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[ 11 C](R)-PK11195 is a marker of activated microglia, which can be used to measure inflammation in neurologic disorders. The purpose of the present study was to define the optimal reference tissue model based on a comparison with a validated plasma input model and using clinical studies and Monte Carlo simulations. Accuracy and reproducibility of reference tissue models were evaluated using Monte Carlo simulations. The effects of noise and variation in specific binding, nonspecific binding and blood volume were evaluated. Dynamic positron emission tomography scans were performed on 13 subjects, and radioactivity in arterial blood was monitored online. In addition, blood samples were taken to generate a metabolite corrected plasma input function. Both a (validated) two-tissue reversible compartment model with K 1 /k 2 fixed to whole cortex and various reference tissue models were fitted to the data. Finally, a simplified reference tissue model (SRTM) corrected for nonspecific binding using plasma input data (SRTM pl_corr ) was investigated. Correlations between reference tissue models (including SRTM pl_corr ) and the plasma input model were calculated. Monte Carlo simulations indicated that low-specific binding results in decreased accuracy and reproducibility. In this respect, the SRTM and SRTM pl_corr performed relatively well. Varying blood volume had no effect on performance. In the clinical evaluation, SRTM pl_corr and SRTM had the highest correlations with the plasma input model (R 2 = 0.82 and 0.78, respectively). SRTM pl_corr is optimal when an arterial plasma input curve is available. Simplified reference tissue model is the best alternative when no plasma input is available. Keywords: microglia; peripheral benzodiazepine receptor; PET (positron emission tomography); PK11195; reference tissue models; tracer kinetic modelling IntroductionCarbon-11 labeled (R)-PK11195 ((R)-1-(2-chlorophenyl)-N-[ 11 C]methyl-N-(1-methylpropyl)-3-isoquinoline carboxamide) is a ligand for the peripheral benzodiazepine receptor. In the brain, this receptor is mainly expressed on activated microglia (Banati et al, 1997). Both [ 11 C](R)-PK11195 and [ 11 C]PK11195 have been used as positron emmision tomography (PET) tracers to study activated microglia in various neurologic disorders. It has been used to study stroke (Ramsay et al, 1992;Pappata et al, 2000;Gerhard et al, 2000Gerhard et al, , 2005a), Alzheimer's disease (Groom et al, 1995; Cagnin et al, 2001a;Versijpt et al, 2003), multiple sclerosis (Banati et al, 2000;Debruyne et al, 2002Debruyne et al, , 2003Versijpt et al, 2005) and various other diseases (Pappata et al, 1991; Banati et al, 1999Banati et al, , 2001Goerres et al, 2001;Cagnin et al, 2001bCagnin et al, , 2004Cicchetti et al, 2002;Gerhard et al, 2003Gerhard et al, , 2004Gerhard et al, , 2005bTurner et al, 2004Turner et al, , 2005Venneti et al, 2004;Henkel et al, 2004;Ouchi et al, 2005). Most studies have used a reference tissue approach to quantify binding, either by applying the simplified reference tissue mod...

(R)-[(11)C]PK11195 ([1-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl]-3-isoquinoline carboxamide) is a ligand for the peripheral benzodiazepine receptor, which, in the brain, is mainly expressed on activated microglia. Using both clinical studies and Monte Carlo simulations, the aim of this study was to determine which tracer kinetic plasma input model best describes (R)-[(11)C]PK11195 kinetics. Dynamic positron emission tomography (PET) scans were performed on 13 subjects while radioactivity in arterial blood was monitored online. Discrete blood samples were taken to generate a metabolite corrected plasma input function. One-tissue, two-tissue irreversible, and two-tissue reversible compartment models, with and without fixing K(1)/k(2) ratio, k(4) or blood volume to whole cortex values, were fitted to the data. The effects of fixing parameters to incorrect values were investigated by varying them over a physiologic range and determining accuracy and reproducibility of binding potential and volume of distribution using Monte Carlo simulations. Clinical data showed that a two-tissue reversible compartment model was optimal for analyzing (R)-[(11)C]PK11195 PET brain studies. Simulations showed that fixing the K(1)/k(2) ratio of this model provided the optimal trade-off between accuracy and reproducibility. It was concluded that a two-tissue reversible compartment model with K(1)/k(2) fixed to whole cortex value is optimal for analyzing (R)-[(11)C]PK11195 PET brain studies.

Positron emission tomography (PET) pharmacokinetic analysis involves fitting of measured PET data to a PET pharmacokinetic model. The fitted parameters may, however, suffer from bias or be unrealistic, especially in the case of noisy data. There are many optimization algorithms, each having different characteristics. The purpose of the present study was to evaluate (1) the performance of different optimization algorithms and (2) the effects of using incorrect weighting factors during optimization in terms of both accuracy and reproducibility of fitted PET pharmacokinetic parameters. In this study, the performance of commonly used optimization algorithms (i.e. interior-reflective Newton methods) and a simulated annealing (SA) method was evaluated. This SA algorithm, known as basin hopping, was modified for the present application. In addition, optimization was performed using various weighting factors. Algorithms and effects of using incorrect weighting factors were studied using both simulated and clinical time-activity curves (TACs). Input data, taken from [(15)O]H(2)O, [(11)C]flumazenil and [(11)C](R)-PK11195 studies, were used to simulate time-activity curves at various variance levels (0-15% COV). Clinical evaluation was based on studies with the same three tracers. SA was able to produce accurate results without the need for selecting appropriate starting values for (kinetic) parameters, in contrast to the interior-reflective Newton method. The latter gave biased results unless it was modified to allow for a range of starting values for the different parameters. For patient studies, where large variability is expected, both SA and the extended Newton method provided accurate results. Simulations and clinical assessment showed similar results for the evaluation of different weighting models in that small to intermediate mismatches between data variance and weighting factors did not significantly affect the outcome of the fits. Large errors were observed only when the mismatch between weighting model and data variance was large. It is concluded that selection of specific optimization algorithms and weighting factors can have a large effect on the accuracy and precision of PET pharmacokinetic analysis. Apart from carefully selecting appropriate algorithms and variance models, further improvement in accuracy might be obtained by using noise reducing strategies, such as wavelet filtering, provided that these methods do not introduce significant bias.

Inflammation in Alzheimer's disease (AD) may be assessed using (R)-[11 C]PK11195 and positron emission tomography. Data can be analyzed using the simplified reference tissue model, provided a suitable reference region is available. This study evaluates various reference regions for analyzing (R)-[11 C]PK11195 scans in patients with mild cognitive impairment (MCI) and probable AD. Healthy subjects (n = 10, 30610 years and n = 10, 7066 years) and patients with MCI (n = 10, 7466 years) and probable AD (n = 9, 7166 years) were included. Subjects underwent a dynamic three-dimensional (R)-[11 C]PK11195 scan including arterial sampling. Gray matter, white matter, total cerebellum and cerebrum, and cluster analysis were evaluated as reference regions. Both plasma input binding potentials of these reference regions (BP PLASMA ) and corresponding reference region input binding potentials of a target region (BP SRTM ) were evaluated. Simulations were performed to assess cluster analysis performance at 5% to 15% coefficient of variation noise levels. Reasonable correlations for BP PLASMA (R 2 = 0.52 to 0.94) and BP SRTM (R 2 = 0.59 to 0.76) were observed between results using anatomic regions and cluster analysis. For cerebellum white matter, cerebrum white matter, and total cerebrum a considerable number of unrealistic BP SRTM values were observed. Cluster analysis did not extract a valid reference region in 10% of the scans. Simulations showed that potentially cluster analysis suffers from negative bias in BP PLASMA . Most anatomic regions outperformed cluster analysis in terms of absence of both scan rejection and bias. Total cerebellum is the optimal reference region in this patient category.