The distribution volume ratio (DVR), which is a linear function of receptor availability, is widely used as a model parameter in imaging studies. The DVR corresponds to the ratio of the DV of a receptor-containing region to a nonreceptor region and generally requires the measurement of an arterial input function. Here we propose a graphical method for determining the DVR that does not require blood sampling. This method uses data from a nonreceptor region with an average tissue-to-plasma efflux constant k2 to approximate the plasma integral. Data from positron emission tomography studies with [11C]raclopride (n = 20) and [11C]d-threo-methylphenidate ([11C]dMP) (n = 8) in which plasma data were taken and used to compare results from two graphical methods, one that uses plasma data and one that does not. k2 was 0.163 and 0.051 min-1 for [11C]raclopride and [11C]dMP, respectively. Results from both methods were very similar, and the average percentage difference between the methods was -0.11% for [11C]raclopride and 0.46% for [11C]dMP for DVR of basal ganglia (BG) to cerebellum (CB). Good agreement between the two methods was also achieved for DVR images created by both methods. This technique provides an alternative method of analysis not requiring blood sampling that gives equivalent results for the two ligands studied. It requires initial studies with blood sampling to determine the average kinetic constant and to test applicability. In some cases, it may be possible to neglect the k2 term if the BG/CB ratio becomes reasonably constant for a sufficiently long period of time over the course of the experiment.

Dopamine's role in inhibitory control is well recognized and its disruption may contribute to behavioral disorders of discontrol such as obesity. However, the mechanism by which impaired dopamine neurotransmission interferes with inhibitory control is poorly understood. We had previously documented a reduction in dopamine D2 receptors in morbidly obese subjects. To assess if the reductions in dopamine D2 receptors were associated with activity in prefrontal brain regions implicated in inhibitory control we assessed the relationship between dopamine D2 receptor availability in striatum with brain glucose metabolism (marker of brain function) in ten morbidly obese subjects (BMI>40 kg/m 2 ) and compared it to that in twelve non-obese controls. PET was used with [ 11 C]raclopride to assess D2 receptors and with [ 18 F] FDG to assess regional brain glucose metabolism. In obese subjects striatal D2 receptor availability was lower than controls and was positively correlated with metabolism in dorsolateral prefrontal, medial orbitofrontal, anterior cingulate gyrus and somatosensory cortices. In controls correlations with prefrontal metabolism were not significant but comparisons with those in obese subjects were not significant, which does not permit to ascribe the associations as unique to obesity. The associations between striatal D2 receptors and prefrontal metabolism in obese subjects suggest that decreases in striatal D2 receptors could contribute to overeating via their modulation of striatal prefrontal pathways, which participate in inhibitory control and salience attribution. The association between striatal D2 receptors and metabolism in somatosensory cortices (regions that process palatability) could underlie one of the mechanisms through which dopamine regulates the reinforcing properties of food. KeywordsOrbitofrontal cortex; Cingulate gyrus; Dorsolateral prefrontal; Dopamine transporters; Raclopride, PET The increase in obesity and associated metabolic diseases seen over the past decade has raised concern that if not controlled this may become the number one preventable public health threat for the 21st century (Sturm, 2002 (Berthoud, 2007). The extent to which individuals differ in their ability to inhibit these responses and control how much they eat is likely to modulate their risk for overeating in our current food rich environments (Berthoud, 2007).We had shown that in healthy individuals D2 receptor availability in the striatum modulated eating behavioral patterns (Volkow et al., 2003). Specifically the tendency to eat when exposed to negative emotions was negatively correlated with D2 receptor availability (the lower the D2 receptors the higher the likelihood that an individual would eat if emotionally stressed). In addition, in a different study, we showed that morbidly obese subjects (BMI>40) had lower than normal D2 receptor availability and these reductions were proportional to their BMI (Wang et al., 2001). These findings led us to postulate that low D2 receptor availability could put an...

The massive health problem associated with cigarette smoking is exacerbated by the addictive properties of tobacco smoke and the limited success of current approaches to cessation of smoking. Yet little is known about the neuropharmacological actions of cigarette smoke that contribute to smoking behaviour, or why smoking is so prevalent in psychiatric disorders and is associated with a decreased risk of Parkinson's disease. Here we report that brains of living smokers show a 40% decrease in the level of monoamine oxidase B (MAO B; EC 1.4.3.4) relative to non-smokers or former smokers. MAO B is involved in the breakdown of dopamine, a neurotransmitter implicated in reinforcing and motivating behaviours as well as movement. MAO B inhibition is therefore associated with enhanced activity of dopamine, as well as with decreased production of hydrogen peroxide, a source of reactive oxygen species. We propose that reduction of MAO B activity may synergize with nicotine to produce the diverse behavioural and epidemiological effects of smoking.

Several studies have documented a strong association between smoking and depression. Because cigarette smoke has been reported to inhibit monoamine oxidase (MAO) A in vitro and in animals and because MAO A inhibitors are effective antidepressants, we tested the hypothesis that MAO A would be reduced in the brain of cigarette smokers. We compared brain MAO A in 15 nonsmokers and 16 current smokers with [ 11 C]clorgyline and positron emission tomography (PET). Four of the nonsmokers were also treated with the antidepressant MAO inhibitor drug, tranylcypromine (10 mg͞day for 3 days) after the baseline PET scan and then rescanned to assess the sensitivity of [ 11 C]clorgyline binding to MAO inhibition. MAO A levels were quantified by using the model term k 3 which is a function of brain MAO A concentration. Smokers had significantly lower brain MAO A than nonsmokers in all brain regions examined (average reduction, 28%). The mean k 3 values for the whole brain were 0.18 ؎ 0.04 and 0.13 ؎ 0.03 cc brain (ml plasma )؊1 min ؊1 for nonsmokers and smokers, respectively; P < 0.0003). Tranylcypromine treatment reduced k 3 by an average of 58% for the different brain regions. Our results show that tobacco smoke exposure is associated with a marked reduction in brain MAO A, and this reduction is about half of that produced by a brief treatment with tranylcypromine. This suggests that MAO A inhibition needs to be considered as a potential contributing variable in the high rate of smoking in depression and in the development of more effective strategies for smoking cessation.There are approximately 1 billion cigarette smokers in the world today and about 3 million die each year from smokingassociated illnesses (1). This places a sense of urgency on understanding the neuropharmacological properties of tobacco smoke and their relationship to smoking behavior and epidemiology. For example, it is not understood why smoking is more prevalent in depression and why smoking cessation is less successful in depressed patients (2, 3). Though it is unlikely that any one factor accounts for the strong association between smoking and depression, it is possible that tobacco smoke may have antidepressant properties. One of the molecular targets proposed to link smoking and depression is monoamine oxidase (MAO) (4, 5), an enzyme which was first associated with mood over 40 years ago when it was discovered that MAO inhibitors had antidepressant properties (6, 7).MAO exists in two subtypes (MAO A and B) that are different gene products (8, 9). In the brain, MAO A oxidizes serotonin and norepinephrine and is found primarily in catecholaminergic neurons, whereas MAO B oxidizes benzylamine and phenethylamine and is localized in serotonergic neurons and in glial cells (10). Both forms oxidize dopamine (11). The antidepressant effects of the nonselective MAO inhibitors are generally attributed to the inhibition of MAO A (12).We recently reported that smokers have reduced brain MAO B relative to nonsmokers and former smokers (13).Others have fo...

The higher-than-normal D(2) receptor availability in nonalcoholic members of alcoholic families supports the hypothesis that high levels of D(2) receptors may protect against alcoholism. The significant associations between D(2) receptors and metabolism in frontal regions involved with emotional reactivity and executive control suggest that high levels of D(2) receptors could protect against alcoholism by regulating circuits involved in inhibiting behavioral responses and in controlling emotions.

Moves to legalize marijuana highlight the urgency to investigate effects of chronic marijuana in the human brain. Here, we challenged 48 participants (24 controls and 24 marijuana abusers) with methylphenidate (MP), a drug that elevates extracellular dopamine (DA) as a surrogate for probing the reactivity of the brain to DA stimulation. We compared the subjective, cardiovascular, and brain DA responses (measured with PET and [ 11 C]raclopride) to MP between controls and marijuana abusers. Although baseline (placebo) measures of striatal DA D2 receptor availability did not differ between groups, the marijuana abusers showed markedly blunted responses when challenged with MP. Specifically, compared with controls, marijuana abusers had significantly attenuated behavioral ("self-reports" for high, drug effects, anxiety, and restlessness), cardiovascular (pulse rate and diastolic blood pressure), and brain DA [reduced decreases in distribution volumes (DVs) of [ 11 C]raclopride, although normal reductions in striatal nondisplaceable binding potential (BP ND )] responses to MP. In ventral striatum (key brain reward region), MP-induced reductions in DVs and BP ND (reflecting DA increases) were inversely correlated with scores of negative emotionality, which were significantly higher for marijuana abusers than controls. In marijuana abusers, DA responses in ventral striatum were also inversely correlated with addiction severity and craving. The attenuated responses to MP, including reduced decreases in striatal DVs, are consistent with decreased brain reactivity to the DA stimulation in marijuana abusers that might contribute to their negative emotionality (increased stress reactivity and irritability) and addictive behaviors.nucleus accumbens | amotivation | cannabinoid 1 receptors | brain imaging | midbrain D espite the high prevalence of marijuana consumption, the effects of marijuana abuse in the human brain are not well understood. Marijuana, like other drugs of abuse, stimulates brain dopamine (DA) signaling in the nucleus accumbens (1, 2), which is a mechanism believed to underlie the rewarding effects of drugs (3-5) and to trigger the neuroadaptations that result in addiction (reviewed in ref. 6). Indeed, in humans, imaging studies have shown that drugs of abuse increase DA release in striatum (including the nucleus accumbens), and these increases have been associated with the subjective experience of reward (7-9). However, for marijuana, the results have been inconsistent: One study reported striatal DA increases during intoxication (10); two studies showed no effects (11, 12); and one study reported DA increases in individuals with a psychotic disorder and in their relatives, but not in controls (13). Imaging studies of the brain DA system in marijuana abusers have also shown different findings from those reported for other types of substance abusers. Specifically, substance abusers (cocaine, methamphetamine, alcohol, heroin, and nicotine), but not marijuana abusers (14-16), show reduced baseline availability ...

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The graphical analysis method, which transforms multiple time measurements of plasma and tissue uptake data into a linear plot, is a useful tool for rapidly obtaining information about the binding of radioligands used in PET studies. The strength of the method is that it does not require a particular model structure. However, a bias is introduced in the case of noisy data resulting in the underestimation of the distribution volume (DV), the slope obtained from the graphical method. To remove the bias, a modification of the method developed by Feng et al. (1993), the generalized linear least squares (GLLS) method, which provides unbiased estimates for compartment models was used. The one compartment GLLS method has a relatively simple form, which was used to estimate the DV directly and as a smoothing technique for more general classes of model structures. In the latter case, the GLLS method was applied to the data in two parts, that is, one set of parameters was determined for times 0 to T1 and a second set from T1 to the end time. The curve generated from these two sets of parameters then was used as input to the graphical method. This has been tested using simulations of data similar to that of the PET ligand [11C]-d-threo-methylphenidate (MP, DV = 35 mL/mL) and 11C raclopride (RAC, DV = 1.92 mL/mL) and compared with two examples from image data with the same tracers. The noise model was based on counting statistics through the half-life of the isotope and the scanning time. Five hundred data sets at each noise level were analyzed. Results (DV) for the graphical analysis (DV(G)), the nonlinear least squares (NLS) method (DV(NLS)), the one-tissue compartment GLLS method (DV(F)), and the two part GLLS followed by graphical analysis (DV(FG)) were compared. DV(FG) was found to increase somewhat with increasing noise and in some data sets at high noise levels no estimate could be obtained. However, at intermediate levels it provided a good estimation of the true DV. This method was extended to use a reference tissue in place of the input function to generate the distribution volume ratio (DVR) to the reference region. A linearized form of the simplified reference tissue method of Lammertsma and Hume (1996) was used. The DVR generated directly from the model (DVR(FL)) was compared with DVR(FG) (determined from a "smoothed" uptake curve as for DV(FG)) using the graphical method.