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Abstract: Quantitative PET studies with arterial blood sampling usually require the correction of the measured total plasma activity for the presence of metabolites. In particular, if labelled metabolites are found in the plasma in significant amounts their presence has to be accounted for, because it is the concentration of the parent tracer which is required for data quantification. This is achieved by fitting a Parent Plasma fraction (PPf) model to discrete metabolite measurements. The commonly used method is based on an individual approach, i.e. for each subject the PPf model parameters are estimated from its own metabolite samples, which are, in general, sparse and noisy. This fact can compromise the quality of the reconstructed arterial input functions, and, consequently, affect the quantification of tissue kinetic parameters. In this study, we proposed a Non-Linear Mixed Effect Modelling (NLMEM) approach to describe metabolite kinetics. Since NLMEM has been developed to provide robust parameter estimates in the case of sparse and/or noisy data, it has the potential to be a reliable method for plasma metabolite correction. Three different PET datasets were considered: [11C]-(+)-PHNO (54 scans), [11C]-PIB (22 scans) and [11C]-DASB (30 scans). For each tracer both simulated and measured data were considered and NLMEM performance was compared with that provided by individual analysis. Results showed that NLMEM provided improved estimates of the plasma parent input function over the individual approach when the metabolite data were sparse or contained outliers. [Copyright &y& Elsevier]

Abstract: Neuroimaging studies place great emphasis on not only the estimation but also the standard error estimates of underlying parameters derived from a temporal model. This allows inferences to be made about the signal estimates and resulting conclusions to be drawn about the underlying data. It can often be advantageous to interrogate temporal models after spatial transformation of the data into the wavelet domain. Wavelet bases provide a multiresolution decomposition of the spatial data dimension and an ensuing reduction in spatial correlation. However, widespread acceptance of these wavelet techniques has been hampered by the limited ability to reconstruct both parametric and error estimates into the image domain after analysis of temporal models in the wavelet domain. This paper introduces a derivation and a fast implementation of a method for the calculation of the variance of the parametric images obtained from wavelet filters. The technique is proposed for a class of estimators that have been shown to be useful in neuroimaging studies. The techniques are demonstrated for both functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) data sets. [Copyright &y& Elsevier]

Basis pursuit denoising is a new approach for data-driven estimation of parametric images from dynamic positron emission tomography (PET) data. At present, this kinetic modeling technique does not allow for the estimation of the errors on the parameters. These estimates are useful when performing subsequent statistical analysis, such as, inference across a group of subjects or when applying partial volume correction algorithms. The difficulty with calculating the error estimates is a consequence of using an overcomplete dictionary of kinetic basis functions. In this paper, a bootstrap approach for the estimation of parameter errors from dynamic PET data is presented. This paper shows that the bootstrap can be used successfully to compute parameter errors on a region of interest or parametric image basis. Validation studies evaluate the methods performance on simulated and measured PET data ([11C]Diprenorphine—opiate receptor and [11C]Raclopride—dopamine D2 receptor). The method is presented in the context of PET neuroreceptor binding studies, however, it has general applicability to a wide range of PET/SPET radiotracers in neurology, oncology and cardiology. [Copyright &y& Elsevier]

Abstract: The characterisation of a pharmacokinetic–receptor occupancy (PK-RO) relationship derived from a PET study is typically modelled in a conventional non-linear least squares (NLLS) framework. In the present work, we explore the application of a non-linear mixed effects approach (NLME) and compare this with NLLS estimation (using both naive pooled data and two-stage approaches) in the context of a direct PK-RO relationship described by an Emax model, using simulated data sets. Target and reference tissue time–activity curves were simulated using a two-tissue compartmental model and an arterial plasma input function for a typical PET study (12 subjects in 3 dose groups with 3 scans each). A range of different PET scenarios was considered to evaluate the impact of between-subject variability and reference region availability. The PET outcome measures derived from the simulations were then used to estimate the parameters of the PK-RO model. The performance of the two approaches was compared in terms of parameters estimates (square mean error SME, root mean square error RMSE) and prediction of the exposure–occupancy relationship. In general, both NLME and NLLS estimation methods provided unbiassed and precise population estimates for the Emax model parameters, although a slight bias was observed for the individual-NLLS method due to a few outliers. The increased value of NLME over NLLS was most notable in the estimation of the between-subject variability (BSV), especially in the case of a more complex PK-RO model when no reference region was available (maximum SME and RMSE values related to BSV of EC 50 of 27.6% and 86.5% from NLME versus 264.6% and 689.5% from NLLS). Overall, the NLME approach provided a more robust estimation and produced less-biassed estimates of the population means and variances than either the NLLS approach for the simulations considered. [Copyright &y& Elsevier]

• Novel reconstruction algorithm combining TOF PET and MR information. • TOF PET reconstruction of acquired PET data. • Modelling and simulation of the GE Signa PET-MR scanner using STIR library. This work demonstrates how computational and physical modelling of the positron emission tomography (PET) image acquisition process for a state-of-the-art integrated PET and magnetic resonance imaging (PET-MR) system can produce images comparable to the manufacturer. The GE SIGNA PET/MR scanner is manufactured by General Electric and has time-of-flight (TOF) capabilities of about 390 ps. All software development took place in the Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) library, which is a widely used open source software to reconstruct data as exported from emission tomography scanners. The new software developments will be integrated into STIR, providing the opportunity for researchers worldwide to establish and expand their image reconstruction methods. Furthermore, this work is of particular significance as it provides the first validation of TOF PET image reconstruction for real scanner datasets using the STIR library. This paper presents the methodology, analysis, and critical issues encountered in implementing an independent reconstruction software package. Acquired PET data were processed via several appropriate algorithms which are necessary to produce an accurate and precise quantitative image. This included mathematical, physical and anatomical modelling of the patient and simulation of various aspects of the acquisition. These included modelling of random coincidences using 'singles' rates per crystals, detector efficiencies and geometric effects. Attenuation effects were calculated by using the STIR's attenuation correction model. Modelling all these effects within the system matrix allowed the reconstruction of PET images which demonstrates the metabolic uptake of the administered radiopharmaceutical. These implementations were validated using measured phantom and clinical datasets. The developments are tested using the ordered subset expectation maximisation (OSEM) and the more recently proposed kernelised expectation maximisation (KEM) algorithm which incorporates anatomical information from MR images into PET reconstruction. [ABSTRACT FROM AUTHOR]

Abstract [11C]PBR28 is a positron emission tomography radioligand used to examine the expression of the 18 kDa translocator protein (TSPO). TSPO is located in glial cells and can function as a marker for immune activation. Since TSPO is expressed throughout the brain, no true reference region exists. For this reason, an arterial input function is required for accurate quantification of [11C]PBR28 binding and the most common outcome measure is the total distribution volume (V T). Notably, V T reflects both specific binding and non-displaceable binding. Therefore, estimates of specific binding, such as binding potential (e.g. BP ND) and specific distribution volume (V S) should theoretically be more sensitive to underlying differences in TSPO expression. It is unknown, however, if unbiased and accurate estimates of these outcome measures are obtainable for [11C]PBR28. The Simultaneous Estimation (SIME) method uses time-activity-curves from multiple brain regions with the aim to obtain a brain-wide estimate of the non-displaceable distribution volume (V ND), which can subsequently be used to improve the estimation of BP ND and V S. In this study we evaluated the accuracy of SIME-derived V ND , and the reliability of resulting estimates of specific binding for [11C]PBR28, using a combination of simulation experiments and in vivo studies in healthy humans. The simulation experiments, based on data from 54 unique [11C]PBR28 examinations, showed that V ND values estimated using SIME were both precise and accurate. Data from a pharmacological competition challenge (n = 5) showed that SIME provided V ND values that were on average 19% lower than those obtained using the Lassen plot, but similar to values obtained using the Likelihood-Estimation of Occupancy technique. Test-retest data (n = 11) showed that SIME-derived V S values exhibited good reliability and precision, while larger variability was observed in SIME-derived BP ND values. The results support the use of SIME for quantifying specific binding of [11C]PBR28, and suggest that V S can be used in complement to the conventional outcome measure V T. Additional studies in patient cohorts are warranted. Highlights • [11C]PBR28 is a radioligand for measuring TSPO, a marker for glial cell activation. • The outcome measure V T contains both specific (V S) and non-specific binding (V ND). • The SIME method, that accounts for V ND , was evaluated for [11C]PBR28 data. • Simulations and blocking data show that SIME accurately estimates V ND. • SIME derived V S was reliable and precise, and can be used for higher sensitivity. [ABSTRACT FROM AUTHOR]

Abstract: In dynamic positron emission tomography (PET) neuroimaging studies, where scan durations often exceed 1h, registration of motion-corrupted dynamic PET images is necessary in order to maintain the integrity of the physiological, pharmacological, or biochemical information derived from the tracer kinetic analysis of the scan. In this work, we incorporate a pharmacokinetic model, which is traditionally used to analyse PET data following any registration, into the registration process itself in order to allow for a groupwise registration of the temporal time frames. The new method is shown to achieve smaller registration errors and improved kinetic parameter estimates on validation data sets when compared with image similarity based registration approaches. When applied to measured clinical data from 10 healthy subjects scanned with [11C]-(+)-PHNO (a dopamine D3/D2 receptor tracer), it reduces the intra-class variability on the receptor binding outcome measure, further supporting the improvements in registration accuracy. Our method incorporates a generic tracer kinetic model which makes it applicable to different PET radiotracers to remove motion artefacts and increase the integrity of dynamic PET studies. [Copyright &y& Elsevier]

Abstract: The D2/D3 agonist radioligand [11C]-(+)-PHNO is currently the most suitable D3 imaging agent available, despite its limited selectivity for the D3 over the D2. Given the collocation of D2 and D3 receptors, and generally higher densities of D2, the separation of D2 and D3 information from [11C]-(+)-PHNO PET data are somewhat complex. This complexity is compounded by recent data suggesting that [11C]-(+)-PHNO PET scans might be routinely performed in non-tracer conditions (with respect to D3 receptors), and that the cerebellum (used as a reference region) might manifest some displaceable binding signal. Here we present the modelling and analysis of data from two human studies which employed an adequate dose range of selective D3 antagonists (GSK598809 and GSK618334) to interrogate the [11C]-(+)-PHNO PET signal. Models describing the changes observed in the PET volume of distribution (VT ) and binding potential (BPND) were used to identify and quantify a [11C]-(+)-PHNO mass dose effect at the D3, and displaceable signal in the cerebellum, as well as providing refined estimates of regional D3 fractions of [11C]-(+)-PHNO BPND. The dose of (+)-PHNO required to occupy half of the available D3 receptors (ED50 PHNO,D3) was estimated as 40ng/kg, and the cerebellum BPND was estimated as 0.40. These findings confirm that [11C]-(+)-PHNO human PET studies are in fact routinely performed under non-tracer conditions. This suggests that (+)-PHNO injection masses should be minimised and tightly controlled in order to mitigate the mass dose effect. The specific binding detected in the cerebellum was modest but could have a significant effect, for example on estimates of D3 potency in drug occupancy studies. A range of methods for the analysis of future [11C]-(+)-PHNO data, incorporating models for the effects quantified here, were developed and evaluated. The comparisons and conclusions drawn from these can inform the design and analysis of future PET studies with [11C]-(+)-PHNO. [Copyright &y& Elsevier]

Abstract: To date, 11C-(R)-PK11195 has been the most widely used TSPO PET imaging probe, although it suffers from high non-specific binding and low signal to noise. A significant number of 2nd generation TSPO radioligands have been developed with higher affinity and/or lower non-specific binding, however there is substantial inter-subject variation in their affinity for the TSPO. TSPO from human tissue samples binds 2nd generation TSPO radioligands with either high affinity (high affinity binders, HABs), or low affinity (LABs) or expresses both HAB and LAB binding sites (mixed affinity binders, MABs). The expression of these different TSPO binding sites in human is encoded by the rs6971 polymorphism in the TSPO gene. Here, we use a predictive biomathematical model to estimate the in vivo performances of three of these 2nd generation radioligands (18F-PBR111, 11C-PBR28, 11C-DPA713) and 11C-(R)-PK11195 in humans. The biomathematical model only relies on in silico, in vitro and genetic data (polymorphism frequencies in different ethnic groups) to predict the radioactivity time course in vivo. In particular, we provide estimates of the performances of these ligands in within-subject (e.g. longitudinal studies) and between-subject (e.g. disease characterisation) PET studies, with and without knowledge of the TSPO binding class. This enables an assessment of the different radioligands prior to radiolabelling or acquisition of any in vivo data. The within-subject performance was characterised in terms of the reproducibility of the in vivo binding potential (%COV[BP ND ]) for each separate TSPO binding class in normal and diseased states (50% to 400% increase in TSPO density), whilst the between-subject performance was characterised in terms of the number of subjects required to distinguish between different populations. The results indicated that the within-subject variability for 18F-PBR111, 11C-PBR28 and 11C-DPA713 (0.9% to 2.2%) was significantly lower than 11C-(R)-PK11195 (16% to 36%) for HABs and MABs in both normal and diseased states. For between-subject studies, sample sizes required to detect 50% differences in TSPO density with the 2nd generation tracers are approximately half that required with 11C-(R)-PK11195 when binding class information is known a priori. As binding class can be identified using a simple genetic test or from peripheral blood assays, the combination of binding class information with 2nd generation TSPO imaging data should provide superior tools to investigate inflammatory processes in humans in vivo. [Copyright &y& Elsevier]

Abstract: [11C]-(+)-PHNO is a D3 preferring PET radioligand which has recently opened the possibility of imaging D3 receptors in the human brain in vivo. This imaging tool allows characterisation of the distribution of D3 receptors in vivo and further investigation of their functional role. The specific [11C]-(+)-PHNO signal is a mixture of D3 and D2 components with the relative magnitude of each component determined by the regional receptor densities. An accurate and reproducible delineation of regions of interest (ROI) is therefore important for optimal analysis of human PET data. We present a set of anatomical guidelines for the delineation of D3 relevant ROIs including substantia nigra, hypothalamus, ventral pallidum/substantia innominata, ventral striatum, globus pallidus and thalamus. Delineation of these structures using this approach allowed for high intra- and inter-operator reproducibility. Subsequently we used a selective D3 antagonist to dissect the total [11C]-(+)-PHNO signal in each region into its D3 and D2 components and estimated the regional fraction of the D3 signal (f PHNO D3). In descending order of magnitude the following results for the f PHNO D3 were obtained: hypothalamus=100%, substantia nigra=100%, ventral pallidum/substantia innominata=75%, globus pallidus=65%, thalamus=43%, ventral striatum=26% and precommissural-ventral putamen=6%. An automated approach for the delineation of these anatomical regions of interest was also developed and investigated in terms of its reproducibility and accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Antipsychotic-induced D2 receptor occupancy values tend to be lower when measured with [123I]IBZM SPECT than with [11C]Raclopride PET. To clarify this issue, D2 receptor occupancy was measured in the same subjects using both techniques. Twenty patients with schizophrenia on monotherapy with risperidone (n =7; 3–9 mg/d), olanzapine (n =5; 5–20 mg/d) or clozapine (n =8; 150–450 mg/d) at stable doses, and ten healthy volunteers (HV) underwent both a [123I]IBZM SPECT and a [11C]Raclopride PET examinations in random order on different days within a week. Patients with schizophrenia were scanned at a fixed interval after last dose administration. Quantification of receptor availability was performed using the most conventional methods from the literature: the tissue ratio derived specific uptake ratios (SUR) were used for SPECT, and simplified reference tissue model (SRTM) derived binding potentials (BPND) for PET. Analysis was performed using both occipital cortex and cerebellum as reference regions for both modalities. Striatal D2 receptor occupancy was measured as the percentage reduction of [123I]IBZM SUR or [11C]Raclopride BPND compared to the population average measured in HV using the same modality. Occupancy values measured by SPECT were lower than those measured with PET, by 12.4% and 13.8% when occipital cortex and cerebellum were used as reference regions. This difference should be taken in consideration when interpreting reported antipsychotic striatal D2 receptor occupancy values from the literature. [Copyright &y& Elsevier]

PET studies of [11C]WAY-100635 binding are proving to be a useful tool to evaluate 5-HT1A receptor function in vivo in humans. We describe the pattern of [11C]WAY-100635 binding in 61 healthy male brains and examine its variability. For all PET scans, binding potential (BP) values for [11C]WAY-100635 in different regions were calculated using a simplified reference tissue model, with the cerebellum as reference region. Specifically we describe (1) region of interest and SPM databases of PET [11C]WAY-100635 binding, including test–retest variability; (2) the sensitivity of [11C]WAY-100635 binding to manipulations of endogenous 5-HT; and (3) correlations between [11C]WAY-100635 binding and radiochemical, demographic, physiological, and behavioral variables. The regional distribution of [11C]WAY-100635 binding in healthy human brain was similar to that reported in vitro. The test–retest variability was ∼12% (range 9–16%) and was similar for all methods of regional sampling. The binding of [11C]WAY-100635 was insensitive to changes in brain 5-HT induced by tryptophan infusion and depletion. Although BP values varied greatly across subjects (range 2.9–6.8), there were no significant correlations of regional and global BP with common radiochemical, demographic, physiological, and personality variables. Specifically, in contrast with two recent small studies, we found no decline of [11C]WAY-100635 binding with age in our large cohort over the age range of 24 to 53 years. Assessment of 5-HT1A receptors in vivo using PET and [11C]WAY-100635 gives reliable measures of 5-HT1A binding. The large between-subject variability observed could not be explained by common methodological, physiological, or behavioral factors and hence the biological basis of this variability remains to be clarified. [Copyright &y& Elsevier]