Population-based input function modeling for [(18)F]FMPEP-d 2, an inverse agonist radioligand for cannabinoid CB1 receptors: validation in clinical studies

Non-Invasive Quantification of the Brain [¹⁸F]FDG-PET Using Inferred Blood Input Function Learned From Total-Body Data With Physical Constraint

Full quantification of brain PET requires the blood input function (IF), which is traditionally achieved through an invasive and time-consuming arterial catheter procedure, making it unfeasible for clinical routine. This study presents a deep learning based method to estimate the input function (DLIF) for a dynamic brain FDG scan. A long short-term memory combined with a fully connected network was used. The dataset for training was generated from 85 total-body dynamic scans obtained on a uEXPLORER scanner. Time-activity curves from 8 brain regions and the carotid served as the input of the model, and labelled IF was generated from the ascending aorta defined on CT image. We emphasize the goodness-of-fitting of kinetic modeling as an additional physical loss to reduce the bias and the need for large training samples. DLIF was evaluated together with existing methods in terms of RMSE, area under the curve, regional and parametric image quantifications. The results revealed that the proposed model can generate IFs that closer to the reference ones in terms of shape and amplitude compared with the IFs generated using existing methods. All regional kinetic parameters calculated using DLIF agreed with reference values, with the correlation coefficient being 0.961 (0.913) and relative bias being 1.68±8.74% (0.37±4.93%) for [Formula: see text] ( [Formula: see text]. In terms of the visual appearance and quantification, parametric images were also highly identical to the reference images. In conclusion, our experiments indicate that a trained model can infer an image-derived IF from dynamic brain PET data, which enables subsequent reliable kinetic modeling.

Feasibility study of a SiPM-fiber detector for non-invasive measurement of arterial input function for preclinical and clinical positron emission tomography

Pharmacokinetic positron emission tomography (PET) studies rely on the measurement of the arterial input function (AIF), which represents the time-activity curve of the radiotracer concentration in the blood plasma. Traditionally, obtaining the AIF requires invasive procedures, such as arterial catheterization, which can be challenging, time-consuming, and associated with potential risks. Therefore, the development of non-invasive techniques for AIF measurement is highly desirable. This study presents a detector for the non-invasive measurement of the AIF in PET studies. The detector is based on the combination of scintillation fibers and silicon photomultipliers (SiPMs) which leads to a very compact and rugged device. The feasibility of the detector was assessed through Monte Carlo simulations conducted on mouse tail and human wrist anatomies studying relevant parameters such as energy spectrum, detector efficiency and minimum detectable activity (MDA). The simulations involved the use of 18F and 68Ga isotopes, which exhibit significantly different positron ranges. In addition, several prototypes were built in order to study the different components of the detector including the scintillation fiber, the coating of the fiber, the SiPMs, and the operating configuration. Finally, the simulations were compared with experimental measurements conducted using a tube filled with both 18F and 68Ga to validate the obtained results. The MDA achieved for both anatomies (approximately 1000 kBq/mL for mice and 1 kBq/mL for humans) falls below the peak radiotracer concentrations typically found in PET studies, affirming the feasibility of conducting non-invasive AIF measurements with the fiber detector. The sensitivity for measurements with a tube filled with 18F (68Ga) was 1.2 (2.07) cps/(kBq/mL), while for simulations, it was 2.81 (6.23) cps/(kBq/mL). Further studies are needed to validate these results in pharmacokinetic PET studies.

Circulating Endocannabinoids and N-Acylethanolamines in Individuals with Cannabis Use Disorder-Preliminary Findings

BACKGROUND

Endocannabinoids and related N-acylethanolamines (NAEs) are bioactive lipids with important physiological functions and putative roles in mental health and addictions. Although chronic cannabis use is associated with endocannabinoid system changes, the status of circulating endocannabinoids and related NAEs in people with cannabis use disorder (CUD) is uncertain.

METHODS

Eleven individuals with CUD and 54 healthy non-cannabis using control participants (HC) provided plasma for measurement by high-performance liquid chromatography-mass spectrometry of endocannabinoids (2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (AEA)) and related NAE fatty acids (N-docosahexaenoylethanolamine (DHEA) and N-oleoylethanolamine (OEA)). Participants were genotyped for the functional gene variant of FAAH (rs324420, C385A) which may affect concentrations of AEA as well as other NAEs (OEA, DHEA).

RESULTS

In overnight abstinent CUD, AEA, OEA and DHEA concentrations were significantly higher (31-40%; p < 0.05) and concentrations of the endocannabinoid 2-AG were marginally elevated (55%, p = 0.13) relative to HC. There were no significant correlations between endocannabinoids/NAE concentrations and cannabis analytes, self-reported cannabis use frequency or withdrawal symptoms. DHEA concentration was inversely related with marijuana craving (r = -0.86; p = 0.001). Genotype had no significant effect on plasma endocannabinoids/NAE concentrations.

CONCLUSIONS

Our preliminary findings, requiring replication, might suggest that activity of the endocannabinoid system is elevated in chronic cannabis users. It is unclear whether this elevation is a compensatory response or a predating state. Studies examining endocannabinoids and NAEs during prolonged abstinence as well as the potential role of DHEA in craving are warranted.

Simulation of a novel, non-invasive radiation detector to measure the arterial input function for dynamic positron emission tomography

BACKGROUND

Dynamic positron emission tomography (dPET) is a nuclear medicine imaging technique providing functional images for organs of interest with applications in oncology, cardiology, and drug discovery. This technique requires the acquisition of the time-course arterial plasma activity concentration, called the arterial input function (AIF), which is conventionally acquired via arterial blood sampling.

PURPOSE

The aim of this study was to (A) optimize the geometry for a novel and cost efficient non-invasive detector called NID designed to measure the AIF for dPET scans through Monte Carlo simulations and (B) develop a clinical data analysis chain to successfully separate the arterial component of a simulated AIF signal from the venous component.

METHODS

The NID was optimized by using an in-house Geant4-based software package. The sensitive volume of the NID consists of a band of 10 cm long and 1 mm in diameter scintillating fibers placed over a wrist phantom. The phantom was simulated as a cylinder, 10 cm long and 6.413 cm in diameter comprised of polyethylene with two holes placed through it to simulate the patient's radial artery and vein. This phantom design was chosen to match the wrist phantom used in our previous proof of concept work. Two geometries were simulated with different arrangements of scintillating fibers. The first design used a single layer of 64 fibers. The second used two layers, an inner layer with 29 fibers and an outer layer with 30 fibers. Four positron emitting radioisotopes were simulated: ¹⁸ F, ¹¹ C, ¹⁵ O, and ⁶⁸ Ga with 100 million simulated decay events per run. The total and intrinsic efficiencies of both designs were calculated as well as the full width half maximum (FWHM) of the signal. In addition, contribution by the annihilation photons versus positrons to the signal was investigated. The results obtained from the two simulated detector models were compared. A clinical data analysis chain using an expectation maximization maximum likelihood algorithm was tested. This analysis chain will be used to separate arterial counts from the total signal.

RESULTS

The second NID design with two layers of scintillating fibers had a higher efficiency for all simulations with a maximum increase of 17% total efficiency for ¹¹ C simulation. All simulations had a significant annihilation photon contribution. The signal for ¹⁸ F and ¹¹ C was almost entirely due to photons. The clinical data analysis chain was within 1% of the true value for 434 out of 440 trials. Further experimental studies to validate these simulations will be required.

CONCLUSIONS

The design of the NID was optimized and its efficiency increased through Monte Carlo simulations. A clinical data analysis chain was successfully developed to separate the arterial component of an AIF signal from the venous component. The simulations show that the NID can be used to accurately measure the AIF non-invasively for dPET scans.

Non-invasive kinetic modelling approaches for quantitative analysis of brain PET studies

Pharmacokinetic modelling with arterial sampling is the gold standard for analysing dynamic PET data of the brain. However, the invasive character of arterial sampling prevents its widespread clinical application. Several methods have been developed to avoid arterial sampling, in particular reference region methods. Unfortunately, for some tracers or diseases, no suitable reference region can be defined. For these cases, other potentially non-invasive approaches have been proposed: (1) a population based input function (PBIF), (2) an image derived input function (IDIF), or (3) simultaneous estimation of the input function (SIME). This systematic review aims to assess the correspondence of these non-invasive methods with the gold standard. Studies comparing non-invasive pharmacokinetic modelling methods with the current gold standard methods using an input function derived from arterial blood samples were retrieved from PubMed/MEDLINE (until December 2021). Correlation measurements were extracted from the studies. The search yielded 30 studies that correlated outcome parameters (V_T, DVR, or BP_ND for reversible tracers; K_i or CMR_glu for irreversible tracers) from a potentially non-invasive method with those obtained from modelling using an arterial input function. Some studies provided similar results for PBIF, IDIF, and SIME-based methods as for modelling with an arterial input function (R² = 0.59-1.00, R² = 0.71-1.00, R² = 0.56-0.96, respectively), if the non-invasive input curve was calibrated with arterial blood samples. Even when the non-invasive input curve was calibrated with venous blood samples or when no calibration was applied, moderate to good correlations were reported, especially for the IDIF and SIME (R² = 0.71-1.00 and R² = 0.36-0.96, respectively). Overall, this systematic review illustrates that non-invasive methods to generate an input function are still in their infancy. Yet, IDIF and SIME performed well, not only with arterial blood calibration, but also with venous or no blood calibration, especially for some tracers without plasma metabolites, which would potentially make these methods better suited for clinical application. However, these methods should still be properly validated for each individual tracer and application before implementation.

Cannabinoid Receptor Type 1 in Parkinson's Disease: A Positron Emission Tomography Study with [18 F]FMPEP-d2

Background

The endocannabinoid system is a widespread neuromodulatory system affecting several biological functions and processes. High densities of type 1 cannabinoid (CB1) receptors and endocannabinoids are found in basal ganglia, which makes them an interesting target group for drug development in basal ganglia disorders such as Parkinson's disease (PD).

Objective

The aim of this study was to investigate CB1 receptors in PD with [¹⁸F]FMPEP‐d₂ positron emission tomography (PET) and the effect of dopaminergic medication on the [¹⁸F]FMPEP‐d₂ binding.

Methods

The data consisted of 16 subjects with PD and 10 healthy control subjects (HCs). All participants underwent a [¹⁸F]FMPEP‐d₂ high‐resolution research tomograph PET examination for the quantitative assessment of cerebral binding to CB1 receptors. To investigate the effect of dopaminergic medication on the [¹⁸F]FMPEP‐d₂ binding, 15 subjects with PD underwent [¹⁸F]FMPEP‐d₂ PET twice, both on and off antiparkinsonian medication.

Results

[¹⁸F]FMPEP‐d₂ distribution volume was significantly lower in the off scan compared with the on scan in basal ganglia, thalamus, hippocampus, and amygdala (P < 0.05). Distribution volume was lower in subjects with PD off than in HCs globally (P < 0.05), but not higher than in HCs in any brain region.

Conclusions

Subjects with PD have lower CB1 receptor availability compared with HCs. PD medication increases CB1 receptor toward normal levels. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

caliPER: A software for blood-free parametric Patlak mapping using PET/MRI input function

Routine clinical use of absolute PET quantification techniques is limited by the need for serial arterial blood sampling for input function and more importantly by the lack of automated pharmacokinetic analysis tools that can be readily implemented in clinic with minimal effort. PET/MRI provides the ability for absolute quantification of PET probes without the need for serial arterial blood sampling using image-derived input functions (IDIFs). Here we introduce caliPER, a modular and scalable software for simplified pharmacokinetic modelling of PET probes with irreversible uptake or binding based on PET/MR IDIFs and Patlak Plot analysis. caliPER generates regional values or parametric maps of net influx rate (K_i) using reconstructed dynamic PET images and anatomical MRI aligned to PET for IDIF vessel delineation. We evaluated the performance of caliPER for blood-free region-based and pixel-wise Patlak analyses of [¹⁸F] FDG by comparing caliPER IDIF to serial arterial blood input functions and its application in imaging brain glucose hypometabolism in Frontotemporal dementia. IDIFs corrected for partial volume errors including spill-out and spill-in effects were similar to arterial blood input functions with a general bias of around 6-8%, even for arteries <5 mm. The K_i and cerebral metabolic rate of glucose estimated using caliPER IDIF were similar to estimates using arterial blood sampling (<2%) and within limits of whole brain values reported in literature. Overall, caliPER is a promising tool for irreversible PET tracer quantification and can simplify the ability to perform parametric analysis in clinical settings without the need for blood sampling.

Effects of Carbidopa Premedication on 18F-FDOPA PET Imaging of Glioma: A Multiparametric Analysis

Simple Summary

¹⁸F-FDOPA PET imaging is routinely used and recommended to assess gliomas. Carbidopa is a peripheral enzyme inhibitor. Carbidopa premedication increases the radiotracer uptake on static images. None of the evidence-based data available to date recommends carbidopa premedication. Our study therefore determined the impact of carbidopa premedication on static, radiomics and dynamic parameters for ¹⁸F-FDOPA PET brain tumor imaging. We show that carbidopa premedication leads to higher SUV and TTP dynamic parameters and impacts SUV-dependent radiomics by the same magnitude in healthy brains and tumors. The carbidopa effect is therefore compensated for by correcting for the tumor-to-healthy-brain ratio, a significant advantage for harmonizing data for multicentric studies. Results were obtained from simulations of time-activity curves using compartmental modeling.

Abstract

Purpose: This study aimed to determine the impact of carbidopa premedication on static, dynamic and radiomics parameters of ¹⁸F-FDOPA PET in brain tumors. Methods: The study included 54 patients, 18 of whom received carbidopa, who underwent ¹⁸F-FDOPA PET for newly diagnosed gliomas. SUV-derived, 105 radiomics features and TTP dynamic parameters were extracted from volumes of interest in healthy brains and tumors. Simulation of the effects of carbidopa on time-activity curves were generated. Results: All static and TTP dynamic parameters were significantly higher in healthy brain regions of premedicated patients (ΔSUV_mean = +53%, ΔTTP = +48%, p < 0.001). Furthermore, carbidopa impacted 81% of radiomics features, of which 92% correlated with SUV_mean (absolute correlation coefficient ≥ 0.4). In tumors, premedication with carbidopa was an independent predictor of SUV_mean (ΔSUV_mean = +52%, p < 0.001) and TTP (ΔTTP = +24%, p = 0.025). All parameters were no longer significantly modified by carbidopa premedication when using ratios to healthy brain. Simulated data confirmed that carbidopa leads to higher tumor TTP values, corrected by the ratios. Conclusion: In ¹⁸F-FDOPA PET, carbidopa induces similarly higher SUV and TTP dynamic parameters and similarly impacts SUV-dependent radiomics in healthy brain and tumor regions, which is compensated for by correcting for the tumor-to-healthy-brain ratio. This is a significant advantage for multicentric study harmonization.

Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient?

Purpose

Dynamic amino acid positron emission tomography (PET) has become essential in neuro-oncology, most notably for its prognostic value in the noninvasive prediction of isocitrate dehydrogenase (IDH) mutations in newly diagnosed gliomas. The 6-[¹⁸F]fluoro-l-DOPA (¹⁸F-FDOPA) kinetic model has an underlying complexity, while previous studies have predominantly used a semiquantitative dynamic analysis. Our study addresses whether a semiquantitative analysis can capture all the relevant information contained in time–activity curves for predicting the presence of IDH mutations compared to the more sophisticated graphical and compartmental models.

Methods

Thirty-seven tumour time–activity curves from ¹⁸F-FDOPA PET dynamic acquisitions of newly diagnosed gliomas (median age = 58.3 years, range = 20.3–79.9 years, 16 women, 16 IDH-wild type) were analyzed with a semiquantitative model based on classical parameters, with (SQ) or without (Ref SQ) a reference region, or on parameters of a fit function (SQ Fit), a graphical Logan model with input function (Logan) or reference region (Ref Logan), and a two-tissue compartmental model previously reported for ¹⁸F-FDOPA PET imaging of gliomas (2TCM). The overall predictive performance of each model was assessed with an area under the curve (AUC) comparison using multivariate analysis of all the parameters included in the model. Moreover, each extracted parameter was assessed in a univariate analysis by a receiver operating characteristic curve analysis.

Results

The SQ model with an AUC of 0.733 for predicting IDH mutations showed comparable performance to the other models with AUCs of 0.752, 0.814, 0.693, 0.786, and 0.863, respectively corresponding to SQ Fit, Ref SQ, Logan, Ref Logan, and 2TCM (p ≥ 0.10 for the pairwise comparisons with other models). In the univariate analysis, the SQ time-to-peak parameter had the best diagnostic performance (75.7% accuracy) compared to all other individual parameters considered.

Conclusions

The SQ model circumvents the complexities of the ¹⁸F-FDOPA kinetic model and yields similar performance in predicting IDH mutations when compared to the other models, most notably the compartmental model. Our study provides supportive evidence for the routine clinical application of the SQ model for the dynamic analysis of ¹⁸F-FDOPA PET images in newly diagnosed gliomas.

Population-based input function for TSPO quantification and kinetic modeling with [11C]-DPA-713

INTRODUCTION

Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [11C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF.

MATERIALS AND METHODS

Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [11C]-DPA-713 PET studies were included. Each subject underwent 90 min of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient-specific AIF (PSAIF, ground-truth standard) and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects and after normalizing the PSAIFs by 3 techniques: (a) Weightsubject×DoseInjected, (b) area under AIF curve (AUC), and (c) Weightsubject×AUC. The variability in the VT measured with PSAIF, in the test-retest study, was determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus, and amygdala) using the Bland-Altman analysis and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed.

RESULTS

Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ± 70%. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is -10% and ±45% for Weightsubject×DoseInjected; +8% and ±50% for AUC; and +2% and ± 38% for Weightsubject×AUC. In all cases, normalizing by Weightsubject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions). Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/HAB), the average VT values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (% difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%).

CONCLUSIONS

PSAIF kinetic results are reproducible with PBIF, with variability in VT within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible and can be an alternative to PSAIF.

Pharmacokinetic modelling for the simultaneous assessment of perfusion and 18F-flutemetamol uptake in cerebral amyloid angiopathy using a reduced PET-MR acquisition time: Proof of concept

PURPOSE

Cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease associated with perivascular β-amyloid deposition. CAA is also associated with strokes due to lobar intracerebral haemorrhage (ICH). ¹⁸F-flutemetamol amyloid ligand PET may improve the early detection of CAA. We performed pharmacokinetic modelling using both full (0-30, 90-120 min) and reduced (30 min) ¹⁸F-flutemetamol PET-MR acquisitions, to investigate regional cerebral perfusion and amyloid deposition in ICH patients.

METHODS

Dynamic¹⁸F-flutemetamol PET-MR was performed in a pilot cohort of sixteen ICH participants; eight lobar ICH cases with probable CAA and eight deep ICH patients. A model-based input function (mIF) method was developed for compartmental modelling. mIF 1-tissue (1-TC) and 2-tissue (2-TC) compartmental modelling, reference tissue models and standardized uptake value ratios were assessed in the setting of probable CAA detection.

RESULTS

The mIF 1-TC model detected perfusion deficits and ¹⁸F-flutemetamol uptake in cases with probable CAA versus deep ICH patients, in both full and reduced PET acquisition time (all P < 0.05). In the reduced PET acquisition, mIF 1-TC modelling reached the highest sensitivity and specificity in detecting perfusion deficits (0.87, 0.77) and ¹⁸F-flutemetamol uptake (0.83, 0.71) in cases with probable CAA. Overall, 52 and 48 out of the 64 brain areas with ¹⁸F-flutemetamol-determined amyloid deposition showed reduced perfusion for 1-TC and 2-TC models, respectively.

CONCLUSION

Pharmacokinetic (1-TC) modelling using a 30 min PET-MR time frame detected impaired haemodynamics and increased amyloid load in probable CAA. Perfusion deficits and amyloid burden co-existed within cases with CAA, demonstrating a distinct imaging pattern which may have merit in elucidating the pathophysiological process of CAA.

Quantification of [18F]UCB-H Binding in the Rat Brain: From Kinetic Modelling to Standardised Uptake Value

PURPOSE

[¹⁸F]UCB-H is a specific positron emission tomography (PET) biomarker for the Synaptic Vesicle protein 2A (SV2A), the binding site of the antiepileptic drug levetiracetam. With a view to optimising acquisition time and simplifying data analysis with this radiotracer, we compared two parameters: the distribution volume (Vt) obtained from Logan graphical analysis using a Population-Based Input Function, and the Standardised Uptake Value (SUV).

PROCEDURES

Twelve Sprague Dawley male rats, pre-treated with three different doses of levetiracetam were employed to develop the methodology. Three additional kainic acid (KA) treated rats (temporal lobe epilepsy model) were also used to test the procedure. Image analyses focused on: (i) length of the dynamic acquisition (90 versus 60 min); (ii) correlations between Vt and SUV over 20-min consecutive time-frames; (iii) and (iv) evaluation of differences between groups using the Vt and the SUV; and (v) preliminary evaluation of the methodology in the KA epilepsy model.

RESULTS

A large correlation between the Vt issued from 60 to 90-min acquisitions was observed. Further analyses highlighted a large correlation (r > 0.8) between the Vt and the SUV. Equivalent differences between groups were detected for both parameters, especially in the 20-40 and 40-60-min time-frames. The same results were also obtained with the epilepsy model.

CONCLUSIONS

Our results enable the acquisition setting to be changed from a 90-min dynamic to a 20-min static PET acquisition. According to a better image quality, the 20-40-min time-frame appears optimal. Due to its equivalence to the Vt, the SUV parameter can be considered in order to quantify [¹⁸F]UCB-H uptake in the rat brain. This work, therefore, establishes a starting point for the simplification of SV2A in vivo quantification with [¹⁸F]UCB-H, and represents a step forward to the clinical application of this PET radiotracer.

Automated GMP production and long-term experience in radiosynthesis of CB1 tracer [18 F]FMPEP-d2

Here, we describe the development of an in-house-built device for the fully automated multistep synthesis of the cannabinoid CB₁ receptor imaging tracer (3R,5R)-5-(3-([¹⁸ F]fluoromethoxy-d₂ )phenyl)-3-(((R)-1-phenylethyl)amino)-1-(4-(trifluoromethyl)phenyl)pyrrolidin-2-one ([¹⁸ F]FMPEP-d₂ ), following good manufacturing practices. The device is interfaced to a HPLC and a sterile filtration unit in a clean room hot cell. The synthesis involves the nucleophilic ¹⁸ F-fluorination of an alkylating agent and its GC purification, the subsequent ¹⁸ F-fluoroalkylation of a precursor molecule, the semipreparative HPLC purification of the ¹⁸ F-fluoroalkylated product, and its formulation for injection. We have optimized the duration and temperature of the ¹⁸ F-fluoroalkylation reaction and addressed the radiochemical stability of the formulated product. During the past 5 years (2013-2018), we have performed a total of 149 syntheses for clinical use with a 90% success rate. The activity yield of the formulated product has been 1.0 ± 0.4 GBq starting from 11 ± 2 GBq and the molar activity 600 ± 300 GBq/μmol at the end of synthesis.

Simulation study of a coincidence detection system for non-invasive determination of arterial blood time-activity curve measurements

Background

Arterial sampling in PET studies for the purposes of kinetic modeling remains an invasive, time-intensive, and expensive procedure. Alternatives to derive the blood time-activity curve (BTAC) non-invasively are either reliant on large vessels in the field of view or are laborious to implement and analyze as well as being prone to many processing errors. An alternative method is proposed in this work by the simulation of a non-invasive coincidence detection unit.

Results

We utilized GATE simulations of a human forearm phantom with a blood flow model, as well as a model for dynamic radioactive bolus activity concentration based on clinical measurements. A fixed configuration of 14 and, also separately, 8 detectors were employed around the phantom, and simulations were performed to investigate signal detection parameters. Bismuth germanate (BGO) crystals proved to show the highest count rate capability and sensitivity to a simulated BTAC with a maximum coincidence rate of 575 cps. Repeatable location of the blood vessels in the forearm allowed a half-ring design with only 8 detectors. Using this configuration, maximum coincident rates of 250 cps and 42 cps were achieved with simulation of activity concentration determined from ¹⁵O and ¹⁸F arterial blood sampling. NECR simulated in a water phantom at 3 different vertical positions inside the 8-detector system (Y = − 1 cm, Y = − 2 cm, and Y = −3 cm) was 8360 cps, 13,041 cps, and 20,476 cps at an activity of 3.5 MBq. Addition of extra axial detection rings to the half-ring configuration provided increases in system sensitivity by a factor of approximately 10.

Conclusions

Initial simulations demonstrated that the configuration of a single half-ring 8 detector of monolithic BGO crystals could describe the simulated BTAC in a clinically relevant forearm phantom with good signal properties, and an increased number of axial detection rings can provide increased sensitivity of the system. The system would find use in the derivation of the BTAC for use in the application of kinetic models without physical arterial sampling or reliance on image-based techniques.

Reliable quantification of 18F-GE-180 PET neuroinflammation studies using an individually scaled population-based input function or late tissue-to-blood ratio

Purpose

Tracer kinetic modeling of tissue time activity curves and the individual input function based on arterial blood sampling and metabolite correction is the gold standard for quantitative characterization of microglia activation by PET with the translocator protein (TSPO) ligand ¹⁸F-GE-180. This study tested simplified methods for quantification of ¹⁸F-GE-180 PET.

Methods

Dynamic ¹⁸F-GE-180 PET with arterial blood sampling and metabolite correction was performed in five healthy volunteers and 20 liver-transplanted patients. Population-based input function templates were generated by averaging individual input functions normalized to the total area under the input function using a leave-one-out approach. Individual population-based input functions were obtained by scaling the input function template with the individual parent activity concentration of ¹⁸F-GE-180 in arterial plasma in a blood sample drawn at 27.5 min or by the individual administered tracer activity, respectively. The total ¹⁸F-GE-180 distribution volume (V_T) was estimated in 12 regions-of-interest (ROIs) by the invasive Logan plot using the measured or the population-based input functions. Late ROI-to-whole-blood and ROI-to-cerebellum ratio were also computed.

Results

Correlation with the reference V_T (with individually measured input function) was very high for V_T with the population-based input function scaled with the blood sample and for the ROI-to-whole-blood ratio (Pearson correlation coefficient = 0.989 ± 0.006 and 0.970 ± 0.005). The correlation was only moderate for V_T with the population-based input function scaled with tracer activity dose and for the ROI-to-cerebellum ratio (0.653 ± 0.074 and 0.384 ± 0.177). Reference V_T, population-based V_T with scaling by the blood sample, and ROI-to-whole-blood ratio were sensitive to the TSPO gene polymorphism. Population-based V_T with scaling to the administered tracer activity and the ROI-to-cerebellum ratio failed to detect a polymorphism effect.

Conclusion

These results support the use of a population-based input function scaled with a single blood sample or the ROI-to-whole-blood ratio at a late time point for simplified quantitative analysis of ¹⁸F-GE-180 PET.

Electronic supplementary material

The online version of this article (10.1007/s00259-020-04810-1) contains supplementary material, which is available to authorized users.

Sex difference in brain CB1 receptor availability in man

The endocannabinoid system (ECS) has a widespread neuromodulatory function in the central nervous system and is involved in important aspects of brain function including brain development, cortical rhythms, plasticity, reward, and stress sensitivity. Many of these effects are mediated via the cannabinoid CB1 receptor (CB1R) subtype. Animal studies convincingly show an interaction between the ECS and sex hormones, as well as a sex difference of higher brain CB1R in males. Human in vivo studies of sex difference have yielded discrepant findings. Gender differences in CB1R availability were investigated in vivo in 11 male and 11 female healthy volunteers using a specific CB1R tracer [¹⁸F]FMPEP-d2 and positron emission tomography (PET). Regional [¹⁸F]FMPEP-d2 distribution volume was used as a proxy for CB1R availability. In addition, we explored whether CB1R availability is linked to neuropsychological functioning. Relative to females, CB1R availability was on average 41% higher in males (p = 0.002) with a regionally specific effect larger in the posterior cingulate and retrosplenial cortices (p = 0.001). Inter-subject variability in CB1R availability was similar in both groups. Voxel-based analyses revealed an inverse association between CB1R availability and visuospatial working memory task performance in both groups (p < 0.001). A CB1R sex difference with a large effect size was observed and should be considered in the design of CB1R-related studies on neuropsychiatric disorders. The behavioural correlates and clinical significance of this difference remain to be further elucidated, but our studies suggest an association between CB1R availability and working memory.

Improved discrimination between benign and malignant LDCT screening-detected lung nodules with dynamic over static 18F-FDG PET as a function of injected dose

Lung cancer mortality rate can be significantly reduced by up to 20% through routine low-dose computed tomography (LDCT) screening, which, however, has high sensitivity but low specificity, resulting in a high rate of false-positive nodules. Combining PET with CT may provide more accurate diagnosis for indeterminate screening-detected nodules. In this work, we investigated low-dose dynamic 18F-FDG PET in discrimination between benign and malignant nodules using a virtual clinical trial based on patient study with ground truth. Six patients with initial LDCT screening-detected lung nodules received 90 min single-bed PET scans following a 10 mCi FDG injection. Low-dose static and dynamic images were generated from under-sampled list-mode data at various count levels (100%, 50%, 10%, 5%, and 1%). A virtual clinical trial was performed by adding nodule population variability, measurement noise, and static PET acquisition start time variability to the time activity curves (TACs) of the patient data. We used receiver operating characteristic (ROC) analysis to estimate the classification capability of standardized uptake value (SUV) and net uptake constant K i from their simulated benign and malignant distributions. Various scan durations and start times (t *) were investigated in dynamic Patlak analysis to optimize simplified acquisition protocols with a population-based input function (PBIF). The area under curve (AUC) of ROC analysis was higher with increased scan duration and earlier t *. Highly similar results were obtained using PBIF to those using image-derived input function (IDIF). The AUC value for K i using optimized t * and scan duration with 10% dose was higher than that for SUV with 100% dose. Our results suggest that dynamic PET with as little as 1 mCi FDG could provide discrimination between benign and malignant lung nodules with higher than 90% sensitivity and specificity for patients similar to the pilot and simulated population in this study, with LDCT screening-detected indeterminate lung nodules.

Pharmacokinetic Characterization of [18F]UCB-H PET Radiopharmaceutical in the Rat Brain

The synaptic vesicle glycoprotein 2A (SV2A), a protein essential to the proper nervous system function, is found in presynaptic vesicles. Thus, SV2A targeting, using dedicated radiotracers combined with positron emission tomography (PET), allows the assessment of synaptic density in the living brain. The first-in-class fluorinated SV2A specific radioligand, [¹⁸F]UCB-H, is now available at high activity through an efficient radiosynthesis compliant with current good manufacturing practices (cGMP). We report here a noninvasive method to quantify [¹⁸F]UCB-H binding in rat brain with microPET. Validation study in rats confirmed the need of high enantiomeric purity to target SV2A in vivo. We demonstrated the reliability of a population-based input function to quantify SV2A in preclinical microPET setting. Finally, we investigated the in vivo metabolism of [¹⁸F]UCB-H and confirmed the negligible amount of radiometabolites in the rat brain. Hence, the in vivo quantification of SV2A using [¹⁸F]UCB-H microPET seems a promising tool for the assessment of the synaptic density in the rat brain, and opens the way for longitudinal follow-up in neurodegenerative disease rodent models.

Feasibility study of TSPO quantification with [18F]FEPPA using population-based input function

PURPOSE

The input function (IF) is a core element in the quantification of Translocator protein 18 kDa with positron emission tomography (PET), as no suitable reference region with negligible binding has been identified. Arterial blood sampling is indeed needed to create the IF (ASIF). In the present manuscript we study individualization of a population based input function (PBIF) with a single arterial manual sample to estimate total distribution volume (VT) for [18F]FEPPA and to replicate previously published clinical studies in which the ASIF was used.

METHODS

The data of 3 previous [18F]FEPPA studies (39 of healthy controls (HC), 16 patients with Parkinson's disease (PD) and 18 with Alzheimer's disease (AD)) was reanalyzed with the new approach. PBIF was used with the Logan graphical analysis (GA) neglecting the vascular contribution to estimate VT. Time of linearization of the GA was determined with the maximum error criteria. The optimal calibration of the PBIF was determined based on the area under the curve (AUC) of the IF and the agreement range of VT between methods. The shape of the IF between groups was studied while taking into account genotyping of the polymorphism (rs6971).

RESULTS

PBIF scaled with a single value of activity due to unmetabolized radioligand in arterial plasma, calculated as the average of a sample taken at 60 min and a sample taken at 90 min post-injection, yielded a good interval of agreement between methods and optimized the area under the curve of IF. In HC, gray matter VTs estimated by PBIF highly correlated with those using the standard method (r2 = 0.82, p = 0.0001). Bland-Altman plots revealed PBIF slightly underestimates (~1 mL/cm3) VT calculated by ASIF (including a vascular contribution). It was verified that the AUC of the ASIF were independent of genotype and disease (HC, PD, and AD). Previous clinical results were replicated using PBIF but with lower statistical power.

CONCLUSION

A single arterial blood sample taken 75 minute post-injection contains enough information to individualize the IF in the groups of subjects studied; however, the higher variability produced requires an increase in sample size to reach the same effect size.

Standardized Input Function for 18F-FDG PET Studies in Mice: A Cautionary Study

Aim of the Study

The aim of this study was to assess the accuracy of a standardized arterial input function (SAIF) for positron emission tomography ¹⁸F-FDG studies in mice. In particular, we tested whether the same SAIF could be applied to populations of mice whose fasting conditions differed.

Methods

The SAIF was first created from a population of fasting mice (n = 11) and validated within this group using a correlation analysis and a leave-one-out procedure. Then, the SAIF was prospectively applied to a population of non-fasting mice (n = 16). The SAIFs were scaled using a single individual blood sample taken 25 min after injection. The metabolic rates of glucose (CMRglc) calculated with the SAIFs were compared with the reference values obtained by full arterial sampling (AIF).

Results

In both populations of mice, CMRglc values showed a very small bias but an important variability. The SAIF/AIF CMRglc ratio in the fasting mice was 0.97 ± 0.22 (after excluding a major outlier). The SAIF/AIF CMRglc ratio in the non-fasting mice was 1.04 ± 0.22. This variability was due to the presence of cases in which the SAIF poorly estimated the shape of the input function based on full arterial sampling.

Conclusion

Although SAIF allows the estimation of the ¹⁸F-FDG mice input function with negligible bias and independently from the fasting state, errors in individual mice (as high as 30–50%) cause an important variability. Alternative techniques, such as image-derived input function, might be a better option for mice PET studies.

Fatty Acid Amide Hydrolase Binding in Brain of Cannabis Users: Imaging With the Novel Radiotracer [11C]CURB

BACKGROUND

One of the major mechanisms for terminating the actions of the endocannabinoid anandamide is hydrolysis by fatty acid amide hydrolase (FAAH), and inhibitors of the enzyme were suggested as potential treatment for human cannabis dependence. However, the status of brain FAAH in cannabis use disorder is unknown.

METHODS

Brain FAAH binding was measured with positron emission tomography and [¹¹C]CURB in 22 healthy control subjects and ten chronic cannabis users during early abstinence. The FAAH genetic polymorphism (rs324420) and blood, urine, and hair levels of cannabinoids and metabolites were determined.

RESULTS

In cannabis users, FAAH binding was significantly lower by 14%-20% across the brain regions examined than in matched control subjects (overall Cohen's d = 0.96). Lower binding was negatively correlated with cannabinoid concentrations in blood and urine and was associated with higher trait impulsiveness.

CONCLUSIONS

Lower FAAH binding levels in the brain may be a consequence of chronic and recent cannabis exposure and could contribute to cannabis withdrawal. This effect should be considered in the development of novel treatment strategies for cannabis use disorder that target FAAH and endocannabinoids. Further studies are needed to examine possible changes in FAAH binding during prolonged cannabis abstinence and whether lower FAAH binding predates drug use.

Modeling Strategies for Quantification of In Vivo 18F-AV-1451 Binding in Patients with Tau Pathology

Aggregation of hyperphosphorylated tau is a major hallmark of many neurodegenerative diseases, including Alzheimer disease (AD). In vivo imaging with PET may offer important insights into pathophysiologic mechanisms, diagnosis, and disease progression. We describe different strategies for quantification of ¹⁸F-AV-1451 (T807) tau binding, including models with blood sampling and noninvasive alternatives. Methods: Fifteen subjects (4 controls, 6 AD, 3 progressive supranuclear palsy, 2 cortico basal syndrome) underwent 180-min PET with ¹⁸F-AV-1451 and arterial blood sampling. Modeling with arterial input functions included 1-, 2-, and 3-tissue-compartment models and the Logan plot. Using the cerebellum as reference region, we applied the simplified reference tissue model 2 and Logan reference plot. Finally, simplified outcome measures were calculated as ratio, with reference to cerebellar concentrations (SUV ratio [SUVR]) and SUVs. Results: Tissue compartment models were not able to describe the kinetics of ¹⁸F-AV-1451, with poor fits in 33%-53% of cortical regions and 80% in subcortical areas. In contrast, the Logan plot showed excellent fits and parameter variance (total volume of distribution SE < 5%). Compared with the 180-min arterial-based Logan model, strong agreement was obtained for the Logan reference plot also for a reduced scan time of 100 min (R² = 0.91) and SUVR 100-120 min (R² = 0.94), with 80-100 min already representing a reasonable compromise between duration and accuracy (R² = 0.93). Time-activity curves and kinetic parameters were equal for cortical regions and the cerebellum in control subjects but different in the putamen. Cerebellar total volumes of distribution were higher in controls than patients. For these methods, increased cortical binding was observed for AD patients and to some extent for cortico basal syndrome, but not progressive supranuclear palsy. Conclusion: The Logan plot provided the best estimate of tau binding using arterial input functions. Assuming that the cerebellum is a valid reference region, simplified methods seem to provide robust alternatives for quantification, such as the Logan reference plot with 100-min scan time. Furthermore, SUVRs between target and cerebellar activities obtained from an 80- to 100-min static scan offer promising potential for clinical routine application.

Imaging of monoamine oxidase-A in the human brain with [11C]befloxatone: quantification strategies and correlation with mRNA transcription maps

INTRODUCTION

[C]Befloxatone is a highly specific, reversible, and selective radioligand for brain PET imaging of monoamine oxidase-A and can be quantified by a two-tissue compartment model (2TCM) and an arterial input function. The aims of the present study were the following: (a) to assess whether in-vivo protein concentration, as measured by [C]befloxatone total distribution volume (VT), is correlated with post-mortem mRNA expression; (b) to replicate in a population of tobacco smokers the results of a recent study on healthy nonsmokers, which showed that spectral analysis (SA) provides a highly accurate estimation of [C]befloxatone-VT at the voxel level; and (c) to validate the use of an input function that would not require arterial sampling.

MATERIALS AND METHODS

Healthy male nonsmokers (n=7) and smokers (n=8) were imaged with PET and [C]befloxatone. Binding was quantified at the regional and voxel level with the Logan plot, multilinear analysis (MA1), and SA. VT values were compared with the reference values obtained by 2TCM at the regional level. [C]Befloxatone binding was compared with mRNA transcription maps from the Allen Human Brain Atlas. A less-invasive input function was obtained with a population-based input function (PBIF) scaled with arterialized venous samples.

RESULTS

mRNA expression was highly correlated with in-vivo 2TCM-VT values both for nonsmokers (R=0.873; P<0.0001) and for smokers (R=0.851; P<0.0001). At the regional level, both Logan and MA1 showed a moderate negative bias (-5 to -10%) compared with the reference VT values. With the exception of a single outlying individual, SA showed little bias and variability (+4.4±3.5%). Although variability was higher than at the regional level, SA provided the most accurate VT estimations at the voxel level: all but one participant had an error of less than 20%. Parametric Logan and MA1 analyses gave highly biased or unusable results. PBIF provided good results in all participants in whom the arterialization of venous blood was successful (all errors of about 10% or less).

CONCLUSION

[C]Befloxatone binding is strongly correlated with the values of mRNA transcription measured in post-mortem brains. At the voxel level, SA is the best available choice for [C]befloxatone quantification, although a higher variability must be expected. When an arterial input function is not technically feasible, a PBIF scaled with arterialized venous samples may provide an acceptable alternative, provided an optimal arterialization can be achieved.

Automated reference region extraction and population-based input function for brain [(11)C]TMSX PET image analyses

[(11)C]TMSX ([7-N-methyl-(11)C]-(E)-8-(3,4,5-trimethoxystyryl)-1,3,7-trimethylxanthine) is a selective adenosine A2A receptor (A2AR) radioligand. In the central nervous system (CNS), A2AR are linked to dopamine D2 receptor function in striatum, but they are also important modulators of inflammation. The golden standard for kinetic modeling of brain [(11)C]TMSX positron emission tomography (PET) is to obtain arterial input function via arterial blood sampling. However, this method is laborious, prone to errors and unpleasant for study subjects. The aim of this work was to evaluate alternative input function acquisition methods for brain [(11)C]TMSX PET imaging. First, a noninvasive, automated method for the extraction of gray matter reference region using supervised clustering (SCgm) was developed. Second, a method for obtaining a population-based arterial input function (PBIF) was implemented. These methods were created using data from 28 study subjects (7 healthy controls, 12 multiple sclerosis patients, and 9 patients with Parkinson's disease). The results with PBIF correlated well with original plasma input, and the SCgm yielded similar results compared with cerebellum as a reference region. The clustering method for extracting reference region and the population-based approach for acquiring input for dynamic [(11)C]TMSX brain PET image analyses appear to be feasible and robust methods, that can be applied in patients with CNS pathology.