattern was similar for both radioligands.

CONCLUSION

Raclopride was (11)C-labeled at the carbonyl position using a palladium-mediated [(11)C]carbonylation reaction. A comparison between ([(11)C]carbonyl)raclopride and ([(11)C]methyl)raclopride with regard to quantitative PET outcome measurements, metabolism of radioligands and protein binding in monkey was performed. The monkey PET study with ([(11)C]carbonyl)raclopride showed similar results as for ([(11)C]methyl)raclopride. The PET studies were performed on 2 subjects.