Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2017 Dec 1.
Published in final edited form as: Semin Nucl Med. 2016 Jan;46(1):20–27. doi: 10.1053/j.semnuclmed.2015.09.001

PET neurochemical imaging modes

Michael S Placzek 1,2, Wenjun Zhao 1, Hsiao-Ying Wey 1, Thomas M Morin 3, Jacob M Hooker 1,*
PMCID: PMC5709996  NIHMSID: NIHMS723652  PMID: 26687854

Abstract

Positron emission tomography (PET) has deep roots in neuroscience stemming from its first applications in brain tumor and brain metabolism imaging. Over the past few decades, PET emerged and continues to play a prominent role in the study of neurochemistry in the living human brain. Over time, neurochemical imaging with PET has been expanded to address a host of research questions related to among many others, protein density, drug occupancy and endogenous neurochemical release. Each of these imaging modes has distinct design and analysis considerations that are critical for enabling quantitative measurements. The number of considerations required for a neurochemical PET study can make it unapproachable. This seminar aims to orient those interested in neurochemical PET imaging to three of the common imaging modes and to provide some perspective on needs that exist for expansion of neurochemical PET imaging.

1. Introduction

Neurochemical imaging with positron emission tomography (PET) comprises a diverse set of molecular targets, radiotracers addressing those targets, experimental designs and analysis options. For those not deeply rooted in the field, the permutation of variables can be overwhelming. Others have reviewed many aspects of PET neuroimaging (Henriksen and Willoch, 2008; Paterson et al 2010; Jones and Rabiner, 2012; Morris et al, 2014; Van de Bittner et al, 2014), but here, we focus on distinguishing features that enable what we term imaging “modes”. Imaging modes, as we have termed them, are imaging experiment designs intended to answer specific chemical neuroscience questions. Each mode has specific considerations and constraints that enable biochemical information to be extracted from the imaging data. We highlight three common modes with the full recognition that other neurochemical imaging modes exist. Our goal with this seminar piece is to try and distill neurochemical imaging with PET to core elements that those new to the field can use as general guidelines for interpreting previous research studies in the literature.

The choice of imaging modes we highlight in this article were based on applications within neuropsychiatric and neurodegenerative disorders as they relate to neurotransmitter and pharmacological research. We discuss a few additional biological targets and scenarios that are frequent in recent literature. Openly neglected are important areas of PET neuroscience including, for example, glucose metabolism (Reivech et al., 1979; Villien et al., 2014), other enzyme activity measurements (Rusjan et al., 2013) and cerebral blood flow and oxygen metabolism (Baron, 1999). The three modes we highlight deal with: 1) measurement of protein density and density changes; 2) determination of drug occupancy and radiotracer competition, and 3) measurement of endogenous neurotransmitter release (Figure 1). Within each of these three areas, we provide examples of experiments that demonstrate the general concepts and constraints. Finally, we discuss some perspective on what we feel are a few out of the many unmet needs within neurochemical imaging with PET.

Figure 1.

Figure 1

Open in a new tab

Three common modes fo PET neuroimaging: 1) Measurement of protein density and density changes; 2) Determination of drug occupancy and radiotracer competition; 3) Measurement of endogenous neurotransmitter release.

2. Characterization of Protein and Density Changes

The measurement of protein expression in the human brain and changes that occur in association with brain dysfunction is a common mode of PET neurochemical imaging. Many protein classes can be targeted with PET radiotracers, but here we will focus on just a few example protein classes that are common in PET neurochemical imaging, providing insight into the types of studies that are conducted for measuring protein and density changes. Among the most common protein classes studied with PET are neuroreceptors, ligand transporters, and enzymes.

Neuroreceptors play a crucial role in neurotransmission and brain function regulation. Changes in the density of certain receptors or transporters have been associated with CNS disease or aging process (Heiss et al., 2006). Receptor density can be measured ex vivo via postmortem autoradiography. However, in vivo quantitative imaging, such as PET, of receptor density can help to elucidate disease mechanisms in the human brain.

For radiotracers to be useful in quantitative measurements of protein density, several criteria must be fulfilled to provide reliable results: 1) sufficient high dynamic range, which allows for accurate measurement of target density in both low and high distribution regions and to facilitate group comparisons (e.g. disease patients versus healthy controls), and 2) low methodological test-retest variability to ensure that differences observed between individuals can be attributed to the biological state of the brain, and 3) insensitivity to endogenous ligand binding, particularly in the ‘baseline or resting’ state of the brain. Clearly, the considerations above are not mutually exclusive and in general are highly radiotracer dependent. Nevertheless, we have outlined two primary experiments which serve as the basis for determining if a specific research question pertaining to protein density can be sufficiently answered with PET imaging.

First, an understanding of the intrasubject test/retest variability is important. By scanning a subject twice under the assumption that the biological state of the brain (protein level and availability of sites for radiotracer binding) has not changed, the difference in measurements provides the absolute minimum change that one could expect to quantify. Of course in actuality, the effect size of a biological change must be much greater than the test/retest variability given that PET sample sizes are often limited by scan costs. Generally, intrasubject variability is on the order of 10–15% (Narendran et al, 2011) and although methodological and analysis improvements are shrinking this number, relatively small changes in protein density are currently difficult to measure. PET imaging of density has thus been most successful in scenarios where protein density changes are large (e.g. >50%) (Volkow et al., 1997).

The second critical consideration (less often predetermined for radiotracers) when measuring density changes with PET provides evidence for insensitivity to endogenous state changes (e.g. endogenous ligand binding changes). For most mass-action driven PET analysis methods, receptor density is commonly represented by binding potential (BP), which is proportional to the number of binding sites (Bmax) and inversely proportional to the dissociation constant (Kd) of the radiotracer for binding sites (BP = Bmax/Kd) (Mintun et al., 1984; Innis et al., 2007). If the radiotracer is in competition for binding sites, then only the available binding sites (i.e. unoccupied) are measured (Bavail), increasing the complexity of absolute protein density (Bmax) measurements with PET (see strategies below). When a radiotracer is insensitive to endogenous ligand binding, the aforementioned complexities can be negated and changes in BP between subjects can more accurately be inferred, as a protein density change. Tests for sensitivity to endogenous release rely on the notion that protein synthesis rates are slow relative to changes in neurotransmitter (or endogenous ligand) concentration. A common experimental design relies on imaging modes (highlighted in the next two sections) which measure changes in neurochemistry. If it has been determined that a particular radiotracer is insensitive to a competition mode, one can assume (albeit with some limitations) that PET signal differences are primarily protein density driven.

Several radiotracers for the serotonin (5-HT) system provide an example of insensitivity to endogenous ligand (serotonin release) and have therefore been used for determining protein density changes in healthy versus diseased subjects. Here we highlight two examples from this receptor class: [11C]WAY-100635 and [11C]DASB. [11C]WAY-100635 is a high affinity antagonist used for in vivo quantification of 5-HT1A receptor density (Fletcher et al., 1993). It was observed that there was no decrease in binding of [11C]WAY-100635 to 5-HT1A receptors after treatment with 5-HT releasing agents (p-chloroamphetamine, fenfluramine and methylenedioxymethamphetamine) or after depletion of 5-HT by treatment with 5-HT synthesis inhibitor (p-chlorophenylalanine) in rodents (Rice et al., 2001). Therefore, a decrease in [11C]WAY-100635 binding likely indicates a reduction in the density of 5-HT1A receptors. As another example, [11C]DASB was developed for quantification of 5-HT transporter (5-HTT) (Wilson et al., 2000, 2002; Frankle et al., 2004; Ginovart et al., 2001; Houle et al., 2000). It is highly selective for 5-HTT with nanomolar affinity, has good dynamic range (VT and BP), and low test-retest variability (<10% in all regions) (Frankle et al., 2004, 2006). As with [11C]WAY- 100635, [11C]DASB has shown insensitivity to drugs that stimulate serotonin release or depletion (Milak et al., 2005; Talbot et al., 2005). As you can see from these two examples, the use of PET neuroimaging to measure protein density for dynamic systems (e.g. neurotransmitter-receptor systems) lead to a convolved and potentially confounded interpretation. Protein density can certainly be a driving factor for PET imaging signal changes, but its overall contribution can be difficult to assess.

The association of PET signal changes with protein density changes is clearer in other cases where endogenous ligands are not in competition with the radiotracer. A primary example is amyloid aggregate imaging, which has been reviewed extensively (Vallabhajosula 2011; Frisoni et al., 2013; Adlard et al., 2014). Another example is the measurement of translocator protein (TSPO) expression with PET, which has been used as a marker of neuroinflammation for several diseases including Alzheimer’s disease (Kreisl et al., 2013), Parkinson’s disease (Gerhard et al., 2006), Huntington’s disease (Pavese et al., 2006) and ALS (Zürcher et al., 2015). [11C]PBR28 binds to TSPO thereby quantifying microglia activation and subsequent neuroinflammation in healthy and diseased subjects. The best evidence of PET signal association with TSPO (protein) density comes from supporting ex vivo analysis studies, for example with immunohistochemistry (Owen et al., 2010).

Clearly, the ability to measure protein density and changes in the living human brain is important and we have only superficially addressed the radiotracers available for this imaging mode. In general, our advice is to avoid specifically attributing PET signal and signal changes to protein density without additional PET or ex vivo data to support a protein-density-based interpretation.

3. Drug Occupancy and Radiotracer Competition

One of the more powerful modes of neural PET imaging has focused on determining occupancy of various psychoactive drugs. Within this context, PET has proven a useful tool for studying target engagement in vivo. These studies have made important advances in the field of neural drug development and neuropsychopharmacology as they have provided evidence of brain uptake, specific binding to the target, and ligand-receptor dynamics. Generally, the experimental design for determining drug occupancy or ligand displacement involves treatment with an exogenous ligand which directly competes with the radiotracer at the binding site. As drug occupancy with PET has been the focus of prior review (Gatley et al., 2003) we will provide an update and highlight the important parameters to be used as general guidelines for conducting drug occupancy or radiotracer competition studies with PET.

When several radiotracers are available for a particular target, selection is critically important to maximize sensitivity to competitive binding with the ligand. In addition to the standard criteria for CNS radiotracers (Van de Bittner et al., 2014), we have highlighted radiotracer criteria for determining drug occupancy using a reversibly binding radiotracer:

  1. High selectivity for the receptor or receptor subclass (e.g. opioid receptor PET tracers which are extremely selective for µ vs Κ or δ ORs).

  2. High dynamic range and low nonspecific or nondisplaceable binding (i.e. low off-target binding).

  3. Occupancy of agonist drugs should be measured with an agonist radiotracer and antagonist drugs measured with an antagonist radiotracer to ensure competition for the same binding site.

  4. Moderate to high in vitro affinity at the receptor (extremely high affinity radiotracers with fast kon and slow koff may display poor sensitivity to ligand challenge).

In addition to radiotracer selection criteria, PET study design is equally important. Over the last several decades, there have been numerous advances in PET experimental design for determining drug occupancy and ligand displacement (Endes et al., 1998). Conventional occupancy determination in vivo with PET can be conducted by pretreatement or co-administration with drug, paired with a bolus injection of the radiotracer. By analyzing radiotracer kinetics from several drug challenge experiments at various doses and comparing to baseline scans, we can determine the effective dose for occupying a certain quantity of receptors. A slightly different approach for measuring drug occupancy or ligand displacement has been conducted by administering a challenge after injection or infusion of the radiotracer. A common experiment for this method is a bolus/infusion (B/I) protocol which requires an initial bolus of the radiotracer followed by a constant infusion. The B/I method was designed to obtain equilibrium or steady state concentration of the radiotracer in brain tissue. This method is less invasive than conventional bolus studies because it typically does not require arterial blood sampling. The advantages of this method are 1) single scan which can assess both baseline and challenge, and 2) data analysis can be simplified in comparison to standard bolus experiments, and 3) venous sampling may be sufficient for determining free radiotracer in blood. In addition, B/I scan times may be shorter than bolus studies for kinetically slow radiotracers (Kimes et al, 2008). Achieving equilibrium with a B/I experiment is not always straightforward and only some regions may achieve equilibrium. We will describe in further detail, the study designs and considerations of drug and/or radiotracer properties for drug occupancy measurements.

Design consideration for drug challenge studies

Radiotracer administration can be varied to increase the sensitivity of PET imaging for a given drug competition measurement. Here we will describe examples of both bolus and B/I study designs and some considerations for conducting each type of experiment. While we focus here on exogenous competition, there are conceptual commonalities which can be extended to endogenous ligand competition, and is the topic of the next section.

Bolus Radiotracer Administration

For bolus competition studies, radiotracer criteria is less stringent than with bolus/infusion but must still meet the minimum CNS radiotracer requirements and follow the general guidelines we have outlined previously. In most instances, the first PET experiment consists of measuring normal or baseline levels of the drug’s target with a bolus injection of the radiotracer for determining baseline kinetics and specific binding (BPND) or volume of distribution (VT) levels. In the follow up experiment, the subject is treated with drug, and a specific uptake time is allotted. Following uptake, which maximizes putative drug binding to the target, a bolus injection of the radiotracer is administered. Simply stated, a reduction in the outcome measure (e.g. decrease in VT or BPND) results in a change in available binding at the receptor and the level of BP reduction is in direct correlation with drug occupancy at the administered dose. Of course, this type of experiment has many underlying assumptions, primarily among them, the radiotracer and drug exhibit mutually exclusive binding. Subtleties in the measure (changes in drug occupancy over the time course of imaging) are often ignored with the assumption that the drug binding and occupancy time-course is slow relative to the imaging scan time-frame (e.g. 60–90 min).

In general, the assumptions and occupancy estimates (as inferred by the kinetic differences between the two bolus scans) are reasonable, and often correlated with less extensive procedures for measuring drug levels, such as plasma drug concentration measurements. One example of using PET to validate plasma drug measurements to be used as an indicator of occupancy was demonstrated by Fowler et al (2009). In this report, drug occupancy levels from oral doses of the monoamine oxidase-A (MAO-A) inhibitor CX157 were determined with [11C]clorgyline. To establish a dosing paradigm for clinical efficacy, they correlated drug occupancy measurements from PET with plasma drug levels, to validate plasma sampling as a biomarker for determine drug occupancy during clinical studies. It was determined that this method provided excellent correlation between PET occupancy measurements and plasma concentration.

Another example of validating methods or assays with PET drug occupancy studies involved determining the in vivo selectivity of an opioid antagonist drug, LY2795050. LY2795050 is a part of a new class of kappa opioid receptor (KOR) antagonist drugs and was reported to have good selectivity for KOR over the mu opioid receptor (MOR) (36:1 KOR:MOR) in a cellular assay (Mitch et al., 2011). To determine the in vivo selectivity for this drug, a PET occupancy study was conducted in rhesus monkeys, utilizing radiolabeled [11C]LY2795050 (KOR radiotracer) and [11C]carfentanil (MOR radiotracer) to assess opioid subtype selectivity (KOR:MOR) (Kim et al, 2013). Animals were treated with the KOR antagonist drug LY2795050 at six doses (1.6 – 400 µg/kg, i.v.) followed by a bolus injection of either [11C]LY2795050 or [11C]carfentanil. Animals underwent a 120 min dynamic PET scan with arterial blood sampling. Following kinetic analysis of the data, it was estimated that LY2795050 achieved 50% MOR occupancy (ED50MOR) at 119 µg/kg and 50% KOR occupancy (ED50KOR) at 15.6 µg/kg. Based on this assessment, it was determined that the in vivo selectivity of this KOR antagonist was 7.6:1 (KOR:MOR), a substantial difference from the previous in vitro selectivity data (36:1 KOR:MOR), highlighting the power of this in vivo assessment with PET.

Bolus/Infusion Radiotracer Administration

Since the first drug challenge PET studies, new experiments have been used to determine binding changes from exogenous or endogenous stimuli. The most common example is radiotracer displacement studies which involve the administration of a challenge after the radiotracer has reached equilibrium with a bolus/infusion (B/I) administration. With a B/I study design, inter-subject variability can create challenges, as radiotracer kinetics and equilibrium may differ from subject to subject. Regardless, this method has demonstrated its sensitivity to pharmacological challenge and typically requires only one scan for obtaining baseline and post-challenge radiotracer kinetics. For determining infusion parameters, the radiotracer should be infused at a rate which obtains equilibrium in the brain region of interest. Analysis of the PET data can be accomplished by taking the ratio of the radioactivity between the target region and a reference region before and after challenge, thus, a percent change in BPND can be quantified. Validation of the B/I method has been established for several PET radiotracers including, but not limited to, raclopride (Ilto et al., 1998), cyclofoxy (Carson et al., 1993), carfentanil (Greenwald et al., 2007), and altanserin (van Dyck et al., 2000). A B/I paradigm has been successfully used to quantify direct drug occupancy targeting the dopamine system (Slifstein et al., 2004; Marenco et al., 2004).

Manipulation of radiotracer administration can have a marked impact on the ability to detect neurochemical changes in the brain and the bolus and B/I methods are only the beginning of what will come. For example, a novel multi-infusion method was recently developed at Yale University, which allows for assessment of Bmax and Kd in vivo (Xia et al., 2015). Continued development in this area will lead to a greater ability to study neurochemistry with PET and will improve our ability to study both exogenous and endogenous stimuli.

4. Endogenous Neurotransmitter Release

Measuring changes in the level of endogenous neurotransmitters has enabled another important mode of PET imaging. This mode follows similar principles to exogenous occupancy studies, in that, a change in neurotransmitter levels will cause a change in occupancy at the receptor leading to a change in binding potential measured with PET (Finnema et al., 2015). This mode involves a release, or change of endogenous ligand induced from either a functional task (Koepp et al., 2001; Zubieta et al., 2001; Zald et al., 2004; Badgaiyan, 2013) or by indirect pharmacological challenge (e.g. amphetamine for increase in DA release) (Volkow et al., 1994). The most important principle for measuring endogenous neurotransmitter level changes with PET is radioligand sensitivity to competition with the endogenous ligand. To date, a limited number of receptor classes have been successful for this PET measurement (dopamine, and limited success with opioid and serotonin receptors) and only a few radiotracers have been capable of measuring changes in synaptic transmission in the living brain. The dopamine targeting radiotracers have been, by far, the most well studied class and [11C]raclopride is the primary radioligand chosen for D2/3 studies. Although these PET study designs differ slightly from drug occupancy measurements, they tend to follow the same experimental methods as outlined in previous sections. A bolus radiotracer administration with a two PET scan paradigm (baseline and challenge) has been commonly used to determine receptor occupancy changes by endogenous ligand release, e.g. endogenous opioid peptide release with experimental pain (Wey et al., 2014). A B/I paradigm has also successfully quantified endogenous dopamine (Carson et al., 1997; Urban et al., 2012; Weiland et al., 2014) and serotonin (Quednow et al., 2012) release through indirect pharmacological challenges. Studies in humans have also demonstrated the utility of a B/I method for detecting endogenous ligand release in response to tasks or stimuli (Scott et al., 2007; Martin-Soelch et al., 2011).

In addition to methodological overlaps between drug occupancy and endogenous ligand level measurements, the radiotracer selection criteria from previous modes can also be extended to measurements of endogenous neurotransmitter release. Building on those guidelines, a key requirement of an ideal radiotracer to detect endogenous neurotransmission is the pharmacokinetic parameters of the radiotracer. A radiotracer with a relatively fast dissociation rate would be more sensitive to synaptic neurotransmitter release due to rapid adjustment of tracer-target binding from changes in neurotransmitter concentration. As an example of these characteristics, an early report measured binding changes of [11C]raclopride in a bolus blocking study to detect changes in dopamine release following indirect pharmacological challenge (Volkow et al., 1994). In this study, methylphenidate (0.5 mg/kg, i.v.) was administered to human subjects followed by [11C]raclopride bolus to assess the changes in binding potential between baseline and challenge scans. At 0.5 mg/kg, the subsequent stimulant induced dopamine release resulted in a 23% decrease in [11C]raclopride binding. Reiterating the necessity for high sensitivity radiotracers for measuring endogenous ligand levels, it is important to note that a 23% decrease is only 13–18% above test-retest variability (5–10% for [11C]raclopride). With human clinical research studies, small changes can be difficult to detect with small subject numbers and costly if additional subject recruitment and scanning must be performed. Since this early report, measuring changes in endogenous dopamine with PET has been one of the most heavily investigated areas and the focus of several reviews (Laruelle et al., 2000). Despite the advances in the detection of endogenous dopamine release, only a few other neuroreceptor systems have demonstrated success measuring fluctuations in endogenous ligands, and with only limited success thus far.

An interesting direction within endogenous release PET measurements is the ability to measure pulses of neurotransmitter release (Endres and Carson, 1998; Kapur and Seeman, 2001). Currently, imaging-tracer methods only allow for detection of a single neurochemical release (Figure 3B, only a single decrease in tracer to target binding) and fail to measure multiple, consecutive releases of neurotransmitters (Figure 3C). Multiple releases of the neurotransmitter with high time resolution during a single PET scan is a powerful technique (Kim et al., 2014; Morris et al., 2005), but remains a challenge for most receptor systems and neurochemical release protocols. To help address this challenge, there is a need to design a new generation of radiotracers with faster protein association and dissociation kinetics (and analysis methods to accompany their use). A radiotracer with a greater koff (lower residence time at the target), can in theory, respond more quickly to endogenous neurochemical surge. Clearly a balance needs to be struck between low residence time and affinity (often closely associated) since radiotracers with low affinity might lead to low signal to background.

Figure 3.

Figure 3

Open in a new tab

Computational simulation comparing the kinetics of slow- and fast-binding radiotracers and subsequent response to consecutive neurotransmitter release. Fast radiotracers (with large kon and koff) respond quickly to multiple endogenous neurotransmitter releases and depletions due to the rapid radiotracer “displacement” and “re-binding” to the target. Slow radiotracers can generally only respond to the first surge, if at all.

5. Summary

The development of PET studies for measuring neurochemical changes requires significant effort and extensive validation of protocols. We have outlined the three most common modes of brain PET as it applies to neuropsychiatric and neurodegenerative disorders related to neurotransmitter and pharmacological research. This review serves as a general guideline for studying 1) protein density and change, and 2) drug occupancy and radiotracer competition, and 3) endogenous neurotransmitter release, with PET. The examples provided illustrate the requirements and considerations when attempting to utilize each mode. Protein density measurements with in vivo imaging such as PET, provide a powerful tool for monitoring disease progression, response to treatment, and diagnosis. Intersubject comparisons of protein density changes with PET relies on the principle that changes in radiotracer binding account for changes in protein density. Typically not emphasized are the assumptions made for defining a change, the methodological criteria employed for conducting such studies, and the challenges that are encountered. We have outlined the criteria which is most often discussed and accounted for when designing protein density measurements with PET. In addition, drug occupancy studies comprise a major component in neurochemical PET studies, and this mode has seen considerable advancement over the years. Currently, two method designs predominate this field and have been used for determining drug occupancy with various neuroreceptors. These include, a two bolus design, measuring baseline kinetics in the first scan and challenge kinetics in the second scan following drug administration. In addition, bolus/infusion paradigms have seen considerable success and offer unique advantages over the two bolus method. The guidelines mentioned provide criteria for each mode and the importance of radiotracer selection on sensitivity to these measurements. Measuring changes in endogenous ligands with PET has been successful with the dopamine system but has been limited success in other neuroreceptor classes mainly due to insufficient radiotracer properties. There has been interest in developing radiotracers with specific kinetic properties for detecting consecutive release of neurotransmitters, but this area is still in the investigational stages. As new advances in radiotracer design and PET instrumentation evolve, the multitude of different studies conducted within each mode will broaden, leading to a better understanding of neurobiological and neurochemical mechanisms.

Figure 2.

Figure 2

Open in a new tab

Effect of receptor density and endogenous ligand occupancy on the number of available binding sites for the radiotracer, binding potential (BP). Understanding the level of endogenous ligand binding is essential for determination of receptor density in vivo as both low density and high density with endogenous occupancy may result in similar BP levels.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  1. Adlard PA, Tran BA, Finkelstein DI, Desmond PM, Johnston LA, Bush AI, et al. A review of β-amyloid neuroimaging in Alzheimer’s disease. Front Neurosci. 2014;8:327. doi: 10.3389/fnins.2014.00327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Badgaiyan RD. Detection of dopamine neurotransmission in “real time”. Front Neurosci. 2013;7 doi: 10.3389/fnins.2013.00125. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Baron J-C. Mapping the Ischaemic Penumbra with PET: Implications for Acute Stroke Treatment. Cerebrovascular Diseases. 1999;9:193–201. doi: 10.1159/000015955. [DOI] [PubMed] [Google Scholar]
  4. Carson RE, Channing MA, Blasberg R, Dunn BB, Cohen RM, Rice KC, Herscovitch P. Comparison of bolus and infusion methods for receptor quantitation: application to [18F]cyclofoxy and positron emission tomography. J. Cereb. Blood Flow Metab. 1993;13:24–42. doi: 10.1038/jcbfm.1993.6. [DOI] [PubMed] [Google Scholar]
  5. Carson RE, Breier A, de Bartolomeis A, Saunders RC, Su TP, Schmall B, et al. Quantification of Amphetamine-Induced Changes in [11C] Raclopride Binding with Continuous Infusion. J Cereb Blood Flow Metab. 1997;17:437–447. doi: 10.1097/00004647-199704000-00009. [DOI] [PubMed] [Google Scholar]
  6. van Dyck CH, Tan P-Z, Baldwin RM, Amici LA, Garg PK, Ng CK, et al. PET Quantification of 5-HT2A Receptors in the Human Brain: A Constant Infusion Paradigm with [18F]Altanserin. J Nucl Med. 2000;41:234–241. [PubMed] [Google Scholar]
  7. Endres CJ, Carson RE. Assessment of Dynamic Neurotransmitter Changes With Bolus or Infusion Delivery of Neuroreceptor Ligands. J Cereb Blood Flow Metab. 1998;18:1196–1210. doi: 10.1097/00004647-199811000-00006. [DOI] [PubMed] [Google Scholar]
  8. Finnema S, Scheinin M, Shahid M, Lehto J, Borroni E, Bang-Andersen B, Sallinen J, Wong E, Farde L, Halldin C, Grimwood S. Psychopharmacology. 2015:1. doi: 10.1007/s00213-015-3938-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Fletcher A, Bill DJ, Bill SJ, Cliffe IA, Dover GM, Forster EA, et al. WAY100135: a novel, selective antagonist at presynaptic and postsynaptic 5-HT1A receptors. European Journal of Pharmacology. 1993;237:283–291. doi: 10.1016/0014-2999(93)90280-u. [DOI] [PubMed] [Google Scholar]
  10. Frankle WG, Huang Y, Hwang D-R, Talbot PS, Slifstein M, Van Heertum R, et al. Comparative Evaluation of Serotonin Transporter Radioligands 11C-DASB and 11C-McN 5652 in Healthy Humans. J Nucl Med. 2004;45:682–694. [PubMed] [Google Scholar]
  11. Frankle WG, Slifstein M, Gunn RN, Huang Y, Hwang D-R, Darr EA, et al. Estimation of Serotonin Transporter Parameters with 11C-DASB in Healthy Humans: Reproducibility and Comparison of Methods. J Nucl Med. 2006;47:815–826. [PubMed] [Google Scholar]
  12. Frisoni GB, Bocchetta M, Chételat G, Rabinovici GD, de Leon MJ, Kaye J, et al. Imaging markers for Alzheimer disease: which vs how. Neurology. 2013;81:487–500. doi: 10.1212/WNL.0b013e31829d86e8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fowler JS, Logan J, Azzaro AJ, Fielding RM, Zhu W, Poshusta AK, et al. Reversible Inhibitors of Monoamine Oxidase-A (RIMAs): Robust, Reversible Inhibition of Human Brain MAO-A by CX157. Neuropsychopharmacology. 2009;35:623–631. doi: 10.1038/npp.2009.167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gatley SJ, Volkow ND, Fowler JS, Ding Y-S, Logan J, Wang G-J, et al. Positron emission tomography and its use to image the occupancy of drug binding sites. Drug Dev Res. 2003;59:194–207. [Google Scholar]
  15. Gerhard A, Pavese N, Hotton G, Turkheimer F, Es M, Hammers A, et al. In vivo imaging of microglial activation with [11C](R)-PK11195 PET in idiopathic Parkinson’s disease. Neurobiology of Disease. 2006;21:404–412. doi: 10.1016/j.nbd.2005.08.002. [DOI] [PubMed] [Google Scholar]
  16. Ginovart N, Wilson AA, Meyer JH, Hussey D, Houle S. Positron emission tomography quantification of [C-11]-DASB binding to the human serotonin transporter: Modeling strategies. J Cerebr Blood F Met. 2001;21:1342–1353. doi: 10.1097/00004647-200111000-00010. [DOI] [PubMed] [Google Scholar]
  17. Greenwald Mark, Johanson Chris-Ellyn, Bueller Joshua, Chang Yan, Moody David E, Kilbourn Michael, Koeppe Robert, Zubieta Jon-Kar. Buprenorphine duration of action: mu-opioid receptor availability and pharmacokinetic and behavioral indices. Biological psychiatry. 2007;61(1):101–110. doi: 10.1016/j.biopsych.2006.04.043. [DOI] [PubMed] [Google Scholar]
  18. Heiss WD, Herholz K. Brain Receptor Imaging. Journal of Nuclear Medicine. 2006;47 [PubMed] [Google Scholar]
  19. Henriksen G, Willoch F. Imaging of opioid receptors in the central nervous system. Brain. 2008;131:1171–1196. doi: 10.1093/brain/awm255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Houle S, Ginovart N, Hussey D, Meyer JH, Wilson AA. Imaging the serotonin transporter with positron emission tomography: initial human studies with [C-11]DAPP and [C-11]DASB. Eur J Nucl Med. 2000;27:1719–1722. doi: 10.1007/s002590000365. [DOI] [PubMed] [Google Scholar]
  21. Ito H, Hietala J, Blomqvist G, Halldin C, Farde L. Comparison of the transient equilibrium and continuous infusion method for quantitative PET analysis of [11C]raclopride binding. J. Cereb. Blood Flow Metab. 1998;18:941–950. doi: 10.1097/00004647-199809000-00003. [DOI] [PubMed] [Google Scholar]
  22. Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab. 2007;27:1533–1539. doi: 10.1038/sj.jcbfm.9600493. [DOI] [PubMed] [Google Scholar]
  23. Jones T, Rabiner EA. The development, past achievements, and future directions of brain PET. J Cereb Blood Flow Metab. 2012;32:1426–1454. doi: 10.1038/jcbfm.2012.20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Kapur S, Seeman P. Does fast dissociation from the dopamine d(2) receptor explain the action of atypical antipsychotics?: A new hypothesis. The American journal of psychiatry. 2001;158:360–369. doi: 10.1176/appi.ajp.158.3.360. [DOI] [PubMed] [Google Scholar]
  25. Kreisl WC, Lyoo CH, McGwier M, Snow J, Jenko KJ, Kimura N, et al. In vivo radioligand binding to translocator protein correlates with severity of Alzheimer's disease. Brain : a journal of neurology. 2013;136:2228–2238. doi: 10.1093/brain/awt145. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Kim SJ, Zheng M-Q, Nabulsi N, Labaree D, Ropchan J, Najafzadeh S, et al. Determination of the In Vivo Selectivity of a New -Opioid Receptor Antagonist PET Tracer 11C-LY2795050 in the Rhesus Monkey. Journal of Nuclear Medicine. 2013;54:1668–1674. doi: 10.2967/jnumed.112.118877. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kim SJ, Sullivan JM, Wang S, Cosgrove KP, Morris ED. Voxelwise lp-ntPET for detecting localized, transient dopamine release of unknown timing: sensitivity analysis and application to cigarette smoking in the PET scanner. Human brain mapping. 2014;35:4876–4891. doi: 10.1002/hbm.22519. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Koepp MJ, Gunn RN, Lawrence AD, Cunningham VJ, Dagher A, Jones T, et al. Evidence for striatal dopamine release during a video game. Nature. 1998;393:266–268. doi: 10.1038/30498. [DOI] [PubMed] [Google Scholar]
  29. Laruelle M. Imaging Synaptic Neurotransmission With in Vivo Binding Competition Techniques: A Critical Review. J Cereb Blood Flow Metab. 2000;20:423–451. doi: 10.1097/00004647-200003000-00001. [DOI] [PubMed] [Google Scholar]
  30. Logan Jean. Graphical analysis of PET data applied to reversible and irreversible tracers. Nuclear medicine and biology. 2000;27(7):661–670. doi: 10.1016/s0969-8051(00)00137-2. [DOI] [PubMed] [Google Scholar]
  31. Marenco S, Carson RE, Berman KF, Herscovitch P, Weinberger DR. Nicotine-Induced Dopamine Release in Primates Measured with [11C]Raclopride PET. Neuropsychopharmacology. 2004;29:259–268. doi: 10.1038/sj.npp.1300287. [DOI] [PubMed] [Google Scholar]
  32. Martin-Soelch C, Szczepanik J, Nugent A, Barhaghi K, Rallis D, Herscovitch P, et al. Lateralization and gender differences in the dopaminergic response to unpredictable reward in the human ventral striatum. European Journal of Neuroscience. 2011;33:1706–1715. doi: 10.1111/j.1460-9568.2011.07642.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Milak MS, Ogden RT, Vinocur DN, Van Heertum RL, Cooper TB, Mann JJ, et al. Effects of tryptophan depletion on the binding of [11C]-DASB to the serotonin transporter in baboons: response to acute serotonin deficiency. Biol Psychiatry. 2005;57:102–106. doi: 10.1016/j.biopsych.2004.09.026. [DOI] [PubMed] [Google Scholar]
  34. Mintun MA, Raichle ME, Kilbourn MR, Wooten GF, Welch MJ. A quantitative model for the in vivo assessment of drug binding sites with positron emission tomography. Ann Neurol. 1984;15:217–227. doi: 10.1002/ana.410150302. [DOI] [PubMed] [Google Scholar]
  35. Morris ED, Yoder KK, Wang C, Normandin MD, Zheng QH, Mock B, et al. ntPET: a new application of PET imaging for characterizing the kinetics of endogenous neurotransmitter release. Molecular imaging. 2005;4:473–489. doi: 10.2310/7290.2005.05130. [DOI] [PubMed] [Google Scholar]
  36. Morris ED, Lucas MV, Petrulli JR, Cosgrove KP. How to Design PET Experiments to Study Neurochemistry: Application to Alcoholism. Yale J Biol Med. 2014;87:33–54. [PMC free article] [PubMed] [Google Scholar]
  37. Mitch CH, Quimby SJ, Diaz N, Pedregal C, de la Torre MG, Jimenez A, et al. Discovery of Aminobenzyloxyarylamides as κ Opioid Receptor Selective Antagonists: Application to Preclinical Development of a κ Opioid Receptor Antagonist Receptor Occupancy Tracer. Journal of Medicinal Chemistry. 2011;54:8000–8012. doi: 10.1021/jm200789r. [DOI] [PubMed] [Google Scholar]
  38. Narendran Rajesh, Mason N Scott, May Maureen A, Chen Chi-Min, Kendro Steve, Ridler Khanum, Rabiner Eugenii A, Laruelle Marc, Mathis Chester A, Frankle W. Gordon. Positron emission tomography imaging of dopamine D2/3 receptors in the human cortex with [11C] FLB 457: reproducibility studies. Synapse. 2011;65(1):35–40. doi: 10.1002/syn.20813. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Owen DR, Guo Q, Kalk NJ, Colasanti A, Kalogiannopoulou D, Dimber R, et al. Determination of [11C]PBR28 binding potential in vivo: a first human TSPO blocking study. J Cereb Blood Flow Metab. 2014;34:989–994. doi: 10.1038/jcbfm.2014.46. [DOI] [PMC free article] [PubMed] [Google Scholar]; Paterson LM, Tyacke RJ, Nutt DJ, Knudsen GM. Measuring endogenous 5-HT release by emission tomography: promises and pitfalls. J Cereb Blood Flow Metab. 2010;30:1682–1706. doi: 10.1038/jcbfm.2010.104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Owen DR, Howell OW, Tang S-P, Wells LA, Bennacef I, Bergstrom M, et al. Two binding sites for [3H]PBR28 in human brain: implications for TSPO PET imaging of neuroinflammation. J Cereb Blood Flow Metab. 2010;30:1608–1618. doi: 10.1038/jcbfm.2010.63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Paterson LM, Tyacke RJ, Nutt DJ, Knudsen GM. Measuring endogenous 5-HT release by emission tomography: promises and pitfalls. J Cereb Blood Flow Metab. 2010;30:1682–1706. doi: 10.1038/jcbfm.2010.104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Pavese N, Gerhard A, Tai YF, Ho AK, Turkheimer F, Barker RA, et al. Microglial activation correlates with severity in Huntington disease A clinical and PET study. Neurology. 2006;66:1638–1643. doi: 10.1212/01.wnl.0000222734.56412.17. [DOI] [PubMed] [Google Scholar]
  43. Placzek MS, Van de Bittner GC, Wey HY, Lukas SE, Hooker JM. Immediate and Persistent Effects of Salvinorin A on the Kappa Opioid Receptor in Rodents, Monitored In Vivo with PET. Neuropsychopharmacology. 2015 doi: 10.1038/npp.2015.159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Quednow BB, Treyer V, Hasler F, Dörig N, Wyss MT, Burger C, et al. Assessment of serotonin release capacity in the human brain using dexfenfluramine challenge and [18F]altanserin positron emission tomography. NeuroImage. 2012;59:3922–3932. doi: 10.1016/j.neuroimage.2011.09.045. [DOI] [PubMed] [Google Scholar]
  45. Raichle ME. Quantitative in vivo autoradiography with positron emission tomography. Brain research. 1979;180:47–68. doi: 10.1016/0165-0173(79)90016-x. [DOI] [PubMed] [Google Scholar]
  46. Rice OV, Gatley SJ, Shen J, Huemmer CL, Rogoz R, DeJesus OT, et al. Effects of endogenous neurotransmitters on the in vivo binding of dopamine and 5-HT radiotracers in mice. Neuropsychopharmacol. 2001;25:679–689. doi: 10.1016/S0893-133X(01)00287-1. [DOI] [PubMed] [Google Scholar]
  47. Rusjan PM, Wilson AA, Mizrahi R, Boileau I, Chavez SE, Lobaugh NJ, et al. Mapping human brain fatty acid amide hydrolase activity with PET. J Cereb Blood Flow Metab. 2013;33:407–414. doi: 10.1038/jcbfm.2012.180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Scott DJ, Stohler CS, Koeppe RA, Zubieta J-K. Time-course of change in [11C]carfentanil and [11C]raclopride binding potential after a nonpharmacological challenge. Synapse. 2007;61:707–714. doi: 10.1002/syn.20404. [DOI] [PubMed] [Google Scholar]
  49. Slifstein M, Narendran R, Hwang D-R, Sudo Y, Talbot PS, Huang Y, et al. Effect of amphetamine on [18F]fallypride in vivo binding to D2 receptors in striatal and extrastriatal regions of the primate brain: Single bolus and bolus plus constant infusion studies. Synapse. 2004;54:46–63. doi: 10.1002/syn.20062. [DOI] [PubMed] [Google Scholar]
  50. Talbot PS, Frankle WG, Hwang D-R, Huang Y, Suckow RF, Slifstein M, et al. Effects of reduced endogenous 5-HT on the in vivo binding of the serotonin transporter radioligand 11CDASB in healthy humans. Synapse. 2005;55:164–175. doi: 10.1002/syn.20105. [DOI] [PubMed] [Google Scholar]
  51. Urban NB, Slifstein M, Meda S, Xu X, Ayoub R, Medina O, et al. Imaging human reward processing with positron emission tomography and functional magnetic resonance imaging. Psychopharmacology (Berl) 2012;221:67–77. doi: 10.1007/s00213-011-2543-6. [DOI] [PubMed] [Google Scholar]
  52. Vallabhajosula S. Positron emission tomography radiopharmaceuticals for imaging brain Betaamyloid. Semin Nucl Med. 2011;41:283–299. doi: 10.1053/j.semnuclmed.2011.02.005. [DOI] [PubMed] [Google Scholar]
  53. Van de Bittner GC, Ricq EL, Hooker JM. A Philosophy for CNS Radiotracer Design. Acc Chem Res. 2014;47:3127–3134. doi: 10.1021/ar500233s. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Villien M, Wey H-Y, Mandeville JB, Catana C, Polimeni JR, Sander CY, et al. Dynamic functional imaging of brain glucose utilization using fPET-FDG. NeuroImage. 2014;100:192–199. doi: 10.1016/j.neuroimage.2014.06.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Volkow Nora D, Wang Gene-Jack, Fowler Joanna S, Logan Jean, Schlyer David, Hitzemann Robert, Lieberman Jeffrey, et al. Imaging endogenous dopamine competition with [11C] raclopride in the human brain. Synapse. 1994;16(4):255–262. doi: 10.1002/syn.890160402. [DOI] [PubMed] [Google Scholar]
  56. Volkow ND, Wang G-J, Fowler JS, Logan J, Gatley SJ, Hitzemann R, et al. Decreased striatal dopaminergic responsiveness in detoxified cocaine-dependent subjects. Nature. 1997;386:830–833. doi: 10.1038/386830a0. [DOI] [PubMed] [Google Scholar]
  57. Weiland BJ, Heitzeg MM, Zald D, Cummiford C, Love T, Zucker RA, et al. Relationship between impulsivity, prefrontal anticipatory activation, and striatal dopamine release during rewarded task performance. Psychiatry research. 2014;223:244–252. doi: 10.1016/j.pscychresns.2014.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Wey H-Y, Catana C, Hooker JM, Dougherty DD, Knudsen GM, Wang DJJ, et al. Simultaneous fMRI-PET of the opioidergic pain system in human brain. NeuroImage. 2014;102(Part 2):275–282. doi: 10.1016/j.neuroimage.2014.07.058. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Wilson AA, Ginovart N, Schmidt M, Meyer JH, Threlkeld PG, Houle S. Novel Radiotracers for Imaging the Serotonin Transporter by Positron Emission Tomography: Synthesis, Radiosynthesis, and in Vitro and ex Vivo Evaluation of 11C-Labeled 2- (Phenylthio)araalkylamines. Journal of Medicinal Chemistry. 2000;43:3103–3110. doi: 10.1021/jm000079i. [DOI] [PubMed] [Google Scholar]
  60. Wilson AA, Ginovart N, Hussey D, Meyer J, Houle S. In vitro and in vivo characterisation of [11C]-DASB: a probe for in vivo measurements of the serotonin transporter by positron emission tomography. Nuclear medicine and biology. 2002;29:509–515. doi: 10.1016/s0969-8051(02)00316-5. [DOI] [PubMed] [Google Scholar]
  61. Xia Y, Zheng M-Q, Holden D, Lin S-f, Kapinos M, Ropchan J, et al. Measurement of Bmax and Kd with the glycine transporter 1 radiotracer 18F-MK6577 using a novel multi-infusion paradigm. J Cereb Blood Flow Metab. 2015 doi: 10.1038/jcbfm.2015.163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Zald DH, Boileau I, El-Dearedy W, Gunn R, McGlone F, Dichter GS, et al. Dopamine Transmission in the Human Striatum during Monetary Reward Tasks. J Neurosci. 2004;24:4105–4112. doi: 10.1523/JNEUROSCI.4643-03.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Zubieta J-K, Smith YR, Bueller JA, Xu Y, Kilbourn MR, Jewett DM, et al. Regional Mu Opioid Receptor Regulation of Sensory and Affective Dimensions of Pain. Science. 2001;293:311–315. doi: 10.1126/science.1060952. [DOI] [PubMed] [Google Scholar]
  64. Zurcher NR, Loggia ML, Lawson R, Chonde DB, Izquierdo-Garcia D, Yasek JE, et al. Increased in vivo glial activation in patients with amyotrophic lateral sclerosis: assessed with [(11)C]- PBR28. NeuroImage Clinical. 2015;7:409–414. doi: 10.1016/j.nicl.2015.01.009. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES