Two-tissue Compartment Model Research Articles

Estimation of kinetic parameters in dynamic FDG PET imaging based on shortened protocols: a virtual clinical study.

This study investigated the estimation of kinetic parameters and production of related parametric Ki images in FDG PET imaging using the proposed shortened protocol (three 3-min/bed routine static images) by means of the simulated annealing (SA) algorithm.Six realistic heterogeneous tumors and various levels of [18F] FDG uptake were simulated by the XCAT phantom. An irreversible two-tissue compartment model (2TCM) using population-based input function was employed. By keeping two routine clinical scans fixed (60-min and 90-min post injection), the effect of the early scan time on optimizing the estimation of the pharmacokinetic parameters was investigated. The SA optimization algorithm was applied to estimate micro- and macro-parameters (K1, k2, k3, Ki).The minimum bias for most parameters was observed at a scan time of 20-min, which was < 10%. A highly significant correlation (> 0.9) as well as limited bias (< 10%) were observed between kinetic parameters generated from twomethods [two-tissue compartment full dynamic scan (2TCM-full) and two-tissue compartment by SA algorithm (2TCM-SA)]. The analysis showed a strong correlation (> 0.8) between (2TCM-SA) Ki and SUV images. In addition, the tumor-to-background ratio (TBR) metric in the parametric (2TCM-SA) Ki images was significantly higher than SUV, although the SUV images provide better Contrast-to-noise ratio relative to parametric (2TCM-SA) Ki images.The proposed shortened protocol by the SA algorithm can estimate the kinetic parameters in FDG PET scan with high accuracy and robustness. It was also concluded that the parametric Ki images obtained from the 2TCM-SA as a complementary image of the SUV possess more quantification information than SUV images and can be used by the nuclear medicine specialist. This method has the potential to be an alternative to a full dynamic PET scan.

Assessing dynamic metabolic heterogeneity in prostate cancer patients via total-body [68Ga]Ga-PSMA-11 PET/CT imaging: quantitative analysis of [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs.

This study aimed to quantitatively assess [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs in prostate cancer using the total-body [68Ga]Ga-PSMA-11 PET/CT and to characterize the dynamic metabolic heterogeneity of prostate cancer. Dynamic total-body [68Ga]Ga-PSMA-11 PET/CT scans were performed on ten prostate cancer patients. Manual delineation of volume-of-interests (VOIs) was performed on multiple normal organs displaying high [68Ga]Ga-PSMA-11 uptake, as well as pathological lesions. Time-to-activity curves (TACs) were generated, and the four compartment models including one-tissue compartmental model (1T1k), reversible one-tissue compartmental model (1T2k), irreversible two-tissue compartment model (2T3k) and reversible two-tissue compartmental model (2T4k) were fitted to each tissue TAC. Various rate constants, including K1 (forward transport rate from plasma to the reversible compartment), k2 (reverse transport rate from the reversible compartment to plasma), k3 (tracer binding on the PSMA-receptor and its internalization), k4 (the externalization rate of the tracer) and Ki (net influx rate), were obtained. The selection of the optimal model for describing the uptake of both lesions and normal organs was determined using the Akaike information criteria (AIC). Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off values for differentiating physiological and pathological [68Ga]Ga-PSMA-11 uptake. Both 1T1k and 1T2k models showed relatively high AIC values compared to the 2T3k and 2T4k models in both pathological lesions and normal organs. The kinetic behavior of pathological lesions was better described by the 2T3k model compared to the 2T4k model, while the normal organs were better described by the 2T4k model. Significant variations in kinetic metrics, such as K1, k2, and k3, and Ki, were observed among normal organs with high [68Ga]Ga-PSMA-11 uptake and pathological lesions. The high Ki value in normal organs was primarily determined by elevated K1 and low k3, rather than k2. Conversely, the high Ki value in pathological lesions, ranking second to the kidney and similar to salivary glands and spleen, was predominantly determined by the highest k3 value. Notably, k3 exhibited the highest performance in distinguishing between physiological and pathological [68Ga]Ga-PSMA-11 uptake, with an area under the curve (AUC) of 0.844 (95% CI, 0.773-0.915), sensitivity of 82.9%, and specificity of 74.1%. The k3 values showed better performance than SUVmean (AUC, 0.659), SUVmax (AUC, 0.637), and other kinetic parameter including K1 (AUC, 0.604), k2 (AUC, 0.634), and Ki (AUC, 0.651). Significant discrepancies in kinetic metrics were detected between pathological lesions and normal organs, despite their shared high uptake of [68Ga]Ga-PSMA-11. Notably, the k3 value exhibits a noteworthy capability to distinguish between pathological lesions and normal organs with elevated [68Ga]Ga-PSMA-11 uptake. This discovery implies that k3 holds promise as a prospective imaging biomarker for distinguishing between pathologic and non-specific [68Ga]Ga-PSMA-11 uptake in patients with prostate cancer.

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice.

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[18F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [18F]Nifene, displaying similar pKa and binding affinity to nicotine. Time-activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

Optimization of Q.Clear reconstruction for dynamic 18F PET imaging

BackgroundQ.Clear, a Bayesian penalized likelihood reconstruction algorithm, has shown high potential in improving quantitation accuracy in PET systems. The Q.Clear algorithm controls noise during the iterative reconstruction through a β penalization factor. This study aimed to determine the optimal β-factor for accurate quantitation of dynamic PET scans.MethodsA Flangeless Esser PET Phantom with eight hollow spheres (4–25 mm) was scanned on a GE Discovery MI PET/CT system. Data were reconstructed into five sets of variable acquisition times using Q.Clear with 18 different β-factors ranging from 100 to 3500. The recovery coefficient (RC), coefficient of variation (CVRC) and root-mean-square error (RMSERC) were evaluated for the phantom data. Two male patients with recurrent glioblastoma were scanned on the same scanner using 18F-PSMA-1007. Using an irreversible two-tissue compartment model, the area under curve (AUC) and the net influx rate Ki were calculated to assess the impact of different β-factors on the pharmacokinetic analysis of clinical PET brain data.ResultsIn general, RC and CVRC decreased with increasing β-factor in the phantom data. For small spheres (< 10 mm), and in particular for short acquisition times, low β-factors resulted in high variability and an overestimation of measured activity. Increasing the β-factor improves the variability, however at a cost of underestimating the measured activity. For the clinical data, AUC decreased and Ki increased with increased β-factor; a change in β-factor from 300 to 1000 resulted in a 25.5% increase in the Ki.ConclusionIn a complex dynamic dataset with variable acquisition times, the optimal β-factor provides a balance between accuracy and precision. Based on our results, we suggest a β-factor of 300–500 for quantitation of small structures with dynamic PET imaging, while large structures may benefit from higher β-factors.Trial registrationClinicaltrials.gov, NCT03951142. Registered 5 October 2019, https://clinicaltrials.gov/ct2/show/NCT03951142. EudraCT no 2018-003229-27. Registered 26 February 2019, https://www.clinicaltrialsregister.eu/ctr-search/trial/2018-003229-27/NO.

Comparison of parametric imaging and SUV imaging with [68Ga]Ga-PSMA-11 using dynamic total-body PET/CT in prostate cancer.

Standardized uptake value (SUV) has been prevalently used to measure [68Ga]Ga-PSMA-11 activity in prostate cancer, but it is susceptible to multiple factors. Parametric imaging allows for absolute quantification of tracer uptake and provides a better diagnostic accuracy that is crucial for lesion detection. However, the clinical significance of total-body parametric imaging of [68Ga]Ga-PSMA-11 remains to be fully assessed. Therefore, the aim of our study is to delve into the diagnostic implications of total-body parametric imaging of [68Ga]Ga-PSMA-11 PET/CT for patients with prostate cancer. Twenty prostate cancer patients were included and underwent a dynamic total-body [68Ga]Ga-PSMA-11 PET/CT scan. An irreversible two-tissue compartment model (2T3k) was fitted for each tissue time-to-activity curve, and the net influx rate (Ki) was obtained. The image quality and semi-quantitative analysis of lesion-to-background ratio (LBR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between parametric images and SUV images. Kinetic modeling using 2T3k demonstrated favorable model fitting in both normal organs and lesions. All of the lesions detected on SUV images (55-60min) could be detected on Ki images. The correlation between Ki, SUVmean, and SUVmax in both normal organs and pathological lesions was found to be positive and statistically significant. Conversely, a moderate positive correlations were found between Ki and K1 (R = 0.69, P < 0.001; R = 0.61, P < 0.001) and Ki and k3 (R = 0.69, P < 0.001; R = 0.62, P < 0.001), in normal organs and pathological lesions, respectively. Visual assessment in Ki images showed less image noise and higher lesions conspicuity compared to SUV images. Ki image-derived LBR, SNR, and CBR of pathological lesions including primary tumors (PTs), lymph node metastases (LNMs) and bone metastases (BMs), exhibited remarkably higher folds (1.4-3.6 folds) compared to those derived from SUV of corresponding lesions. Total-body parametric imaging of [68Ga]Ga-PSMA-11 enhanced lesion contrast and improved lesion detectability compared to SUV images. This may potentially serve as an imaging biomarker and theranostic tool for precise diagnosis and treatment evaluation in prostate cancer patients.

Dispersion-corrected extracorporeal arterial input functions in PET studies of mice: a comparison to intracorporeal microprobe measurements

BackgroundKinetic modelling of dynamic PET typically requires knowledge of the arterial radiotracer concentration (arterial input function, AIF). Its accurate determination is very difficult in mice. AIF measurements in an extracorporeal shunt can be performed; however, this introduces catheter dispersion. We propose a framework for extracorporeal dispersion correction and validated it by comparison to invasively determined intracorporeal AIFs using implanted microprobes.ResultsThe response of an extracorporeal radiation detector to radioactivity boxcar functions, characterised by a convolution-based dispersion model, gave best fits using double-gamma variate and single-gamma variate kernels compared to mono-exponential kernels for the investigated range of flow rates. Parametric deconvolution with the optimal kernels was performed on 9 mice that were injected with a bolus of 39 ± 25 MBq [18F]F-PSMA-1007 after application of an extracorporeal circulation for three different flow rates in order to correct for dispersion. Comparison with synchronous implantation of microprobes for invasive aortic AIF recordings showed favourable correspondence, with no significant difference in terms of area-under-curve after 300 s and 5000 s. One-tissue and two-tissue compartment model simulations were performed to investigate differences in kinetic parameters between intra- and extracorporeally measured AIFs. Results of the modelling study revealed kinetic parameters close to the chosen simulated values in all compartment models.ConclusionThe high correspondence of simultaneously intra- and extracorporeally determined AIFs and resulting model parameters establishes a feasible framework for extracorporeal dispersion correction. This should allow more precise and accurate kinetic modelling in small animal experiments.

Quantification of P-glycoprotein function at the human blood-brain barrier using [18F]MC225 and PET

IntroductionP-glycoprotein (P-gp) is one of the most studied efflux transporters at the blood-brain barrier. It plays an important role in brain homeostasis by protecting the brain from a variety of endogenous and exogeneous substances. Changes in P-gp function are associated both with the onset of neuropsychiatric diseases, including Alzheimer’s disease and Parkinson’s disease, and with drug-resistance, for example in treatment-resistant depression. The most widely used approach to measure P-gp function in vivo is (R)-[11C]verapamil PET. (R)-[11C]verapamil is, however, an avid P-gp substrate, which complicates the use of this tracer to measure an increase in P-gp function as its baseline uptake is already very low. [18F]MC225 was developed to measure both increases and decreases in P-gp function.AimThe aim of this study was (1) to identify the pharmacokinetic model that best describes [18F]MC225 kinetics in the human brain and (2) to determine test-retest variability.MethodsFive (2 male, 3 female) of fourteen healthy subjects (8 male, 6 female, age 67 ± 5 years) were scanned twice (injected dose 201 ± 47 MBq) with a minimum interval of 2 weeks between scans. Each scanning session consisted of a 60-min dynamic [18F]MC225 scan with continuous arterial sampling. Whole brain grey matter data were fitted to a single tissue compartment model, and to reversible and irreversible two tissue-compartment models to obtain various outcome parameters (in particular the volume of distribution (VT), Ki, and the rate constants K1 and k2). In addition, a reversible two-tissue compartment model with fixed k3/k4 was included. The preferred model was selected based on the weighted Akaike Information Criterion (AIC) score. Test-retest variability (TRTV) was determined to assess reproducibility.ResultsSixty minutes post-injection, the parent fraction was 63.8 ± 4.0%. The reversible two tissue compartment model corrected for plasma metabolites with an estimated blood volume (VB) showed the highest AIC weight score of 34.3 ± 17.6%. The TRVT of the VT for [18F]MC225 PET scans was 28.3 ± 20.4% for the whole brain grey matter region using this preferred model.Conclusion[18F]MC225 VT, derived using a reversible two-tissue compartment model, is the preferred parameter to describe P-gp function in the human BBB. This outcome parameter has an average test-retest variability of 28%.Trial registrationEudraCT 2020-001564-28. Registered 25 May 2020.

Parametric maps of spatial two-tissue compartment model for prostate dynamic contrast enhanced MRI - comparison with the standard tofts model in the diagnosis of prostate cancer.

The spatial two-tissue compartment model (2TCM) was used to analyze prostate dynamic contrast enhanced (DCE) MRI data and compared with the standard Tofts model. A total of 29 patients with biopsy-confirmed prostate cancer were included in this IRB-approved study. MRI data were acquired on a Philips Achieva 3T-TX scanner. After T2-weighted and diffusion-weighted imaging, DCE data using 3D T1-FFE mDIXON sequence were acquired pre- and post-contrast media injection (0.1 mmol/kg Multihance) for 60 dynamic scans with temporal resolution of 8.3s/image. The 2TCM has one fast ([Formula: see text] and [Formula: see text]) and one slow ([Formula: see text] and [Formula: see text]) exchanging compartment, compared with the standard Tofts model parameters (Ktrans and kep). On average, prostate cancer had significantly higher values (p < 0.01) than normal prostate tissue for all calculated parameters. There was a strong correlation (r = 0.94, p < 0.001) between Ktrans and [Formula: see text] for cancer, but weak correlation (r = 0.28, p < 0.05) between kep and [Formula: see text]. Average root-mean-square error (RMSE) in fits from the 2TCM was significantly smaller (p < 0.001) than the RMSE in fits from the Tofts model. Receiver operating characteristic (ROC) analysis showed that fast [Formula: see text] had the highest area under the curve (AUC) than any other individual parameter. The combined four parameters from the 2TCM had a considerably higher AUC value than the combined two parameters from the Tofts model. The 2TCM is useful for quantitative analysis of prostate DCE-MRI data and provides new information in the diagnosis of prostate cancer.

Synaptic density in aging mice measured by [18F]SynVesT-1 PET

Synaptic alterations in certain brain structures are related to cognitive decline in neurodegeneration and in aging. Synaptic loss in many neurodegenerative diseases can be visualized by positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A). However, the use of SV2A PET for studying synaptic changes during aging is not particularly explored. Thus, in the present study, PET ligand [18F]SynVesT-1, which binds to SV2A, was used to investigate synaptic density at different ages in healthy mice.Wild type C57BL/6 mice divided into three age groups (4–5 months (n = 7), 12–14 months (n = 11), 17–19 months (n = 7)) were PET scanned with [18F]SynVesT-1. Brain retention of [18F]SynVesT-1 expressed as the volume of distribution (VIDIF) was calculated using an image-derived input function. Estimates of VIDIF were derived using either a one-tissue compartment model (1TCM), a two-tissue compartment model (2TCM), or the Logan plot with blood input to find the best-fit model for [18F]SynVesT-1. After the PET scans, tissue sections were immunostained for the detection of SV2A and neuronal markers.We found that [18F]SynVesT-1 data acquired 60 min post intravenously injection and analyzed with 1TCM described the brain pharmacokinetics of the radioligand in mice well. [18F]SynVesT-1 brain retention was lower in the oldest group of mice, indicating a decrease in synaptic density in this age group. However, no gradual age-dependent decrease in synaptic density at a region-specific level was observed. Immunostaining indicated that SV2A expression and neuron numbers were similar across all three age groups. In general, these data obtained in healthy aging mice are consistent with previous findings in humans where synaptic density appeared stable during aging up to a certain age, after which a small decrease is observed.

In vivo evaluation of a novel 18F-labeled PET radioligand for translocator protein 18 kDa (TSPO) in monkey brain

Purpose[18F]SF51 was previously found to have high binding affinity and selectivity for 18 kDa translocator protein (TSPO) in mouse brain. This study sought to assess the ability of [18F]SF51 to quantify TSPO in rhesus monkey brain.MethodsPositron emission tomography (PET) imaging was performed in monkey brain (n = 3) at baseline and after pre-blockade with the TSPO ligands PK11195 and PBR28. TSPO binding was calculated as total distribution volume corrected for free parent fraction in plasma (VT/fP) using a two-tissue compartment model. Receptor occupancy and nondisplaceable uptake were determined via Lassen plot. Binding potential (BPND) was calculated as the ratio of specific binding to nondisplaceable uptake. Time stability of VT was used as an indirect probe to detect radiometabolite accumulation in the brain. In vivo and ex vivo experiments were performed in mice to determine the distribution of the radioligand.ResultsAfter [18F]SF51 injection, the concentration of brain radioactivity peaked at 2.0 standardized uptake value (SUV) at ~ 10 min and declined to 30% of the peak at 180 min. VT/fP at baseline was generally high (203 ± 15 mL· cm−3) and decreased by ~ 90% after blockade with PK11195. BPND of the whole brain was 7.6 ± 4.3. VT values reached levels similar to terminal 180-min values by 100 min and remained relatively stable thereafter with excellent identifiability (standard errors < 5%), suggesting that no significant radiometabolites accumulated in the brain. Ex vivo experiments in mouse brain showed that 96% of radioactivity was parent. No significant uptake was observed in the skull, suggesting a lack of defluorination in vivo.ConclusionThe results demonstrate that [18F]SF51 is an excellent radioligand that can quantify TSPO with a good ratio of specific to nondisplaceable uptake and has minimal radiometabolite accumulation in brain. Collectively, the results suggest that [18F]SF51 warrants further evaluation in humans.

Metabolic kinetic modeling of [11C]methionine based on total-body PET in multiple myeloma.

Multiple myeloma (MM) is a malignant disease characterized by the secretion of monoclonal immunoglobulins and has a high demand for amino acids. [11C]methionine total-body PET is capable of noninvasive dynamic monitoring of radiotracer in vivo, thus providing a way to reveal the dynamic changes of myeloma metabolism. This study aims to analyze the metabolic process of [11C]methionine based on kinetic modeling, and to preliminary reveal its application value in MM. Dynamic total-body [11C]methionine PET/CT was conducted with uEXPLORER in 12 subjects (9 MM patients and 3 controls). The tissue time activity curves (TACs) of organs and bone marrows were extracted. Model fitting of TACs was operated using PMOD Kinetic Modeling. After validation by Goodness of fit (GOF), the reversible two-tissue compartment model (2T4k) was used to further analysis. R software was used to analyze the correlation between kinetic parameters and clinical indicators. The 2T4k has passed the criterion of GOF and was used to fit the data of 0-20 minutes. The [11C]methionine net uptake rate (Ki) was significantly higher in the MM lesions than in the non-myeloma controls (control: 0.040±0.007 mL/g/min, MM: 0.171±0.108 mL/g/min, p=0.009). The Ki values were found to be correlated with M protein levels in MM patients. MM patients with t(4;14) translocations had an elevated k4 value compared with t(4;14) negative patients. MM lesions have a propensity for uptake of [11C]methionine. The serum levels of M protein are correlated with [11C]methionine uptake rate in myeloma. Metabolic classification based on the k4 value may be a promising strategy for risk stratification in MM.

Diagnostic value of dynamic 18F-FDG PET/CT imaging in non-small cell lung cancer and FDG hypermetabolic lymph nodes.

We aimed to investigate the diagnostic value of dynamic 2-deoxy-2-[18F]-fluoro-D-glucose positron emission tomography-computed tomography in non-small cell lung cancer and fluoro-D-glucose hypermetabolic lymph nodes. Patients who made an active appointment for positron emission tomography-computed tomography were randomly enrolled by referring to previous imaging data and clinical information. Finally, 34 histopathologically confirmed non-small cell lung cancers (18 adenocarcinoma and 16 squamous cell carcinoma cases) were prospectively studied using dynamic and static 2-deoxy-2-[18F]-fluoro-D-glucose positron emission tomography-computed tomography imaging (the diagnostic study has not yet been registered on a clinical trial platform). In dynamic positron emission tomography images, a volume of interest, defined by the thoracic aorta, was selected for estimating the arterial input function. Patlak and irreversible two-tissue compartment model analyses were performed based on the pixel points to obtain first-order characteristic kinetic parameters for each lesion and hypermetabolic lymph node. The first-order characteristic kinetic parameters were obtained based on the basic data of dynamic positron emission tomography images in the corresponding model and the lesion delineation of region-of-interest based on computed tomography images, such as V_Median (the median gray intensity of V), k3_Entropy, VB_Entropy, K1_Uniformity, and ki_Uniformity. The first-order characteristic kinetic parameters were also modeled by logistic regression for the differential diagnosis of non-small cell lung cancer and hypermetabolic lymph nodes. Maximum and mean standard uptake values (SUVmax and SUVmean, respectively) were obtained from static positron emission tomography images. The diagnostic efficacy of the parameters was evaluated using the receiver operating characteristic curve and the DeLong test. There was a significant difference in the V_Median values of adenocarcinoma and squamous cell carcinoma. The regression models for K1, k3, and V provided good predictions of adenocarcinoma and squamous cell carcinoma typology. Significant differences were observed in k3_Entropy, VB_Entropy, K1_Uniformity, and ki_Uniformity between benign and malignant lymph nodes. The regression model of Ki, VB, and k3 could make a good prediction for identifying benign and malignant lymph nodes. Dynamic 2-deoxy-2-[18F]-fluoro-D-glucose positron emission tomography-computed tomography imaging showed high diagnostic value in the staging of non-small cell lung cancer and fluoro-D-glucose hypermetabolic lymph nodes, and can be of great use in non-small cell lung cancer lymph node staging and surgical decision-making.

Quantitative assessment of translocator protein (TSPO) in the non-human primate brain and clinical translation of [18F]LW223 as a TSPO-targeted PET radioligand

ObjectivesTranslocator protein 18 kDa (TSPO) positron emission tomography (PET) can be harnessed for the non-invasive detection of macrophage-driven inflammation. [18F]LW223, a newly reported TSPO PET tracer which was insensitive to rs6971 polymorphism, showed favorable performance characteristics in a recent imaging study involving a rat myocardial infarction model. To enable quantitative neuroimaging with [18F]LW223, we conducted kinetic analysis in the non-human primate (NHP) brain. Further, we sought to assess the utility of [18F]LW223-based TSPO imaging in a first-in-human study. MethodsRadiosynthesis of [18F]LW223 was accomplished on an automated module, whereas molar activities, stability in formulation, lipophilicity and unbound free fraction (fu) of the probe were measured. Brain penetration and target specificity of [18F]LW223 in NHPs were corroborated by PET-MR imaging under baseline and pre-blocking conditions using the validated TSPO inhibitor, (R)-PK11195, at doses ranging from 5 to 10 mg/kg. Kinetic modeling was performed using one-tissue compartment model (1TCM), two-tissue compartment model (2TCM) and Logan graphical analyses, using dynamic PET data acquisition, arterial blood collection and metabolic stability testing. Clinical PET scans were performed in two healthy volunteers (HVs). Regional brain standard uptake value ratio (SUVr) was assessed for different time intervals. Results[18F]LW223 was synthesized in non-decay corrected radiochemical yields (n.d.c. RCYs) of 33.3 ± 6.5% with molar activities ranging from 1.8 ± 0.7 Ci/µmol (n = 11). [18F]LW223 was stable in formulation for up to 4 h and LogD7.4 of 2.31 ± 0.13 (n = 6) and fu of 5.80 ± 1.42% (n = 6) were determined. [18F]LW223 exhibited good brain penetration in NHPs, with a peak SUV value of ca. 1.79 in the whole brain. Pre-treatment with (R)-PK11195 substantially accelerated the washout and attenuated the area under the time-activity curve, indicating in vivo specificity of [18F]LW223 towards TSPO. Kinetic modeling demonstrated that 2TCM was the most suitable model for [18F]LW223-based neuroimaging. Global transfer rate constants (K1) and total volumes of distribution (VT) were found to be 0.10 ± 0.01 mL/cm3/min and 2.30 ± 0.17 mL/cm3, respectively. Dynamic PET data analyses across distinct time windows revealed that the VT values were relatively stable after 60 min post-injection. In a preliminary clinical study with two healthy volunteers, [18F]LW223 exhibited good brain uptake and considerable tracer retention across all analyzed brain regions. Of note, an excellent correlation between SUVr with VT was obtained when assessing the time interval from 20 to 40 min post tracer injection (SUVr(20–40 min), R2 = 0.94, p < 0.0001), suggesting this time window may be suitable to estimate specific binding to TSPO in human brain. ConclusionOur findings indicate that [18F]LW223 is suitable for quantitative TSPO-targeted PET imaging in higher species. Employing state-of-the-art kinetic modeling, we found that [18F]LW223 was effective in mapping TSPO throughout the NHP brain, with best model fits obtained from 2TCM and Logan graphical analyses. Overall, our results indicate that [18F]LW223 exhibits favorable tracer performance characteristics in higher species, and this novel imaging tool may hold promise to provide effective neuroinflammation imaging in patients with neurological disease.

In Vivo Imaging and Kinetic Modeling of Novel Glycogen Synthase Kinase-3 Radiotracers [11C]OCM-44 and [18F]OCM-50 in Non-Human Primates.

Glycogen synthase kinase 3 (GSK-3) is a potential therapeutic target for a range of neurodegenerative and psychiatric disorders. The goal of this work was to evaluate two leading GSK-3 positron emission tomography (PET) radioligands, [11C]OCM-44 and [18F]OCM-50, in non-human primates to assess their potential for clinical translation. A total of nine PET scans were performed with the two radiotracers using arterial blood sampling in adult rhesus macaques. Brain regional time-activity curves were extracted and fitted with one- and two-tissue compartment models using metabolite-corrected arterial input functions. Target selectivity was assessed after pre-administration of the GSK-3 inhibitor PF-04802367 (PF-367, 0.03-0.25 mg/kg). Both radiotracers showed good brain uptake and distribution throughout grey matter. [11C]OCM-44 had a free fraction in the plasma of 3% at baseline and was metabolized quickly. The [11C]OCM-44 volume of distribution (VT) values in the brain increased with time; VT values from models fitted to truncated 60-min scan data were 1.4-2.9 mL/cm3 across brain regions. The plasma free fraction was 0.6% for [18F]OCM-50 and VT values (120-min) were 0.39-0.87 mL/cm3 in grey matter regions. After correcting for plasma free fraction increases during blocking scans, reductions in regional VT indicated >80% target occupancy by 0.1 mg/kg of PF-367 for both radiotracers, supporting target selectivity in vivo. [11C]OCM-44 and [18F]OCM-50 warrant further evaluation as radioligands for imaging GSK-3 in the brain, though radio-metabolite accumulation may confound image analysis.

18F]F13640: a selective agonist PET radiopharmaceutical for imaging functional 5-HT1A receptors in humans

PurposeF13640 (a.k.a. befiradol, NLX-112) is a highly selective 5-HT1A receptor ligand that was selected as a PET radiopharmaceutical-candidate based on animal studies. Due to its high efficacy agonist properties, [18F]F13640 binds preferentially to functional 5-HT1A receptors, which are coupled to intracellular G-proteins. Here, we characterize brain labeling of 5-HT1A receptors by [18F]F13640 in humans and describe a simplified model for its quantification.MethodsPET/CT and PET-MRI scans were conducted in a total of 13 healthy male volunteers (29 ± 9 years old), with arterial input functions (AIF) (n = 9) and test–retest protocol (n = 8). Several kinetic models were compared (one tissue compartment model, two-tissue compartment model, and Logan); two models with reference region were also evaluated: simplified reference tissue model (SRTM) and the logan reference model (LREF).Results[18F]F13640 showed high uptake values in raphe nuclei and cortical regions. SRTM and LREF models showed a very high correlation with kinetic models using AIF. As concerns test–retest parameters and the prolonged binding kinetics of [18F]F13640, better reproducibility, and reliability were found with the LREF method. Cerebellum white matter and frontal lobe white matter stand out as suitable reference regions.ConclusionThe favorable brain labeling and kinetic profile of [18F]F13640, its high receptor specificity and its high efficacy agonist properties open new perspectives for studying functionally active 5-HT1A receptors, unlike previous radiopharmaceuticals that act as antagonists. [18F]F13640’s kinetic properties allow injection outside of the PET scanner with delayed acquisitions, facilitating the design of innovative longitudinal protocols in neurology and psychiatry.Trial Registration.Trial Registration EudraCT 2017–002,722-21.

Dynamic Total-Body PET/CT Imaging Reveals Kinetic Distribution of 68Ga-DOTATATE in Normal Organs.

To investigate the biodistribution and kinetic constants of 68Ga-DOTATATE in normal organs through dynamic total-body positron emission tomography/computed tomography (PET/CT). Seven patients who experienced endoscopic resection of gastric neuroendocrine tumor were enrolled. Dynamic total-body PET/CT scans over 60 min were performed. Time-activity curves were obtained by drawing regions of interest in normal organs. Rate constants, including K 1, k 2, k 3, and vB, were computed using a two-tissue compartment model. Factor analysis was used to compare the rate constants among subjects and regions. Hierarchical cluster analysis was performed to identify organs with similar kinetic characteristics. The highest uptake of 68Ga-DOTATATE was observed in the spleen followed by kidneys, adrenals, liver, pituitary gland, pancreas head, prostate, pancreas body, and thyroid, parotid, and submandibular glands. Low background level of 68Ga-DOTATATE uptake was observed in the nasal mucosa, bone, blood pool, and cerebrum. In addition, the uptake in the pancreas head was noted to be higher than the pancreas body (P < 0.001) on the basis of each time point of dynamic PET. There were differences of rate constants among different organs. The mean K 1 ranged from 0.0507 min-1 in the left nasal mucosa to 1.21 min-1 in the left kidney, and mean k 2 ranged from 0.0174 min-1 in the spleen to 4.4487 min-1 in the left cerebrum. The mean k 3 ranged from 0.0563 min-1 in the right cerebrum to 4.6309 min-1 in the left adrenal, and mean vB ranged from 0.0001 in the left cerebrum to 0.2489 in the right adrenal. However, none of the rate constants was significantly different among subjects or among different sites within a single organ. Three groups of organs with similar kinetic characteristics were identified: (1) cerebrum; (2) pituitary gland, liver, adrenal, and prostate; and (3) nasal mucosa, parotid and submandibular glands, thyroid, spleen, pancreas, kidney, and bone. Uptake and clearance of 68Ga-DOTATATE, in terms of kinetic constants, were different in different organs. The kinetic parameters of 68Ga-DOTATATE in different organs provide a reference for future dynamic PET imaging.

Small-animal PET study for noninvasive quantification of transmembrane AMPA receptor regulatory protein γ-8 (TARP γ-8) in the brain

Transmembrane AMPA receptor regulatory protein γ-8 (TARP γ-8) mediates various AMPA receptor functions. Recently, [11C]TARP-2105 was developed as a PET ligand for TARP γ-8 imaging. We performed a full kinetic analysis of [11C]TARP-2105 using PET with [11C]TARP-2105 for the first time. The distribution volume (VT), which is a macro parameter consisting of the K1–k4 rate constants in the two-tissue compartment model analysis, exhibited the following rank order: hippocampus (1.4 ± 0.3) > amygdala (1.0 ± 0.2) > frontal cortex (0.9 ± 0.2) > striatum (0.8 ± 0.2) ≫ cerebellum (0.5 ± 0.1) ≈ thalamus (0.5 ± 0.1) > pons (0.4 ± 0.1 mL/cm3). These heterogenous VT values corresponded with the order of biological distribution of TARP γ-8 in the brain. To validate the reference tissue model, the binding potential (BPND) of [11C]TARP-2105 for TARP γ-8 was estimated using general methods (SRTM, MRTM0, Logan reference model, and ratio method). These BPNDs based on reference models indicated excellent correlation (R2 > 0.9) to the indirect BPNDs based on 2TCM with moderate reproducibility (%variability ≈ 10). PET with [11C]TARP-2105 enabled noninvasive BPND estimation and visual mapping of TARP γ-8 in the living rat brain.

Development of a minimally invasive simultaneous estimation method for quantifying translocator protein binding with [18F]FEPPA positron emission tomography

BackgroundThe purpose of this study was to assess the feasibility of using a minimally invasive simultaneous estimation method (SIME) to quantify the binding of the 18-kDa translocator protein tracer [18F]FEPPA. Arterial sampling was avoided by extracting an image-derived input function (IDIF) that was metabolite-corrected using venous blood samples. The possibility of reducing scan duration to 90 min from the recommended 2–3 h was investigated by assuming a uniform non-displaceable distribution volume (VND) to simplify the SIME fitting.ResultsSIME was applied to retrospective data from healthy volunteers and was comprised of both high-affinity binders (HABs) and mixed-affinity binders (MABs). Estimates of global VND and regional total distribution volume (VT) from SIME were not significantly different from values obtained using a two-tissue compartment model (2CTM). Regional VT estimates were greater for HABs compared to MABs for both the 2TCM and SIME, while the SIME estimates had lower inter-subject variability (41 ± 17% reduction). Binding potential (BPND) values calculated from regional VT and brain-wide VND estimates were also greater for HABs, and reducing the scan time from 120 to 90 min had no significant effect on BPND. The feasibility of using venous metabolite correction was evaluated in a large animal model involving a simultaneous collection of arterial and venous samples. Strong linear correlations were found between venous and arterial measurements of the blood-to-plasma ratio and the remaining [18F]FEPPA fraction. Lastly, estimates of BPND and the specific distribution volume (i.e., VS = VT − VND) from a separate group of healthy volunteers (90 min scan time, venous-scaled IDIFs) agreed with estimates from the retrospective data for both genotypes.ConclusionsThe results of this study demonstrate that accurate estimates of regional VT, BPND and VS can be obtained by applying SIME to [18F]FEPPA data. Furthermore, the application of SIME enabled the scan time to be reduced to 90 min, and the approach worked well with IDIFs that were scaled and metabolite-corrected using venous blood samples.

Evaluation of [18F]PF-06455943 as a Potential LRRK2 PET Imaging Agent in the Brain of Nonhuman Primates.

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are the common causes of inherited Parkinson's disease (PD) and emerged as a causative PD gene. Particularly, LRRK2-Gly2019Ser mutation was reported to alter the early phase of neuronal differentiation, increasing cell death. Selective inhibitors of LRRK2 kinase activity were considered as a promising therapeutic target for PD treatment. However, the development of effective brain-penetrant LRRK2 inhibitors remains challenging. Recently, we have developed a novel positron emission tomography (PET) radioligand for LRRK2 imaging and demonstrated preferable tracer properties in rodents. Herein, we evaluate [18F]PF-06455943 quantification methods in the nonhuman primate (NHP) brain using full kinetic modeling with radiometabolite-corrected arterial blood samples, and homologous blocking with two doses (0.1 and 0.3 mg/kg). Kinetic analysis results demonstrated that a two-tissue compartmental model and a Logan graphical analysis are appropriate for [18F]PF-06455943 PET quantification. In addition, we observed that total distribution volume (VT) values can be reliably estimated with as short as a 30 min scan duration. Homologous blocking studies confirmed the specific binding of [18F]PF-06455943 and revealed that the nonradioactive mass of PF-06455943 achieved 45-55% of VT displacement in the whole brain. This work supports the translation of [18F]PF-06455943 PET imaging for the human brain and target occupancy studies.

Dynamic FDG-PET imaging for differentiating metastatic from non-metastatic lymph nodes of lung cancer.

18F-fluorodeoxyglucose (FDG) PET/CT has been widely used in tumor diagnosis, staging, and response evaluation. To determine an optimal therapeutic strategy for lung cancer patients, accurate staging is essential. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may fail to differentiate between benign and malignant lesions. Lymph nodes (LNs) in the mediastinal and pulmonary hilar regions with high FDG uptake due to granulomatous lesions such as tuberculosis, which has a high prevalence in China, pose a diagnostic challenge. This study aims to evaluate the diagnostic value of the quantitative metabolic parameters derived from dynamic 18F-FDG PET/CT in differentiating metastatic and non-metastatic LNs in lung cancer. One hundred and eight patients with pulmonary nodules were enrolled to perform 18F-FDG PET/CT dynamic + static imaging with informed consent. One hundred and thirty-five LNs in 29 lung cancer patients were confirmed by pathology. Static image analysis parameters including LN-SUVmax, LN-SUVmax/primary tumor SUVmax (LN-SUVmax/PT-SUVmax), mediastinal blood pool SUVmax (MBP-SUVmax), LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter. Quantitative parameters including K1, k2, k3 and Ki and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. Ki/K1 was computed subsequently as a separate marker. We further divided the LNs into mediastinal LNs (N=82) and pulmonary hilar LNs (N=53). Wilcoxon rank-sum test or Independent-samples T-test and receiver-operating characteristic (ROC) analysis was performed on each parameter to compare the diagnostic efficacy in differentiating lymph node metastases from inflammatory uptake. P<0.05 were considered statistically significant. Among the 135 FDG-avid LNs confirmed by pathology, 49 LNs were non-metastatic, and 86 LNs were metastatic. LN-SUVmax, MBP-SUVmax, LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter couldn't well differentiate metastatic from non-metastatic LNs (P>0.05). However, LN-SUVmax/PT-SUVmax have good performance in the differential diagnosis of non-metastatic and metastatic LNs (P=0.039). Dynamic metabolic parameters in addition to k3, the parameters including K1, k2, Ki, and Ki/K1, on the other hand, have good performance in the differential diagnosis of metastatic and non-metastatic LNs (P=0.045, P=0.001, P=0.001, P=0.001, respectively). For ROC analysis, the metabolic parameters Ki (AUC of 0.672 [0.579-0.765], sensitivity 0.395, specificity 0.918) and Ki/K1 (AUC of 0.673 [0.580-0.767], sensitivity 0.570, specificity 0.776) have good performance in the differential diagnosis of metastatic from non-metastatic LNs than SUVmax (AUC of 0.596 [0.498-0.696], sensitivity 0.826, specificity 0.388), included the mediastinal region and pulmonary hilar region. Compared with SUVmax, quantitative parameters such as K1, k2, Ki and Ki/K1 showed promising results for differentiation of metastatic and non-metastatic LNs with high uptake. The Ki and Ki/K1 had a high differential diagnostic value both in the mediastinal region and pulmonary hilar region.