A regularized full reference tissue model for PET neuroreceptor mapping

Plastic changes in the central auditory system involving the GABAergic system accompany age-related hearing loss. Such processes can be investigated with positron emission tomography (PET) imaging using [18F]flumazenil ([18F]FMZ). Here, [18F]FMZ PET-based modeling approaches allow a simple and reliable quantification of GABAA receptor binding capacity revealing regional differences and age-related changes. Sixty-minute list-mode PET acquisitions were performed in 9 young (range 5-6months) and 11 old (range 39-42months) gerbils, starting simultaneously with the injection of [18F]FMZ via femoral vein. Non-displaceable binding potentials (BPnd) with pons as reference region were calculated for auditory cortex (AC), inferior colliculus (IC), medial geniculate body (MGB), somatosensory cortex (SC), and cerebellum (CB) using (i) a two-tissue compartment model (2TCM), (ii) the Logan plot with image-derived blood-input (Logan (BI)), (iii) a simplified reference tissue model (SRTM), and (iv) the Logan reference model (Logan (RT)). Statistical parametric mapping analysis (SPM) comparing young and old gerbils was performed using 3D parametric images for BPnd based on SRTM. Results were verified with in vitro autoradiography from five additional young gerbils. Model assessment included the Akaike information criterion (AIC). Hearing was evaluated using auditory brainstem responses. BPnd differed significantly between models (p < 0.0005), showing the smallest mean difference between 2TCM as reference and SRTM as simplified procedure. SRTM revealed the lowest AIC values. Both volume of distribution (r2 = 0.8793, p = 0.018) and BPnd (r2 = 0.8216, p = 0.034) correlated with in vitro autoradiography data. A significant age-related decrease of receptor binding was observed in auditory (AC, IC, MGB) and other brain regions (SC and CB) (p < 0.0001, unpaired t test) being confirmed by SPM using pons as reference (p < 0.0001, uncorrected). Imaging of GABAA receptor binding capacity in gerbils using [18F]FMZ PET revealed SRTM as a simple and robust quantification method of GABAA receptors. Comparison of BPnd in young and old gerbils demonstrated an age-related decrease of GABAA receptor binding.

Phosphodiesterase 10A (PDE10A) inhibitors show therapeutic effects for diseases with striatal pathology. PET radiotracers have been developed to quantify in vivo PDE10A levels and target engagement for therapeutic interventions. The aim of this study was to compare two potent and selective PDE10A radiotracers, [11C]TZ1964B and [18F]MNI659 in the nonhuman primate (NHP) brain. Double scans in the same cynomolgus monkey on the same day were performed after injection of [11C]TZ1964B and [18F]MNI659. Specific uptake was determined in two ways: nondisplaceable binding potential (BPND) was calculated using cerebellum as the reference region and the PDE‐10A enriched striatum as the target region of interest (ROI); the area under the time–activity curve (AUC) for the striatum to cerebellum ratio was also calculated. High‐performance liquid chromatography (HPLC) analysis of solvent‐extracted NHP plasma identified the percentage of intact tracer versus radiolabeled metabolites samples post injection of each radiotracer. Both radiotracers showed high specific accumulation in NHP striatum. [11C]TZ1964B has higher striatal retention and lower specific striatal uptake than [18F]MNI659. The BPND estimates of [11C]TZ1964B were 3.72 by Logan Reference model (LoganREF) and 4.39 by simplified reference tissue model (SRTM); the BPND estimates for [18F]MNI659 were 5.08 (LoganREF) and 5.33 (SRTM). AUC ratios were 5.87 for [11C]TZ1964B and 7.60 for [18F]MNI659. Based on BPND values in NHP striatum, coefficients of variation were ~10% for [11C]TZ1964B and ~30% for [18F]MNI659. Moreover, the metabolism study showed the percentage of parent compounds were ~70% for [11C]TZ1964B and ~50% for [18F]MNI659 60 min post injection. These data indicate that either [11C]TZ1964B or [18F]MNI659 could serve as suitable PDE10A PET radiotracers with distinguishing features for particular clinical application.

The aim of the present study is to evaluate the validity of the simplified reference tissue model (SRTM) and of Logan graphical analysis with reference tissue (LGAR) for quantification of histamine H1 receptors (H1Rs) by using positron emission tomography (PET) with [11C]doxepin. These model-based analytic methods (SRTM and LGAR) are compared to Logan graphical analysis (LGA) and to the one-tissue model (1TM), using complete datasets obtained from 5 healthy volunteers. Since HIR concentration in the cerebellum can be regarded as negligibly small, the cerebellum was selected as the reference tissue in the present study. The comparison of binding potential (BP) values estimated by LGAR and 1TM showed good agreement; on the other hand, SRTM turned out to be unstable concerning parameter estimation in several regions of the brain. By including the results of noise analysis, LGAR became a reliable method for parameter estimation of [11C]doxepin data in the cortical regions.

PET analysis is conventionally performed as a two-stage process of quantification followed by analysis. We recently introduced SiMBA (Simultaneous Multifactor Bayesian Analysis), a hierarchical model that performs quantification and analysis for all brain regions of all individuals at once, and in so doing improves both the accuracy of parameter estimation and inferential efficiency. However until now, SiMBA has only been implemented for the two-tissue compartment model. We have now extended this general approach to also allow a non-invasive reference tissue implementation that includes both the full reference tissue model (FRTM) and the simplified reference tissue model (SRTM). Although the FRTM did not successfully converge and gave rise to unlikely parameter estimates for this application, the SRTM described the data well. In simulated data, SiMBA improves quantitative parameter estimation accuracy, reducing error by, on average, 57% for binding potential () using SRTM. In considerations of statistical power, our simulation studies indicate that the efficiency of SiMBA modeling approximately corresponds to improvements that would require doubling the sample size if using conventional methods, with no increase in the false-positive rate. We applied the model to PET data measured with [11C]AZ10419369, which binds selectively to the serotonin 1B receptor, in datasets collected at three different PET centres (n = 139, n = 44 and n = 39). We show that SiMBA yields replicable inferences by comparing associations between PET parameters and age in the different datasets. Moreover, we show that time activity curve data from different centres can be combined in a single SiMBA model using covariates to control between-centre parameter differences, in order to harmonise data between centres. In summary, we present a novel approach for non-invasive quantification and analysis of PET time activity curve data which improves quantification and inferences, enables effective between-centre data harmonisation, and also yields replicable outcomes. This method has the potential to significantly expand the range of research questions which can be meaningfully tested using conventional sample sizes with PET imaging.

We report a novel forward-model implementation of the full reference tissue model (fFTRM) that addresses the fast-exchange approximation employed by the simplified reference tissue model (SRTM) by incorporating a non-zero dissociation time constant from the specifically bound compartment. The forward computational approach avoided errors associated with noisy and nonorthogonal basis functions using an inverse linear model. Compared to analysis by a multilinear single-compartment reference tissue model (MRTM), fFTRM provided improved accuracy for estimation of binding potentials at early times in the scan, with no worse reproducibility across sessions. To test the model’s ability to identify small focal changes in binding potential using a within-scan challenge, we employed a nonhuman primate model of focal dopamine release elicited by deep brain microstimulation remote to ventral striatum (VST) during imaging by simultaneous PET and fMRI. The new model reported an unambiguously lateralized response in VST consistent with fMRI, whereas the MRTM-derived response was not lateralized and was consistent with simulations of model bias. The proposed model enabled better accuracy in PET [11C]raclopride displacement studies and may also facilitate challenges sooner after injection, thereby recovering some sensitivity lost to radioactive decay of the PET tracer.

[(18)F]SPA-RQ (substance P antagonist receptor quantifier) labels the substance P-preferring (NK(1)) receptor in human brain. A prior study showed that [(18)F]SPA-RQ brain uptake can be quantified with a reference tissue method and thereby avoid invasive blood sampling. The purposes of this study were to compare three different reference tissue methods and to assess test-retest reproducibility. Eight healthy subjects underwent two [(18)F]SPA-RQ scans. We calculated the binding potential (BP), which is proportional to receptor density, from both regional volume of interest and voxel-wise data. We compared three reference tissue methods: simplified reference tissue model, multilinear reference tissue model (MRTM), and its two-parameter version (MRTM2). The three methods generated equivalent values of regional BP, but MRTM2 was the most resistant to noise. Temporally stable values of BP were obtained with 240 min of imaging data. MRTM2 had excellent test-retest reproducibility, with high reliability (intraclass correlation > 0.9) and low variability (< 10%). In addition to regional volume of interest analysis, we also created parametric images of BP, variability, and reliability based on voxel-wise time-activity data. The reproducibility of parametric BP was also good, with variability < 20% and reliability > 0.7 in gray matter regions. In conclusion, a two-parameter reference tissue method (MRTM2) provided reproducible and reliable measurements of [(18)F]SPA-RQ brain uptake using 240 min of both regional and voxel-wise data.

The purpose of this study is to investigate errors in quantitative analysis for estimating dopamine D(2) receptor occupancy of antipsychotics with agonist radioligand [(11)C]MNPA by numerical simulation, with particular attention to the validity of a quantitative approach based on the use of a reference region. Synthetic data were validated using clinical data combined with a bootstrap approach. Time-activity curves (TACs) of [(11)C]MNPA were simulated, and the reliability of binding potential (BP(ND)) and occupancy estimated by nonlinear least square (NLS) fitting and a simplified reference tissue model (SRTM) were investigated for various noise levels and scan durations. In the human positron emission tomography (PET) study with and without antipsychotic, risperidone, the uncertainty of BP(ND) and occupancy estimated by SRTM was investigated using resampled TACs based on bootstrap approach with weighted residual errors of fitting. For both NLS and SRTM, it was possible to have <3% of bias in occupancy estimates of [(11)C]MNPA by 60 mins. However, shortened scan duration degrades the quantification of very small binding potentials, especially in case of SRTM. Observations were replicated on the clinical data. Results showed that dopamine D(2) receptor occupancy by antipsychotics can be estimated precisely in region of interest analysis by SRTM with a longer than 60-min [(11)C]MNPA PET scan duration.

The aim of this study was to measure the test-retest reliability of 11C-N,N-dimethyl-2-(2'-amino-4'-hydroxymethylphenylthio)benzylamine (11C-HOMADAM) imaging of serotonin transporter (SERT) density in healthy control subjects. Methods: Two female and 2 male volunteers participated in the study, with each undergoing three 90-min 11C-HOMADAM PET scans. Time-activity curves were derived from SERT-rich structures and fit to 2 models: a simplified reference tissue model and a multilinear graphical model. Binding potential, the ratio of specifically bound uptake to nondisplaceable uptake at equilibrium, was calculated from the model parameter estimates. Ninety-five percent confidence intervals and the intraclass correlation coefficient (ICC) were calculated and adjusted for repeated measures. Results: The ICC values ranged from -0.13 in the dorsal raphe to 0.88 in the caudate nucleus. The highest average ICC values were in the striatum, but other regions were sensitive to measurement outliers. Conclusion: Good-to-excellent test-retest reliability was observed for SERT binding in the striatum. The dorsal raphe ICC value was sensitive to a measurement outlier. 11C-HOMADAM binding potential calculated from the simplified reference tissue model and the multilinear graphical model were robust and in good agreement.

Cariprazine is a dopamine D(3)/D(2) receptor partial agonist antipsychotic candidate, which binds with high affinity to dopamine D(3) and D(2) receptors (with ∼10-fold higher in vitro affinity to D(3) vs. D(2) receptors) and with moderate affinity to 5-HT(1A) receptors. The main objective of the present molecular imaging investigation was to evaluate the uptake and reversible binding of 11-C labeled cariprazine in the nonhuman primate brain, in relation to the known distributions of dopamine D(2) and D(3) receptors. We examined the brains of two cynomolgus monkeys at baseline condition as well as during a pharmacological blocking condition, using unlabeled cariprazine or raclopride as blockers before injection of [(11) C]cariprazine. Of the total injected radioactivity, ∼7% entered the brain and ∼3-4% remained in the brain after 90 min, indicating good blood brain barrier penetration and slow washout. It was possible to block cariprazine binding with unlabeled cariprazine and raclopride indicating that [(11) C]cariprazine binds to dopamine D(3)/D(2) receptors. Nondisplaceable binding potential (BPND) measurements, using a simplified reference tissue model and cerebellum as the reference region, yielded values of ∼1.5 and 0.3 in the striatum and thalamus, respectively. Striatum BPND values were reduced by 80 and 85% following pretreatment with 0.1 mg/kg IV injection of unlabeled cariprazine and 1 mg/kg IV injection of unlabeled raclopride, respectively. The data confirm that cariprazine, a novel antipsychotic drug candidate, enters the nonhuman primate brain readily and binds to dopamine D(3)/D(2) receptors. Furthermore, in PET imaging [(11) C]cariprazine can effectively visualize dopamine D(3)/D(2) receptors in the nonhuman primate brain.

BackgroundGlutamate is the main excitatory neurotransmitter in the brain, acting through ionotropic and metabotropic receptors, such as the neuronal metabotropic glutamate receptor 5 (mGluR5). The radiotracer [11C]ABP688 binds allosterically to the mGluR5, providing a valuable tool to understand glutamatergic function. We have previously shown that neuronal [11C]ABP688 binding is influenced by astrocyte activation. Specifically, the activation of glutamate transport in astrocytes via glutamate‐transporter‐1 (GLT‐1) results in an elevated [11C]ABP688 binding within the ventral anterior thalamus, but no changes in other regions. However, whether changes at the network level occur remains elusive. We evaluated Glutamatergic Brain Networks (GBNs) before and after activating astrocytes.MethodMicro‐PET acquisitions were performed in adult Sprague‐Dawley rats (n = 5) at baseline and after a pharmacological challenge to activate astrocytes. Before the scan, rats received either saline (vehicle) or ceftriaxone (CEF, 200mg/kg), an antibiotic that induces GLT‐1 activation. Then, [11C]ABP688 was administered i.v., followed by a 60‐minute dynamic scan. The nondisplaceable binding potential (BPND) was estimated using the simplified reference tissue model, with the cerebellum as a reference region. [11C]ABP688 BPND was extracted for 12 volumes of interest. GBNs based on [11C]ABP688 regional BPND were assembled with a multiple sampling scheme in MATLAB (p‐value &lt; 0.05).ResultAstrocyte activation induced GBN hyperconnectivity after astrocyte activation, with the strength of association between the cerebral hemispheres, such as in the frontal and parietal cortices (Figure 1, A‐B). After GLT‐1 activation, the connections were diffused, including regions that were not part of the network at baseline, such as the cerebellum. Graph measures show a significant increase in global efficiency, average degree, density, and average clustering coefficient (Figure 1, C‐G). These measures indicate an increase in connections and network cohesiveness. The reduction in assortativity can be related to the new regions on the GBN after the challenge.ConclusionOur results show that GBNs assessed with [11C]ABP688 are sensitive to astrocyte activation. Alterations in glutamate levels, as observed in dysfunctions like glutamatergic excitotoxicity present in AD, could disrupt the cohesion of the glutamatergic network, leading to brain dysfunction.

PET analysis is conventionally performed as a two-stage process of quantification followed by analysis. We recently introduced SiMBA (Simultaneous Multifactor Bayesian Analysis), a hierarchical model that performs quantification and analysis for all brain regions of all individuals at once, and in so doing improves both the accuracy of parameter estimation as well as inferential efficiency. However until now, SiMBA has only been implemented for the two-tissue compartment model. We have now extended this general approach to also allow a non-invasive reference tissue implementation that includes both the full reference tissue model and the simplified reference tissue model. In simulated data, SiMBA improves quantitative parameter estimation accuracy, reducing error by, on average, 57% for binding potential (). In considerations of statistical power, our simulation studies indicate that the efficiency of SiMBA modeling approximately corresponds to improvements that would require doubling the sample size if using conventional methods, with no increase in the false positive rate. We applied the model to PET data measured with [11C]AZ10419369, which binds selectively to the serotonin 1B receptor, in datasets collected at three different PET centres (n=139, n=44 and n=39). We show that SiMBA yields replicable inferences by comparing associations between PET parameters and age in the different datasets. Moreover, we show that time activity curve data from different centres can be combined in a single SiMBA model using covariates to control between-centre parameter differences, in order to harmonise data between centres. In summary, we present a novel approach for noninvasive quantification and analysis of PET time activity curve data which improves quantification and inferences, enables effective between-centre data harmonisation, and also yields replicable outcomes. This method has the potential to significantly expand the range of research questions which can be meaningfully tested using conventional sample sizes with PET imaging.

Dopamine D 2 receptor binding in drug-naïve patients with schizophrenia examined with raclopride-C11 and positron emission tomography

This [11C]flumazenil (FMZ) study evaluates the performance of various parametric analysis methods and their ability to detect statistically significant group differences. Dynamic 60-min FMZ scans were performed in eight healthy and nine individuals with major depressive disorder. Parametric volume of distribution (VT) images were generated using a basis function method (BFM) implementation of the single tissue compartment model (1T) and Logan plot analysis, both with a metabolite-corrected arterial plasma input function. Parametric binding potential (BP ND) images were generated using multilinear reference tissue methods (MRTM0-4), reference Logan and receptor parametric mapping (RPM1-2), with pons as a reference region. Standardized uptake value (SUV) and SUV ratio-to-pons (SUVr) images were calculated over the time interval 30-40 and 20-60 min postinjection. The resulting VT, BP ND, SUV and SUVr values were compared with nonlinear regression values, using both the 1T model and the simplified reference tissue model. Statistical parametric mapping (SPM5) was used to detect group differences, with an emphasis on the bilateral parahippocampal gyri. BFM was more accurate than Logan, but showed more variability. Both RPM methods and MRTM2 showed the best average correlation with the simplified reference tissue model. In using SPM, SUV and SUVr images provided the best contrast between groups in the parahippocampal gyri, but provided large underestimation and overestimation in quantitative comparisons. BFM and RPM methods allowed for the determination of perfusion effects. Parametric Logan VT, MRTM2 and RPM1-2 BP ND methods allow the best quantitative comparison of FMZ binding between groups and show good discriminating performance in SPM analysis.

This work assesses the one-step late maximum likelihood expectation maximization (OSL-MLEM) 4D PET reconstruction algorithm for direct estimation of parametric images from raw PET data when using the simplified reference tissue model with the basis function method (SRTM-BFM) for the kinetic analysis. To date, the OSL-MLEM method has been evaluated using kinetic models based on two-tissue compartments with an irreversible component. We extend the evaluation of this method for two-tissue compartments with a reversible component, using SRTM-BFM on simulated 3D + time data sets (with use of [11C]raclopride time-activity curves from real data) and on real data sets acquired with the high resolution research tomograph. The performance of the proposed method is evaluated by comparing voxel-level binding potential (BPND) estimates with those obtained from conventional post-reconstruction kinetic parameter estimation. For the commonly chosen number of iterations used in practice, our results show that for the 3D + time simulation, the direct method delivers results with lower %RMSE at the normal count level (decreases of 9–10 percentage points, corresponding to a 38–44% reduction), and also at low count levels (decreases of 17–21 percentage points, corresponding to a 26–36% reduction). As for the real 3D data set, the results obtained follow a similar trend, with the direct reconstruction method offering a 21% decrease in %CV compared to the post reconstruction method at low count levels. Thus, based on the results presented herein, using the SRTM-BFM kinetic model in conjunction with the OSL-MLEM direct 4D PET MLEM reconstruction method offers an improvement in performance when compared to conventional post reconstruction methods.

Kinetics modeling and occupancy studies of a novel C-11 PET tracer for VAChT in nonhuman primates