Kinetic Evaluation of [11C]Dihydrotetrabenazine by Dynamic PET

Department of Internal Medicine, University of Michigan, Ann Arbor, USA.
Journal of Cerebral Blood Flow & Metabolism (Impact Factor: 5.41). 12/1996; 16(6):1288-99. DOI: 10.1097/00004647-199611000-00025
Source: PubMed


(+)-alpha-[11C]Dihydrotetrabenazine (DTBZ) binds to the vesicular monoamine transporter (VMAT2) located in presynaptic vesicles. The purpose of this work was to evaluate various model configurations for analysis of [11C]DTBZ with the aim of providing the optimal measure of monoamine vesicular transporter density obtainable from a single dynamic PET study. PET studies on seven young normal volunteer subjects, ages 20-35, were performed following i.v. injection of 666 +/- 37 MBq (18 +/- 1 mCi) of (+)-alpha-[11C]DTBZ. Dynamic acquisition consisted of a 15-frame sequence over 1 h. Analysis methods included both creation of pixel-by-pixel functional images of transport (K1) and binding (DVtot) and nonlinear least-squares analysis of volume-of-interest data. Pixel-by-pixel calculations were performed for both two-compartment weighted integral calculations and slope-intercept estimations from Logan plots. Nonlinear least-squares analysis was performed applying model configurations with both two-compartments, estimating K1 and DVtot and three compartments, estimating K1-k4. For the more complex configuration, we examined the stability of various binding-related parameters including k3 (konBmax'), k3/k4 (Bmax'/Kd), DVsp[(K1/k2)(k3/k4)], and DVtot [K1/k2(1 + k3/k4)]. The three-compartment model provided significantly improved goodness-of-fit compared to the two-compartment model, yet did not increase the uncertainty in the estimate of the DVtot. Without constraining parameters in the three-compartment model fits, DVtot was found to provide a more stable estimate of binding density than either k3, k3/k4, or DVsp. The two-compartment least-squares analysis yielded approximately 10% underestimations of the total distribution. However, this bias was found to be very consistent from region to region as well as across subjects as indicated by the correlation between two- and three-compartment DVtot estimates of 0.997. We conclude that (+)-alpha-[11C]DTBZ and PET can provide excellent measures of VMAT2 density in the human brain.

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    • "The outcome measure derived from this analysis is BP ND , which refers to the specific to non-specific partition coefficient equal to B max /K D where B max is unoccupied VMAT2 density, and 1/K D is the in vivo affinity of 11 C-DTBZ. The simplified reference tissue model has been shown to be an appropriate model for quantifying DTBZ data in humans without arterial input function (Koeppe et al., 1996; Chan et al., 1999). To address the possibility of volume loss in the patient groups potentially affecting the analysis, partial volume effect correction on time activity curve data was implemented using the Rousset algorithm (Rousset et al., 1998). "
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    ABSTRACT: The ability to dynamically use various aspects of cognition is essential to daily function, and reliant on dopaminergic transmission in cortico-striatal circuitry. Our aim was to investigate both striatal and cortical dopaminergic changes in patients with Parkinson's disease with mild cognitive impairment, who represent a vulnerable group for the development of dementia. We hypothesized severe striatal dopamine denervation in the associative (i.e. cognitive) region and cortical D2 receptor abnormalities in the salience and executive networks in Parkinson's disease with mild cognitive impairment compared with cognitively normal patients with Parkinson's disease and healthy control subjects. We used positron emission tomography imaging with dopaminergic ligands (11)C-dihydrotetrabenazine, to investigate striatal dopamine neuron integrity in the associative subdivision and (11)C-FLB 457, to investigate cortical D2 receptor availability in patients with Parkinson's disease (55-80 years of age) with mild cognitive impairment (n = 11), cognitively normal patients with Parkinson's disease (n = 11) and age-matched healthy control subjects (n = 14). Subjects were administered a neuropsychological test battery to assess cognitive status and determine the relationship between dopaminergic changes and cognitive performance. We found that patients with mild cognitive impairment had severe striatal dopamine depletion in the associative (i.e. cognitive) subdivision as well as reduced D2 receptor availability in the bilateral insula, a key cognitive hub, compared to cognitively normal patients and healthy subjects after controlling for age, disease severity and daily dopaminergic medication intake. Associative striatal dopamine depletion was predictive of D2 receptor loss in the insula of patients with Parkinson's disease with mild cognitive impairment, demonstrating interrelated striatal and cortical changes. Insular D2 levels also predicted executive abilities in these patients as measured using a composite executive z-score obtained from neuropsychological testing. Furthermore we assessed cortical thickness to ensure that D2 receptor changes were not confounded by brain atrophy. There was no difference between groups in cortical thickness in the insula, or any other cortical region of interest. These findings suggest that striatal dopamine denervation combined with insular D2 receptor loss underlie mild cognitive impairment in Parkinson's disease and in particular decline in executive function. Furthermore, these findings suggest a crucial and direct role for dopaminergic modulation in the insula in facilitating cognitive function.
    Full-text · Article · Dec 2013 · Brain
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    • "A few PET ligands have been successfully validated in humans to measure VMAT2 density in vivo. Already quite early, [ 11 C]DTBZ was evaluated by Koeppe et al. (1996) and is still in use today (e.g., Boileau et al. 2010). Another [ 11 C] tetrabenazine (see Canney et al. 1995, for early evaluation of tetrabenazines) that has already been tested in humans over a decade ago is the carbon-labeled methoxytetrabenazine [ 11 C]MTBZ (Vander Borght et al. 1995), but which has, to our knowledge, not been used recently to measure VMAT2 in vivo. "
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    Full-text · Article · Sep 2011 · Amino Acids
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    • "However, in many cases it is desirable to perform parametric analysis on pixelwise data, which have much higher noise levels than ROI data. Although parametric imaging has been applied effectively using both linear (Blomqvist, 1984; Blomqvist et al., 1990; Carson et al., 1986; Chen et al., 1998; Feng et al., 1993; Gunn et al., 1997; Koeppe et al., 1996) and nonlinear regression (Herholz, 1987; Huang and Zhou, 1998; Kimura et al., 2002; O'Sullivan, 1994; Zhou et al., 2002c), conventional nonlinear regression is less desirable because it tends to be time consuming and provides parametric images of poor images quality, that is, either too much noise or too much resolution loss if spatial smoothing is applied. To avoid nonlinear regression for SRTM when applying Eq. (2), a basis function method has been developed by sampling discrete values of the nonlinear macroparameter (k 2 /(1ϩBP)) and eliminating the two linear parameters (R 1 and k 2 Ϫ R 1 k 2 /(1 ϩ BP)) by regular linear regression (Gunn et al., 1997; Lawton and Sylvestre, 1971). "
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    ABSTRACT: For the quantitative analysis of ligand-receptor dynamic positron emission tomography (PET) studies, it is often desirable to apply reference tissue methods that eliminate the need for arterial blood sampling. A common technique is to apply a simplified reference tissue model (SRTM). Applications of this method are generally based on an analytical solution of the SRTM equation with parameters estimated by nonlinear regression. In this study, we derive, based on the same assumptions used to derive the SRTM, a new set of operational equations of integral form with parameters directly estimated by conventional weighted linear regression (WLR). In addition, a linear regression with spatial constraint (LRSC) algorithm is developed for parametric imaging to reduce the effects of high noise levels in pixel time activity curves that are typical of PET dynamic data. For comparison, conventional weighted nonlinear regression with the Marquardt algorithm (WNLRM) and nonlinear ridge regression with spatial constraint (NLRRSC) were also implemented using the nonlinear analytical solution of the SRTM equation. In contrast to the other three methods, LRSC reduces the percent root mean square error of the estimated parameters, especially at higher noise levels. For estimation of binding potential (BP), WLR and LRSC show similar variance even at high noise levels, but LRSC yields a smaller bias. Results from human studies demonstrate that LRSC produces high-quality parametric images. The variance of R(1) and k(2) images generated by WLR, WNLRM, and NLRRSC can be decreased 30%-60% by using LRSC. The quality of the BP images generated by WLR and LRSC is visually comparable, and the variance of BP images generated by WNLRM can be reduced 10%-40% by WLR or LRSC. The BP estimates obtained using WLR are 3%-5% lower than those estimated by LRSC. We conclude that the new linear equations yield a reliable, computationally efficient, and robust LRSC algorithm to generate parametric images of ligand-receptor dynamic PET studies.
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