Genetic Polymorphisms in Organic Cation Transporter 1 Attenuates Hepatic Metformin Exposure in Humans.

Metformin has been used successfully to treat type 2 diabetes for decades. However, the efficacy of the drug varies considerably from patient to patient and this may in part be due to its pharmacokinetic properties. The aim of this study was to examine if common polymorphisms in SLC22A1, encoding the transporter protein OCT1, affect the hepatic distribution of metformin in humans. We performed noninvasive 11 C-metformin positron emission tomography (PET)/computed tomography (CT) to determine hepatic exposure in 12 subjects genotyped for variants in SLC22A1. Hepatic distribution of metformin was significantly reduced after oral intake in carriers of M420del and R61C variants in SLC22A1 without being associated with changes in circulating levels of metformin. Our data show that genetic polymorphisms in transporter proteins cause variation in hepatic exposure to metformin, and it demonstrates the application of novel imaging techniques to investigate pharmacogenetic properties in humans.

Point-spread function reconstructed PET images of sub-centimeter lesions are not quantitative.

BACKGROUND: PET image reconstruction methods include modeling of resolution degrading phenomena, often referred to as point-spread function (PSF) reconstruction. The aim of this study was to develop a clinically relevant phantom and characterize the reproducibility and accuracy of high-resolution PSF reconstructed images of small lesions, which is a prerequisite for using PET in the prediction and evaluation of responses to treatment. Sets of small homogeneous 18F-spheres (range 3-12 mm diameter, relevant for small lesions and lymph nodes) were suspended and covered by a 11C-silicone, which provided a scattering medium and a varying sphere-to-background ratio. Repeated measurements were made on PET/CT scanners from two vendors using a wide range of reconstruction parameters. Recovery coefficients (RCs) were measured for clinically used volume-of-interest definitions. RESULTS: For non-PSF images, RCs were reproducible and fell monotonically as the sphere diameter decreased, which is the expected behavior. PSF images converged slower and had artifacts: RCs did not fall monotonically as sphere diameters decreased but had a maximum RC for sphere sizes around 8 mm, RCs could be greater than 1, and RCs were less reproducible. To some degree, post-reconstruction filters could suppress PSF artifacts. CONCLUSIONS: High-resolution PSF images of small lesions showed artifacts that could lead to serious misinterpretations when used for monitoring treatment response. Thus, it could be safer to use non-PSF reconstruction for quantitative purposes unless PSF reconstruction parameters are optimized for the specific task.

Positron emission tomography of hepatic first-pass metabolism of ammonia in pig.

Hepatic first-pass metabolism plays a key role in metabolic regulation and drug metabolism. Metabolic processes can be quantified in vivo by positron emission tomography scanning (PET). We wished to develop a PET technique to measure hepatic first-pass metabolism of ammonia. Seven anaesthetised pigs were given positron-labelled ammonia, (13)NH(3), into the portal vein and into the vena cava as successive 2-min infusions followed by 22-min dynamic liver scanning. Vena cava infusion data were used to account for recirculation of tracer and metabolites following the portal vein infusion. The scan data were analysed by a model of sinusoidal zonation of ammonia metabolism with periportal urea formation and perivenous formation of glutamine. The hepatic extraction fraction of (13)NH(3) was 0.73+/-0.16 (mean+/-SD, n=7 pigs). Values of clearance of ammonia to urea and to glutamine were obtained, as were rate constants for washout of these two metabolites. Overall, the modelling showed half of the ammonia uptake to be converted to urea and half to glutamine. The washout rate constant for glutamine was about one-tenth of that for urea. We conclude that hepatic first-pass metabolism of ammonia was successfully assessed by PET.

Metabolites of (18)F-FDG and 3-O-(11)C-methylglucose in pig liver.

UNLABELLED: PET uses (18)F-FDG widely to estimate glucose metabolism in vivo. Dynamic PET data are evaluated by kinetic models of the metabolic pathways. Knowledge of the metabolites of FDG is of critical importance for the interpretation of kinetic PET studies. The purpose of this study was to determine the metabolic pathways of FDG and 3-O-(11)C-methylglucose (MG) in liver tissue in vivo. It is usually assumed that MG is not metabolized and FDG is converted to (18)F-FDG-6-phosphate (FDG-6-P). METHODS: The study was performed on 6 anesthetized 40-kg pigs that were given the 2 tracers intravenously. The content of metabolites was determined in successive liver tissue biopsies. Freeze-clamped liver tissue samples were subjected to extraction by acetonitrile at -5 degrees C to -10 degrees C, and extracts were analyzed by radio-high-performance liquid chromatography (radio-HPLC). The findings were identified by means of radio-HLPC measurements of the products of in vitro enzymatic reactions. RESULTS: The applied extraction technique provided almost quantitative recovery of the radioactivity from tissue. After MG injection, only MG was detectable in the liver tissue; no labeled metabolites were found. After FDG injection, 2 metabolites were identified, FDG-6-P and 2-(18)F-fluoro-2-deoxy-6-phosphogluconate (FD-6-PG1). The tissue content of FDG increased rapidly, and, after 5 min, only FDG was identified; hereafter, the fraction of FDG decreased to approximately 40% of the tissue radioactivity after 180 min. After 20 min, FDG-6-P was found in each of the pigs and it increased throughout the measurement period of 180 min, with a somewhat slower rise at late time points. FD-6-PG1 began to appear in the liver tissue after 45 min and increased throughout the 180-min experiment, with the increase somewhat slower than that of FDG-6-P. After 180 min, approximately 40% of the metabolites was attributed to FD-6-PG1. The content of other metabolites was <2%, even after 180 min. CONCLUSION: After the FDG injection, not only FDG-6-P but also FD-6-PG1 were formed in the liver. Any possible incorporation of FDG into glycogen was of minor importance.

Loss of metabolites from monkey striatum during PET with FDOPA.

The decarboxylation of 6-[(18)F]fluorodopa (FDOPA) and retention of the product [(18)F]fluorodopamine within vesicles of catecholamine fibers results in the labeling of dopamine-rich brain regions during FDOPA/PET studies. However, this metabolic trapping is not irreversible due to the eventual diffusion of [(18)F]fluorodopamine metabolites from brain. Consequently, time-radioactivity recordings of striatum are progressively influenced by metabolite loss. In linear analyses, the net blood-brain clearance of FDOPA (K(D)(i), ml g(-1) min(-1)) can be corrected for this loss by the elimination rate constant k(Lin)(cl) (min(-1)). Similarly, the DOPA decarboxylation rate constant (k(D)(3), min(-1)) calculated by compartmental analysis can also be corrected for metabolite loss by the elimination rate constant k(DA)(9) (min(-1)). To compare the two methods, we calculated the two elimination rate constants using data recorded during 240 min of FDOPA circulation in normal monkeys and in monkeys with unilateral 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) lesions. Use of the extended models increased the magnitudes of K(D)(i) and k(D)(3) in striatum; in the case of k(D)(3), variance of the estimate was substantially improved upon correction for metabolite loss. The rate constants for metabolite loss were higher in MPTP-lesioned monkey striatum than in normal striatum. The high correlation between individual estimates of k(Lin)(cl) and k(DA)(9) suggests that both rate constants reveal loss of decarboxylated metabolites from brain.

Liver kinetics of glucose analogs measured in pigs by PET: importance of dual-input blood sampling.

UNLABELLED: Metabolic processes studied by PET are quantified traditionally using compartmental models, which relate the time course of the tracer concentration in tissue to that in arterial blood. For liver studies, the use of arterial input may, however, cause systematic errors to the estimated kinetic parameters, because of ignorance of the dual blood supply from the hepatic artery and the portal vein to the liver. METHODS: Six pigs underwent PET after [15O]carbon monoxide inhalation, 3-O-[11C]methylglucose (MG) injection, and [18F]FDG injection. For the glucose scans, PET data were acquired for 90 min. Hepatic arterial and portal venous blood samples and flows were measured during the scan. The dual-input function was calculated as the flow-weighted input. RESULTS: For both MG and FDG, the compartmental analysis using arterial input led to systematic underestimation of the rate constants for rapid blood-tissue exchange. Furthermore, the arterial input led to absurdly low estimates for the extracellular volume compared with the independently measured hepatic blood volume of 0.25 +/- 0.01 mL/mL (milliliter blood per milliliter liver tissue). In contrast, the use of a dual-input function provided parameter estimates that were in agreement with liver physiology. Using the dual-input function, the clearances into the liver cells (K1 = 1.11 +/- 0.11 mL/min/mL for MG; K1 = 1.07 +/- 0.19 mL/min/mL for FDG) were comparable with the liver blood flow (F = 1.02 +/- 0.05 mL/min/mL). As required physiologically, the extracellular volumes estimated using the dual-input function were larger than the hepatic blood volume. The linear Gjedde-Patlak analysis produced parameter estimates that were unaffected by the choice of input function, because this analysis was confined to time scales for which the arterial-input and dual-input functions were very similar. CONCLUSION: Compartmental analysis of MG and FDG kinetics using dynamic PET data requires measurements of dual-input activity concentrations. Using the dual-input function, physiologically reasonable parameter estimates of K1, k2, and Vp were obtained, whereas the use of conventional arterial sampling underestimated these parameters compared with independent measurements of hepatic flow and hepatic blood volume. In contrast, the linear Gjedde-Patlak analysis, being less informative but more robust, gave similar parameter estimates (K, V) with both input functions.

Kinetics of the metabolism of four PET radioligands in living minipigs.

Most radioligands are substantially metabolised in peripheral organs during the course of positron emission tomography (PET) recordings. Accurate determination of plasma concentrations of unmetabolised radioligands is often important for quantification of data from PET studies. The fractions of untransformed radioligand and radioactive metabolites in plasma extracts must then be measured. Temporal changes in these fractions are influenced by the rate constant of appearance of total radioactive metabolites in plasma (apparent rate constant of metabolism in plasma, k(0)) and the net rate constant of elimination of all radioactive metabolites from plasma (k(-1)). In order to clarify the relationship between radioligand fractions and rate constants, plasma samples collected from Göttingen minipigs during PET recordings using four different binding site ligands were analysed by radio high performance liquid chromatography. The calculated plasma concentrations of parent compounds and their radioactive metabolites were used to calculate k(0) and k(-1) for 11C-labelled NNC 112, NS 2214, PK 11195 and raclopride in minipigs using a novel application of the tissue-slope intercept plot. In general, the apparent rate constant of metabolism in plasma was found to be greater in the minipig than in man. The reported kinetic analysis enables the apparent metabolism of PET radioligands in plasma to be quantified.

Dynamic 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography of liver tumours without blood sampling.

Positron emission tomography (PET) using 2-[18F]fluoro-2-deoxy-D-glucose (FDG) is a useful diagnostic tool for the detection of tumours. Using dynamic FDG PET, net metabolic clearance of FDG, K, can be calculated by Gjedde-Patlak analysis of the time course of the radioactivity concentrations in tissue and arterial blood. We examined whether time-activity curves (TACs) based on arterial blood sampling could be replaced by TACs obtained from the descending aorta in dynamic PET scans of patients with liver tumours. The study was performed in two parts, using data from dynamic liver scans with arterial blood sampling in human subjects: First, data from four patients with no liver tumours and five patients with liver tumours were used as a training group. Volumes of interest were defined in the descending aorta (aorta VOIs) by four different methods. K values were calculated based on the corresponding TACs and compared with those based on TACs of the arterial blood sample radioactivity concentrations. The aorta VOI which gave K values that were in best agreement with the K values based on the arterial blood sample measurements was called the AORTA-VOI. Use of the AORTA-VOI was subsequently tested in a test group of 19 tumour patients by comparing the K values from the AORTA-VOI with the K values based on the arterial blood sample measurements. The AORTA-VOI consisted of the sum of small regions of interest (ROIs) drawn in the centre of the aorta (approximately six pixels of 2.4x2.4 mm per transaxial slice of 3.1 mm thickness) in as many transaxial slices as possible (30-40 slices). There were no statistically significant differences between the two sets of K values. The ratio of K values in tumour tissue to K values in reference tissue was 2.1-9.7:1 (mean, 5.4:1) based on the AORTA TACs, and 2.1-8.4:1 (mean, 4.6:1) based on blood sample TACs (P>0.3). We conclude that arterial blood sampling can be replaced by the present AORTA-VOI in the calculation of the net metabolic clearance of FDG in dynamic PET studies of liver tumours in human subjects.