A linear model for estimation of neurotransmitter response profiles from dynamic PET data

Novel multi-modal methodology to investigate placebo response in major depressive disorder

The neurobiological mechanisms underlying the placebo phenomenon in patients with major depressive disorder (MDD) remain largely unknown. The progressive rise in rates of placebo responses within clinical trials over the past two decades may impede the detection of a true signal and thus present a major obstacle in new treatment development. Understanding the mechanisms would have several important implications, including (1) identifying biomarkers of placebo responders (thereby identifying those individuals who could benefit therapeutically from such interventions), (2) opening new avenues for manipulating such mechanisms to maximize symptom reduction, and (3) refining treatments with approaches that decrease (in clinical trials) or increase (in clinical practice) the placebo response. Here we investigated the research question: is the dopaminergic system one of the neurobiological underpinnings of the placebo response within MDD? Inspired by preclinical and clinical findings that have implicated dopamine in the occurrence, prediction, and expectation of reward, we hypothesized that dopaminergic activity in the mesolimbic system is a critical mediator of placebo response in MDD. To test this hypothesis, we designed a double-blind, placebo-controlled, sequential parallel comparison design clinical trial aimed at maximizing placebo antidepressant response. We integrated behavioral, imaging, and hemodynamic probes of mesocorticolimbic dopaminergic pathways within the context of manipulations of psychological constructs previously linked to placebo responses (e.g., expectation of improvement). The aim of this manuscript is to present the rationale of the study design and to demonstrate how a cross-modal methodology may be utilized to investigate the role of reward circuitry in placebo response in MDD.

Novel voxelwise residual analysis of [11C]raclopride PET data improves detection of low-amplitude dopamine release

Existing methods for voxelwise transient dopamine (DA) release detection rely on explicit kinetic modeling of the [11C]raclopride PET time activity curve, which at the voxel level is typically confounded by noise, leading to poor performance for detection of low-amplitude DA release-induced signals. Here we present a novel data-driven, task-informed method-referred to as Residual Space Detection (RSD)-that transforms PET time activity curves to a residual space where DA release-induced perturbations can be isolated and processed. Using simulations, we demonstrate that this method significantly increases detection performance compared to existing kinetic model-based methods for low-magnitude DA release (simulated +100% peak increase in basal DA concentration). In addition, results from nine healthy controls injected with a single bolus of [11C]raclopride performing a finger tapping motor task are shown as proof-of-concept. The ability to detect relatively low magnitudes of dopamine release in the human brain using a single bolus injection, while achieving higher statistical power than previous methods, may additionally enable more complex analyses of neurotransmitter systems. Moreover, RSD is readily generalizable to multiple tasks performed during a single PET scan, further extending the capabilities of task-based single-bolus protocols.

Amphetamine-induced dopamine release in rat: Whole-brain spatiotemporal analysis with [11C]raclopride and positron emission tomography

Whole-brain mapping of drug effects are needed to understand the neural underpinnings of drug-related behaviors. Amphetamine administration is associated with robust increases in striatal dopamine (DA) release. Dopaminergic terminals are, however, present across several associative brain regions, which may contribute to behavioral effects of amphetamine. Yet the assessment of DA release has been restricted to a few brain regions of interest. The present work employed positron emission tomography (PET) with [11C]raclopride to investigate regional and temporal characteristics of amphetamine-induced DA release across twenty sessions in adult female Sprague Dawley rats. Amphetamine was injected intravenously (2 mg/kg) to cause displacement of [11C]raclopride binding from DA D2-like receptors, assessed using temporally sensitive pharmacokinetic PET model (lp-ntPET). We show amphetamine-induced [11C]raclopride displacement in the basal ganglia, and no changes following saline injections. Peak occupancy was highest in nucleus accumbens, followed by caudate-putamen and globus pallidus. Importantly, significant amphetamine-induced displacement was also observed in several extrastriatal regions, and specifically in thalamus, insula, orbitofrontal cortex, and secondary somatosensory area. For these, peak occupancy occurred later and was lower as compared to the striatum. Collectively, these findings demonstrate distinct amphetamine-induced DA responses across the brain, and that [11C]raclopride-PET can be employed to detect such spatiotemporal differences.

Dopamine release in human associative striatum during reversal learning

The dopaminergic system is firmly implicated in reversal learning but human measurements of dopamine release as a correlate of reversal learning success are lacking. Dopamine release and hemodynamic brain activity in response to unexpected changes in action-outcome probabilities are here explored using simultaneous dynamic [11C]Raclopride PET-fMRI and computational modelling of behavior. When participants encounter reversed reward probabilities during a card guessing game, dopamine release is observed in associative striatum. Individual differences in absolute reward prediction error and sensitivity to errors are associated with peak dopamine receptor occupancy. The fMRI response to perseverance errors at the onset of a reversal spatially overlap with the site of dopamine release. Trial-by-trial fMRI correlates of absolute prediction errors show a response in striatum and association cortices, closely overlapping with the location of dopamine release, and separable from a valence signal in ventral striatum. The results converge to implicate striatal dopamine release in associative striatum as a central component of reversal learning, possibly signifying the need for increased cognitive control when new stimuli-responses should be learned.

Machine learning methods for tracer kinetic modelling

Tracer kinetic modelling based on dynamic PET is an important field of Nuclear Medicine for quantitative functional imaging. Yet, its implementation in clinical routine has been constrained by its complexity and computational costs. Machine learning poses an opportunity to improve modelling processes in terms of arterial input function prediction, the prediction of kinetic modelling parameters and model selection in both clinical and preclinical studies while reducing processing time. Moreover, it can help improving kinetic modelling data used in downstream tasks such as tumor detection. In this review, we introduce the basics of tracer kinetic modelling and present a literature review of original works and conference papers using machine learning methods in this field.

Neural circuit selective for fast but not slow dopamine increases in drug reward

The faster a drug enters the brain, the greater its addictive potential, yet the brain circuits underlying the rate dependency to drug reward remain unresolved. With simultaneous PET-fMRI we linked dynamics of dopamine signaling, brain activity/connectivity, and self-reported 'high' in 20 adults receiving methylphenidate orally (results in slow delivery) and intravenously (results in fast delivery) (trial NCT03326245). We estimated speed of striatal dopamine increases to oral and IV methylphenidate and then tested where brain activity was associated with slow and fast dopamine dynamics (primary endpoint). We then tested whether these brain circuits were temporally associated with individual 'high' ratings to methylphenidate (secondary endpoint). A corticostriatal circuit comprising the dorsal anterior cingulate cortex and insula and their connections with dorsal caudate was activated by fast (but not slow) dopamine increases and paralleled 'high' ratings. These data provide evidence in humans for a link between dACC/insula activation and fast but not slow dopamine increases and document a critical role of the salience network in drug reward.

Kinetic models for estimating occupancy from single-scan PET displacement studies

The traditional design of PET target engagement studies is based on a baseline scan and one or more scans after drug administration. We here evaluate an alternative design in which the drug is administered during an on-going scan (i.e., a displacement study). This approach results both in lower radiation exposure and lower costs. Existing kinetic models assume steady state. This condition is not present during a drug displacement and consequently, our aim here was to develop kinetic models for analysing PET displacement data. We modified existing compartment models to accommodate a time-variant increase in occupancy following the pharmacological in-scan intervention. Since this implies the use of differential equations that cannot be solved analytically, we developed instead one approximate and one numerical solution. Through simulations, we show that if the occupancy is relatively high, it can be estimated without bias and with good accuracy. The models were applied to PET data from six pigs where [11C]UCB-J was displaced by intravenous brivaracetam. The dose-occupancy relationship estimated from these scans showed good agreement with occupancies calculated with Lassen plot applied to baseline-block scans of two pigs. In summary, the proposed models provide a framework to determine target occupancy from a single displacement scan.

Time-varying SUVr reflects the dynamics of dopamine increases during methylphenidate challenges in humans

Dopamine facilitates cognition and is implicated in reward processing. Methylphenidate, a dopamine transporter blocker widely used to treat attention-deficit/hyperactivity disorder, can have rewarding and addictive effects if injected. Since methylphenidate's brain uptake is much faster after intravenous than oral intake, we hypothesize that the speed of dopamine increases in the striatum in addition to its amplitude underly drug reward. To test this we use simulations and PET data of [¹¹C]raclopride's binding displacement with oral and intravenous methylphenidate challenges in 20 healthy controls. Simulations suggest that the time-varying difference in standardized uptake value ratios for [¹¹C]raclopride between placebo and methylphenidate conditions is a proxy for the time-varying dopamine increases induced by methylphenidate. Here we show that the dopamine increase induced by intravenous methylphenidate (0.25 mg/kg) in the striatum is significantly faster than that by oral methylphenidate (60 mg), and its time-to-peak is strongly associated with the intensity of the self-report of "high". We show for the first time that the "high" is associated with the fast dopamine increases induced by methylphenidate.

Drug characteristics derived from kinetic modeling: combined 11C-UCB-J human PET imaging with levetiracetam and brivaracetam occupancy of SV2A

BACKGROUND

Antiepileptic drugs, levetiracetam (LEV) and brivaracetam (BRV), bind to synaptic vesicle glycoprotein 2A (SV2A). In their anti-seizure activity, speed of brain entry may be an important factor. BRV showed faster entry into the human and non-human primate brain, based on more rapid displacement of SV2A tracer ¹¹C-UCB-J. To extract additional information from previous human studies, we developed a nonlinear model that accounted for drug entry into the brain and binding to SV2A using brain ¹¹C-UCB-J positron emission tomography (PET) data and the time-varying plasma drug concentration, to assess the kinetic parameter K₁ (brain entry rate) of the drugs.

METHOD

Displacement (LEV or BRV p.i. 60 min post-tracer injection) and post-dose scans were conducted in five healthy subjects. Blood samples were collected for measurement of drug concentration and the tracer arterial input function. Fitting of nonlinear differential equations was applied simultaneously to time-activity curves (TACs) from displacement and post-dose scans to estimate 5 parameters: K₁ (drug), K₁(¹¹C-UCB-J, displacement), K₁(¹¹C-UCB-J, post-dose), free fraction of ¹¹C-UCB-J in brain (f_ND(¹¹C-UCB-J)), and distribution volume of ¹¹C-UCB-J (V_T(UCB-J)). Other parameters (K_D(drug), K_D(¹¹C-UCB-J), f_P(drug), f_P(¹¹C-UCB-J, displacement), f_P(¹¹C-UCB-J, post-dose), f_ND(drug), k_off(drug), k_off(¹¹C-UCB-J)) were fixed to literature or measured values.

RESULTS

The proposed model described well the TACs in all subjects; however, estimates of drug K₁ were unstable in comparison with ¹¹C-UCB-J K₁ estimation. To provide a conservative estimate of the relative speed of brain entry for BRV vs. LEV, we determined a lower bound on the ratio BRV K₁/LEV K₁, by finding the lowest BRV K₁ or highest LEV K₁ that were statistically consistent with the data. Specifically, we used the F test to compare the residual sum of squares with fixed BRV K₁ to that with floating BRV K₁ to obtain the lowest possible BRV K₁; the same analysis was performed to find the highest LEV K₁. The lower bound of the ratio BRV K₁/LEV K₁ was ~ 7.

CONCLUSIONS

Under appropriate conditions, this advanced nonlinear model can directly estimate entry rates of drugs into tissue by analysis of PET TACs. Using a conservative statistical cutoff, BRV enters the brain at least sevenfold faster than LEV.

Nicotine Patch Alters Patterns of Cigarette Smoking-Induced Dopamine Release: Patterns Relate to Biomarkers Associated With Treatment Response

INTRODUCTION

Tobacco smoking is a major public health burden. The first-line pharmacological treatment for tobacco smoking is nicotine replacement therapy (eg, the nicotine patch (NIC)). Nicotine acts on nicotinic-acetylcholine receptors on dopamine terminals to release dopamine in the ventral and dorsal striatum encoding reward and habit formation, respectively.

AIMS AND METHODS

To better understand treatment efficacy, a naturalistic experimental design combined with a kinetic model designed to characterize smoking-induced dopamine release in vivo was used. Thirty-five tobacco smokers (16 female) wore a NIC (21 mg, daily) for 1-week and a placebo patch (PBO) for 1-week in a randomized, counter-balanced order. Following 1-week under NIC and then overnight abstinence, smokers participated in a 90-minute [11C]raclopride positron emission tomography scan and smoked a cigarette while in the scanner. Identical procedures were followed for the PBO scan. A time-varying kinetic model was used at the voxel level to model transient dopamine release peaking instantaneously at the start of the stimulus and decaying exponentially. Magnitude and spatial extent of dopamine release were estimated. Smokers were subcategorized by nicotine dependence level and nicotine metabolism rate.

RESULTS

Dopamine release magnitude was enhanced by NIC in ventral striatum and diminished by NIC in dorsal striatum. More-dependent smokers activated more voxels than the less-dependent smokers under both conditions. Under PBO, fast metabolizers activated more voxels in ventral striatum and fewer voxels in dorsal striatum compared to slow metabolizers.

CONCLUSIONS

These findings demonstrate that the model captured a pattern of transient dopamine responses to cigarette smoking which may be different across smoker subgroup categorizations.

IMPLICATIONS

This is the first study to show that NIC alters highly localized patterns of cigarette smoking-induced dopamine release and that levels of nicotine dependence and nicotine clearance rate contribute to these alterations. This current work included a homogeneous subject sample with regards to demographic and smoking variables, as well as a highly sensitive model capable of detecting significant acute dopamine transients. The findings of this study add support to the recent identification of biomarkers for predicting the effect of nicotine replacement therapies on dopamine function which could help refine clinical practice for smoking cessation.

Assessment of motion and model bias on the detection of dopamine response to behavioral challenge

Compartmental modeling analysis of ¹¹C-raclopride (RAC) PET data can be used to measure the dopaminergic response to intra-scan behavioral tasks. Bias in estimates of binding potential (BP_ND) and its dynamic changes (ΔBP_ND) can arise both when head motion is present and when the compartmental model used for parameter estimation deviates from the underlying biology. The purpose of this study was to characterize the effects of motion and model bias within the context of a behavioral task challenge, examining the impacts of different mitigation strategies. Seventy healthy adults were administered bolus plus constant infusion RAC during a simultaneous PET/magnetic resonance (MR) scan with a reward task experiment. BP_ND and ΔBP_ND were estimated using an extension of the Multilinear Reference Tissue Model (E-MRTM2) and a new method (DE-MRTM2) was proposed to selectively discount the contribution of the initial uptake period. Motion was effectively corrected with a standard frame-based approach, which performed equivalently to a more complex reconstruction-based approach. DE-MRTM2 produced estimates of ΔBP_ND in putamen and nucleus accumbens that were significantly different from those estimated from E-MRTM2, while also decoupling ΔBP_ND values from first-pass k₂' estimation and removing skew in the spatial bias distribution of parametric ΔBP_ND estimates within the striatum.

Spatiotemporal Kernel Reconstruction for Linear Parametric Neurotransmitter PET Kinetic Modeling in Motion Correction Brain PET of Awake Rats

The linear parametric neurotransmitter positron emission tomography (lp-ntPET) kinetic model can be used to detect transient changes (activation) in endogenous neurotransmitter levels. Preclinical PET scans in awake animals can be performed to investigate neurotransmitter transient changes. Here we use the spatiotemporal kernel reconstruction (Kernel) for noise reduction in dynamic PET, and lp-ntPET kinetic modeling. Kernel is adapted for motion correction reconstruction, applied in awake rat PET scans. We performed 2D rat brain phantom simulation using the ntPET model at 3 different noise levels. Data was reconstructed with independent frame reconstruction (IFR), IFR with HYPR denoising, and Kernel, and lp-ntPET kinetic parameters (k 2a : efflux rate, γ: activation magnitude, t d : activation onset time, and t p : activation peak time) were calculated. Additionally, significant activation magnitude (γ) difference with respect to a region with no activation (rest) was calculated. Finally, [11C]raclopride experiments were performed in anesthetized and awake rats, injecting cold raclopride at 20 min after scan start to simulate endogenous neurotransmitter release. For simulated data at the regional level, IFR coefficient of variation (COV) of k 2a , γ, t d and t p was reduced with HYPR denoising, but Kernel showed the lowest COV (2 fold reduction compared with IFR). At the pixel level the same trend is observed for k 2a , γ, t d and t p COV, but reduction is larger with Kernel compared with IFR (10-14 fold). Bias in γ with respect with noise-free values was additionally reduced using Kernel (difference of 292, 72.4, and -6.92% for IFR, IFR+KYPR, and Kernel, respectively). Significant difference in activation between the rest and active region could be detected at a simulated activation of 160% for IFR and IFR+HYPR, and of 120% for Kernel. In rat experiments, lp-ntPET parameters have better confidence intervals using Kernel. In the γ, and t d parametric maps, the striatum structure can be identified with Kernel but not with IFR. Striatum voxel-wise γ, t d and t p values have lower variability using Kernel compared with IFR and IFR+HYPR. The spatiotemporal kernel reconstruction adapted for motion correction reconstruction allows to improve lp-ntPET kinetic modeling noise in awake rat studies, as well as detection of subtle neurotransmitter activations.

A multi-pronged investigation of option generation using depression, PET and modafinil

Option generation is a critical process in decision making, but previous studies have largely focused on choices between options given by a researcher. Consequently, how we self-generate options for behaviour remain poorly understood. Here, we investigated option generation in major depressive disorder and how dopamine might modulate this process, as well as the effects of modafinil (a putative cognitive enhancer) on option generation in healthy individuals. We first compared differences in self-generated options between healthy non-depressed adults [n = 44, age = 26.3 years (SD 5.9)] and patients with major depressive disorder [n = 54, age = 24.8 years (SD 7.4)]. In the second study, a subset of depressed individuals [n = 22, age = 25.6 years (SD 7.8)] underwent PET scans with 11C-raclopride to examine the relationships between dopamine D2/D3 receptor availability and individual differences in option generation. Finally, a randomized, double-blind, placebo-controlled, three-way crossover study of modafinil (100 mg and 200 mg), was conducted in an independent sample of healthy people [n = 19, age = 23.2 years (SD 4.8)] to compare option generation under different doses of this drug. The first study revealed that patients with major depressive disorder produced significantly fewer options [t(96) = 2.68, P = 0.009, Cohen's d = 0.54], albeit with greater uniqueness [t(96) = -2.54, P = 0.01, Cohen's d = 0.52], on the option generation task compared to healthy controls. In the second study, we found that 11C-raclopride binding potential in the putamen was negatively correlated with fluency (r = -0.69, P = 0.001) but positively associated with uniqueness (r = 0.59, P = 0.007). Hence, depressed individuals with higher densities of unoccupied putamen D2/D3 receptors in the putamen generated fewer but more unique options, whereas patients with lower D2/D3 receptor availability were likely to produce a larger number of similar options. Finally, healthy participants were less unique [F(2,36) = 3.32, P = 0.048, partial η2 = 0.16] and diverse [F(2,36) = 4.31, P = 0.021, partial η2 = 0.19] after taking 200 mg versus 100 mg and 0 mg of modafinil, while fluency increased linearly with dosage at a trend level [F(1,18) = 4.11, P = 0.058, partial η2 = 0.19]. Our results show, for the first time, that option generation is affected in clinical depression and that dopaminergic activity in the putamen of patients with major depressive disorder may play a key role in the self-generation of options. Modafinil was also found to influence option generation in healthy people by reducing the creativity of options produced.

Dopamine and fear memory formation in the human amygdala

Learning which environmental cues that predict danger is crucial for survival and accomplished through Pavlovian fear conditioning. In humans and rodents alike, fear conditioning is amygdala-dependent and rests on similar neurocircuitry. Rodent studies have implicated a causative role for dopamine in the amygdala during fear memory formation, but the role of dopamine in aversive learning in humans is unclear. Here, we show dopamine release in the amygdala and striatum during fear learning in humans. Using simultaneous positron emission tomography and functional magnetic resonance imaging, we demonstrate that the amount of dopamine release is linked to strength of conditioned fear responses and linearly coupled to learning-induced activity in the amygdala. Thus, like in rodents, formation of amygdala-dependent fear memories in humans seems to be facilitated by endogenous dopamine release, supporting an evolutionary conserved neurochemical mechanism for aversive memory formation.

Dissecting Motor and Cognitive Component Processes of a Finger-Tapping Task With Hybrid Dopamine Positron Emission Tomography and Functional Magnetic Resonance Imaging

Striatal dopamine is involved in facilitation of motor action as well as various cognitive and emotional functions. Positron emission tomography (PET) is the primary imaging method used to investigate dopamine function in humans. Previous PET studies have shown striatal dopamine release during simple finger tapping in both the putamen and the caudate. It is likely that dopamine release in the putamen is related to motor processes while dopamine release in the caudate could signal sustained cognitive component processes of the task, but the poor temporal resolution of PET has hindered firm conclusions. In this study we simultaneously collected [11C]Raclopride PET and functional Magnetic Resonance Imaging (fMRI) data while participants performed finger tapping, with fMRI being able to isolate activations related to individual tapping events. The results revealed fMRI-PET overlap in the bilateral putamen, which is consistent with a motor component process. Selective PET responses in the caudate, ventral striatum, and right posterior putamen, were also observed but did not overlap with fMRI responses to tapping events, suggesting that these reflect non-motor component processes of finger tapping. Our findings suggest an interplay between motor and non-motor-related dopamine release during simple finger tapping and illustrate the potential of hybrid PET-fMRI in revealing distinct component processes of cognitive functions.

[11C]PBR28 radiotracer kinetics are not driven by alterations in cerebral blood flow

The positron emission tomography (PET) radiotracer [¹¹C]PBR28 has been increasingly used to image the translocator protein (TSPO) as a marker of neuroinflammation in a variety of brain disorders. Interrelatedly, similar clinical populations can also exhibit altered brain perfusion, as has been shown using arterial spin labelling in magnetic resonance imaging (MRI) studies. Hence, an unsolved debate has revolved around whether changes in perfusion could alter delivery, uptake, or washout of the radiotracer [¹¹C]PBR28, and thereby influence outcome measures that affect interpretation of TSPO upregulation. In this simultaneous PET/MRI study, we demonstrate that [¹¹C]PBR28 signal elevations in chronic low back pain patients are not accompanied, in the same regions, by increases in cerebral blood flow (CBF) compared to healthy controls, and that areas of marginal hypoperfusion are not accompanied by decreases in [¹¹C]PBR28 signal. In non-human primates, we show that hypercapnia-induced increases in CBF during radiotracer delivery or washout do not alter [¹¹C]PBR28 outcome measures. The combined results from two methodologically distinct experiments provide support from human data and direct experimental evidence from non-human primates that changes in CBF do not influence outcome measures reported by [¹¹C]PBR28 PET imaging studies and corresponding interpretations of the biological meaning of TSPO upregulation.

Assessment of transient dopamine responses to smoked cannabis

BACKGROUND

Dopaminergic mechanisms that may underlie cannabis' reinforcing effects are not well elucidated in humans. This positron emission tomography (PET) imaging study used the dopamine D2/3 receptor antagonist [11C]raclopride and kinetic modelling testing for transient changes in radiotracer uptake to assess the striatal dopamine response to smoked cannabis in a preliminary sample.

METHODS

PET emission data were acquired from regular cannabis users (n = 14; 7 M/7 F; 19-32 years old) over 90 min immediately after [11C]raclopride administration (584 ± 95 MBq) as bolus followed by constant infusion (Kbol = 105 min). Participants smoked a cannabis cigarette, using a paced puff protocol, 35 min after scan start. Plasma concentrations of Δ9-THC and metabolites and ratings of subjective "high" were collected during imaging. Striatal dopamine responses were assessed voxelwise with a kinetic model testing for transient reductions in [11C]raclopride binding, linear-parametric neurotransmitter PET (lp-ntPET) (cerebellum as a reference region).

RESULTS

Cannabis smoking increased plasma Δ9-THC levels (peak: 0-10 min) and subjective high (peak: 0-30 min). Significant clusters (>16 voxels) modeled by transient reductions in [11C]raclopride binding were identified for all 12 analyzed scans. In total, 26 clusters of significant responses to cannabis were detected, of which 16 were located in the ventral striatum, including at least one ventral striatum cluster in 11 of the 12 analyzed scans.

CONCLUSIONS

These preliminary data support the sensitivity of [11C]raclopride PET with analysis of transient changes in radiotracer uptake to detect cannabis smoking-induced dopamine responses. This approach shows future promise to further elucidate roles of mesolimbic dopaminergic signaling in chronic cannabis use. ClinicalTrials.gov Identifier: NCT02817698.

Detecting and classifying neurotransmitter signals from ultra-high sensitivity PET data: the future of molecular brain imaging

Efforts to build the next generation of brain PET scanners are underway. It is expected that a new scanner (NS) will offer anorder-of-magnitude improvementin sensitivity to counts compared to the current state-of-the-art, Siemens HRRT. Our goal was to explore the use of the anticipated increased sensitivity in combination with the linear-parametric neurotransmitter PET (lp-ntPET) model to improve detection and classification of transient dopamine (DA) signals. We simulated striatal [¹¹C]raclopride PET data to be acquired on a future NS which will offer ten times the sensitivity of the HRRT. The simulated PET curves included the effects of DA signals that varied in start-times, peak-times, and amplitudes. We assessed the detection sensitivity of lp-ntPET to various shapes of DA signal. We evaluated classification thresholds for their ability to separate 'early'- versus 'late'-peaking, and 'low'- versus 'high'-amplitude events in a 4D phantom. To further refine the characterization of DA signals, we developed a weighted k-nearest neighbors (wkNN) algorithm to incorporate information from the neighborhood around each voxel to reclassify it, with a level of certainty. Our findings indicate that the NS would expand the range of detectable neurotransmitter events to 72%, compared to the HRRT (31%). Application of wkNN augmented the detection sensitivity to DA signals in simulated NS data to 92%. This work demonstrates that the ultra-high sensitivity expected from a new generation of brain PET scanner, combined with a novel classification algorithm, will make it possible to accurately detect and classify short-lived DA signals in the brain based on their amplitude and timing.

PET-ABC: fully Bayesian likelihood-free inference for kinetic models

Aims.We describe an intuitive, easy to use method called PET-ABC that enables full Bayesian statistical inference from single subject dynamic PET data. The performance of PET-ABC was compared with weighted non-linear least squares (WNLS) in terms of reliability of kinetic parameter estimation and statistical power for model selection.Methods.Dynamic PET data based on 1-tissue and 2-tissue compartmental models were simulated with 2 noise models and 3 noise levels. PET-ABC was used to evaluate the reliability of parameter estimates under each condition. It was also used to perform model selection for a simulated noisy dataset composed of a mixture of 1- and 2-tissue compartment kinetics. Finally, PET-ABC was used to analyze a non-steady state dynamic [¹¹C] raclopride study performed on a fully conscious rat administered either 2 mg.kg^-1amphetamine or saline 20 min after tracer injection.Results.PET-ABC yielded posterior point estimates for model parameters with smaller variance than WNLS, as well as probability density functions indicating confidence intervals for those estimates. It successfully identified the superiority of a 2-tissue compartment model to fit the simulated mixed model data. For the drug challenge study, the post observation probability of striatal displacement of the PET signal was 0.9 for amphetamine and approximately 0 for saline, indicating a high probability of amphetamine-induced endogenous dopamine release in the striatum. PET-ABC also demonstrated superior statistical power to WNLS (0.87 versus 0.09) for selecting the correct model in a simulated ligand displacement study.Conclusions.PET-ABC is a simple and intuitive method that provides complete Bayesian statistical analysis of single subject dynamic PET data, including the extent to which model parameter estimates and model choice are supported by the data. Software for PET-ABC is freely available as part of thePETabcpackagehttps://github.com/cgrazian/PETabc.

[18F]F13640, a 5-HT1A Receptor Radiopharmaceutical Sensitive to Brain Serotonin Fluctuations

Introduction

Serotonin is involved in a variety of physiological functions and brain disorders. In this context, efforts have been made to investigate the in vivo fluctuations of this neurotransmitter using positron emission tomography (PET) imaging paradigms. Since serotonin is a full agonist, it binds preferentially to G-protein coupled receptors. In contrast, antagonist PET ligands additionally interact with uncoupled receptors. This could explain the lack of sensitivity to serotonin fluctuations of current 5-HT_1A radiopharmaceuticals which are mainly antagonists and suggests that agonist radiotracers would be more appropriate to measure changes in neurotransmitter release. The present study evaluated the sensitivity to endogenous serotonin release of a recently developed, selective 5-HT_1A receptor PET radiopharmaceutical, the agonist [¹⁸F]F13640 (a.k.a. befiradol or NLX-112).

Materials and Methods

Four cats each underwent three PET scans with [¹⁸F]F13640, i.e., a control PET scan of 90 min, a PET scan preceded 30 min before by an intravenous injection 1 mg/kg of d-fenfluramine, a serotonin releaser (blocking challenge), and a PET scan comprising the intravenous injection of 1 mg/kg of d-fenfluramine 30 min after the radiotracer injection (displacement challenge). Data were analyzed with regions of interest and voxel-based approaches. A lp-ntPET model approach was implemented to determine the dynamic of serotonin release during the challenge study.

Results

D-fenfluramine pretreatment elicited a massive inhibition of [¹⁸F]F13640 labeling in regions known to express 5-HT_1A receptors, e.g., raphe nuclei, hippocampus, thalamus, anterior cingulate cortex, caudate putamen, occipital, frontal and parietal cortices, and gray matter of cerebellum. Administration of d-fenfluramine during PET acquisition indicates changes in occupancy from 10% (thalamus) to 31% (gray matter of cerebellum) even though the dissociation rate of [¹⁸F]F13640 over the 90 min acquisition time was modest. The lp-ntPET simulation succeeded in differentiating the control and challenge conditions.

Conclusion

The present findings demonstrate that labeling of 5-HT_1A receptors with [¹⁸F]F13640 is sensitive to serotonin concentration fluctuations in vivo. Although the data underline the need to perform longer PET scan to ensure accurate measure of displacement, they support clinical development of [¹⁸F]F13640 as a tool to explore experimental paradigms involving physiological or pathological (neurological or neuropsychiatric pathologies) fluctuations of extracellular serotonin.

Denoising non-steady state dynamic PET data using a feed-forward neural network

The quality of reconstructed dynamic PET images, as well as the statistical reliability of the estimated pharmacokinetic parameters is often compromised by high levels of statistical noise, particularly at the voxel level. Many denoising strategies have been proposed, both in the temporal and spatial domain, which substantially improve the signal to noise ratio of the reconstructed dynamic images. However, although most filtering approaches are fairly successful in reducing the spatio-temporal inter-voxel variability, they may also average out or completely eradicate the critically important temporal signature of a transient neurotransmitter activation response that may be present in a non-steady state dynamic PET study. In this work, we explore an approach towards temporal denoising of non-steady state dynamic PET images using an artificial neural network, which was trained to identify the temporal profile of a time-activity curve, while preserving any potential activation response. We evaluated the performance of a feed-forward perceptron neural network to improve the signal to noise ratio of dynamic [¹¹C]raclopride activation studies and compared it with the widely used highly constrained back projection (HYPR) filter. Results on both simulated Geant4 Application for Tomographic Emission data of a realistic rat brain phantom and experimental animal data of a freely moving animal study showed that the proposed neural network can efficiently improve the noise characteristics of dynamic data in the temporal domain, while it can lead to a more reliable estimation of voxel-wise activation response in target region. In addition, improvements in signal-to-noise ratio achieved by denoising the dynamic data using the proposed neural network led to improved accuracy and precision of the estimated model parameters of the lp-ntPET model, compared to the HYPR filter. The performance of the proposed denoising approach strongly depends on the amount of noise in the dynamic PET data, with higher noise leading to substantially higher variability in the estimated parameters of the activation response. Overall, the feed-forward network led to a similar performance as the HYPR filter in terms of spatial denoising, but led to notable improvements in terms of temporal denoising, which in turn improved the estimation activation parameters.

Early environmental enrichment and impoverishment differentially affect addiction-related behavioral traits, cocaine-taking, and dopamine D2/3 receptor signaling in a rat model of vulnerability to drug abuse

RATIONALE

Risk factors for drug addiction include genetics, environment, and behavioral traits such as impulsivity and novelty preference (NP), which have been related to deficits in striatal dopamine (DA) D_2/3-receptors (D_2/3R) and heightened amphetamine (AMPH)-induced DA release. However, the influence of the early rearing environment on these behavioral and neurochemical variables is not clear.

OBJECTIVES

We investigated the influence of early rearing environment on striatal D_2/3R availabilities and AMPH-induced DA release in relation to impulsivity, NP, and propensity to drug self-administration (SA) in "addiction-prone" Roman high- (RHA) and "addiction-resistant" Roman low-avoidance (RLA) rats.

METHODS

Animals were reared post-weaning in either environmental enrichment (EE) or impoverishment (EI) and were assessed at adulthood for impulsivity, NP, and propensity to cocaine SA. EE and EI rats were also scanned using single-photon emission computed tomography to concurrently measure in vivo striatal D_2/3R availability and AMPH-induced DA release.

RESULTS

EE vs. EI was associated with heightened impulsivity and a lack of NP in both rat lines. Higher dorsal striatal D_2/3R densities were found in RHA EE and higher AMPH-induced DA release in RLA EE. Both impulsivity and NP were negatively correlated to dorsal striatal D_2/3R availabilities and positively correlated with AMPH-induced DA release in EI but not in EE. EE vs. EI was related to a faster rate of cocaine intake and elevated active timeout responses in RHAs.

CONCLUSION

Our results suggest non-monotonic, environment-dependent, relationships between impulsivity, NP, and D_2/3R-mediated signaling, and suggest that EI vs. EE may decrease the reinforcing effects of psychostimulants in predisposed individuals.

A Monte Carlo approach for improving transient dopamine release detection sensitivity

Current methods using a single PET scan to detect voxel-level transient dopamine release-using F-test (significance) and cluster size thresholding-have limited detection sensitivity for clusters of release small in size and/or having low release levels. Specifically, simulations show that voxels with release near the peripheries of such clusters are often rejected-becoming false negatives and ultimately distorting the F-distribution of rejected voxels. We suggest a Monte Carlo method that incorporates these two observations into a cost function, allowing erroneously rejected voxels to be accepted under specified criteria. In simulations, the proposed method improves detection sensitivity by up to 50% while preserving the cluster size threshold, or up to 180% when optimizing for sensitivity. A further parametric-based voxelwise thresholding is then suggested to better estimate the release dynamics in detected clusters. We apply the Monte Carlo method to a pilot scan from a human gambling study, where additional parametrically unique clusters are detected as compared to the current best methods-results consistent with our simulations.

Dopamine D2/3 Receptor Availabilities and Evoked Dopamine Release in Striatum Differentially Predict Impulsivity and Novelty Preference in Roman High- and Low-Avoidance Rats

BACKGROUND

Impulsivity and novelty preference are both associated with an increased propensity to develop addiction-like behaviors, but their relationship and respective underlying dopamine (DA) underpinnings are not fully elucidated.

METHODS

We evaluated a large cohort (n = 49) of Roman high- and low-avoidance rats using single photon emission computed tomography to concurrently measure in vivo striatal D2/3 receptor (D2/3R) availability and amphetamine (AMPH)-induced DA release in relation to impulsivity and novelty preference using a within-subject design. To further examine the DA-dependent processes related to these traits, midbrain D2/3-autoreceptor levels were measured using ex vivo autoradiography in the same animals.

RESULTS

We replicated a robust inverse relationship between impulsivity, as measured with the 5-choice serial reaction time task, and D2/3R availability in ventral striatum and extended this relationship to D2/3R levels measured in dorsal striatum. Novelty preference was positively related to impulsivity and showed inverse associations with D2/3R availability in dorsal striatum and ventral striatum. A high magnitude of AMPH-induced DA release in striatum predicted both impulsivity and novelty preference, perhaps owing to the diminished midbrain D2/3-autoreceptor availability measured in high-impulsive/novelty-preferring Roman high-avoidance animals that may amplify AMPH effect on DA transmission. Mediation analyses revealed that while D2/3R availability and AMPH-induced DA release in striatum are both significant predictors of impulsivity, the effect of striatal D2/3R availability on novelty preference is fully mediated by evoked striatal DA release.

CONCLUSIONS

Impulsivity and novelty preference are related but mediated by overlapping, yet dissociable, DA-dependent mechanisms in striatum that may interact to promote the emergence of an addiction-prone phenotype.

PET imaging of neurotransmission using direct parametric reconstruction

Receptor ligand-based dynamic Positron Emission Tomography (PET) permits the measurement of neurotransmitter release in the human brain. For single-scan paradigms, the conventional method of estimating changes in neurotransmitter levels relies on fitting a pharmacokinetic model to activity concentration histories extracted after PET image reconstruction. However, due to the statistical fluctuations of activity concentration data at the voxel scale, parametric images computed using this approach often exhibit low signal-to-noise ratio, impeding characterization of neurotransmitter release. Numerous studies have shown that direct parametric reconstruction (DPR) approaches, which combine image reconstruction and kinetic analysis in a unified framework, can improve the signal-to-noise ratio of parametric mapping. However, there is little experience with DPR in imaging of neurotransmission and the performance of the approach in this application has not been evaluated before in humans. In this report, we present and evaluate a DPR methodology that computes 3-D distributions of ligand transport, binding potential (BP_ND) and neurotransmitter release magnitude (γ) from a dynamic sequence of PET sinograms. The technique employs the linear simplified reference region model (LSRRM) of Alpert et al. (2003), which represents an extension of the simplified reference region model that incorporates time-varying binding parameters due to radioligand displacement by release of neurotransmitter. Estimation of parametric images is performed by gradient-based optimization of a Poisson log-likelihood function incorporating LSRRM kinetics and accounting for the effects of head movement, attenuation, detector sensitivity, random and scattered coincidences. A ¹¹C-raclopride simulation study showed that the proposed approach substantially reduces the bias and variance of voxel-wise γ estimates as compared to standard methods. Moreover, simulations showed that detection of release could be made more reliable and/or conducted using a smaller sample size using the proposed DPR estimator. Likewise, images of BP_ND computed using DPR had substantially improved bias and variance properties. Application of the method in human subjects was demonstrated using ¹¹C-raclopride dynamic scans and a reward task, confirming the improved quality of the estimated parametric images using the proposed approach.

Methods for Quantifying Neurotransmitter Dynamics in the Living Brain With PET Imaging

Positron emission tomography (PET) neuroimaging in neuropsychiatry is a powerful tool for the quantification of molecular brain targets to characterize disease, assess disease subtype differences, evaluate short- and long-term effects of treatments, or even to measure neurotransmitter levels in healthy and psychiatric conditions. In this work, we present different methodological approaches (time-invariant models and models with time-varying terms) that have been used to measure dynamic changes in neurotransmitter levels induced by pharmacological or behavioral challenges in humans. The developments and potential use of hybrid PET/magnetic resonance imaging (MRI) for neurotransmission brain research will also be highlighted.

Model Comparison Metrics Require Adaptive Correction if Parameters Are Discretized: Proof-of-Concept Applied to Transient Signals in Dynamic PET

Linear parametric neurotransmitter PET (lp-ntPET) is a novel kinetic model that estimates the temporal characteristics of a transient neurotransmitter component in PET data. To preserve computational simplicity in estimation, the parameters of the nonlinear term that describe this transient signal are discretized, and only a limited set of values for each parameter are allowed. Thus, linear estimation can be performed. Linear estimation is implemented using predefined basis functions that incorporate the discretized parameters. The implementation of the model using discretized parameters poses unique challenges for significance testing. Significance testing employs model comparison metrics to determine the significance of the improvement of the fit accomplished by including a basis function, i.e. it determines the presence of a transient signal in the PET data. A false positive occurs when the bases overfit data that do not contain a transient component. The number of parameters in a model, p, is necessary to determine the degrees of freedom in the model. In turn, p is crucial for the calculation of model selection metrics and controlling the false positive rate (FPR). In this work, we first explore the effect of parameter discretization on FPR by fitting simulated null data with varying numbers of bases. We demonstrate the dependence of FPR on number of bases. Then, we propose a correction to the number of parameters in the model, p^eff , which adapts to the number of bases used. Implementing model selection with p^eff maintains a stable FPR independent of number of bases.

Advances in simultaneous PET/MR for imaging neuroreceptor function

Hybrid imaging using PET/MRI has emerged as a platform for elucidating novel neurobiology, molecular and functional changes in disease, and responses to physiological or pharmacological interventions. For the central nervous system, PET/MRI has provided insights into biochemical processes, linking selective molecular targets and distributed brain function. This review highlights several examples that leverage the strengths of simultaneous PET/MRI, which includes measuring the perturbation of multi-modal imaging signals on dynamic timescales during pharmacological challenges, physiological interventions or behavioral tasks. We discuss important considerations for the experimental design of dynamic PET/MRI studies and data analysis approaches for comparing and quantifying simultaneous PET/MRI data. The primary focus of this review is on functional PET/MRI studies of neurotransmitter and receptor systems, with an emphasis on the dopamine, opioid, serotonin and glutamate systems as molecular neuromodulators. In this context, we provide an overview of studies that employ interventions to alter the activity of neuroreceptors or the release of neurotransmitters. Overall, we emphasize how the synergistic use of simultaneous PET/MRI with appropriate study design and interventions has the potential to expand our knowledge about the molecular and functional dynamics of the living human brain. Finally, we give an outlook on the future opportunities for simultaneous PET/MRI.

Bayesian Estimation of the ntPET Model in Single-Scan Competition PET Studies

This paper proposes an innovative method, named b-ntPET, for solving a competition model in PET. The model is built upon the state-of-the-art method called lp-ntPET. It consists in identifying the parameters of the PET kinetic model relative to a reference region that rule the steady state exchanges, together with the identification of four additional parameters defining a displacement curve caused by an endogenous neurotransmitter discharge, or by a competing injected drug targeting the same receptors as the PET tracer. The resolution process of lp-ntPET is however suboptimal due to the use of discretized basis functions, and is very sensitive to noise, limiting its sensitivity and accuracy. Contrary to the original method, our proposed resolution approach first estimates the probability distribution of the unknown parameters using Markov-Chain Monte-Carlo sampling, distributions from which the estimates are then inferred. In addition, and for increased robustness, the noise level is jointly estimated with the parameters of the model. Finally, the resolution is formulated in a Bayesian framework, allowing the introduction of prior knowledge on the parameters to guide the estimation process toward realistic solutions. The performance of our method was first assessed and compared head-to-head with the reference method lp-ntPET using well-controlled realistic simulated data. The results showed that the b-ntPET method is substantially more robust to noise and much more sensitive and accurate than lp-ntPET. We then applied the model to experimental animal data acquired in pharmacological challenge studies and human data with endogenous releases induced by transcranial direct current stimulation. In the drug challenge experiment on cats using [¹⁸F]MPPF, a serotoninergic 1A antagonist radioligand, b-ntPET measured a dose response associated with the amount of the challenged injected concurrent 5-HT1A agonist, where lp-ntPET failed. In human [¹¹C]raclopride experiment, contrary to lp-ntPET, b-ntPET successfully detected significant endogenous dopamine releases induced by the stimulation. In conclusion, our results showed that the proposed method b-ntPET has similar performance to lp-ntPET for detecting displacements, but with higher resistance to noise and better robustness to various experimental contexts. These improvements lead to the possibility of detecting and characterizing dynamic drug occupancy from a single PET scan more efficiently.

Maturation of the human striatal dopamine system revealed by PET and quantitative MRI

The development of the striatum dopamine (DA) system through human adolescence, a time of increased sensation seeking and vulnerability to the emergence of psychopathology, has been difficult to study due to pediatric restrictions on direct in vivo assessments of DA. Here, we applied neuroimaging in a longitudinal sample of n = 146 participants aged 12–30. R2′, an MR measure of tissue iron which co-localizes with DA vesicles and is necessary for DA synthesis, was assessed across the sample. In the 18–30 year-olds (n = 79) we also performed PET using [11C]dihydrotetrabenazine (DTBZ), a measure of presynaptic vesicular DA storage, and [11C]raclopride (RAC), an indicator of D2/D3 receptor availability. We observed decreases in D2/D3 receptor availability with age, while presynaptic vesicular DA storage (as measured by DTBZ), which was significantly associated with R2′ (standardized coefficient = 0.29, 95% CI = [0.11, 0.48]), was developmentally stable by age 18. Our results provide new evidence for maturational specialization of the striatal DA system through adolescence.

How the human dopamine system changes during adolescence is still unclear. Here, the authors combine PET and quantitative MRI measures to show that dopamine D2/D3 receptor availability decreases with age while presynaptic dopamine vesicular storage was developmentally stable by age 18

Is There a Role for GPCR Agonist Radiotracers in PET Neuroimaging?

Positron emission tomography (PET) is a molecular imaging modality that enables in vivo exploration of metabolic processes and especially the pharmacology of neuroreceptors. G protein-coupled receptors (GPCRs) play an important role in numerous pathophysiologic disorders of the central nervous system. Thus, they are targets of choice in PET imaging to bring proof concept of change in density in pathological conditions or in pharmacological challenge. At present, most radiotracers are antagonist ligands. In vitro data suggest that properties differ between GPCR agonists and antagonists: antagonists bind to receptors with a single affinity, whereas agonists are characterized by two different affinities: high affinity for receptors that undergo functional coupling to G-proteins, and low affinity for those that are not coupled. In this context, agonist radiotracers may be useful tools to give functional images of GPCRs in the brain, with high sensitivity to neurotransmitter release. Here, we review all existing PET radiotracers used from animals to humans and their role for understanding the ligand-receptor paradigm of GPCR in comparison with corresponding antagonist radiotracers.

Intranasal naloxone rapidly occupies brain mu-opioid receptors in human subjects

Nasal spray formulations of naloxone, a mu-opioid receptor (MOR) antagonist, are currently used for the treatment of opioid overdose. They may have additional therapeutic utility also in the absence of opioid agonist drugs, but the onset and duration of action at brain MORs have been inadequately characterized to allow such projections. This study provides initial characterization of brain MOR availability at high temporal resolution following intranasal (IN) naloxone administration to healthy volunteers in the absence of a competing opioid agonist. Fourteen participants were scanned twice using positron emission tomography (PET) and [¹¹C]carfentanil, a selective MOR agonist radioligand. Concentrations of naloxone in plasma and MOR availability (relative to placebo) were monitored from 0 to 60 min and at 300-360 min post naloxone. Naloxone plasma concentrations peaked at ~20 min post naloxone, associated with slightly delayed development of brain MOR occupancy (half of peak occupancy reached at ~10 min). Estimated peak occupancies were 67 and 85% following 2 and 4 mg IN doses, respectively. The estimated half-life of occupancy disappearance was ~100 min. The rapid onset of brain MOR occupancy by IN naloxone, evidenced by the rapid onset of its action in opioid overdose victims, was directly documented in humans for the first time. The employed high temporal-resolution PET method establishes a model that can be used to predict brain MOR occupancy from plasma naloxone concentrations. IN naloxone may have therapeutic utility in various addictions where brain opioid receptors are implicated, such as gambling disorder and alcohol use disorder.

Direct Estimation of Voxel-Wise Neurotransmitter Response Maps From Dynamic PET Data

Computational methods, such as the linear parametric neurotransmitter PET (lp-ntPET) method, have been developed to characterize the transient changes in radiotracer kinetics in the target tissue during endogenous neurotransmitter release. In this paper, we describe and evaluate a parametric reconstruction algorithm that uses an expectation maximization framework, along with the lp-ntPET model, to estimate the endogenous neurotransmitter response to stimuli directly from the measured PET data. Computer simulations showed that the proposed direct reconstruction method offers improved accuracy and precision for the estimated timing parameters of the neurotransmitter response at the voxel level ( t_d=1±2 min, for activation onset bias and standard deviation) compared with conventional post reconstruction modeling ( t_d=4±7 min). In addition, we applied the proposed direct parameter estimation methodology to a [¹¹C]raclopride displacement study of an awake rat and generated parametric maps illustrating the magnitude of ligand displacement from striatum. Although the estimated parametric maps of activation magnitude obtained from both direct and post reconstruction methodologies suffered from false positive activations, the proposed direct reconstruction framework offered more reliable parametric maps when the activation onset parameter was constrained.

Time-dependent assessment of stimulus-evoked regional dopamine release

To date, the spatiotemporal release of specific neurotransmitters at physiological levels in the human brain cannot be detected. Here, we present a method that relates minute-by-minute fluctuations of the positron emission tomography (PET) radioligand [11C]raclopride directly to subsecond dopamine release events. We show theoretically that synaptic dopamine release induces low frequency temporal variations of extrasynaptic extracellular dopamine levels, at time scales of one minute, that can evoke detectable temporal variations in the [11C]raclopride signal. Hence, dopaminergic activity can be monitored via temporal fluctuations in the [11C]raclopride PET signal. We validate this theory using fast-scan cyclic voltammetry and [11C]raclopride PET in mice during chemogenetic activation of dopaminergic neurons. We then apply the method to data from human subjects given a palatable milkshake and discover immediate and-for the first time-delayed food-induced dopamine release. This method enables time-dependent regional monitoring of stimulus-evoked dopamine release at physiological levels.

Effects of flow changes on radiotracer binding: Simultaneous measurement of neuroreceptor binding and cerebral blood flow modulation

The potential effects of changes in blood flow on the delivery and washout of radiotracers has been an ongoing question in PET bolus injection studies. This study provides practical insight into this topic by experimentally measuring cerebral blood flow (CBF) and neuroreceptor binding using simultaneous PET/MRI. Hypercapnic challenges (7% CO₂) were administered to non-human primates in order to induce controlled increases in CBF, measured with pseudo-continuous arterial spin labeling. Simultaneously, dopamine D₂/D₃ receptor binding of [¹¹C]raclopride or [¹⁸F]fallypride was monitored with dynamic PET. Experiments showed that neither time activity curves nor quantification of binding through binding potentials ( BP_ND) were measurably affected by CBF increases, which were larger than two-fold. Simulations of experimental procedures showed that even large changes in CBF should have little effect on the time activity curves of radiotracers, given a set of realistic assumptions. The proposed method can be applied to experimentally assess the flow sensitivity of other radiotracers. Results demonstrate that CBF changes, which often occur due to behavioral tasks or pharmacological challenges, do not affect PET [¹¹C]raclopride or [¹⁸F]fallypride binding studies and their quantification. The results from this study suggest flow effects may have limited impact on many PET neuroreceptor tracers with similar properties.

Toward whole-brain dopamine movies: a critical review of PET imaging of dopamine transmission in the striatum and cortex

The mesocorticolimbic dopamine (DA) circuit, comprising the mesolimbic and mesocortical DA pathways, plays a crucial role in reward, cognitive control, and motivation. The positron emission tomography (PET) radiotracer, [C-11]raclopride, has been used widely to image DA receptors and DA changes in the mesolimbic pathway before and after pharmacological and behavioral challenges. In certain circumstances, properties of traditional kinetic models-used to analyze dynamic PET data-are not well-suited to describing the effects of stimulus-induced DA release. To combat model shortcomings, the authors have advanced a suite of models that characterizes PET data in the presence of time-varying DA release. We review select [C-11]raclopride studies of the striatum during cigarette smoking to illustrate the advantages of such models. DA receptors occur in lower density in the cortex than the striatum. This, as well as higher relative background signal, poses a serious challenge to quantitative PET of DA changes in the mesocortical system. Novel high affinity radioligands [F-18]fallypride and [C-11]FLB457 have been used to image mesocortical DA transmission. Models with time-varying terms may also hold the key to optimizing sensitivity to changes in mesocortical DA. As an illustration, we compare recent PET studies of the effect of stress on cortical DA release. Finally, we consider some challenges and strategies for further optimization of sensitivity of PET to stimulus-induced DA changes throughout the whole brain.

Open-field PET: Simultaneous brain functional imaging and behavioural response measurements in freely moving small animals

A comprehensive understanding of how the brain responds to a changing environment requires techniques capable of recording functional outputs at the whole-brain level in response to external stimuli. Positron emission tomography (PET) is an exquisitely sensitive technique for imaging brain function but the need for anaesthesia to avoid motion artefacts precludes concurrent behavioural response studies. Here, we report a technique that combines motion-compensated PET with a robotically-controlled animal enclosure to enable simultaneous brain imaging and behavioural recordings in unrestrained small animals. The technique was used to measure in vivo displacement of [¹¹C]raclopride from dopamine D2 receptors (D2R) concurrently with changes in the behaviour of awake, freely moving rats following administration of unlabelled raclopride or amphetamine. The timing and magnitude of [¹¹C]raclopride displacement from D2R were reliably estimated and, in the case of amphetamine, these changes coincided with a marked increase in stereotyped behaviours and hyper-locomotion. The technique, therefore, allows simultaneous measurement of changes in brain function and behavioural responses to external stimuli in conscious unrestrained animals, giving rise to important applications in behavioural neuroscience.

Advances in PET Methodology

Recent advances in disease understanding, instrumentation technology, and computationally demanding image analysis approaches are opening new frontiers in the investigation of movement disorders and brain disease in general. A key aspect is the recognition of the need to determine molecular correlates to early functional and metabolic connectivity alterations, which are increasingly recognized as useful signatures of specific clinical disease phenotypes. Such multi-modal approaches are highly likely to provide new information on pathogenic mechanisms and to help the identification of novel therapeutic targets. This chapter describes recent methodological developments in PET starting with a very brief overview of radiotracers relevant to movement disorders while emphasizing the development of instrumentation, algorithms and imaging analysis methods relevant to multi-modal investigation of movement disorders.

News and views on in-vivo imaging of neurotransmission using PET and MRI

Molecular neuroimaging with PET is an integrated tool in psychiatry research and drug-development for as long as this modality has been available, in particular for studying neurotransmission and endogenous neurotransmitter release. Pharmacologic, behavioral and other types of challenges are currently applied to induce changes in neurochemical levels that can be inferred through their effects on changes in receptor binding and related outcome measures. Based on the availability of tracers that are sensitive for measuring neurotransmitter release these experiments have focused on the brain's dopamine system, while recent developments have extended those studies to other targets such as the serotonin or choline system. With the introduction of hybrid, truly simultaneous PET/MRI systems, in-vivo imaging of the dynamics of neuroreceptor signal transmission in the brain using PET and functional MRI (fMRI) has become possible. fMRI has the ability to provide information about the effects of receptor function that are complementary to the PET measurement. Dynamic acquisition of both PET and fMRI signals enables not only an in-vivo real-time assessment of neurotransmitter or drug binding to receptors but also dynamic receptor adaptations and receptor-specific neurotransmission. While fMRI temporal resolution is comparatively fast in relation to PET, the timescale of observable biological processes is highly dependent on the kinetics of radiotracers and study design. Overall, the combination of the specificity of PET radiotracers to neuroreceptors, fMRI signal as a functional readout and integrated study design promises to expand our understanding of the location, propagation and connections of brain activity in health and disease.

Sexual dimorphism in striatal dopaminergic responses promotes monogamy in social songbirds

In many songbird species, males sing to attract females and repel rivals. How can gregarious, non-territorial songbirds such as zebra finches, where females have access to numerous males, sustain monogamy? We found that the dopaminergic reward circuitry of zebra finches can simultaneously promote social cohesion and breeding boundaries. Surprisingly, in unmated males but not in females, striatal dopamine neurotransmission was elevated after hearing songs. Behaviorally too, unmated males but not females persistently exchanged mild punishments in return for songs. Song reinforcement diminished when dopamine receptors were blocked. In females, we observed song reinforcement exclusively to the mate’s song, although their striatal dopamine neurotransmission was only slightly elevated. These findings suggest that song-triggered dopaminergic activation serves a dual function in social songbirds: as low-threshold social reinforcement in males and as ultra-selective sexual reinforcement in females. Co-evolution of sexually dimorphic reinforcement systems can explain the coexistence of gregariousness and monogamy.

While monogamy is rare within the animal kingdom, some species – including humans and many birds – can be highly social and yet sustain monogamous relationships. Zebra finches, for example, are among a number of species of songbirds in which numerous males and females live closely together but maintain monogamous partnerships. Male songbirds use their songs to attract females, who do not themselves sing. But if female birds are attracted to any male song, how do they manage to remain monogamous when surrounded by potential suitors?

In songbirds, and in humans too, a region of the brain called the striatum regulates both social and sexual behaviors. It does this by modulating the release of a molecule called dopamine, which is the brain’s reward signal. Tokarev et al. show that hearing songs triggers dopamine release within the striatum of unattached male zebra finches, but has no such effect in single females. Unattached male songbirds will also put up with irritating puffs of air in exchange for being able to watch videos of singing birds, whereas unattached females will not. Female songbirds with partners will tolerate the air puffs, but only if the videos are accompanied with the songs of their own mate.

These findings suggest that song serves as a generic social stimulus for zebra finch males, helping large numbers of birds to live together. By contrast, for a female zebra finch, the song of her partner is a highly selective sexual stimulus. These sex-specific responses to the same socially-relevant stimuli may explain how gregarious animals are able to maintain monogamous pair bonds. More generally, these results are a step towards understanding how brain reward systems regulate social interactions. Studying these mechanisms in songbird species with different social and mating systems could ultimately provide insights into social and sexual behavior in people.

A framework for designing dynamic lp-ntPET studies to maximize the sensitivity to transient neurotransmitter responses to drugs: Application to dopamine and smoking

The "linear parametric neurotransmitter PET" (lp-ntPET) model was introduced to capture the time course of transient endogenous neurotransmitter response to drug stimulus from dynamic PET data. We previously used this novel analysis tool to probe the short-lived dopamine (DA) response induced by cigarette smoking in the PET scanner. It allowed us to find a sex difference in the DA signature of cigarette smoking. To make best use of this tool to characterize neurotransmitter response to drug stimulus, the sensitivity of lp-ntPET to detect such responses must be maximized. We designed a series of simulation studies to examine the impact of the following factors on the sensitivity of lp-ntPET using smoking-induced DA release as an example application: tracer delivery protocol, pre-processing for image denoising, timing of the smoking task, duration of the PET scan, and dose of the radiotracer. Our results suggest that a Bolus paradigm could replace a more difficult B/I paradigm without sacrificing the sensitivity of the method. Pre-processing the PET data with the de-noising algorithm HYPR could improve the sensitivity. The optimal timing to start the smoking task is 45min in a 90min scan and 35min in a 75min scan. A mild shortening of the scan time from 90mCi to 75min should be acceptable without loss of sensitivity. We suggest a lower dose limit of a bolus injection at 16mCi to limit underestimation of DA activation. This study established the framework to optimize the experimental design for reaching the full potential of lp-ntPET to detect neurotransmitter responses to drugs or even behavioral tasks.

Combined PET/MRI: from Status Quo to Status Go. Summary Report of the Fifth International Workshop on PET/MR Imaging; February 15-19, 2016; Tübingen, Germany

This article provides a collaborative perspective of the discussions and conclusions from the fifth international workshop of combined positron emission tomorgraphy (PET)/magnetic resonance imaging (MRI) that was held in Tübingen, Germany, from February 15 to 19, 2016. Specifically, we summarise the second part of the workshop made up of invited presentations from active researchers in the field of PET/MRI and associated fields augmented by round table discussions and dialogue boards with specific topics. This year, this included practical advice as to possible approaches to moving PET/MRI into clinical routine, the use of PET/MRI in brain receptor imaging, in assessing cardiovascular diseases, cancer, infection, and inflammatory diseases. To address perceived challenges still remaining to innovatively integrate PET and MRI system technologies, a dedicated round table session brought together key representatives from industry and academia who were engaged with either the conceptualisation or early adoption of hybrid PET/MRI systems. Discussions during the workshop highlighted that emerging unique applications of PET/MRI such as the ability to provide multi-parametric quantitative and visual information which will enable not only overall disease detection but also disease characterisation would eventually be regarded as compelling arguments for the adoption of PET/MR. However, as indicated by previous workshops, evidence in favour of this observation is only growing slowly, mainly due to the ongoing inability to pool data cohorts from independent trials as well as different systems and sites. The participants emphasised that moving from status quo to status go entails the need to adopt standardised imaging procedures and the readiness to act together prospectively across multiple PET/MRI sites and vendors.

A regularized full reference tissue model for PET neuroreceptor mapping

The full reference tissue model (FRTM) is a PET analysis framework that includes both free and specifically bound compartments within tissues, together with rate constants defining association and dissociation from the specifically bound compartment. The simplified reference tissue model (SRTM) assumes instantaneous exchange between tissue compartments, and this "1-tissue" approximation reduces the number of parameters and enables more robust mapping of non-displaceable binding potentials. Simulations based upon FRTM have shown that SRTM exhibits biases that are spatially dependent, because biases depend upon binding potentials. In this work, we describe a regularized model (rFRTM) that employs a global estimate of the dissociation rate constant from the specifically bound compartment (k₄). The model provides an internal calibration for optimizing k₄ through the reference-region outflow rate k₂', a model parameter that should be a global constant but varies regionally in SRTM. Estimates of k₄ by rFRTM are presented for four PET radioligands. We show that SRTM introduces bias in parameter estimates by assuming an infinite value for k₄, and that rFRTM ameliorates bias with an appropriate choice of k₄. Theoretical considerations and simulations demonstrate that rFRTM reduces bias in non-displaceable binding potentials. A two-parameter reduction of the model (rFRTM2) provides robust mapping at a voxel-wise level. With a structure similar to SRTM, the model is easily implemented and can be applied as a PET reference region analysis that reduces parameter bias without substantially altering parameter variance.

Kinetic Diversity of Striatal Dopamine: Evidence from a Novel Protocol for Voltammetry

In vivo voltammetry reveals substantial diversity of dopamine kinetics in the rat striatum. To substantiate this kinetic diversity, we evaluate the temporal distortion of dopamine measurements arising from the diffusion-limited adsorption of dopamine to voltammetric microelectrodes. We validate two mathematical procedures for correcting adsorptive distortion, both of which substantiate that dopamine's apparent kinetic diversity is not an adsorption artifact.

Imaging Agonist-Induced D2/D3 Receptor Desensitization and Internalization In Vivo with PET/fMRI

This study investigated the dynamics of dopamine receptor desensitization and internalization, thereby proposing a new technique for non-invasive, in vivo measurements of receptor adaptations. The D2/D3 agonist quinpirole, which induces receptor internalization in vitro, was administered at graded doses in non-human primates while imaging with simultaneous positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). A pronounced temporal divergence between receptor occupancy and fMRI signal was observed: occupancy remained elevated while fMRI responded transiently. Analogous experiments with an antagonist (prochlorperazine) and a lower-affinity agonist (ropinirole) exhibited reduced temporal dissociation between occupancy and function, consistent with a mechanism of desensitization and internalization that depends upon drug efficacy and affinity. We postulated a model that incorporates internalization into a neurovascular-coupling relationship. This model yielded in vivo desensitization/internalization rates (0.2/min for quinpirole) consistent with published in vitro measurements. Overall, these results suggest that simultaneous PET/fMRI enables characterization of dynamic neuroreceptor adaptations in vivo, and may offer a first non-invasive method for assessing receptor desensitization and internalization.