Positron emission tomography compartmental models

Test-retest reproducibility of cannabinoid-receptor type 1 availability quantified with the PET ligand [¹¹C]MePPEP

Background

Endocannabinoids are involved in normal cognition, and dysfunction in cannabinoid-receptor-mediated neurotransmission has been suggested in a variety of neurological and psychiatric pathologies. The type 1 cannabinoid receptor (CB₁) is widely expressed in the human central nervous system. The objective of this study was to quantify the test–retest reproducibility of measures of the PET ligand [¹¹C]MePPEP in order to assess the stability of CB₁-receptor quantification in humans in vivo.

Methods

Fifteen healthy subjects (eight females; median age 32 years, range 25 to 65 years) had a 90-minute PET scan on two occasions after injection of a median dose of [¹¹C]MePPEP of 364 MBq. Metabolite-corrected arterial plasma input functions were obtained for all scans. Eight ROIs, reflecting different levels of receptor densities/concentrations, were defined automatically: hippocampus, anterior cingulate gyrus, inferior frontal gyrus, caudate nucleus, globus pallidus, nucleus accumbens, thalamus, and pons. We used seven quantification methods: reversible compartmental models with one and two tissue classes, two and four rate constants, and a variable blood volume term (2kbv; 4kbv); model-free (spectral) analyses with and without regularisation, including one with voxel-wise quantification; the simplified reference tissue model (SRTM) with pons as a pseudo-reference region; and modified standard uptake values (mSUVs) calculated for the period of ~ 30–60 min after injection. Percentage test–retest change and between-subject variability were both assessed, and test–retest reliability was quantified by the intraclass correlation coefficient (ICC). The ratio of binding estimates pallidum:pons served as an indicator of a method's ability to reflect binding heterogeneity.

Results

Neither the SRTM nor the 4kbv model produced reliable measures, with ICCs around zero. Very good (> 0.75) or excellent (> 0.80) ICCs were obtained with the other methods. The most reliable were spectral analysis parametric maps (average across regions ± standard deviation 0.83 ± 0.03), rank shaping regularised spectral analysis (0.82 ± 0.05), and the 2kbv model (0.82 ± 0.09), but mSUVs were also reliable for most regions (0.79 ± 0.13). Mean test–retest changes among the five well-performing methods ranged from 12 ± 10% for mSUVs to 16% for 2kbv. Intersubject variability was high, with mean between-subject coefficients of variation ranging from 32 ± 13% for mSUVs to 45% for 2kbv. The highest pallidum:pons ratios of binding estimates were achieved by mSUV (4.2), spectral analysis-derived parametric maps (3.6), and 2kbv (3.6).

Conclusion

Quantification of CB₁ receptor availability using [¹¹C]MePPEP shows good to excellent reproducibility with several kinetic models and model-free analyses, whether applied on a region-of-interest or voxelwise basis. Simple mSUV measures were also reliable for most regions, but do not allow fully quantitative interpretation. [¹¹C]MePPEP PET is well placed as a tool to investigate CB₁-receptor mediated neurotransmission in health and disease.

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[11C]MePPEP is a PET tracer for cannabinoid receptors (CB1R).

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Extensive evaluation of [11C]MePPEP data quantification strategies in large sample

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We highlight successful methods to quantify CB1R in regions of interest.

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Highly reliable parametric maps (ICC 0.83 ± 0.03) allow whole-brain surveys.

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Modified standard uptake values also reliable, without arterial input functions

Kinetic modeling in pre-clinical positron emission tomography

Pre-clinical positron emission tomography (PET) has evolved in the last few years from pure visualization of radiotracer uptake and distribution towards quantification of the physiological parameters. For reliable and reproducible quantification the kinetic modeling methods used to obtain relevant parameters of radiotracer tissue interaction are important. Here we present different kinetic modeling techniques with a focus on compartmental models including plasma input models and reference tissue input models. The experimental challenges off deriving the plasma input function in rodents and the effect of anesthesia are discussed. Finally, in vivo application of kinetic modeling in various areas of pre-clinical research is presented and compared to human data.

Recent Trends in PET Image Interpretations Using Volumetric and Texture-based Quantification Methods in Nuclear Oncology

Image quantification studies in positron emission tomography/computed tomography (PET/CT) are of immense importance in the diagnosis and follow-up of variety of cancers. In this review we have described the current image quantification methodologies employed in (18)F-fluorodeoxyglucose ((18)F-FDG) PET in major oncological conditions with particular emphasis on tumor heterogeneity studies. We have described various quantitative parameters being used in PET image analysis. The main contemporary methodology is to measure tumor metabolic activity; however, analysis of other image-related parameters is also increasing. Primarily, we have identified the existing role of tumor heterogeneity studies in major cancers using (18)F-FDG PET. We have also described some newer radiopharmaceuticals other than (18)F-FDG being studied/used in the management of these cancers. Tumor heterogeneity studies are being performed in almost all major oncological conditions using (18)F-FDG PET. The role of these studies is very promising in the management of these conditions.

Joint parametric reconstruction and motion correction framework for dynamic PET data

In this paper we propose a novel algorithm for jointly performing data based motion correction and direct parametric reconstruction of dynamic PET data. We derive a closed form update for the penalised likelihood maximisation which greatly enhances the algorithm's computational efficiency for practical use. Our algorithm achieves sub-voxel motion correction residual with noisy data in the simulation-based validation and reduces the bias of the direct estimation of the kinetic parameter of interest. A preliminary evaluation on clinical brain data using [18F]Choline shows improved contrast for regions of high activity. The proposed method is based on a data-driven kinetic modelling method and is directly applicable to reversible and irreversible PET tracers, covering a range of clinical applications.

Sparsity Constrained Mixture Modeling for the Estimation of Kinetic Parameters in Dynamic PET

The estimation and analysis of kinetic parameters in dynamic positron emission tomography (PET) is frequently confounded by tissue heterogeneity and partial volume effects. We propose a new constrained model of dynamic PET to address these limitations. The proposed formulation incorporates an explicit mixture model in which each image voxel is represented as a mixture of different pure tissue types with distinct temporal dynamics. We use Cramér-Rao lower bounds to demonstrate that the use of prior information is important to stabilize parameter estimation with this model. As a result, we propose a constrained formulation of the estimation problem that we solve using a two-stage algorithm. In the first stage, a sparse signal processing method is applied to estimate the rate parameters for the different tissue compartments from the noisy PET time series. In the second stage, tissue fractions and the linear parameters of different time activity curves are estimated using a combination of spatial-regularity and fractional mixture constraints. A block coordinate descent algorithm is combined with a manifold search to robustly estimate these parameters. The method is evaluated with both simulated and experimental dynamic PET data.

Spatio-temporal pharmacokinetic model based registration of 4D PET neuroimaging data

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 [(11)C]-(+)-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.

Tracer kinetic modeling of [(11)C]AFM, a new PET imaging agent for the serotonin transporter

[(11)C]AFM, or [(11)C]2-[2-(dimethylaminomethyl)phenylthio]-5-fluoromethylphenylamine, is a new positron emission tomography (PET) radioligand with high affinity and selectivity for the serotonin transporter (SERT). The purpose of this study was to determine the most appropriate kinetic model to quantify [(11)C]AFM binding in the healthy human brain. Positron emission tomography data and arterial input functions were acquired from 10 subjects. Compartmental modeling and the multilinear analysis-1(MA1) method were tested using the arterial input functions. The one-tissue model showed a lack of fit in low-binding regions, and the two-tissue model failed to estimate parameters reliably. Regional time-activity curves were well described by MA1. The rank order of [(11)C]AFM binding potential (BPND) matched well with the known regional SERT densities. For routine use of [(11)C]AFM, several noninvasive methods for quantification of regional binding were evaluated, including simplified reference tissue models (SRTM and SRTM2), and multilinear reference tissue models (MRTM and MRTM2). The best methods for region of interest (ROI) analysis were MA1, MRTM2, and SRTM2, with fixed population kinetic values ( or b') for the reference methods. The MA1 and MRTM2 methods were best for parametric imaging. These results showed that [(11)C]AFM is a suitable PET radioligand to image and quantify SERT in humans.

Direct estimation of kinetic parametric images for dynamic PET

Dynamic positron emission tomography (PET) can monitor spatiotemporal distribution of radiotracer in vivo. The spatiotemporal information can be used to estimate parametric images of radiotracer kinetics that are of physiological and biochemical interests. Direct estimation of parametric images from raw projection data allows accurate noise modeling and has been shown to offer better image quality than conventional indirect methods, which reconstruct a sequence of PET images first and then perform tracer kinetic modeling pixel-by-pixel. Direct reconstruction of parametric images has gained increasing interests with the advances in computing hardware. Many direct reconstruction algorithms have been developed for different kinetic models. In this paper we review the recent progress in the development of direct reconstruction algorithms for parametric image estimation. Algorithms for linear and nonlinear kinetic models are described and their properties are discussed.

Noninvasive k3 estimation method for slow dissociation PET ligands: application to [11C]Pittsburgh compound B

Background

Recently, we reported an information density theory and an analysis of three-parameter plus shorter scan than conventional method (3P+) for the amyloid-binding ligand [¹¹C]Pittsburgh compound B (PIB) as an example of a non-highly reversible positron emission tomography (PET) ligand. This article describes an extension of 3P + analysis to noninvasive ‘3P++’ analysis (3P + plus use of a reference tissue for input function).

Methods

In 3P++ analysis for [¹¹C]PIB, the cerebellum was used as a reference tissue (negligible specific binding). Fifteen healthy subjects (NC) and fifteen Alzheimer's disease (AD) patients participated. The k₃ (index of receptor density) values were estimated with 40-min PET data and three-parameter reference tissue model and were compared with that in 40-min 3P + analysis as well as standard 90-min four-parameter (4P) analysis with arterial input function. Simulation studies were performed to explain k₃ biases observed in 3P++ analysis.

Results

Good model fits of 40-min PET data were observed in both reference and target regions-of-interest (ROIs). High linear intra-subject (inter-15 ROI) correlations of k₃ between 3P++ (Y-axis) and 3P + (X-axis) analyses were shown in one NC (r² = 0.972 and slope = 0.845) and in one AD (r² = 0.982, slope = 0.655), whereas inter-subject k₃ correlations in a target region (left lateral temporal cortex) from 30 subjects (15 NC + 15 AD) were somewhat lower (r² = 0.739 and slope = 0.461). Similar results were shown between 3P++ and 4P analyses: r² = 0.953 for intra-subject k₃ in NC, r² = 0.907 for that in AD and r² = 0.711 for inter-30 subject k₃. Simulation studies showed that such lower inter-subject k₃ correlations and significant negative k₃ biases were not due to unstableness of 3P++ analysis but rather to inter-subject variation of both k₂ (index of brain-to-blood transport) and k₃ (not completely negligible) in the reference region.

Conclusions

In [¹¹C]PIB, the applicability of 3P++ analysis may be restricted to intra-subject comparison such as follow-up studies. The 3P++ method itself is thought to be robust and may be more applicable to other non-highly reversible PET ligands with ideal reference tissue.

[¹⁸F]Altanserin and small animal PET: impact of multidrug efflux transporters on ligand brain uptake and subsequent quantification of 5-HT₂A receptor densities in the rat brain

INTRODUCTION

The selective 5-hydroxytryptamine type 2a receptor (5-HT(2A)R) radiotracer [(18)F]altanserin is a promising ligand for in vivo brain imaging in rodents. However, [(18)F]altanserin is a substrate of P-glycoprotein (P-gp) in rats. Its applicability might therefore be constrained by both a differential expression of P-gp under pathological conditions, e.g. epilepsy, and its relatively low cerebral uptake. The aim of the present study was therefore twofold: (i) to investigate whether inhibition of multidrug transporters (MDT) is suitable to enhance the cerebral uptake of [(18)F]altanserin in vivo and (ii) to test different pharmacokinetic, particularly reference tissue-based models for exact quantification of 5-HT(2A)R densities in the rat brain.

METHODS

Eighteen Sprague-Dawley rats, either treated with the MDT inhibitor cyclosporine A (CsA, 50 mg/kg, n=8) or vehicle (n=10) underwent 180-min PET scans with arterial blood sampling. Kinetic analyses of tissue time-activity curves (TACs) were performed to validate invasive and non-invasive pharmacokinetic models.

RESULTS

CsA application lead to a two- to threefold increase of [(18)F]altanserin uptake in different brain regions and showed a trend toward higher binding potentials (BP(ND)) of the radioligand.

CONCLUSIONS

MDT inhibition led to an increased cerebral uptake of [(18)F]altanserin but did not improve the reliability of BP(ND) as a non-invasive estimate of 5-HT(2A)R. This finding is most probable caused by the heterogeneous distribution of P-gp in the rat brain and its incomplete blockade in the reference region (cerebellum). Differential MDT expressions in experimental animal models or pathological conditions are therefore likely to influence the applicability of imaging protocols and have to be carefully evaluated.

Estimate of FDG excretion by means of compartmental analysis and ant colony optimization of nuclear medicine data

[¹⁸F]fluoro-2-deoxy-D-glucose (FDG) is one of the most utilized tracers for positron emission tomography (PET) applications in oncology. FDG-PET relies on higher glycolytic activity in tumors compared to normal structures as the basis of image contrast. As a glucose analog, FDG is transported into malignant cells which typically exhibit an increased radioactivity. However, different from glucose, FDG is not reabsorbed by the renal system and is excreted to the bladder. The present paper describes a novel computational method for the quantitative assessment of this excretion process. The method is based on a compartmental analysis of FDG-PET data in which the excretion process is explicitly accounted for by the bladder compartment and on the application of an ant colony optimization (ACO) algorithm for the determination of the tracer coefficients describing the FDG transport effectiveness. The validation of this approach is performed by means of both synthetic data and real measurements acquired by a PET device for small animals (micro-PET). Possible oncological applications of the results are discussed in the final section.

Positron Emission Tomography as a Method for Measuring Drug Delivery to Tumors in vivo: The Example of [(11)C]docetaxel

Systemic anticancer treatments fail in a substantial number of patients. This may be caused by inadequate uptake and penetration of drugs in malignant tumors. Consequently, improvement of drug delivery to solid tumors may enhance its efficacy. Before evaluating strategies to enhance drug uptake in tumors, better understanding of drug delivery to human tumors is needed. Positron emission tomography (PET) is an imaging technique that can be used to monitor drug pharmacokinetics non-invasively in patients, based on radiolabeling these drugs with short-lived positron emitters. In this mini review, principles and potential applications of PET using radiolabeled anticancer drugs will be discussed with respect to personalized treatment planning in oncology. In particular, it will be discussed how these radiolabeled anticancer drugs could help to develop strategies for improved drug delivery to solid tumors. The development and clinical implementation of PET using radiolabeled anticancer drugs will be illustrated by validation studies of carbon-11 labeled docetaxel ([(11)C]docetaxel) in lung cancer patients.

Assessment of cerebral P-glycoprotein expression and function with PET by combined [11C]inhibitor and [11C]substrate scans in rats

INTRODUCTION

The adenosine triphosphate-binding cassette (ABC) transporter P-glycoprotein (Pgp) protects the brain from accumulation of lipophilic compounds by active efflux transport across the blood-brain barrier. Changes in Pgp function/expression may occur in neurological disorders, such as epilepsy, Alzheimer's or Parkinson's disease. In this work we investigated the suitability of the radiolabeled Pgp inhibitors [(11)C]elacridar and [(11)C]tariquidar to visualize Pgp density in rat brain with PET.

METHODS

Rats underwent a first PET scan with [(11)C]elacridar (n = 5) or [(11)C]tariquidar (n = 6) followed by a second scan with the Pgp substrate (R)-[(11)C]verapamil after administration of unlabeled tariquidar at a dose which half-maximally inhibits cerebral Pgp (3 mg/kg). Compartmental modeling using an arterial input function and Logan graphical analysis were used to estimate rate constants and volumes of distribution (VT) of radiotracers in different brain regions.

RESULTS

Brain PET signals of [(11)C]elacridar and [(11)C]tariquidar were very low (~0.5 standardized uptake value, SUV). There was a significant negative correlation between VT and K1 (i.e. influx rate constant from plasma into brain) values of [(11)C]elacridar or [(11)C]tariquidar and VT and K1 values of (R)-[(11)C]verapamil in different brain regions which was consistent with binding of [(11)C]inhibitors to Pgp and efflux of (R)-[(11)C]verapamil by Pgp.

CONCLUSION

The small Pgp binding signals obtained with [(11)C]elacridar and [(11)C]tariquidar limit the applicability of these tracers to measure cerebral Pgp density. PET tracers with higher (i.e. subnanomolar) binding affinities will be needed to visualize the low density of Pgp in brain.

Pharmacokinetic analysis of [18F]FAZA in non-small cell lung cancer patients

PURPOSE

[(18)F]Fluoroazomycin arabinoside (FAZA) is a positron emission tomography (PET) tracer developed to enable identification of hypoxic regions within a tumour. The aims of this study were to determine the optimal kinetic model along with validation of using alternatives to arterial blood sampling for analysing [(18)F]FAZA studies and to assess the validity of simplified analytical methods.

METHODS

Dynamic 70-min [(18)F]FAZA PET/CT scans were obtained from nine non-small cell lung cancer patients. Continuous arterial blood sampling, together with manual arterial and venous sampling, was performed to derive metabolite-corrected plasma input functions. Volumes of interest (VOIs) were defined for tumour, healthy lung muscle and adipose tissue generating [(18)F]FAZA time-activity curves (TACs). TACs were analysed using one- and two-tissue compartment models using both metabolite-corrected blood sampler plasma input functions (BSIF) and image-derived plasma input functions (IDIF).

RESULTS

The reversible two-tissue compartment model with blood volume parameter (2T4k+VB) best described kinetics of [(18)F]FAZA in tumours. Volumes of distribution (VT) obtained using IDIF correlated well with those derived using BSIF (R(2) = 0.82). Venous samples yielded the same radioactivity concentrations as arterial samples for times >50 min post-injection (p.i.). In addition, both plasma to whole blood ratios and parent fractions were essentially the same for venous and arterial samples. Both standardised uptake value (SUV), normalised to lean body mass, and tumour to blood ratio correlated well with VT (R(2) = 0.77 and R(2) = 0.87, respectively, at 50-60 min p.i.), although a bias was observed at low VT.

CONCLUSION

The 2T4k+VB model provided the best fit to the dynamic [(18)F]FAZA data. IDIF with venous blood samples can be used as input function. Further data are needed to validate the use of simplified methods.

Modeling of PET data in CNS drug discovery and development

Positron emission tomography (PET) is increasingly used in drug discovery and development for evaluation of CNS drug disposition and for studies of disease biomarkers to monitor drug effects on brain pathology. The quantitative analysis of PET data is based on kinetic modeling of radioactivity concentrations in plasma and brain tissue compartments. A number of quantitative methods of analysis have been developed that allow the determination of parameters describing drug pharmacokinetics and interaction with target binding sites in the brain. The optimal method of quantification depends on the properties of the radiolabeled drug or radioligand and the binding site studied. We here review the most frequently used methods for quantification of PET data in relation to CNS drug discovery and development. The utility of PET kinetic modeling in the development of novel CNS drugs is illustrated by examples from studies of the brain kinetic properties of radiolabeled drug molecules.

The 2D Hotelling filter - a quantitative noise-reducing principal-component filter for dynamic PET data, with applications in patient dose reduction

Background

In this paper we apply the principal-component analysis filter (Hotelling filter) to reduce noise from dynamic positron-emission tomography (PET) patient data, for a number of different radio-tracer molecules. We furthermore show how preprocessing images with this filter improves parametric images created from such dynamic sequence.

We use zero-mean unit variance normalization, prior to performing a Hotelling filter on the slices of a dynamic time-series. The Scree-plot technique was used to determine which principal components to be rejected in the filter process. This filter was applied to [¹¹C]-acetate on heart and head-neck tumors, [¹⁸F]-FDG on liver tumors and brain, and [¹¹C]-Raclopride on brain. Simulations of blood and tissue regions with noise properties matched to real PET data, was used to analyze how quantitation and resolution is affected by the Hotelling filter. Summing varying parts of a 90-frame [¹⁸F]-FDG brain scan, we created 9-frame dynamic scans with image statistics comparable to 20 MBq, 60 MBq and 200 MBq injected activity. Hotelling filter performed on slices (2D) and on volumes (3D) were compared.

Results

The 2D Hotelling filter reduces noise in the tissue uptake drastically, so that it becomes simple to manually pick out regions-of-interest from noisy data. 2D Hotelling filter introduces less bias than 3D Hotelling filter in focal Raclopride uptake. Simulations show that the Hotelling filter is sensitive to typical blood peak in PET prior to tissue uptake have commenced, introducing a negative bias in early tissue uptake. Quantitation on real dynamic data is reliable. Two examples clearly show that pre-filtering the dynamic sequence with the Hotelling filter prior to Patlak-slope calculations gives clearly improved parametric image quality. We also show that a dramatic dose reduction can be achieved for Patlak slope images without changing image quality or quantitation.

Conclusions

The 2D Hotelling-filtering of dynamic PET data is a computer-efficient method that gives visually improved differentiation of different tissues, which we have observed improve manual or automated region-of-interest delineation of dynamic data. Parametric Patlak images on Hotelling-filtered data display improved clarity, compared to non-filtered Patlak slope images without measurable loss of quantitation, and allow a dramatic decrease in patient injected dose.

Studies of the metabotropic glutamate receptor 5 radioligand [¹¹C]ABP688 with N-acetylcysteine challenge in rhesus monkeys

Detecting changes in receptor binding at the metabotropic glutamate receptor 5 (mGluR5) with the PET allosteric antagonist, [¹¹C]ABP688, may be valuable for studying dysfunctional glutamate transmission associated with psychiatric illnesses. This study was designed to validate the findings of a recent pilot study in baboons which reported a significant global decrease from baseline [¹¹C]ABP688 binding after increasing endogenous glutamate with 50 mg/kg N-acetylcysteine (NAC), with no change from test to retest. In rhesus monkeys (n = 5), paired [¹¹C]ABP688 scans were performed on the same day on the Focus-220 as follows (n = 3 per group): test-retest, baseline-NAC (50 mg/kg), and baseline-NAC (100 mg/kg). Multiple modeling methods were evaluated for kinetic analysis to estimate the total volume of distribution (VT ) and non-displaceable binding potential (BP(ND)) in regions-of-interest (ROIs), with the cerebellum gray matter (CGM) as the reference region. There was an increasing trend from test to retest BP(ND) across ROIs (13%). NAC (50 mg/kg and 100 mg/kg) increased VT (5% and 19%) and decreased BP(ND) (3% and 10%), respectively, significant only for VT in ROIs at the 100 mg/kg dose. High intersubject variability in BP(ND) was comparable to that reported in the baboon study. However, interpretability of BP(ND) is difficult with increases in VT in the CGM reference region at the higher NAC dose. Additionally, the net reduction in BP(ND) from the baseline-NAC scans may be obscured due to observed increases in test-retest BP(ND). Thus, we did not strictly replicate the findings in the baboon study based on BP(ND).

Suitability of [18F]altanserin and PET to determine 5-HT2A receptor availability in the rat brain: in vivo and in vitro validation of invasive and non-invasive kinetic models

PURPOSE

While the selective 5-hydroxytryptamine type 2a receptor (5-HT2AR) radiotracer [18F]altanserin is well established in humans, the present study evaluated its suitability for quantifying cerebral 5-HT2ARs with positron emission tomography (PET) in albino rats.

PROCEDURES

Ten Sprague Dawley rats underwent 180 min PET scans with arterial blood sampling. Reference tissue methods were evaluated on the basis of invasive kinetic models with metabolite-corrected arterial input functions. In vivo 5-HT2AR quantification with PET was validated by in vitro autoradiographic saturation experiments in the same animals.

RESULT

Overall brain uptake of [18F]altanserin was reliably quantified by invasive and non-invasive models with the cerebellum as reference region shown by linear correlation of outcome parameters. Unlike in humans, no lipophilic metabolites occurred so that brain activity derived solely from parent compound. PET data correlated very well with in vitro autoradiographic data of the same animals.

CONCLUSION

[18F]Altanserin PET is a reliable tool for in vivo quantification of 5-HT2AR availability in albino rats. Models based on both blood input and reference tissue describe radiotracer kinetics adequately. Low cerebral tracer uptake might, however, cause restrictions in experimental usage.

Introduction to the analysis of PET data in oncology

Several reviews on specific topics related to positron emission tomography (PET) ranging in complexity from introductory to highly technical have already been published. This introduction to the analysis of PET data was written as a simple guide of the different phases of analysis of a given PET dataset, from acquisition to preprocessing, to the final data analysis. Although sometimes issues specific to PET in neuroimaging will be mentioned for comparison, most of the examples and applications provided will refer to oncology. Due to the limitations of space we couldn't address each issue comprehensively but, rather, we provided a general overview of each topic together with the references that the interested reader should consult. We will assume a familiarity with the basic principles of PET imaging.

Advances in PET imaging of P-glycoprotein function at the blood-brain barrier

Efflux transporter P-glycoprotein (P-gp) at the blood-brain barrier (BBB) restricts substrate compounds from entering the brain and may thus contribute to pharmacoresistance observed in patient groups with refractory epilepsy and HIV. Altered P-gp function has also been implicated in neurodegenerative diseases such as Alzheimer's and Parkinson's disease. Positron emission tomography (PET), a molecular imaging modality, has become a promising method to study the role of P-gp at the BBB. The first PET study of P-gp function was conducted in 1998, and during the past 15 years two main categories of P-gp PET tracers have been investigated: tracers that are substrates of P-gp efflux and tracers that are inhibitors of P-gp function. PET, as a noninvasive imaging technique, allows translational research. Examples of this are preclinical investigations of P-gp function before and after administering P-gp modulating drugs, investigations in various animal and disease models, and clinical investigations regarding disease and aging. The objective of the present review is to give an overview of available PET radiotracers for studies of P-gp and to discuss how such studies can be designed. Further, the review summarizes results from PET studies of P-gp function in different central nervous system disorders.

Potential contribution of aromatase inhibition to the effects of nicotine and related compounds on the brain

Cigarette smoking continues to be a major public health problem, and while smoking rates in men have shown some decrease over the last few decades, smoking rates among girls and young women are increasing. Practically all of the important aspects of cigarette smoking and many effects of nicotine are sexually dimorphic (reviewed by Pogun and Yararbas, 2009). Women become addicted more easily than men, while finding it harder to quit. Nicotine replacement appears to be less effective in women. This may be linked to the observation that women are more sensitive than men to non-nicotine cues or ingredients in cigarettes. The reasons for these sex differences are mostly unknown. Several lines of evidence suggest that many of the reported sex differences related to cigarette smoking may stem from the inhibitory effects of nicotine and other tobacco alkaloids on estrogen synthesis via the enzyme aromatase (cyp19a gene product). Aromatase is the last enzyme in estrogen biosynthesis, catalyzing the conversion of androgens to estrogens. This review provides a summary of experimental evidence supporting brain aromatase as a potential mediator and/or modulator of nicotine actions in the brain, contributing to sex differences in smoking behavior. Additional research on the interaction between tobacco smoke, nicotine, and aromatase may help devise new, sex specific methods for prevention and treatment of smoking addiction.

A non-linear mixed effect modelling approach for metabolite correction of the arterial input function in PET studies

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.

Pharmacokinetic modeling of P-glycoprotein function at the rat and human blood-brain barriers studied with (R)-[11C]verapamil positron emission tomography

Background

This study investigated the influence of P-glycoprotein (P-gp) inhibitor tariquidar on the pharmacokinetics of P-gp substrate radiotracer (R)-[¹¹C]verapamil in plasma and brain of rats and humans by means of positron emission tomography (PET).

Methods

Data obtained from a preclinical and clinical study, in which paired (R)-[¹¹C]verapamil PET scans were performed before, during, and after tariquidar administration, were analyzed using nonlinear mixed effects (NLME) modeling. Administration of tariquidar was included as a covariate on the influx and efflux parameters (Q_in and Q_out) in order to investigate if tariquidar increased influx or decreased outflux of radiotracer across the blood–brain barrier (BBB). Additionally, the influence of pilocarpine-induced status epilepticus (SE) was tested on all model parameters, and the brain-to-plasma partition coefficient (V_T-NLME) was calculated.

Results

Our model indicated that tariquidar enhances brain uptake of (R)-[¹¹C]verapamil by decreasing Q_out. The reduction in Q_out in rats during and immediately after tariquidar administration (sevenfold) was more pronounced than in the second PET scan acquired 2 h after tariquidar administration (fivefold). The effect of tariquidar on Q_out in humans was apparent during and immediately after tariquidar administration (twofold reduction in Q_out) but was negligible in the second PET scan. SE was found to influence the pharmacological volume of distribution of the central brain compartment V_br1. Tariquidar treatment lead to an increase in V_T-NLME, and pilocarpine-induced SE lead to increased (R)-[¹¹C]verapamil distribution to the peripheral brain compartment.

Conclusions

Using NLME modeling, we were able to provide mechanistic insight into the effects of tariquidar and SE on (R)-[¹¹C]verapamil transport across the BBB in control and 48 h post SE rats as well as in humans.

Advantages of a dual-tracer model over reference tissue models for binding potential measurement in tumors

The quantification of tumor molecular expression in vivo could have a significant impact for informing and monitoring emerging targeted therapies in oncology. Molecular imaging of targeted tracers can be used to quantify receptor expression in the form of a binding potential (BP) if the arterial input curve or a surrogate of it is also measured. However, the assumptions of the most common approaches (reference tissue models) may not be valid for use in tumors. In this study, the validity of reference tissue models is investigated for use in tumors experimentally and in simulations. Three different tumor lines were grown subcutaneously in athymic mice and the mice were injected with a mixture of an epidermal growth factor receptor-targeted fluorescent tracer and an untargeted fluorescent tracer. A one-compartment plasma input model demonstrated that the transport kinetics of both tracers was significantly different between tumors and all potential reference tissues, and using the reference tissue model resulted in a theoretical underestimation in BP of 50% ± 37%. On the other hand, the targeted and untargeted tracers demonstrated similar transport kinetics, allowing a dual-tracer approach to be employed to accurately estimate BP (with a theoretical error of 0.23% ± 9.07%). These findings highlight the potential for using a dual-tracer approach to quantify receptor expression in tumors with abnormal hemodynamics, possibly to inform the choice or progress of molecular cancer therapies.

Importance of quantification for the analysis of PET data in oncology: review of current methods and trends for the future

In oncology, positron emission tomography (PET) is an important tool for tumour diagnosis and staging, assessment of response to treatment and evaluation of the pharmacokinetic properties and efficacy of new drugs. Despite its quantitative potential, however, in daily clinical practice PET is used almost exclusively with 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) and, in addition, [(18)F]FDG data are normally assessed visually or using simple indices as the standardised uptake value (SUV). After explaining why more sophisticated quantification methods can be useful in oncology, the paper reviews the approaches that are commonly used and those available but not routinely employed. Particular emphasis is addressed to the SUV, for its importance in clinical practice. Issues specific to PET quantification in oncology and related examples are then discussed. Finally, some ideas for the development of new quantitative methods for analysing PET data in oncology and for the application of approaches already existing but not commonly employed are presented.

Fourier domain closed-form formulas for estimation of kinetic parameters in reversible multi-compartment models

Background

Compared with static imaging, dynamic emission computed tomographic imaging with compartment modeling can quantify in vivo physiologic processes, providing useful information about molecular disease processes. Dynamic imaging involves estimation of kinetic rate parameters. For multi-compartment models, kinetic parameter estimation can be computationally demanding and problematic with local minima.

Methods

This paper offers a new perspective to the compartment model fitting problem where Fourier linear system theory is applied to derive closed-form formulas for estimating kinetic parameters for the two-compartment model. The proposed Fourier domain estimation method provides a unique solution, and offers very different noise response as compared to traditional non-linear chi-squared minimization techniques.

Results

The unique feature of the proposed Fourier domain method is that only low frequency components are used for kinetic parameter estimation, where the DC (i.e., the zero frequency) component in the data is treated as the most important information, and high frequency components that tend to be corrupted by statistical noise are discarded. Computer simulations show that the proposed method is robust without having to specify the initial condition. The resultant solution can be fine tuned using the traditional iterative method.

Conclusions

The proposed Fourier-domain estimation method has closed-form formulas. The proposed Fourier-domain curve-fitting method does not require an initial condition, it minimizes a quadratic objective function and a closed-form solution can be obtained. The noise is easier to control, simply by discarding the high frequency components, and emphasizing the DC component.

Kinetic parameter estimation using a closed-form expression via integration by parts

Dynamic emission computed tomographic imaging with compartment modeling can quantify in vivo physiologic processes, eliciting more information regarding underlying molecular disease processes than is obtained from static imaging. However, estimation of kinetic rate parameters for multi-compartment models can be computationally demanding and problematic due to local minima. A number of techniques for kinetic parameter estimation have been studied and are in use today, generally offering a tradeoff between computation time, robustness of fit and flexibility with differing sets of assumptions. This paper presents a means to eliminate all differential operations by using the integration-by-parts method to provide closed-form formulas, so that the mathematical model is less sensitive to data sampling and noise. A family of closed-form formulas are obtained. Computer simulations show that the proposed method is robust without having to specify the initial condition.

Gaussian process models of dynamic PET for functional volume definition in radiation oncology

In routine oncologic positron emission tomography (PET), dynamic information is discarded by time-averaging the signal to produce static images of the "standardised uptake value" (SUV). Defining functional volumes of interest (VOIs) in terms of SUV is flawed, as values are affected by confounding factors and the chosen time window, and SUV images are not sensitive to functional heterogeneity of pathological tissues. Also, SUV iso-contours are highly affected by the choice of threshold and no threshold, or other SUV-based segmentation method, is universally accepted for a given VOI type. Gaussian Process (GP) time series models describe macro-scale dynamic behavior arising from countless interacting micro-scale processes, as is the case for PET signals from heterogeneous tissue. We use GPs to model time-activity curves (TACs) from dynamic PET and to define functional volumes for PET oncology. Probabilistic methods of tissue discrimination are presented along with novel contouring methods for functional VOI segmentation. We demonstrate the value of GP models for voxel classification and VOI contouring of diseased and metastatic tissues with functional heterogeneity in prostate PET. Classification experiments reveal superior sensitivity and specificity over SUV calculation and a TAC-based method proposed in recent literature. Contouring experiments reveal differences in shape between gold-standard and GP VOIs and correlation with kinetic models shows that the novel VOIs contain extra clinically relevant information compared to SUVs alone. We conclude that the proposed models offer a principled data analysis technique that improves on SUVs for oncologic VOI definition. Continuing research will generalize GP models for different oncology tracers and imaging protocols with the ultimate goal of clinical use including treatment planning.

Optimization of supervised cluster analysis for extracting reference tissue input curves in (R)-[(11)C]PK11195 brain PET studies

Performance of two supervised cluster analysis (SVCA) algorithms for extracting reference tissue curves was evaluated to improve quantification of dynamic (R)-[(11)C]PK11195 brain positron emission tomography (PET) studies. Reference tissues were extracted from images using both a manually defined cerebellum and SVCA algorithms based on either four (SVCA4) or six (SVCA6) kinetic classes. Data from controls, mild cognitive impairment patients, and patients with Alzheimer's disease were analyzed using various kinetic models including plasma input, the simplified reference tissue model (RPM) and RPM with vascular correction (RPMV(b)). In all subject groups, SVCA-based reference tissue curves showed lower blood volume fractions (V(b)) and volume of distributions than those based on cerebellum time-activity curve. Probably resulting from the presence of specific signal from the vessel walls that contains in normal condition a significant concentration of the 18 kDa translocation protein. Best contrast between subject groups was seen using SVCA4-based reference tissues as the result of a lower number of kinetic classes and the prior removal of extracerebral tissues. In addition, incorporation of V(b) in RPM improved both parametric images and binding potential contrast between groups. Incorporation of V(b) within RPM, together with SVCA4, appears to be the method of choice for analyzing cerebral (R)-[(11)C]PK11195 neurodegeneration studies.

RECONSTRUCTION OF DYNAMIC PET IMAGES USING ACCURATE SYSTEM POINT SPREAD FUNCTION MODELING: EFFECTS ON PARAMETRIC IMAGES

Quantitative analysis of positron emission tomography (PET) dynamic images allows to estimate physiological parameters such as glucose metabolic rate (GMR), perfusion, and cardiac output (CO). However, several physical effects such as photon attenuation, scatter and partial volume can reduce the accuracy of parameter estimation. The main goal of this work was to improve small animal PET image quality by introducing system point spread function (PSF) in the reconstruction scheme and to evaluate the effect of partial volume correction (PVC) on physiological parameter estimation. Images reconstructed respectively using constant and spatially variant (SV) PSFs and no PSF modeling was compared. The proposed algorithms were tested on simulated and real phantoms and mice images. Results show that the SV-PSF-based reconstruction method provides a significant contrast improvement of small animals PET cardiac images and, thus, the effects of PVC on physiological parameters were evaluated using such algorithm. Simulations show that the proposed PVC method reduces errors with respect to the true values for parametric images of GMR and perfusion. A reduction of CO percentage error with respect to the original value was also obtained using the SF-PSF approach. In conclusion, SV-PSF reconstruction method provides a more accurate estimation of several physiological parameters obtained from a dynamic PET scan.

A short-scan method for k(3) estimation with moderately reversible PET ligands: application of irreversible model to early-phase PET data

Long dynamic scans (60-120 min) are often required for estimating the k(3) value, an index of receptor density, by positron emission tomography (PET). However, the precision of k(3) is usually low in kinetic analyses for reversible PET ligands compared with irreversible ligands. That is largely due to unstable estimation of the dissociation rate constant, k(4). We propose a novel '3P+' method for estimating k(3) of moderately reversible ligands, where a 3-parameter model without k(4) is applied to early-phase PET data to obtain a good model-fit of k(3) estimation. By using [(11)C] Pittsburgh compound B (PIB) (k(4) = 0.018/min) as an example of a moderately reversible ligand, the 3P+ method simulation with a 28 min PET scan yielded less than 3% k(3) relative bias with a +100% k(3) change. In [(11)C]PIB PET scans of 15 normal controls (NC) and nine patients with Alzheimer's disease (AD), the 3P+ method provided a precise k(3) estimate (mean SE of 13.6% in parietal cortex; covariance matrix method). The results revealed linear correlations (r = 0.964) of parietal k(3) values in 24 subjects between 28minute 3P+ method and conventional 90 minute 4-parameter method. A good separation of k(3) between NC and AD groups (P < 0.001; t-test) was replicated in 28 minute 3P+ method. The short-scan 3P+ method may be a practical alternative method for analyzing reversible ligands.

Quantification of ligand PET studies using a reference region with a displaceable fraction: application to occupancy studies with [(11)C]-DASB as an example

This paper aims to build novel methodology for the use of a reference region with specific binding for the quantification of brain studies with radioligands and positron emission tomography (PET). In particular: (1) we introduce a definition of binding potential BP(D)=DVR-1 where DVR is the volume of distribution relative to a reference tissue that contains ligand in specifically bound form, (2) we validate a numerical methodology, rank-shaping regularization of exponential spectral analysis (RS-ESA), for the calculation of BP(D) that can cope with a reference region with specific bound ligand, (3) we demonstrate the use of RS-ESA for the accurate estimation of drug occupancies with the use of correction factors to account for the specific binding in the reference. [(11)C]-DASB with cerebellum as a reference was chosen as an example to validate the methodology. Two data sets were used; four normal subjects scanned after infusion of citalopram or placebo and further six test-retest data sets. In the drug occupancy study, the use of RS-ESA with cerebellar input plus corrections produced estimates of occupancy very close the ones obtained with plasma input. Test-retest results demonstrated a tight linear relationship between BP(D) calculated either with plasma or with a reference input and high reproducibility.

Decreased defluorination using the novel beta-cell imaging agent [18F]FE-DTBZ-d4 in pigs examined by PET

Background

Fluorine-18 dihydrotetrabenazine [DTBZ] analogues, which selectively target the vesicular monoamine transporter 2 [VMAT2], have been extensively studied for in vivo quantification of beta cell mass by positron-emission tomography [PET]. This study describes a novel deuterated radioligand [¹⁸F]fluoroethyl [FE]-DTBZ-d4, aimed to increase the stability against in vivo defluorination previously observed for [¹⁸F]FE-DTBZ.

Methods

[¹⁸F]FE-DTBZ-d4 was synthesized by alkylation of 9-O-desmethyl-(+)-DTBZ precursor with deuterated [¹⁸F]FE bromide ([¹⁸F]FCD₂CD₂Br). Radioligand binding potential [BP] was assessed by an in vitro saturation homogenate binding assay using human endocrine and exocrine pancreatic tissues. In vivo pharmacokinetics and pharmacodynamics [PK/PD] was studied in a porcine model by PET/computed tomography, and the rate of defluorination was quantified by compartmental modeling.

Results

[¹⁸F]FE-DTBZ-d4 was produced in reproducible good radiochemical yield in 100 ± 20 min. Radiochemical purity of the formulated product was > 98% for up to 5 h with specific radioactivities that ranged from 192 to 529 GBq/μmol at the end of the synthesis. The in vitro BP for VMAT2 in the islet tissue was 27.0 ± 8.8, and for the exocrine tissue, 1.7 ± 1.0. The rate of in vivo defluorination was decreased significantly (k_{defluorination} = 0.0016 ± 0.0007 min^-1) compared to the non-deuterated analogue (k_{defluorination} = 0.012 ± 0.002 min^-1), resulting in a six fold increase in half-life stability.

Conclusions

[¹⁸F]FE-DTBZ-d4 has similar PK and PD properties for VMAT2 imaging as its non-deuterated analogue [¹⁸F]FE-DTBZ in addition to gaining significantly increased stability against defluorination. [¹⁸F]FE-DTBZ-d4 is a prime candidate for future preclinical and clinical studies on focal clusters of beta cells, such as in intramuscular islet grafts.

Characterization of [11C]RO5013853, a novel PET tracer for the glycine transporter type 1 (GlyT1) in humans

We characterize a novel radioligand for the glycine transporter type 1 (GlyT1), [(11)C]RO5013853, in humans. Ten healthy male volunteers, 23-60 years of age, were enrolled in this PET study; seven subjects participated in the evaluation of test-retest reliability and three subjects in whole body dosimetry. Subjects were administered intravenous bolus injections of approximately 1100 MBq (30 mCi) [(11)C]RO5013853 with a high specific activity of about 481 GBq (13 Ci)/μmol. Standard compartmental model analysis with arterial plasma input function, and an alternative noninvasive analysis method which was evaluated and validated by occupancy studies in both baboons and humans, were performed. Mean parameter estimates of the volumes of distribution (VT) obtained by a 2-tissue 5-parameter model were higher in the cerebellum, pons, and thalamus (1.99 to 2.59 mL/mL), and lower in the putamen, caudate, and cortical areas (0.86 to 1.13 mL/mL), with estimates showing less than 10% difference between test and retest scans. Tracer retention was effectively blocked by the specific glycine reuptake inhibitor (GRI), bitopertin (RG1678). [(11)C]RO5013853 was safe and well tolerated. Human dosimetry studies showed that the effective dose was approximately 0.0033 mSv/MBq, with the liver receiving the highest absorbed dose. In conclusion, quantitative dynamic PET of the human brain after intravenous injection of [(11)C]RO5013853 attains reliable measurements of GlyT1 binding in accordance with the expected transporter distribution in the human brain. [(11)C]RO5013853 is a radioligand suitable for further clinical PET studies. Full characterization of a novel radiotracer for GlyT1 in humans is provided. The tracer has subsequently been used to assess receptor occupancy in healthy volunteers and to estimate occupancy at doses associated with best efficacy in a clinical trial with schizophrenic patients with predominantly negative symptoms.

Further evaluation of quantum chemical methods for the prediction of non-specific binding of positron emission tomography tracers

The non-specific binding of candidate positron emission tomography (PET) radiotracers causes resulting PET images to have poor contrast and is a key determinant for the success or failure of imaging drugs. Non-specific binding is thought to arise when radiotracers bind to cell membranes and moieties other than their intended target. Our previous preliminary work has proposed the use of the drug-lipid interaction energy descriptor to predict the level of non-specific binding in vivo using a limited set of ten well known PET radiotracers with kinetic modelling data taken from the literature. This work validates and extends the use of the drug-lipid interaction energy descriptor using a new set of twenty-two candidate PET radiotracers with non-specific binding data recently collected at the same imaging centre with consistent methodology. As with the previous set of radiotracers, a significant correlation is found between the quantum chemical drug-lipid interaction energy and in vivo non-specific binding experimental values. In an effort to speed up the calculation process, several semi-empirical quantum chemical methods were assessed for their ability to reproduce the ab initio results. However no single semi-empirical method was found to consistently reproduce the level of correlation achieved with ab initio quantum chemical methods.

Technical aspects of amyloid imaging for Alzheimer's disease

[¹¹C]Pittsburgh Compound B positron emission tomography has now been extensively used to evaluate the amyloid load in different types of dementia and has become a powerful research tool in the field of neurodegenerative diseases. In the present short review we discuss the properties of amyloid imaging agent [¹¹C]Pittsburgh Compound B, the different modalities of molecular imaging, image processing and data analysis, and newer amyloid imaging agents.

Cumulative input function method for linear compartmental models and spectral analysis in PET

Compartmental modeling and spectral analysis are often used for tracer kinetic modeling in positron emission tomography (PET). The concentrations in kinetic equations are usually considered to be instantaneous, whereas PET data are inherently integrated over time, which leads to uncertainties in the results. A new formalism for kinetic analysis that uses cumulative tracer concentrations and avoids approximating the image-derived input function and PET measurements with midframe instantanous values was developed. We assessed the improvements of the new formalism over the midframe approximation methods for three commonly used radiopharmaceuticals: [(11)C]raclopride, 2'-deoxy-2'-[(18)F]fluoro-D-glucose (FDG), and 3'-deoxy-3'-[(18)F]fluoro-thymidine (FLT). We found that improvements are case dependent and often not negligible. Improvements for determination of binding potential for [(11)C]raclopride ranged from 5% to 25%. Improvements in estimation accuracy of FDG and FLT microparameters ranged up to 25%. On the other hand, estimation of macroparameter K(i)=K(1)k(3)/(k(2)+k(3)) for FDG or FLT did not show significant benefit with the new method; only modest improvement up to 2% was observed. Assessment of the benefits of using new method is far from being exhaustive, but possibly significant improvement was demonstrated. Therefore, we consider the proposed algorithm a necessary component of any kinetic analysis software.

Unique distribution of aromatase in the human brain: in vivo studies with PET and [N-methyl-11C]vorozole

Aromatase catalyzes the last step in estrogen biosynthesis. Brain aromatase is involved in diverse neurophysiological and behavioral functions including sexual behavior, aggression, cognition, and neuroprotection. Using positron emission tomography (PET) with the radiolabeled aromatase inhibitor [N-methyl-(11)C]vorozole, we characterized the tracer distribution and kinetics in the living human brain. Six young, healthy subjects, three men and three women, were administered the radiotracer alone on two separate occasions. Women were scanned in distinct phases of the menstrual cycle. Specificity was confirmed by pretreatment with a pharmacological (2.5 mg) dose of the aromatase inhibitor letrozole. PET data were acquired over a 90-min period and regions of interest placed over selected brain regions. Brain and plasma time activity curves, corrected for metabolites, were used to derive kinetic parameters. Distribution volume (V(T)) values in both men and women followed the following rank order: thalamus > amygdala = preoptic area > medulla (inferior olive) > accumbens, pons, occipital and temporal cortex, putamen, cerebellum, and white matter. Pretreatment with letrozole reduced V(T) in all regions, though the size of the reduction was region-dependent, ranging from ∼70% blocking in thalamus andpreoptic area to ∼10% in cerebellum. The high levels of aromatase in thalamus and medulla (inferior olive) appear to be unique to humans. These studies set the stage for the noninvasive assessment of aromatase involvement in various physiological and pathological processes affecting the human brain.

(R)-[11C]verapamil PET studies to assess changes in P-glycoprotein expression and functionality in rat blood-brain barrier after exposure to kainate-induced status epilepticus

BACKGROUND

Increased functionality of efflux transporters at the blood-brain barrier may contribute to decreased drug concentrations at the target site in CNS diseases like epilepsy. In the rat, pharmacoresistant epilepsy can be mimicked by inducing status epilepticus by intraperitoneal injection of kainate, which leads to development of spontaneous seizures after 3 weeks to 3 months. The aim of this study was to investigate potential changes in P-glycoprotein (P-gp) expression and functionality at an early stage after induction of status epilepticus by kainate.

METHODS

(R)-[11C]verapamil, which is currently the most frequently used positron emission tomography (PET) ligand for determining P-gp functionality at the blood-brain barrier, was used in kainate and saline (control) treated rats, at 7 days after treatment. To investigate the effect of P-gp on (R)-[11C]verapamil brain distribution, both groups were studied without or with co-administration of the P-gp inhibitor tariquidar. P-gp expression was determined using immunohistochemistry in post mortem brains. (R)-[11C]verapamil kinetics were analyzed with approaches common in PET research (Logan analysis, and compartmental modelling of individual profiles) as well as by population mixed effects modelling (NONMEM).

RESULTS

All data analysis approaches indicated only modest differences in brain distribution of (R)-[11C]verapamil between saline and kainate treated rats, while tariquidar treatment in both groups resulted in a more than 10-fold increase. NONMEM provided most precise parameter estimates. P-gp expression was found to be similar for kainate and saline treated rats.

CONCLUSIONS

P-gp expression and functionality does not seem to change at early stage after induction of anticipated pharmacoresistant epilepsy by kainate.

Advances in biomathematical modeling for PET neuroreceptor imaging

The quantitative application of PET neuroreceptor imaging to study pathophysiology, diagnostics and drug development has continued to benefit from associated advances in biomathematical imaging methodology. We review some of these advances with particular focus on multi-modal image processing, tracer kinetic modeling, occupancy studies and discovery and development of novel radioligands.:

Dynamic single photon emission computed tomography--basic principles and cardiac applications

The very nature of nuclear medicine, the visual representation of injected radiopharmaceuticals, implies imaging of dynamic processes such as the uptake and wash-out of radiotracers from body organs. For years, nuclear medicine has been touted as the modality of choice for evaluating function in health and disease. This evaluation is greatly enhanced using single photon emission computed tomography (SPECT), which permits three-dimensional (3D) visualization of tracer distributions in the body. However, to fully realize the potential of the technique requires the imaging of in vivo dynamic processes of flow and metabolism. Tissue motion and deformation must also be addressed. Absolute quantification of these dynamic processes in the body has the potential to improve diagnosis. This paper presents a review of advancements toward the realization of the potential of dynamic SPECT imaging and a brief history of the development of the instrumentation. A major portion of the paper is devoted to the review of special data processing methods that have been developed for extracting kinetics from dynamic cardiac SPECT data acquired using rotating detector heads that move as radiopharmaceuticals exchange between biological compartments. Recent developments in multi-resolution spatiotemporal methods enable one to estimate kinetic parameters of compartment models of dynamic processes using data acquired from a single camera head with slow gantry rotation. The estimation of kinetic parameters directly from projection measurements improves bias and variance over the conventional method of first reconstructing 3D dynamic images, generating time-activity curves from selected regions of interest and then estimating the kinetic parameters from the generated time-activity curves. Although the potential applications of SPECT for imaging dynamic processes have not been fully realized in the clinic, it is hoped that this review illuminates the potential of SPECT for dynamic imaging, especially in light of new developments that enable measurement of dynamic processes directly from projection measurements.

Identification and evaluation of [11C]GSK931145 as a novel ligand for imaging the type 1 glycine transporter with positron emission tomography

The type-1 glycine transporter (GlyT1) is an important target for the development of new medications for schizophrenia. A specific and selective positron emission tomography (PET) GlyT1 ligand would facilitate drug development studies to determine whether a drug reaches this target and help establish suitable doses for clinical trials. This article describes the evaluation of three candidate GlyT1 PET radioligands (GSK931145, GSK565710, and GSK991022) selected from a library of compounds based on favorable physicochemical and pharmacological properties. Each candidate was successfully labeled using [(11)C]methyl iodide or [(11)C]methyl triflate and administered to a pig pre- and postadministration with a pharmacological dose of a GlyT1 inhibitor to determine their suitability as PET ligands in the porcine brain in vivo. All three candidate ligands were analyzed quantitatively with compartment analyses employing a plasma input function. [(11)C]GSK931145 showed good brain penetration and a heterogeneous distribution in agreement with reported GlyT1 localization. Following pretreatment with GSK565710, uptake of [(11)C]GSK931145 was reduced to homogeneous levels. Although [(11)C]GSK565710 also showed good brain penetration and a heterogeneous distribution, the apparent level of specific binding was reduced compared to [(11)C]GSK931145. In contrast, [(11)C]GSK991022 showed a much lower brain penetration and resultant signal following pretreatment with GSK565710. Based on these findings [(11)C]GSK931145 was identified as the most promising ligand for imaging GlyT1 in the porcine brain, possessing good brain penetration, specific signal, and reversible kinetics. [(11)C]GSK931145 is now being progressed into higher species.

Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy

We developed an anatomy-guided 4D closed-form algorithm to directly reconstruct parametric images from projection data for (nearly) irreversible tracers. Conventional methods consist of individually reconstructing 2D/3D PET data, followed by graphical analysis on the sequence of reconstructed image frames. The proposed direct reconstruction approach maintains the simplicity and accuracy of the expectation-maximization (EM) algorithm by extending the system matrix to include the relation between the parametric images and the measured data. A closed-form solution was achieved using a different hidden complete-data formulation within the EM framework. Furthermore, the proposed method was extended to maximum a posterior reconstruction via incorporation of MR image information, taking the joint entropy between MR and parametric PET features as the prior. Using realistic simulated noisy [(11)C]-naltrindole PET and MR brain images/data, the quantitative performance of the proposed methods was investigated. Significant improvements in terms of noise versus bias performance were demonstrated when performing direct parametric reconstruction, and additionally upon extending the algorithm to its Bayesian counterpart using the MR-PET joint entropy measure.

Reducing modeling error of graphical methods for estimating volume of distribution measurements in PIB-PET study

Graphical analysis methods are widely used in positron emission tomography quantification because of their simplicity and model independence. But they may, particularly for reversible kinetics, lead to bias in the estimated parameters. The source of the bias is commonly attributed to noise in the data. Assuming a two-tissue compartmental model, we investigate the bias that originates from modeling error. This bias is an intrinsic property of the simplified linear models used for limited scan durations, and it is exaggerated by random noise and numerical quadrature error. Conditions are derived under which Logan's graphical method either over-or under-estimates the distribution volume in the noise-free case. The bias caused by modeling error is quantified analytically. The presented analysis shows that the bias of graphical methods is inversely proportional to the dissociation rate. Furthermore, visual examination of the linearity of the Logan plot is not sufficient for guaranteeing that equilibrium has been reached. A new model which retains the elegant properties of graphical analysis methods is presented, along with a numerical algorithm for its solution. We perform simulations with the fibrillar amyloid beta radioligand [11C] benzothiazole-aniline using published data from the University of Pittsburgh and Rotterdam groups. The results show that the proposed method significantly reduces the bias due to modeling error. Moreover, the results for data acquired over a 70min scan duration are at least as good as those obtained using existing methods for data acquired over a 90min scan duration.