Effects of Citalopram Infusion on the Serotonin Transporter Binding of [ 11 C]DASB in Healthy Controls

Abstract

The positron emission tomography (PET) ligand [¹¹C]DASB is currently the most widely used imaging agent for quantitative studies of the serotonin transporter (SERT) in human brain. The aim of this work was to assess the effects of an intravenous infusion of 10 mg citalopram, a selective serotonin reuptake inhibitor (SSRI), before the PET scan on the kinetics of [¹¹C]DASB in arterial plasma and in selected brain regions. Four healthy male volunteers underwent two PET scans with a mean of 523 MBq injected activity after either placebo or Citalopram infusion in a randomised design. The Citalopram infusion led to a substantial increase of the area under the curve of the metabolite-corrected arterial plasma input function. Total volumes of distribution V_T were estimated applying the Logan plot to regional time—activity curves or by generating parametric maps with spectral analysis. A mean reduction of the cerebellar V_T of 19% with Logan analysis and of 24% with spectral analysis was observed after Citalopram infusion, which confirms previous findings of displaceable SERT ligand binding in cerebellar grey matter. The SERT occupancy for six target regions with moderate to high binding was 60% derived from BP_ND and 69% derived from BP_P.

Keywords

Citalopram positron emission tomography reference region serotonin transporter tracer kinetic modelling

Introduction

Serotonin (5-hydroxytryptamine, 5-HT) is a neurotransmitter that plays a pivotal role in the pathophysiology of mood disorders and in the regulation of emotion. In the central nervous system, the serotonin transporter (SERT) or serotonin reuptake site is located on the presynaptic nerve endings and plays a key role in the regulation of the serotonin levels in the synaptic cleft. Selective serotonin reuptake inhibitors (SSRIs) provide the means to increase the serotonin concentrations in the synapse and to augment serotonergic neurotransmission. They are widely used in the treatment of mood and anxiety disorders, such as major depressive disorder, obsessive—compulsive disorder, and generalised anxiety disorder.

Underscoring its central position in the regulation of serotonergic function, a number of attempts have been made to perform in vivo quantification of SERT binding in humans with either single photon emission computerised tomography or positron emission tomography (PET). The two PET radioligands, which have been most widely used in the last decade, are the ¹¹C-labelled (+) enantiomer of trans-1,2,3,5,6,10β-hexahydro-6-[4-(methylthio)phenyl]-pyrrolo[2,1-α]-isoquinoline or [¹¹C](+)McN5652 (Suehiro et al, 1993) and (N,N-dimethyl-2-(2-amino-4-cyanophenylthio)benzylamine labelled with ¹¹C or [¹¹C]DASB (Houle et al, 2000). Of these two, comparison in animals and humans have shown that [¹¹C]DASB has the advantages of a higher ratio of specific binding to nonspecific binding and of a measurable free fraction in plasma (Szabo et al, 2002; Frankle et al, 2004).

Various tracer kinetic modelling approaches for human [¹¹C]DASB studies making use of a plasma input function or of a reference tissue input function were compared (Ginovart et al, 2001; Frankle et al, 2006; Ogden et al, 2007). Furthermore, methods for the fast generation of parametric maps using a cerebellar time—activity curve (TAC) as the input function were presented (Ichise et al, 2003; Kim et al, 2006).

In general, the quantification of the specific binding in brain PET studies is based on two assumptions regarding the use of a reference region (Cunningham and Lammertsma, 1995). (1)

The reference region should effectively be devoid of specific binding.

(2)

The free and nonspecific binding of the radioligand should be uniform across the entire brain such that the binding estimate in the reference region can be used as a measure of the free and nonspecific binding in the other parts of the brain.

Specifically in studies of PET radioligand binding to the SERT, a growing amount of evidence suggests that these assumptions may not be fully met. Four examples may serve here as a cross-section through these findings. (1)

Szabo et al (2002) observed changes of [¹¹C](+) McN5652 binding and of [¹¹C]DASB binding in the cerebellum of baboons after lesioning with MDMA (methylenedioxymethamphetamine) or treatment with the SSPI paroxetine.

(2)

Ikoma et al (2002) developed a dual scan paradigm based on administering of both stereo-isomers of [¹¹C]McN5652, the nonspecifically binding [¹¹C](−)McN5652, and the SERT selective [¹¹C](+)McN5652 (Suehiro et al, 1993), to obtain estimates of the regionally variable free and nonspecific binding of [¹¹C](+)McN5652.

(3)

Kish et al (2005) found in postmortem brain of normal adult subjects a SERT concentration in cerebellar cortex and white matter of approximately 20% of the concentration in cerebral cortex or 5% of the concentration in striatum.

(4)

Parsey et al 2006a) reported a 33% reduction of the [¹¹C]DASB distribution volume in cerebellar grey matter after daily oral sertraline treatment in healthy volunteers.

The changes of radioligand binding to the SERT in the cerebellum observed by, for example, Szabo et al (2002), Kent et al (2002), and Parsey et al (2006a) were all greater than what can be expected from in vitro measurements of the SERT density (Kretzschmar et al, 2003; Kish et al, 2005).

Therefore, the aim of this study was to assess the effects of a single bolus infusion of 10 mg of the SSRI Citalopram on the [¹¹C]DASB kinetics in the plasma and in the brain of healthy humans.

Although Citalopram infusion has been used as a neuropharmacologic probe of serotonergic function (Lotrich et al, 2005), only one functional imaging study with PET after parenteral Citalopram has been published so far describing local changes in cerebral glucose metabolism (Smith et al, 2002). However, brain SERT occupancy measured with PET after oral Citalopram administration were reported (Meyer et al, 2001; Meyer et al, 2004). Our aim, therefore, was to in vivo characterise the blockade of the SERT-binding sites after Citalopram infusion using [¹¹C]DASB as an imaging probe specifically binding to the SERT and to compare the results with those previously published after oral Citalopram administration.

Materials and methods

Subjects and Medication

Four healthy male control subjects (aged 49, 37, 57, and 42 years) gave written informed consent to be included in the study. Subjects were randomised to receive either a slow intravenous infusion of Citalopram 10 mg or placebo for more than 30 mins starting 45 mins before injection of the radioligand. The dose and timing of the injection were based on previous studies showing robust and sustained effects of this dose of Citalopram on anterior pituitary hormones—a putative marker of serotonergic system integrity (Attenburrow et al, 2001; Bhagwagar et al, 2002). As published by Lotrich et al (2005) (Figure 3), this schedule leads in healthy control subjects to a fairly stable Citalopram plasma concentration of about 10 ng/mL between 45 and 150 mins after the start of the infusion with little between-subject variability.

Subjects were studied at least a week apart for both experiments, mean interval 9 ± 3.4 days. All subjects were screened using the Structured Clinical Interview for DSM-IV Disorders (First et al, 1997) to exclude any current or lifetime history of Axis I disorders. None of them had any first-degree relative with any major psychiatric illness. Exclusion criterion included current or past serious medical or neurological illness, alcohol or illicit substance dependence, and recent use (not less than three months) of any centrally acting medication. The Research Ethics Committee of the Hammersmith Hospitals Trust and the Administration of Radioactive Substances Advisory Committee (ARSAC) of the United Kingdom approved the study.

All PET studies were performed in the early morning or late afternoon within a time window of approximately 3 h. Subjects arrived at least 2 h before the PET scan and had a cannula placed in the radial artery and a venous cannula inserted in the contralateral antecubital vein.

Positron Emission Tomography Scans

The radiotracer [¹¹C]DASB was synthesised as previously described (Wilson et al, 2000) by reaction of [¹¹C]methyl-iodide with the desmethyl precursor. The standard DASB and the precursor desmethyl DASB were obtained from Target Molecules Ltd (Southampton, UK). [¹¹C]DASB was injected by hand into an antecubital vein as a smooth bolus for more than 30 secs. The injected radioactivity dose was between 487 and 547 MBq (mean: 523 MBq, s.d.: 24 MBq). The radiochemical purity of the injected [¹¹C]DASB was high and ranged from 97% to 100% with a mean of 98% and an s.d. of 1.2%. The injected mass of cold DASB varied between 1.07 and 7.05 μg with a mean value of 2.4 μgg and an s.d. of 1.9 μg. The specific activity was on average 81.0 GBq μmol⁻¹ with an s.d. of 30.6 GBq μmol⁻¹.

All PET scans were performed on the high-sensitivity Siemens/CTI scanner ECAT EXACT3D with an axial field of view of 23.4 cm and 95 reconstructed transaxial image planes (Spinks et al, 2000). To reduce the effect of activity outside the direct field of view in brain scans, the tomograph was equipped with annular side shielding (Spinks et al, 1998). A 5-mins transmission scan using a ¹³⁷Cs point source was performed before each study for subsequent attenuation correction and scatter correction (Watson et al, 1996). The 90-mins three-dimensional dynamic emission scan was acquired in list mode. In the post-acquisition frame rebinning, 28 time frames of increasing length were generated (30 secs background frame before the injection, then one 15 secs frame, one 5 secs frame, one 10 secs frame, three 30 secs frames, three 60 secs frames, three 120 secs frames, three 180 secs frames, eight 300 secs frames, and four 450 secs frames). The spatial resolution of the images reconstructed using the reprojection algorithm with the ramp and Colsher filters set to Nyquist frequency is close to isotropic: 5.1 mm full width at half maximum transaxially and 5.9 mm full width at half maximum axially averaged over a radius of 10 cm from the centre of the field of view (Spinks et al, 2000). Positron emission tomography data were not corrected for head motion. On the basis of visual inspection of the tissue TACs, it was ensured that all PET scans were free of detectable head motion.

Arterial whole blood activity was monitored continuously for the first 28 mins of the scan with a bismuth germanate coincidence detector (Ranicar et al, 1991). For the initial 10 mins during which the peak of radioactivity in the blood occurs and fine temporal sampling of the signal is required, the blood flow rate through the detector system was set to 5 mL/mins. Thereafter, the blood pump rate was reduced to 2.5 mL/mins. Ten discrete arterial blood samples were taken at 3, 9, 15, 21, 28, 35, 42, 50, 70, and 90 mins into heparinised syringes. The activity concentration of the whole blood and the plasma were measured.

Eight plasma samples per scan (at 3, 9, 15, 21, 35, 50, 70, and 90 mins) were analysed for metabolites using a semiautomated system with online solid-phase extraction followed by reverse-phase chromatography with online radioactivity and UV detectors and integration system (Luthra et al, 1993). The plasma samples were loaded onto the solid-phase extraction column and eluted with di-ammoniumhydrogen phosphate (0.01 mol/L) and further analysed using reverse-phase column (μ-Bondapak C₁₈ column, 30 × 0.78 cm internal diameter) eluted with a mixture of ammonium formate (10 mmol/L) and methanol (35:65 v/v) at a flow rate of 3 mL/mins. The eluate was monitored for UV absorbance at 254 nm and radioactivity and subsequent data captured on a PC-based integrator. The overall recovery was calculated from the collected radioactivity coming off the HPLC column and from the measurement of the radioactivity of the aqueous phase relative to the total radioactivity loaded onto the solid-phase extraction column. The amount of [¹¹C]DASB and its radioactive metabolites at a given time point was calculated from the decay-corrected integrated radiochromatogram and the levels of radioactivity in the solid-phase extraction eluate and expressed as a percentage of total plasma sample injected.

Magnetic Resonance Scans and Definition of Volumes of Interest

All volunteers had a structural T₁ magnetic resonance (MR) scan performed on either 0.5 or 1.5 T MR scanners (GE Signa scanner; GE Medical Systems, Milwaukee, WI, USA). All structural scans were inspected by an independent clinical neuroradiologist and found to be normal. Magnetic resonance images (MRIs) were resliced to a voxel size of 1 × 1 × 1 mm³, centred on anterior commissure and aligned to the AC-PC line.

Magnetic resonance images were coregistered to the individual PET images summed from 9 mins after injection until the end of the PET scan using SPM2 (Functional Imaging Laboratory, London, UK), which adopts a rigid body transformation using normalised mutual information method. Volumes of interest (VOIs) were defined on the coregistered MRI with the help of a probabilistic brain atlas template (Hammers et al, 2002; Hammers et al, 2003). The standard MNI T₁ template (available in the SPM2) was normalised to the coregistered individual MRI and the deformation parameters were applied to the probabilistic atlas. This normalised brain atlas was resliced to PET space and segmented with SPM2 (Ashburner and Friston, 1997) to obtain data from grey matter only. The following seven VOIs were chosen for the analysis.

SERT moderate to rich regions: brainstem, thalamus, amygdala, putamen, and caudate,

a region with moderate SERT density: hippocampus,

a region with very low concentration of SERT: cerebellum. We obtained data from posterior cerebellar grey matter up to 5 to 8 slices carefully avoiding spill over from occipital cortex or venous sinuses by placing the volume of interest well within the cerebellar cortex area leaving a margin of several millimetres around to the outer borders of the cerebellum as defined in Hammers et al (2003), page 240.

The dynamic PET scans were then sampled by applying the individual VOI object maps to create regional tissue TACs.

Generation of the Plasma Input Function

For the generation of the plasma input functions, the time course of the plasma-to-blood ratio, obtained from the first five discrete arterial samples at 3, 9, 15, 21, and 28 mins scan time, was first fitted to a sigmoidal.

Then, the measurement of the arterial whole blood activity obtained from the continuous detector system (Ranicar et al, 1991) was multiplied with that ratio to obtain a total plasma activity curve for the first 28 mins of the scan. This curve was then combined with the discrete plasma activity concentration measurements at 35, 42, 50, 70, and 90 mins to an input function describing the total plasma activity concentration for the entire scan.

The input function of the activity concentration due to unmetabolised [¹¹C]DASB in plasma was then created by multiplying the total plasma activity input function with the function obtained from the fit of the model for the parent fraction in plasma to the eight measurements of the parent compound during the scan. Finally, the time delay of the arrival of the radioactivity bolus at the peripheral sampling site relative to the brain was determined (Hinz and Turkheimer, 2006).

All calculations were performed using Matlab® (The MathWorks Inc., Natick, MA, USA) on Sun Ultra™ 10 workstations (Sun Microsystems Inc., Santa Clara, CA, USA).

Quantification of the Ligand Binding in Tissue

For the quantitation of the [¹¹C]DASB binding in brain tissue, different previously used approaches were considered (Ginovart et al, 2001; Frankle et al, 2006; Ogden et al, 2007), with the aim of expressing the radioligand binding in tissue relative to the radioligand concentration in the arterial plasma to be able to assess the properties of the reference region.

Estimates of compartmental model parameters were obtained from weighted fits of the regional TACs. Details of this procedure were described in a previous study (Hinz et al, 2007). As a second method, the graphical analysis of reversible radioligand binding using the plasma input function (Logan et al, 1990) was applied to obtain regional estimates of the total volume of distribution V_T from the slope of the linear part of the plot. Finally, spectral analysis (Cunningham and Jones, 1993) was used to create parametric images of V_T. The functional basis was set up with 100 functions logarithmically spaced between 0.0007 and 0.1/secs.

The binding potential of the nondisplaceable binding BP_ND was then calculated indirectly

B P_{N D} = V_{T}^{t a r g e t r e g i o n} / V_{T}^{c e r e b e l l u m} - 1

(1)

and the binding potential of the specifically bound radioligand relative to the parent radioligand in plasma BP_P was also calculated indirectly

B P_{p} = V_{T}^{t a r g e t r e g i o n} - V_{T}^{c e r e b e l l u m}

(2)

The occupancy was expressed as the percentage reduction of the binding potential between baseline and blocked condition

O c c = (1 - B P^{b l o c k e d} / B P^{b a s e l i n e}) \times 100 %

(3)

where Occ_P was used to indicate occupancy derived from BP_P and Occ_ND was used to indicate that the occupancy was calculated from BP_ND.

Results

Input Function

In Figure 1, the observed time courses of the ratio of plasma activity concentration over whole blood activity concentration are plotted for the two different scanning conditions. Under baseline condition after placebo infusion, the plasma-over-whole blood activity concentration ratio (POB ratio) was smaller than one, which means that the radioactivity concentration in whole blood was higher than in plasma. Owing to similarities in the properties of the membranes of red blood cells with the properties of the blood—brain barrier (BBB), the higher concentration of a lipophilic radiotracer such as [¹¹C]DASB, which is thought to cross the BBB by passive diffusion, in the red cell fraction than in the plasma fraction can be expected. During the time course of the PET scans, the POB ratios were continually increasing. This is consistent with the fact that the radiolabelled metabolites of [¹¹C]DASB were reported to be more polar than the parent compound [¹¹C]DASB (Wilson et al, 2000) and as such are expected to preferentially accumulate in the plasma fraction rather than the red cell fraction.

Figure 1

Ratio of plasma activity concentration over whole blood activity concentration after placebo infusion (circles) or Citalopram infusion (crosses). The mean values with their standard deviations are given for each of the 10 discrete arterial blood samples.

In the initial phase of the scans performed after Citalopram infusion, the POB ratios were significantly higher than under baseline condition. As the scans progressed, this difference became gradually smaller, such that at the end of the scans at 90 mins, the POB ratios were no different between baseline and blocked condition. The initially higher POB ratio is likely because of Citalopram blocking the SERT-binding sites on the platelets, which are part of the red cell fraction when the blood samples are centrifuged. As a consequence, the concentration of [¹¹C]DASB in plasma is higher than in the red cell fraction. Because more and more radioactivity in the blood is represented by radiolabelled metabolites than by the unmetabolised [¹¹C]DASB and because the Citalopram concentration in blood is also going down, the partition of the radioactivity between plasma and the red cell fraction approaches that observed after placebo infusion.

In Figure 2, the time course of the fraction of the radioactivity in plasma that is because of the unmetabolised parent compound [¹¹C]DASB is depicted for the two conditions. Despite the fact that the radiochemical purity of the injected dose was at least 97%, the parent fraction measured in the 3-mins sample was well below 90% (after Citalopram infusion) or below 80% (after placebo infusion). A similar low parent fraction of the first arterial sample, followed by a higher parent fraction in the second samples has been reported by Parsey et al (2006b). Dynamic acquisitions of the activity distributions in humans, baboons, and rhesus monkeys have shown that for the first 5 mins or so more than 50% of the total injected [¹¹C]DASB activity are concentrated in the lungs (Lu et al, 2004; Bélanger et al, 2004; Tipre et al, 2004). As the lungs have been described as an organ of high metabolic activity and with a high concentration of serotonin reuptake sites, the intravenous infusion of Citalopram before the [¹¹C]DASB administration and the subsequent blockade of the SERT-binding sites in the periphery by Citalopram are consistent with the observed increase of the parent fraction at the onset of the PET scan. As the scan progressed, the differences between the measured parent fractions under baseline and blocked condition are no longer significant (Figure 2). As with the POB ratio, at the end of the PET scan at 90 mins, there is no difference between the two conditions in the parent fraction. The statistical uncertainty of the late parent fraction measurements was in the order of 5% to 10% as the entire late scan time chromatograms had only a few thousand counts acquired over an HPLC run time of 12 mins, and the parent fraction peak then represented about 10% of the total plasma radioactivity.

Figure 2

Fraction of unmetabolised parent compound in arterial plasma. The plotted bars represent mean values and standard deviations from the four scans under each condition (baseline scans marked by circles and blocked scans marked by crosses).

To be able to account for this qualitative difference in the measured time course of the parent fraction, two different mathematical functions were used. The first model function is a sigmoidal

P a r e n t (t) = c - \frac{p_{1} + p_{2} x}{(p_{3} / x)^{p_{4}} + 1}

(4)

where x = t/3600 secs is the normalised time, p₁ > 0, p₂ > 0, p₃ > 0, and p₄ > 0 are the four free parameters of the model, and c is a fixed parameter of the model equal to the value of the function at t = 0. This function is strongly monotonic decreasing and, therefore, cannot have a local maximum. It was used to fit the parent fraction measurements of all four PET scans after Citalopram infusion and of two scans (subjects 1 and 4) after placebo infusion, because in these six cases the measured values were monotonically decreasing.

For the measurements of the parent fraction in plasma obtained in subjects 2 and 3 after placebo infusion where the measured parent fractions at 9 mins were greater than those at 3 mins, the following model function with five free parameters was used to allow for a local maximum

P a r e n t (t) = q_{1} e^{+ (q_{2} t - q_{3} t^{2})} + q_{4} - q_{5} t

(5)

with all q_i > 0 (i = 1 … 5). This lack of monotony under baseline condition is reflected in Figure 2 by the standard deviation of the second time point (9 mins) being much smaller than the standard deviation of the first time point (3 mins).

The overall impact of the Citalopram infusion on the [¹¹C]DASB arterial plasma input functions is expressed as the AUC (area under the curve) for all four subjects in Table 1. After 5 mins, the AUC after Citalopram infusion was by a factor of two to three more than after placebo infusion. This relative increase of the bioavailability of [¹¹C]DASB after SSRI administration continued throughout the scan, although to a lesser extent such that at 90 mins, the AUCs were, on average, 24% increased in comparison with the placebo scans.

Table 1

Area under the curve (AUC) in Bq/cm³/mins per MBq injected of the activity concentration (corrected for radioactive decay) due to parent compound [¹¹C]DASB in plasma

	Subject 1		Subject 2		Subject 3		Subject 4
Scan time (mins)	Placebo	Citalopram	Placebo	Citalopram	Placebo	Citalopram	Placebo	Citalopram
5	49.7	103.0	30.6	89.1	28.2	122.4	44.6	98.2
30	158.1	196.2	151.7	207.7	165.8	259.8	140.3	194.6
90	225.7	250.4	245.9	295.5	272.2	353.9	196.3	247.5

Tissue Response

In correspondence with the known distribution of the SERT in human brain and as previously reported (Houle et al, 2000), high uptake of [¹¹C]DASB was observed in thalamus, midbrain, and hypothalamus, moderate uptake in hippocampus and basal ganglia, and relatively low uptake in the cerebellum. Figure 3 shows tissue TACs from five selected regions of one subject after placebo infusion and after Citalopram infusion, respectively. Under baseline condition and consistent with the observations by Frankle et al (2004), the local maxima of the TACs occurred, dependent on the speed of the regional kinetics, between 20 and 60 mins. After Citalopram infusion, the peak times of the regional TACs were reached earlier (between 10 and 30 mins); thus, the kinetics were accelerated in comparison with the baseline condition. The peak activity concentration in the cerebellum was—as a consequence of the increased availability of [¹¹C]DASB in plasma—higher after Citalopram infusion than it was after placebo infusion (Figure 3).

Figure 3

Five selected regional tissue TACs from one subject after placebo infusion (A) and after Citalopram infusion (B), respectively. The lines represent the fits through the measured data points as obtained with the two-tissue compartment model.

The regional TACs were initially fitted to the reversible two-tissue compartment, four rate constants model with a free blood volume term without constraints, details of the procedure were described previously (Hinz et al, 2007). However, in several instances, difficulties with the convergence of the minimisation algorithms were encountered, and negative estimates of the rate constant k₄ were obtained. Sometimes even the estimates of the rate constant k₃ were negative. Similar difficulties to obtain reliable estimates for the unconstrained two-tissue, four rate constants compartment model were reported by Frankle et al (2006). After a reduction of the model order to an unconstrained reversible one-tissue, two rate constants model with a free blood volume term, the parameter estimation procedures always converged to a solution. However, the quality of the fits, particularly in regions with lower uptake, often deteriorated substantially relative to the fits with the four rate constants model, as indicated by the residual sum of the squared errors.

Therefore, the graphical analysis of reversible binding (Logan et al, 1990) was used to obtain estimates of the total volumes of distribution V_T without explicitly deciding on the model order. One of the requirements of the graphical analysis is the choice of the threshold time t* from which the portion of the graph is fitted by a straight line whose slope then provides an estimate of V_T (Logan et al, 1990). If this portion of the graph still has a remaining curvature, then the straight line fit is a secant rather than a tangent to the graph and as such provides an underestimation of the gradient of the curve. This effect is illustrated in Figure 4 showing the relative underestimations of the slope as a function of the choice of the threshold time t*.

Figure 4

Relative bias of the estimated slopes from the Logan plot analysis as a function of the threshold time t*. The bars in black represent the mean values and standard deviations across the four subjects under baseline condition (A) and after Citalopram infusion (B).

Theoretically, two data points would be sufficient for a straight line. However, such fits with zero degrees of freedom would provide only parameter estimates, which are extremely sensitive to the noise in these two measurements that is a particular problem when these two points are obtained from the low count data of the last two frames of a 90–mins PET scan with a ¹¹C-labelled compound. To calculate the relative bias of the estimated slope, the ‘true’ value of the Logan plot slope needs to be known, which means this value has, at the same time, to be an unbiased and low variance estimate of the slope. For the purpose of the calculations presented in Figure 4, the ‘true' Logan plot slope was obtained from the mean value of the slopes estimated from the last four, five, and six frames of the dynamic study, that is, fits with two, three, and four degrees of freedom as the model function has the two free parameters slope and intercept. This ‘true’ slope value corresponds to a 0% relative bias in Figure 4.

The underestimation of the slope is less severe under the blocked condition (Figure 4B) than under the baseline condition (Figure 4A). As the tracer kinetics in blood and tissue were faster after Citalopram infusion, the steady-state conditions required to achieve linearity of the Logan plot (Logan et al, 1990) were approached faster than after placebo infusion. In Figure 4, the Citalopram infusion also appears to have resulted in a reduction of the between-subject variability. The mean rate of change of the slope estimate with increasing threshold time t* plateaus off after about 35 mins in Figure 4A. This value was therefore chosen as the threshold time t* for the data analysis, that is, the transformed data from frames 20 to 28 were fitted to a straight line. This threshold provided a trade-off between parameter bias (underestimation of the slope on average 3%) and parameter variance arising from fits based on eight data points or six degrees of freedom. As the Citalopram infusion led to the described faster kinetics in tissue and for consistency of the methods, the same t*-value was used for all subjects and regions, and for both conditions.

The results from all four subjects are given in Table 2. A negative bias of parameter estimates obtained with the Logan plot has been shown by Slifstein and Laruelle (2000); however, previous investigators reported that the Logan analysis estimates obtained from [¹¹C]DASB regional tissue TACs, that is, data sets of good statistical quality in comparison with the voxel level, appeared to be largely unbiased (Ginovart et al, 2001; Frankle et al, 2006).

Table 2

Parameter estimates from the graphical analysis of reversible binding of the regional tissue time—activity curves

	Subject 1					Subject 2					Subject 3					Subject 4
	Placebo		Citalopram			Placebo		Citalopram			Placebo		Citalopram			Placebo		Citalopram
Volume of interest name	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P
Cerebellum	9.2		9.2			9.9		7.9			12.7		9.6			9.3		6.4
Amygdala	26.3	1.85	15.3	0.66	65	30.6	2.08	13.5	0.70	66	41.5	2.27	14.7	0.54	76	29.5	2.17	11.9	0.85	61
		17.1		6.1	65		20.6		5.6	73		28.8		5.1	82		20.2		5.4	73
Brainstem	26.9	1.92	15.3	0.66	66	30.1	2.03	13.3	0.68	66	34.5	1.71	14.4	0.50	71	25.4	1.74	11.3	0.75	57
		17.7		6.1	66		20.1		5.4	73	21.8		4.8		78		16.1		4.8	70
Caudate	23.7	1.57	13.5	0.46	71	23.4	1.35	12.9	0.62	54	31.7	1.49	14.5	0.51	66	22.5	1.42	9.9	0.54	62
		14.5		4.2	71		13.5		4.9	63		19.0		4.9	74	13.2		3.5		74
Hippocampus	17.0	0.84	12.1	0.31	64	19.6	0.97	11.7	0.48	51	26.5	1.08	13.7	0.44	60	17.4	0.87	10.0	0.57	35
		7.8		2.8	63		9.7		3.8	61		13.8		4.2	70		8.1		3.6	55
Putamen	29.1	2.15	16.2	0.75	65	29.5	1.97	15.7	0.99	50	34.6	1.72	16.3	0.71	59	28.5	2.06	13.4	1.09	47
		19.8		7.0	65		19.5		7.8	60		21.8		6.8	69		19.2		7.0	64
Thalamus	28.7	2.11	14.4	0.55	74	28.6	1.88	13.9	0.75	60	30.5	1.40	15.6	0.63	55	28.4	2.06	12.6	0.96	54
		19.5		5.1	74		18.7		6.0	68		17.8		6.0	66		19.1		6.1	68
Mean ± s.d.					67 ± 4					58 ± 7					64 ± 8					52 ± 10
					67 ± 4					66 ± 6					73 ± 6					67 ± 7

The total volumes of distribution V_T and the binding potentials relative to parent in plasma concentration BP_P are given in units of mL plasma per mL extravascular tissue, the binding potentials of the nondisplaceable uptake BP_ND are unitless, and the occupancies Occ_ND and Occ_P are expressed in %.

The reduction of the cerebellar V_T from the baseline to the blocked condition was 19% ± 13% for the four subjects. A paired two-tailed t-test did not reject the null hypothesis that there was no significant difference of the cerebellar V_T between the baseline and blocked scans (P > 0.067). This, however, indicates a trend towards significance.

The intrasubject variability of the occupancy OCC_ND calculated from BP_ND between the six regions listed in Table 2 was highest in subject 4 with 10% or less for the others. The mean occupancy Occ_ND from all four subjects was 60%. The mean occupancy Occ_P calculated from BP_P from all four subjects was 69%.

Two parametric images of the total volume of distribution V_T after placebo infusion and Citalopram infusion are shown in Figure 5. Visual inspection reveals that the V_T in the Citalopram scan is lower in all regions of the brain including the cerebellum compared with the baseline scan performed after placebo infusion. The parameter estimates obtained from sampling the parametric maps generated with spectral analysis are given for all four subjects in Table 3. Individual V_T estimates are higher than those obtained from the regional analyses of tissue TACs with the Logan plot. This may be because of a negative bias in the estimates obtained from the Logan analysis (Slifstein and Lamelle, 2000), a positive bias in the V_T estimates obtained with spectral analysis at the voxel level that is characterised by a lower signal-to-noise ratio than the tissue TACs (Cunningham et al, 1998) or a combination of these two factors. In either case, the reduction of the cerebellar V_T in the parametric maps from the baseline to the blocked condition was 24% ± 11% for the four subjects. A paired two-tailed t-test rejected the null hypothesis that there was no significant difference of the cerebellar V_T between the baseline and blocked scans (P < 0.041). Therefore, the changes of the cerebellar V_T in the parametric maps were statistically significant.

Figure 5

Oblique slice through parametric images of the total volume of distribution V_T from the same subject as in Figure 3 generated with spectral analysis after placebo infusion (A) and after Citalopram infusion (B).

Table 3

Parameter estimates from sampling the parametric maps of V_T generated with spectral analysis

	Subject 1					Subject 2					Subject 3					Subject 4
	Placebo		Citalopram			Placebo		Citalopram			Placebo		Citalopram			Placebo		Citalopram
Volume of interest name	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P	V_T	BP_ND BP_P	V_T	BP_ND BP_P	Occ_ND Occ_P
Cerebellum	11.8		10.8			13.5		10.3			17.1		11.5		11.7		8.4
Amygdala	30.4	1.58	18.4	0.71	55	32.0	1.36	16.4	0.59	57	37.3	1.18	18.5	0.61	48	33.8	1.88	15.0	0.80	58
		18.6		7.6	59		18.5		6.1	67		20.2		7.0	65		22.0		6.7	70
Brainstem	30.3	1.57	18.1	0.68	57	31.6	1.33	16.0	0.54	59	35.0	1.04	17.3	0.51	51	29.5	1.51	13.8	0.66	57
		18.5		7.3	60		18.0		5.6	69		17.8		5.8	67		17.7		5.5	69
Caudate	30.4	1.58	15.1	0.40	75	30.1	1.22	14.7	0.43	65	39.5	1.30	17.3	0.51	61	27.6	1.35	11.7	0.40	70
		18.6		4.3	77		16.5		4.4	73		22.4		5.8	74		15.8		3.3	79
Hippocampus	21.9	0.86	14.1	0.30	65	23.6	0.74	13.8	0.33	55	31.1	0.82	16.8	0.46	43	21.3	0.81	11.9	0.43	48
		10.2		3.3	68		10.1		3.4	66		14.0		5.3	62		9.5		3.6	63
Putamen	36.1	2.06	18.2	0.69	67	37.1	1.74	18.1	0.75	57	43.1	1.51	19.0	0.65	57	34.5	1.94	15.5	0.85	56
		24.3		7.4	70		23.5		7.7	67		25.9		7.5	71		22.7		7.1	69
Thalamus	35.8	2.03	16.5	0.53	74	35.3	1.61	15.9	0.54	66	38.5	1.25	18.5	0.61	51	34.5	1.94	14.5	0.73	62
		24.0		5.7	76		21.8		5.6	74		21.4		7.0	67		22.8		6.1	73
Mean ± s.d.					65 ± 8					60 ± 5					52 ± 6					58 ± 8
					68 ± 8					69 ± 4					68 ± 4					70 ± 5

The mean occupancy Occ_ND calculated from BP_ND across all subjects was 59%. When BP_P was used to calculate the occupancy Occ_P, then a mean occupancy was 69%. The mean occupancy findings are in agreement with those obtained from the Logan analysis. Regardless of the kinetic model used, the occupancies calculated from BP_P are always equal to or greater than the occupancies calculated from BP_ND.

Discussion

A single intravenous infusion of 10 mg Citalopram 45 mins before administering an intravenous [¹¹C]DASB bolus led to a substantial increase of the concentration of [¹¹C]DASB in arterial plasma compared with a similar paradigm that employed a saline placebo infusion before the [¹¹C]DASB PET scan. This appears to be a consequence of the blockade of the peripheral SERT-binding sites, for instance, in the lungs, the organ that was shown to have the highest uptake of [¹¹C]DASB in the early phase of the PET scan (Lu et al, 2004; Bélanger et al, 2004; Tipre et al, 2004).

As a consequence of these quite dramatic changes to the time course of the [¹¹C]DASB concentration in the plasma, the kinetics of the [¹¹C]DASB binding in brain tissue was also affected in the sense that the peak activity of the regional TACs occurred earlier during the scanning period than in baseline condition. The total volumes of distribution V_T were lower in the blocked scans in all brain regions examined including the cerebellar grey matter, the region with the lowest SERT concentration. The mean reduction of the cerebellar V_T was 19% (graphical analysis of reversible binding performed on the regional tissue TACs) and 24% (as obtained from the parametric images of V_T generated with spectral analysis) for the four subjects in our cohort. There was, however, one subject in whom the cerebellar V_T remained unchanged when the graphical analysis of reversible binding of the TAC was performed (Table 2, subject 1). The reductions of the cerebellar V_T of this investigation are in line with previous reports by Parsey et al (2006a) who found in a [¹¹C]DASB study 33% occupancy in cerebellar grey matter of subjects after an acute treatment with sertraline or by Kent et al (2002) who reported from a [¹¹C]McN5652 study of five subjects with social phobia a reduction of the cerebellar V_T of 23% ± 12% after paroxetine treatment. However, these reductions appear to be higher than expected from a blockade of the specific binding of the radioligand in the cerebellum given that the specific binding of [³H]citalopram in autoradiographic studies of porcine brain has been reported as only 2.3 pmol/g tissue in the cerebellum in comparison with 26 pmol/g tissue in the amygdaloid area (Kretzschmar et al, 2003). From postmortem immunoreactivity studies of human brain an amygdala-to-cerebellar cortex SERT ratio of 35 has been reported (Kish et al, 2005). Several authors (Szabo et al, 2002; Kent et al, 2002) therefore suggested that the experimental paradigms employed in the SERT imaging studies with PET such as MDMA lesioning or SSRI administration may have affected what is generally termed as ‘nondisplaceable binding.’ However, the underlying nature of these effects is unclear. Rochat et al (1999) reported that the Citalopram transport across the BBB is mediated by a carrier mechanism. If [¹¹C]DASB competed with Citalopram for the same BBB transport mechanism, then the entry of [¹¹C]DASB into the brain might be reduced in the presence of Citalopram.

Despite these changes of the V_T in the cerebellum, we obtained indirect estimates of the binding potentials BP_ND and BP_P from which regional occupancy estimates Occ_ND and Occ_P were calculated (Tables 2 and 3). As previously demonstrated, the BP_ND-derived occupancy estimates Occ_ND underestimate the true occupancy in a target region if the total volume of distribution V_T from a reference region with displaceable binding is used as a measure of the volume of distribution of the nondisplaceable binding V_ND in the target region (Asselin et al, 2007). In contrast, the BP_P-derived occupancy estimates Occ_P are always equal to or greater than the BP_ND-derived occupancies Occ_ND. The case that both methods to calculate the occupancy give the same result occurred for subject 1 in Table 2, because there was no change in the cerebellar V_T, which indicates that in this case the assumption of no displaceable binding in the reference region was not violated. The mathematical derivation in the Appendix details circumstances under which the true and apparent occupancy calculated from BP_P are the same in the presence of specific binding in the reference regions. The observation that the mean BP_ND-derived occupancy in our study is about 10% smaller than the mean BP_P-derived occupancy corresponds with a mean BP_ND^{reference region (blocked)} of 0.11. Nevertheless, the occupancy estimates obtained were fairly homogeneous across the SERT-rich regions considered with Occ_P showing much less between-subject variability than Occ_ND. Because it was not possible to obtain reliable measurements of the [¹¹C]DASB free fraction in plasma f_P in this study, the possibility of changes of f_P between the baseline and blocked condition could not be eliminated. Conversely, the comparability of BP_ND between the two conditions requires that the free fraction of the nondisplaceable compartment f_ND has not changed. Therefore, using BP_P as the outcome parameter has the advantage over the use of BP_ND that BP_P can provide occupancy estimates, which are not biased in the presence of specific binding in the reference region provided that there are no differential occupancies across regions. The mathematical expression for the BP_P-derived occupancy calculation that followed from equations (2) and (3) (also compared with equation (A3) in the Appendix)

O c c_{P} = \frac{V_{T}^{b a s e l i n e} - V_{T}^{b l o c k e d}}{V_{T}^{b a s e l i n e} - V_{N D}} \cdot 100 %

(6)

is identical with the equation provided by Lassen et al (1995) (equation 11) for the calculation of occupancy in studies without a receptor-free reference region.

In agreement with previous reports (Frankle et al, 2004; Frankle et al, 2006), VOIs with low SERT density (e.g., cortical areas) could not be reliably quantified with [¹¹C]DASB (data not shown). Furthermore, the same two reports described difficulties in obtaining ‘good’ fits of the regional tissue TACs with reversible compartmental models (with either one tissue compartment/two rate constants or two tissue compartments/four rate constants) as indicated by a nonrandom distribution of the residuals (Frankle et al, 2004). Similar problems were also encountered in this study. A possible reason may be the violation of the assumption that the rate constants of the compartmental models are constant over time. The experimental paradigm of infusing Citalopram 45 mins before commencing the PET scan probably results in kinetic parameters changing with time. This is consistent with the observation that the rate constants k₃ and k₄ of the two-tissue compartment, four rate constants model appeared to be most frequently suffering from these identifiability problems, which are the constants expected to be primarily affected by the action of the SSRI at the binding sites. In contrast, the graphical analysis of reversible binding and spectral analysis provided the macroparameter V_T as outcome measure and, therefore, appeared to be less sensitive to the violation of the requirement of time constancy of an underlying microparameter. A full discussion of the system identifiability properties after changes of the specific binding of the radioligand has been provided for instance by Endres and Carson (1998). However, the parametric images of V_T generated with spectral analysis may be positively biased in comparison with the results obtained from an analysis of regional tissue TACs. The differences between the V_T obtained from regional analysis (Table 2) and the V_T obtained from sampling parametric maps (Table 3) are in line with those differences previously reported from an investigation into balancing bias, reliability, and noise properties of spectral analysis generated parametric maps from studies with [¹¹C]diprenorphine, which is a nonsubtype selective opiate receptor ligand with slow kinetics in tissue (Hammers et al, 2007). Owing to its relatively slow kinetics in tissue—for instance Frankle et al (2004) determined a minimal scanning time of 95 mins required to derive time-invariant distribution volumes in all regions—a parametric image of the value of the impulse response function (IRF) at a late time point may be a measure of [¹¹C]DASB binding more robust to noise-induced bias than the parametric image of V_T (Cunningham et al, 1998). Such a recommendation to use IRF images instead of V_T images to facilitate the comparison between studies or subjects in different physiological or pharmacological conditions had previously been made for the generation of parametric images of [¹¹C]diprenorphine binding with spectral analysis (Tadokoro et al, 1993). However, this option was not investigated here, because we were interested in quantifying the changes of regional [¹¹C]DASB binding with a parameter that is established across the discipline and can be obtained with many of the widely used analysis methods—therefore, the distribution volume V_T and not the late scan time value of the IRF was used.

Malizia et al (1997) suggested investigating whether the prior blockade of the SERT sites in peripheral organs might be a useful strategy to increase the amount of radiotracer available for binding to the SERT sites in the brain, and, hence, improve the signal in brain imaging studies without administering more radioactivity. Selective serotonin reuptake inhibitors that are unable to cross the BBB appear to be the most promising candidates for such investigations.

The past years have seen continued efforts to develop radioligands that would enable quantification of the binding to the SERT in brain regions with low SERT density, which cannot be reliably assessed with [¹¹C](+)McN5652 or [¹¹C]DASB. As for other neuroreceptor systems, for instance the dopaminergic system where the quantification of the binding to extrastriatal D₂/D₃ receptors was enabled by the introduction of high-affinity radioligands such as [¹¹C]FLB 457 (Asselin et al, 2007), the efforts appear to be directed towards an increase of the affinity of the putative radioligands for the SERT. However, the abundance of the SERT in many parts of the body outside the brain may prevent the success of these efforts to achieve reliable quantification of SERT binding in low SERT brain areas with high-affinity radioligands if they are not combined with measures to reduce, at the same time, the binding of the radioligands to peripheral SERT sites.

In summary, the mean SERT occupancy in the cohort of four subjects was estimated at 60% when calculated from binding potential estimates of the nondisplaceable binding BP_ND, and at 69% when calculated from binding potential estimates of the specifically bound radioligand relative to the parent radioligand in plasma BP_P. Lotrich et al (2005) (Figure 3) reported a mean plasma Citalopram concentration of circa 10 ng/mL between 45 and 150 mins after an infusion of 10 mg Citalopram in healthy control subjects. Meyer et al (2004) (Figure 1) measured a striatal SERT occupancy of about 50% for a plasma Citalopram concentration of 10 ng/mL in subjects who had received daily oral doses of Citalopram for 4 weeks. The same authors reported an occupancy of 80% across five SSRIs (including Citalopram) at minimum therapeutic doses. In conclusion, our data suggest that a 10-mg Citalopram infusion in healthy control subjects results in an acute SERT occupancy of 60% to 70%, which is below the 80% occupancy reported from minimum therapeutic doses of SSRIs, including oral Citalopram.

Footnotes

Acknowledgements

We gratefully acknowledge the excellent work of Safiye Osman with the bioanalysis and quality control teams. We thank Leonhard Schnorr and Debbie Richards for their expert technical support. Andy Blythe, Hope McDevitt, Stella Ahier, Andreanna Williams, and Ann Peers receive our thanks for their assistance in making the scans possible. Sabrina Fancy provided invaluable help in recruiting volunteers. We express our thanks to Dr Federico Turkheimer for his advice on statistical tests. A special thank goes to Dr Marie-Claude Asselin for her inspiration to develop the on the effect of specific binding in the reference region on the calculation of the occupancy.

The authors have no conflict of interest and nothing to disclose in relation to the work presented here.

Appendix

In Asselin et al (2007), a mathematical derivation of the effect of specific binding in the reference tissue on the calculation of the occupancy was given. It showed that in this case, the apparent occupancy Occ_ND is an underestimation of the true occupancy Occ_ND described by the equation

where BP_ND^{reference region (blocked)} is the binding potential of the nondisplaceable binding in the reference region under the blocked condition. This relationship was derived using the binding potentials of the nondisplaceable binding as outcome measures and assuming that the volumes of distribution of the nondisplaceable uptake V_ND do not differ between the target and the reference region and between the baseline and the blocked condition, and that there is no differential occupancy between the target and the reference region.

Here, the effect of specific binding in the reference tissue on the calculation of the occupancy is derived when the occupancy Occ_P is calculated from the binding potentials relative to the parent in plasma concentration BP_P

Expressing the binding potentials in terms of the total volume of distribution V_T and the volume of distribution of the nondisplaceable uptake V_ND

again assuming that the volumes of distribution of the nondisplaceable uptake are the same between regions and conditions, that is, V_ND^{target region (baseline)} = V_ND^{reference region (baseline)} = V_ND^{target region (blocked)} = V_ND^{reference region (blocked)}.

If now the total volume of distribution in the reference region V_T^{reference region}, which contains specific binding sites is used as an estimate of the volume of distribution of the nondisplaceable uptake V_ND, an apparent occupancy Occ'_P will be calculated

Expanding nominator and denominator with V_ND yields

Now replacing V_T-V_ND with BP_P leads to

Again making use of the assumption that the occupancy in all brain regions including the reference region is the same, that is,

gives the following relationship between apparent and true occupancy

This means that if the occupancy is derived from the binding potentials relative to the parent in plasma concentration BP_P, then the presence of specific binding in the reference region introduces no bias.

References

Ashburner

Friston

(1997) Multimodal image coregistration and partitioning—a unified framework. Neuroimage 6:209–17.

Asselin

Montgomery

Grasby

Hume

(2007) Quantification of PET studies with the very high-affinity dopamine D2/D3 receptor ligand [11C]FLB 457: re-evaluation of the validity of using a cerebellar reference region. J Cereb Blood Flow Metab 27: 378–92.

Attenburrow

Mitter

Whale

Terao

Cowen

(2001) Low-dose Citalopram as a 5-HT neuroendocrine probe. Psychopharmacology 155:323–6.

Bélanger

Simpson

Wang

Van Heertum

Mann

Parsey

(2004) Biodistribution and radiation dosimetry of [11C]DASB in baboons. Nucl Med Biol 31:1097–102.

Bhagwagar

Whale

Cowen

(2002) State and trait abnormalities in serotonin function in major depression. Br J Psychiatry 180:24–8.

Cunningham

Gunn

Byrne

Matthews

(1998) Suppression of noise artifacts in spectral analysis of dynamic PET data. In: Quantitative Functional Brain Imaging with Positron Emission Tomography ( Carson

Herscovitch

Daube-Witherspoon

, eds), San Diego, CA: Academic Press, 329–34.

Cunningham

Jones

(1993) Spectral analysis of dynamic PET studies. J Cereb Blood Flow Metab 13:15–23.

Cunningham

Lammertsma

(1995) Radioligand studies in brain: kinetic analysis of PET data. Med Chem Res 5:79–96.

Endres

Carson

(1998) Assessment of dynamic neurotransmitter changes with bolus or infusion delivery of neuroreceptor ligands. J Cereb Blood Flow Metab 18:1196–210.

10.

First

Spitzer

Gibbon

Williams

JBW

(1997) Structured Clinical Interview for DSM-IV Axis I disorders—Clinician Version (SCID-CV). Washington, DC: American Psychiatric Press.

11.

Frankle

Huang

Hwang

Talbot

Slifstein

Van Heertum

Abi-Dargham

Lamelle

(2004) Comparative evaluation of serotonin transporter radioligands ¹¹C-DASB and ¹¹C-McN 5652 in healthy humans. J Nucl Med 45:682–94.

12.

Frankle

Slifstein

Gunn

Huang

Hwang

Darr

Narendran

Abi-Dargham

Lamelle

(2006) Estimation of serotonin transporter parameters with ¹¹C-DASB in healthy humans: reproducibility and comparison of methods. J Nucl Med 47:815–26.

13.

Ginovart

Wilson

Meyer

Hussey

Houle

(2001) Positron emission tomography quantification of [11C]-DASB binding to the human serotonin transporter: modeling strategies. J Cereb Blood Flow Metab 21:1342–53.

14.

Hammers

Allom

Koepp

Free

Myers

Lemieux

Mitchell

Brooks

Duncan

(2003) Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Hum Brain Mapp 19:224–47.

15.

Hammers

Asselin

Turkheimer

Hinz

Osman

Hotton

Brooks

Duncan

Koepp

(2007) Balancing bias, reliability, noise properties and the need for parametric maps in quantitative ligand PET: [11C]diprenorphine test—retest data. Neuroimage 38:82–94.

16.

Hammers

Koepp

Free

Brett

Richardson

Labbe

Cunningham

Brooks

Duncan

(2002) Implementation and application of a brain template for multiple volumes of interest. Hum Brain Mapp 15:165–74.

17.

Hinz

Bhagwagar

Cowen

Cunningham

Grasby

(2007) Validation of a tracer kinetic model for the quantification of 5-HT2A receptors in human brain with [11C]MDL 100,907. J Cereb Blood Flow Metab 27:161–72.

18.

Hinz

Turkheimer

(2006) Determination of tracer arrival delay with spectral analysis. IEEE Trans Nucl Sci 53:212–9.

19.

Houle

Ginovart

Hussey

Meyer

Wilson

(2000) Imaging the serotonin transporter with positron emission tomography: initial human studies with [11C]DAPP and [11C]DASB. Eur J Nucl Med 27:1719–22.

20.

Ichise

Liow

Takano

Model

Toyama

Suhara

Suzuki

Innis

Carson

(2003) Linearized reference tissue parametric imaging methods: application to [11C]DASB positron emission tomography studies of the serotonin transporter in human brain. J Cereb Blood Flow Metab 23:1096–112.

21.

Ikoma

Suhara

Toyama

Ichimiya

Takano

Sudo

Inoue

Yasuno

Suzuki

(2002) Quantitative analysis for estimating binding potential of the brain serotonin transporter with [11C]McN5652. J Cereb Blood Flow Metab 22:490–501.

22.

Kent

Coplan

Lombardo

Hwang

Huang

Mawlawi

Van Heertum

Slifstein

Abi-Dargham

Gorman

Lamelle

(2002) Occupancy of brain serotonin transporters during treatment with paroxetine in patients with social phobia: a positron emission tomography study with [11C]McN 5652. Psychopharmacology 164:341–8.

23.

Kim

Ichise

Sangare

Innis

(2006) PET imaging of serotonin transporters with [11C]DASB: test—retest reproducibility using a multilinear reference tissue parametric imaging method. J Nucl Med 47:208–14.

24.

Kish

Furukawa

Chang

Tong

Ginovart

Wilson

Houle

Meyer

(2005) Regional distribution of serotonin transporter protein in postmortem human brain: is the cerebellum a SERT-free brain region? Nucl Med Biol 32:123–8.

25.

Kretzschmar

Brust

Zessin

Cumming

Bergmann

Johannsen

(2003) Autoradiographic imaging of the serotonin transporter in the brain of rats and pigs using S-([18F]fluoromethyl)-(+)-McN5652. Eur Neuropsycho-pharmacol 13:387–97.

26.

Lassen

Bartenstein

Lammertsma

Prevett

Turton

Luthra

Osman

Bloomfield

Jones

Patsalos

O'Connell

Duncan

Vanggaard Andersen

(1995) Benzodiazepine receptor quantification in vivo in humans using [11C]flumazenil and PET: application of the steady-state principle. J Cereb Blood Flow Metab 15:152–65.

27.

Logan

Fowler

Volkow

Wolf

Dewey

Schlyer

MacGregor

Hitzemann

Bendriem

Gatley

Christman

(1990) Graphical analysis of reversible radioligand binding from time—activity measurements applied to [N-11C-methyl]-(−)-cocaine PET studies in human subjects. J Cereb Blood Flow Metab 10:740–7.

28.

Lotrich

Bies

Muldoon

Manuck

Smith

Pollock

(2005) Neuroendocrine response to intravenous Citalopram in healthy control subjects: pharmacokinetic influences. Psychopharmacology 178:268–75.

29.

Ichise

Liow

Ghose

Vines

Innis

(2004) Biodistribution and radiation dosimetry of the serotonin transporter ligand ¹¹C-DASB determined from human whole-body PET. J Nucl Med 45:1555–9.

30.

Luthra

Osman

Turton

Vaja

Dowsett

Brady

(1993) An automated system based on solid phase extraction and HPLC for the routine determination in plasma of unchanged [11C]-l-deprenyl; [11C]diprenrophine; [11C]flumazenil; [11C]raclopride; and [11C]Scherring 23390. J Lab Comp Badiopharm 32:518–20.

31.

Malizia

Melichar

Brown

Gunn

Reynolds

Jones

Nutt

(1997) Demonstration of clomipramine and venlafaxine occupation at serotonin reuptake sites in man in vivo. J Psychopharmacol 11:279–81.

32.

Meyer

Wilson

Ginovart

Goulding

Hussey

Hood

Houle

(2001) Occupancy of serotonin transporters by paroxetine and Citalopram during treatment of depression: a [11C]DASB PET imaging study. Am J Psychiatry 158:1843–9.

33.

Meyer

Wilson

Sagrati

Hussey

Carella

Potter

Ginovart

Spencer

Cheok

Houle

(2004) Serotonin transporter occupancy of five selective serotonin reuptake inhibitors at different doses: an [11C]DASB positron emission tomography study. Am J Psychiatry 161:826–35.

34.

Ogden

Ojha

Erlandsson

Oquendo

Mann

Parsey

(2007) In vivo quantification of serotonin transporters using [11C]DASB and positron emission tomography in humans: modeling considerations. J Cereb Blood Flow Metab 27:205–17.

35.

Parsey

Kent

Oquendo

Richards

Pratap

Cooper

Arango

Mann

(2006a) Acute occupancy of brain serotonin transporter by sertraline as measured by [11C]DASB and positron emission tomography. Biol Psychiatry 59:821–8.

36.

Parsey

Ojha

Ogden

Erlandsson

Kumar

Landgrebe

Van Heertum

Mann

(2006b) Metabolite considerations in the in vivo quantification of serotonin transporters using ¹¹C-DASB and PET in humans. J Nucl Med 47:1796–802.

37.

Ranicar

Williams

Schnorr

Clark

Rhodes

Bloomfield

Jones

(1991) The on-line monitoring of continuously withdrawn arterial blood during PET studies using a single BGO/photomultiplier assembly and non-stick tubing. Med Prog Technol 17:259–64.

38.

Rochat

Baumann

Audus

(1999) Transport mechanisms for the antidepressant Citalopram in brain microvessel endothelium. Brain Res 831:229–36.

39.

Slifstein

Lamelle

(2000) Effects of statistical noise on graphic analysis of PET neuroreceptor studies. J Nucl Med 41:2083–8.

40.

Smith

Dhawan

Gunduz

Carbon

Kirshner

Larson

Chaly

Belakhleff

Kramer

Greenwald

Kane

Laghrissi-Thode

Pollock

Eidelber

(2002) Serotonin modulation of cerebral glucose metabolism measured with positron emission tomography (PET) in human subjects. Synapse 45:105–12.

41.

Spinks

Jones

Bloomfield

Bailey

Miller

Hogg

Jones

Vaigneur

Reed

Young

Newport

Moyers

Casey

Nutt

(2000) Physical characteristics of the ECAT EXACT3D positron tomograph. Phys Med Biol 45:2601–18.

42.

Spinks

Miller

Bailey

Bloomfield

Livieratos

Jones

(1998) The effect of activity outside the direct field of view in a 3D-only whole-body positron tomograph. Phys Med Biol 43:895–904.

43.

Suehiro

Scheffel

Ravert

Dannais

Wagner

Jr (1993) [11C](+)McN5652 as a radiotracer for imaging serotonin uptake sites with PET. Life Sci 53:883–92.

44.

Szabo

McCann

Wilson

Scheffel

Owonikoko

Mathews

Ravert

Hilton

Dannals

Ricaurte

(2002) Comparison of (+)-11C-McN5652 and ¹¹C-DASB as serotonin transporter radioligands under various experimental conditions. J Nucl Med 43:678–92.

45.

Tadokoro

Jones

AKP

Cunningham

Sashin

Grootoonk

Ashburner

Jones

(1993) Parametric images of ¹¹C-diprenorphine binding using spectral analysis of dynamic PET images acquired in 3D. In: Quantification of Brain Function: Tracer Kinetics and Image Analysis in Brain PET ( Uemura

Jones

Lassen

Kanno

, eds), New York: Excerpta Medica, 289–94.

46.

Tipre

Fujita

Ichise

Vines

Innis

(2004) Radiation dosimetry estimates for the PET serotonin transporter probe ¹¹C-DASB determined from whole-body imaging in non-human primates. Nucl Med Commun 25:81–6.

47.

Watson

Newport

Casey

(1996) A single scatter simulation technique for scatter correction in three-dimensional PET. In: Three-Dimensional Image Reconstruction in Badiology and Nuclear Medicine ( Grangeat

Amans

J-L

, eds), Kluwer: Dordrecht, 255–68.

48.

Wilson

Ginovart

Schmidt

Meyer

Threlkeld

Houle

(2000) 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. J Med Chem 43:3103–10.