Quantification of [11C]Raclopride PET studies
Raclopride (RP) is a dopamine D2 receptor antagonist which, when labeled with 11C (Farde et al., 1985), is suitable and widely used for quantitative imaging of dopamine D2 receptors (D2R) in the striatum with PET (Laruelle 2000). [11C]Raclopride (RP) uptake is sensitive to competition from endogenous dopamine (DA), and can be used in imaging of the changes in synaptic dopamine concentration in reproducible manner (Koepp et al., 1998; Wang et al., 1999). When the DA concentration has returned to baseline levels, the agonist-induced D2-receptor internalization can be measured (Weinstein et al., 2017).
Caffeine increases striatal dopamine D2 receptor availability (Volkow et al., 2015), which should be taken into consideration in countries like Finland and Sweden where coffee consumption is very high.
[11C]Raclopride has a long time been one of the most widely used PET tracers, and even worked as a model tracer in development and validation of new analysis methods. Therefore, this is is not a comprehensive list of analysis methods for [11C]raclopride, but merely a list of models of practical use in Turku PET Centre.
Models with plasma input
Lammertsma et al. (1996) compared one- and two-tissue compartment models (1TCM and 2TCM) with arterial plasma input function, and found that two tissue compartments were required to achieve decent fit, also in cerebellum, but BPND estimates from two-tissue compartment model had too high standard errors. The compartment model fit to the whole brain curve precede the regional fits to determine a common plasma delay time. Compartment model includes the blood volume. Binding potential was calculated from VT values of striatum and cerebellum.
Multiple time graphic analysis (MTGA) for reversible tracers (Logan plot) with metabolite corrected plasma input has been shown to provide reproducible VT and distribution volume ratio (DVR) maps (Wang et al., 1999). However, graphical analysis is known to produce biased estimates of VT and BPND (Slifstein and Laruelle, 2000), although the bias may be effectively canceled out of receptor occupancy estimates.
Models with reference tissue input
The cerebellum is nearly devoid of D2 and D3 receptors, and specific binding of RP is thought to be negligible in the cerebellum. Therefore, cerebellum is commonly used as reference tissue in RP PET studies.
Reference tissue compartment model
Simplified reference tissue model (SRTM) has since its introduction (Lammertsma and Hume, 1996) been the most popular method of analysis of RP PET data. The parameters of simplified model (R1, k2 and BPND) can be solved not only using traditional nonlinear fitting but also using linearized methods (leading to negative bias in BPND in case of noisy data), or with basis function method (Gunn et al., 1997), which enable the calculation of BPND maps. Choice of weights is important with the SRTM (Thiele & Buchert, 2008; Normandin et al., 2012). Long-term test-retest reliability studies have shown good reproducibility, even in thalamus (Alakurtti et al., 2015).
Endogenous dopamine release reduces RP binding, and the effect can be quantitated using SRTM extended with time-dependent activation function (Alpert et al., 2003; Bäckman et al., 2017).
Multiple time graphic analysis (MTGA) for reversible tracers (Logan plot) can be applied to RP PET data with cerebellum curve instead of metabolite corrected plasma input to produce DVR estimates (BPND=DVR-1). However, graphical analysis is known to produce biased estimates with noisy data (Slifstein and Laruelle, 2000).
In the classical method described by Farde et al. (1989), k3/k4 is estimated as Bound/Free (B/F) ratio at “transient equilibrium state”, at the peak time of striatum - cerebellum curve. Because the assumption of similar free tracer concentration in striatum and reference tissue (cerebellum) is not true, this method leads to biased binding estimates (Ito et al., 1998), although the effect on occupancy estimates is minimal (Olssson and Farde, 2001).
Since the peak time of bound curve is difficult to determine, a certain time range is often used. Nyberg et al. (1996) studied the test-retest reliability of putamen-to-cerebellum ratio at 9-45 min, and this method has since been used for example by Nordström et al. (1998).
In clinical use, the simplified reference tissue model (SRTM) with cerebellum as the reference region is recommended.
RP PET studies that are conducted using bolus+infusion (BI) protocol can be analyzed simply by calculating tissue-to-reference tissue ratio after equilibrium has been reached. The time range where tissue curves are on a constant level must be determined visually by plotting the regional time-activity concentration curves. Thereafter, ratio during that time range can be calculated either regionally or to produce a ratio image.
To analyze bolus+infusion studies using ntPET or other kinetic methods, please contact Jarkko Johansson or Jouni Tuisku.
Preparing the plasma input for modelling
A dedicated program for RP for corrections of plasma and blood data is not available, because [11C]raclopride studies do not usually include blood sampling. However, the low-level software can be used to prepare the input data for modelling.
In RP studies the plasma parent fractions can be fitted using Hill-type function.
Vascular volume fraction
Time delay corrected blood curve can be used to correct the PET image or regional TAC data for the impact of blood activity in tissue vasculature, using either predetermined VB or by fitting VB as an additional compartmental model parameter.
At present, strong filtering before modelling may be appropriate to reduce noise and noise-induced bias.
Estimate a VT image using dynamic PET image, previously
corrected plasma TAC, and
-2, for example:
imglhdv -2 ra1234apc_delay.kbq ra1234dy1.v ra1234dv.v
To retrieve BPND images with plasma input, first calculate the mean VT inside cerebellum ROI from the VT image. Then, divide the VT image with this cerebellum VT value, using imgcalc, for example:
imgcalc ra1234dv.v : 1.325 ra1234dvr.v
and then subtract 1.0 from it, for example:
imgcalc ra1234dvr.v - 1 ra1234bp.v
Estimate regional VT, or DVR using cerebellum
as reference region, using
Alakurtti K, Johansson JJ, Joutsa J, Laine M, Bäckman L, Nyberg L, Rinne JO. Long-term test-retest reliability of striatal and extrastriatal dopamine D2/3 receptor binding: study with [11C]raclopride and high-resolution PET. J Cereb Blood Flow Metab. 2015; 35: 1199-1205.
Alpert NM, Badgaiyan RD, Livni E, Fischman AJ. A novel method for noninvasive detection of neuromodulatory changes in specific neurotransmitter systems. Neuroimage 2003; 19: 1049–1060.
Black KJ, Piccirillo ML, Koller JM, Hseih T, Wang L, Mintun MA. Levodopa effects on [11C]raclopride binding in the resting human brain [v1; ref status: awaiting peer review, http://f1000r.es/4oe] F1000Research 2015; 4:23 (doi: 10.12688/f1000research.5672.1).
Bäckman L, Waris O, Johansson J, Andersson M, Rinne JO, Alakurtti K, Soveri A, Laine M, Nyberg L. Increased dopamine release after working-memory updating training: neurochemical correlates of transfer. Sci Rep. 2017; 7(1): 7160. DOI: 10.1038/s41598-017-07577-y
Farde L, Ehrin E, Eriksson L, Greitz T, Hall H, Hedström C-G, Litton J-E, Sedvall G. Substituted benzamides as ligands for visualization of dopamine receptor binding in the human brain by positron emission tomography. Proc Natl Acad Sci USA 1985; 82: 3863-3867.
Farde L, Eriksson L, Blomquist G, Halldin C. Kinetic analysis of central [11C]raclopride binding to D2-dopamine receptors studied by PET - a comparison to the equilibrium analysis. J Cereb Blood Flow Metab. 1989; 9(5): 696-708.
Farde L, Wiesel F-A, Jansson P, Uppfeldt G, G, Wahlen A, Sedvall G. An open label trial of raclopride in acute schizophrenia. Confirmation of D2-dopamine receptor occupancy by PET. Psychopharmacology 1988; 94: 1-7.
Gunn RN, Lammertsma AA, Hume SP, Cunningham VJ. Parametric imaging of ligand-receptor binding in PET using a simplified reference region model. Neuroimage 1997; 6:279-287.
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.
Kodaka F, Ito H, Kimura Y, Fujie S, Takano H, Fujiwara H, Sasaki T, Nakayama K, Halldin C, Farde L, Suhara T. Test-retest reproducibility of dopamine D2/3 receptor binding in human brain measured by PET with [11C]MNPA and [11C]raclopride. Eur J Nucl Med Mol Imaging 2013; 40(4): 574-579.
Koepp MJ, Gunn RN, Lawrence AD, Cunningham VJ, Dagher A, Jones T, Brooks DJ, Bench CJ, Grasby PM. Evidence for striatal dopamine release during a video game. Nature 1998; 393: 266-268.
Lammertsma AA, Bench CJ, Hume SP, Osman S, Gunn K, Brooks DJ, Frackowiak RSJ. Comparison of methods for analysis of clinical [11C]Raclopride studies. J Cereb Blood Flow Metab. 1996; 16: 42-52.
Lammertsma AA, Hume SP. Simplified reference tissue model for PET receptor studies. Neuroimage 1996; 4:153-158.
Laruelle M. Imaging synaptic neurotransmission with in vivo binding competition techniques: a critical review. J Cereb Blood Flow Metab. 2000; 20: 423-451.
Nordström A-L, Olsson H, Halldin C. A PET study of D2 dopamine receptor density at different phases of the menstrual cycle. Psychiatry Res. 1998; 83(1): 1-6.
Normandin MD, Koeppe RA, Morris ED. Selection of weighting factors for quantification of PET radioligand binding using simplified reference tissue models with noisy input functions. Phys Med Biol. 2012; 57: 609-629.
Nyberg S, Farde L, Halldin C. Test-retest reliability of central [11C]raclopride binding at high D2 receptor occupancy. A PET study in haloperidol-treated patients. Psychiatry Res. 1996; 67: 163-171.
Olsson H, Farde L. Potentials and pitfalls using high affinity radioligands in PET and SPET determinations on regional drug induced D2 receptor occupancy - a simulation study based on experimental data. Neuroimage 2001; 14(4): 936-945.
Slifstein M, Laruelle M. Effects of statistical noise on graphic analysis of PET neuroreceptor studies. J Nucl Med. 2000; 41: 2083-2088.
Thiele F, Buchert R. Evaluation of non-uniform weighting in non-linear regression for pharmacokinetic neuroreceptor modelling. Nucl Med Commun. 2008; 29: 179-188.
Volkow ND, Wang G-J, Logan J, Alexoff D, Fowler JS, Thanos PK, Wong C, Casado V, Ferre S, Tomasi D. Caffeine increases striatal dopamine D2/D3 receptor availability in the human brain. Transl Psychiatry 2015; 5: e549.
Wang G-J, Volkow ND, Fowler JS, Logan J, Pappas NR, Wong CT, Hitzemann RJ, Netusil N. Reproducibility of repeated measures of endogenous dopamine competition with [11C]raclopride in the human brain in response to methylphenidate. J Nucl Med. 1999; 40: 1285-1291.
Weinstein JJ, van de Giessen E, Rosengard RJ, Xu X, Ojeil N, Brucato G, Gil RB, Kegeles LS, Laruelle M, Slifstein M, Abi-Dargham A. PET imaging of dopamine-D2 receptor internalization in schizophrenia. Mol Psychiatry 2017 (in press).
Created at: 2007-05-23
Updated at: 2017-08-22
Written by: Vesa Oikonen