Two-tissue Compartment Model Research Articles

Reproducibility of [18F]MK-6240 kinetics in brain studies with shortened dynamic PET protocol in healthy/cognitively normal subjects

Background[18F]MK-6240 is a neurofibrillary tangles PET radiotracer that has been broadly used in aging and Alzheimer’s disease (AD) studies. Majority of [18F]MK-6240 PET studies use dynamic acquisitions longer than 60 min to assess the tracer kinetic parameters. As of today, no consensus has been established on the optimum dynamic PET scan time. In this study, we assess the reproducibility of [18F]MK-6240 quantitative metrics using shortest dynamic PET protocols in cognitively normal subjects. PET metrics were measured through two-tissue compartment model (2TCM) and Logan model to estimate VT and DVR, as well as SUVR from 90 to 120 min (SUVR90 − 120 min) post-tracer injection for brain regions. 2TCM was carried out using the 120 min dynamic coffee break dataset (first scan from 0 to 60 min p.i., second scan from 90 to 120 min p.i.) and then repeated after stepwise shortening it by 5 min. The dynamic scan length that reproduced the 120 min dynamic scans-based VT to within 10% error was defined as the shortest acquisition time (SAT). The SAT SUVR90 − 120 min was deduced from the SAT dataset by extrapolation of each image pixel time-activity curve to 120 min. The reproducibility of the 120 min dynamic scans-based VT2TCM, DVR2TCM, DVRLogan, and SUVR using the SAT was assessed using Passing-Bablock analysis. The limits of reproducibility of each PET metrics were determined using Bland-Altman analysis.ResultsA dynamic SAT of 40 min yielded < 10% error in [18F]MK-6240 VT2TCM’s for all brain regions, compared to those measured using the 120 min datasets. SAT-based analysis did not show statistically significant systemic or proportional biases in VT2TCM, DVR2TCM, DVRLogan, or SUVR compared to those deduced from the full dynamic dataset of 120 min. A mean difference between the 120 min- and SAT-based analysis of less than 4%, 10%, 15%, and 20% existed in the VT2TCM, DVR2TCM, DVRLogan, and SUVR respectively.ConclusionKinetic modeling of [18F]MK-6240 PET can be accurately performed using dynamic scan times as short as 40 min. This can facilitate studies with [18F]MK-6240 PET and improve patients accrual. Further work would be necessary to confirm the reproducibility of these results for patients in dementia spectra.

Preclinical characterization of [18F]D2-LW223: an improved metabolically stable PET tracer for imaging the translocator protein 18 kDa (TSPO) in neuroinflammatory rodent models and non-human primates.

Positron emission tomography (PET) targeting translocator protein 18 kDa (TSPO) can be used for the noninvasive detection of neuroinflammation. Improved in vivo stability of a TSPO tracer is beneficial for minimizing the potential confounding effects of radiometabolites. Deuteration represents an important strategy for improving the pharmacokinetics and stability of existing drug molecules in the plasma. This study developed a novel tracer via the deuteration of [18F]LW223 and evaluated its in vivo stability and specific binding in neuroinflammatory rodent models and nonhuman primate (NHP) brains. Compared with LW223, D2-LW223 exhibited improved binding affinity to TSPO. Compared with [18F]LW223, [18F]D2-LW223 has superior physicochemical properties and favorable brain kinetics, with enhanced metabolic stability and reduced defluorination. Preclinical investigations in rodent models of LPS-induced neuroinflammation and cerebral ischemia revealed specific [18F]D2-LW223 binding to TSPO in regions affected by neuroinflammation. Two-tissue compartment model analyses provided excellent model fits and allowed the quantitative mapping of TSPO across the NHP brain. These results indicate that [18F]D2-LW223 holds significant promise for the precise quantification of TSPO expression in neuroinflammatory pathologies of the brain.

Preparation and Preclinical Evaluation of 18F-Labeled Olutasidenib Derivatives for Non-Invasive Detection of Mutated Isocitrate Dehydrogenase 1 (mIDH1).

Mutations of isocitrate dehydrogenase 1 (IDH1) are key biomarkers for glioma classification, but current methods for detection of mutated IDH1 (mIDH1) require invasive tissue sampling and cannot be used for longitudinal studies. Positron emission tomography (PET) imaging with mIDH1-selective radioligands is a promising alternative approach that could enable non-invasive assessment of the IDH status. In the present work, we developed efficient protocols for the preparation of four 18F-labeled derivatives of the mIDH1-selective inhibitor olutasidenib. All four probes were characterized by cellular uptake studies with U87 glioma cells harboring a heterozygous IDH1 mutation (U87-mIDH) and the corresponding wildtype cells (U87-WT). In addition, the most promising probe was evaluated by PET imaging in healthy mice and mice bearing subcutaneous U87-mIDH and U87-WT tumors. Although all four probes inhibited mIDH1 with variable potencies, only one of them ([18F]mIDH-138) showed significantly higher in vitro uptake into U87-mIDH compared to U87-WT cells. In addition, PET imaging with [18F]mIDH-138 in mice demonstrated good in vivo stability and low non-specific uptake of the probe, but also revealed significantly higher uptake into U87-WT compared to U87-mIDH tumors. Finally, application of a two-tissue compartment model (2TCM) to the PET data indicated that preferential tracer uptake into U87-WT tumors results from higher specific binding rather than from differences in tracer perfusion. In conclusion, these results corroborate recent findings that mIDH1-selective inhibition may not directly correlate with mIDH1-selective target engagement and indicate that in vivo engagement of wildtype and mutated IDH1 may be governed by factors that are not faithfully reproduced by in vitro assays, both of which could complicate development of PET probes.

Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging

Introduction:We propose a novel approach for the non-invasive quantification of dynamic PET imaging data, focusing on the arterial input function (AIF) without the need for invasive arterial cannulation. Methods:Our method utilizes a combination of three-dimensional depth-wise separable convolutional layers and a physically informed deep neural network to incorporatea priori knowledge about the AIF’s functional form and shape, enabling precise predictions of the concentrations of [11C]PBR28 in whole blood and the free tracer in metabolite-corrected plasma. Results:We found a robust linear correlation between our model’s predicted AIF curves and those obtained through traditional, invasive measurements. We achieved an average cross-validated Pearson correlation of 0.86 for whole blood and 0.89 for parent plasma curves. Moreover, our method’s ability to estimate the volumes of distribution across several key brain regions – without significant differences between the use of predicted versus actual AIFs in a two-tissue compartmental model – successfully captures the intrinsic variability related to sex, the binding affinity of the translocator protein (18 kDa), and age. Conclusions:These results not only validate our method’s accuracy and reliability but also establish a foundation for a streamlined, non-invasive approach to dynamic PET data quantification. By offering a precise and less invasive alternative to traditional quantification methods, our technique holds significant promise for expanding the applicability of PET imaging across a wider range of tracers, thereby enhancing its utility in both clinical research and diagnostic settings.

Exact parameter identification in PET pharmacokinetic modeling using the irreversible two tissue compartment model * *This work was partly funded by the NIH Grants P41-EB017183 and R01-EB031199-02.

Objective. In quantitative dynamic positron emission tomography (PET), time series of images, reflecting the tissue response to the arterial tracer supply, are reconstructed. This response is described by kinetic parameters, which are commonly determined on basis of the tracer concentration in tissue and the arterial input function. In clinical routine the latter is estimated by arterial blood sampling and analysis, which is a challenging process and thus, attempted to be derived directly from reconstructed PET images. However, a mathematical analysis about the necessity of measurements of the common arterial whole blood activity concentration, and the concentration of free non-metabolized tracer in the arterial plasma, for a successful kinetic parameter identification does not exist. Here we aim to address this problem mathematically. Approach. We consider the identification problem in simultaneous pharmacokinetic modeling of multiple regions of interests of dynamic PET data using the irreversible two-tissue compartment model analytically. In addition to this consideration, the situation of noisy measurements is addressed using Tikhonov regularization. Furthermore, numerical simulations with a regularization approach are carried out to illustrate the analytical results in a synthetic application example.Main results. We provide mathematical proofs showing that, under reasonable assumptions, all metabolic tissue parameters can be uniquely identified without requiring additional blood samples to measure the arterial input function. A connection to noisy measurement data is made via a consistency result, showing that exact reconstruction of the ground-truth tissue parameters is stably maintained in the vanishing noise limit. Furthermore, our numerical experiments suggest that an approximate reconstruction of kinetic parameters according to our analytic results is also possible in practice for moderate noise levels. Significance. The analytical result, which holds in the idealized, noiseless scenario, suggests that for irreversible tracers, fully quantitative dynamic PET imaging is in principle possible without costly arterial blood sampling and metabolite analysis.

The value of net influx constant based on FDG PET/CT dynamic imaging in the differential diagnosis of metastatic from non-metastatic lymph nodes in lung cancer.

This study aims to evaluate the value of the dynamic and static quantitative metabolic parameters derived from 18F-fluorodeoxyglucose (FDG)-positron emission tomography/CT (PET/CT) in the differential diagnosis of metastatic from non-metastatic lymph nodes (LNs) in lung cancer and to validate them based on the results of a previous study. One hundred and twenty-one patients with lung nodules or masses detected on chest CT scan underwent 18F-FDG PET/CT dynamic + static imaging with informed consent. A retrospective collection of 126 LNs in 37 patients with lung cancer was pathologically confirmed. Static image analysis parameters include LN-SUVmax and LN-SUVmax/primary tumor SUVmax (LN-SUVmax/PT-SUVmax). Dynamic metabolic parameters including the net influx rate (Ki) and the surrogate of perfusion (K1) and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. Ki/K1 was then calculated as a separate marker. Based on the pathological findings, we divided into a metastatic group and a non-metastatic group. The χ2 test was used to evaluate the agreement of the individual and combined diagnosis of each metabolic parameter with the gold standard. The receiver-operating characteristic (ROC) analysis was performed for each parameter to determine the diagnostic efficacy in differentiating non-metastatic from metastatic LNs with high FDG-avid. P < 0.05 was considered statistically significant. Among the 126 FDG-avid LNs confirmed by pathology, 70 LNs were metastatic, and 56 LNs were non-metastatic. For ROC analysis, in separate assays, the dynamic metabolic parameter Ki [sensitivity (SEN) of 84.30%, specificity (SPE) of 94.60%, accuracy of 88.89%, and AUC of 0.895] had a better diagnostic value than the static metabolic parameter SUVmax (SEN of 82.90%, SPE of 62.50%, accuracy of 74.60%, and AUC of 0.727) in differentiating between metastatic from non-metastatic LNs groups, respectively. In the combined diagnosis group, the combined SUVmax + Ki diagnosis had a better diagnostic value in the differential diagnosis of metastatic from non-metastatic LNs, with SEN, SPE, accuracy, and AUC of 84.3%, 94.6%, 88.89%, and 0.907, respectively. When the cutoff value of Ki was 0.022ml/g/min, it had a high diagnostic value in the differential diagnosis between metastasis and non-metastasis in FDG-avid LNs of lung cancer, especially in improving the specificity. The combination of SUVmax and Ki is expected to be a reliable metabolic parameter for N-staging of lung cancer.

Total-body dynamic PET/CT imaging reveals kinetic distribution of [13N]NH3 in normal organs.

To systematically investigate kinetic metrics and metabolic trapping of [13N]NH3 in organs. Eleven participants performed total-body [13N]NH3 dynamic positron emission tomography (PET). Regions of interest were drawn in organs to obtain time-to-activity curves (TACs), which were fitted with an irreversible two-tissue compartment model (2TC) to investigate constant rates K1, k2 and k3, and to calculate Ki. Additionally, one-tissue compartment model using full data (1TCfull) and the first four minutes of data (1TC4min) were fitted to TAC data. K1 and k2 were compared among different models to assess [13N]NH3 trapping in organs. Kinetic rates of [13N]NH3 varied significantly among organs. The mean K1 ranged from 0.049 mL/cm3/min in the muscle to 2.936 mL/cm3/min in the kidney. The k2 and k3 were lowest in the liver (0.001min- 1) and in the pituitary (0.009min- 1), while highest in the kidney (0.587min- 1) and in the liver (0.800min- 1), respectively. The Ki was largest in the myocardium (0.601 ± 0.259 mL/cm3/min) while smallest in the bone marrow (0.028 ± 0.022 mL/cm3/min). Three groups of organs with similar kinetic characteristics were revealed: (1) the thyroid, the lung, the spleen, the pancreas, and the kidney; (2) the liver and the muscle; and (3) the cortex, the white matter, the cerebellum, the pituitary, the parotid, the submandibular gland, the myocardium, the bone, and the bone marrow. Obvious k3 was identified in multiple organs, and significant changes of K1 in multiple organs and k2 in most organs were found between 2TC and 1TCfull, but both K1 and k2 were comparable between 2TC and 1TC4min. The kinetic rates of [13N]NH3 differed among organs with some have obvious 13N-anmmonia trapping. The normal distribution of kinetic metrics of 13N-anmmonia in organs can serve as a reference for its potential use in tumor imaging.

Kinetic modeling of 18 F-PI-2620 binding in the brain using an image-derived input function with total-body PET.

Accurate quantification of tau binding from 18 F-PI-2620 PET requires kinetic modeling and an input function. Here, we implemented a non-invasive Image-derived input function (IDIF) derived using the state-of-the-art total-body uEXPLORER PET/CT scanner to quantify tau binding and tracer delivery rate from 18 F-PI-2620 in the brain. Additionally, we explored the impact of scan duration on the quantification of kinetic parameters. Total-body PET dynamic data from 15 elderly participants were acquired. Time-activity curves from the grey matter regions of interest (ROIs) were fitted to the two-tissue compartmental model (2TCM) using a subject-specific IDIF derived from the descending aorta. ROI-specific kinetic parameters were estimated for different scan durations ranging from 10 to 90 minutes. Logan graphical analysis was also used to estimate the total distribution volume (V T ). Differences in kinetic parameters were observed between ROIs, including significant reduction in tracer delivery rate (K 1 ) in the medial temporal lobe. All kinetic parameters remained relatively stable after the 60-minute scan window across all ROIs, with K 1 showing high stability after 30 minutes of scan duration. Excellent correlation was observed between V T estimated using 2TCM and Logan plot analysis. This study demonstrated the utility of IDIF with total-body PET in investigating 18 F-PI-2620 kinetics in the brain.

Evaluation of [11C]UCB-A positron emission tomography in human brains

BackgroundIn preclinical studies, the positron emission tomography (PET) imaging with [11C]UCB-A provided promising results for imaging synaptic vesicle protein 2A (SV2A) as a proxy for synaptic density. This paper reports the first-in-human [11C]UCB-A PET study to characterise its kinetics in healthy subjects and further evaluate SV2A-specific binding.ResultsTwelve healthy subjects underwent 90-min baseline [11C]UCB-A scans with PET/MRI, with two subjects participating in an additional blocking scan with the same scanning procedure after a single dose of levetiracetam (1500 mg). Our results indicated abundant [11C]UCB-A brain uptake across all cortical regions, with slow elimination. Kinetic modelling of [11C]UCB-A PET using various compartment models suggested that the irreversible two-tissue compartment model best describes the kinetics of the radioactive tracer. Accordingly, the Patlak graphical analysis was used to simplify the analysis. The estimated SV2A occupancy determined by the Lassen plot was around 66%. Significant specific binding at baseline and comparable binding reduction as grey matter precludes the use of centrum semiovale as reference tissue.Conclusions[11C]UCB-A PET imaging enables quantifying SV2A in vivo. However, its slow kinetics require a long scan duration, which is impractical with the short half-life of carbon-11. Consequently, the slow kinetics and complicated quantification methods may restrict its use in humans.

Dual-time-point dynamic 68Ga-PSMA-11 PET/CT for parametric imaging generation in prostate cancer.

To investigate the optimal dual-time-point (DTP) approaches using dynamic 68Ga-PSMA-11 PET/CT imaging to generate parametric images for prostate cancer patients. Fifteen patients with prostate cancer were intravenously administered 68Ga-PSMA-11 of 181.9 ± 47.2MBq, followed by an immediate 60min dynamic PET/CT scan. List-mode data were reconstructed into 25 timeframes (6 × 10s, 8 × 30s, and 11 × 300s) and corrected for motion and partial volume effect. DTP parametric images were generated using different interval time points of 5min and 10min, with a minimum of 30min time interval. Net influx rates (Ki) were calculated through the fitting of a single irreversible two-tissue compartmental model. Intraclass correlation coefficient (ICC) values between DTP protocols and 60min Ki were obtained. Lesion-to-background ratios (LBRs) of Ki and standardized uptake value (SUV) images in each DTP protocol were determined. The DTP protocol of 5-10min with a 40-45min interval showed the highest ICC of 0.988 compared with the 60min Ki, whereas the ICC values for the intervals of 0-5min with 55-60min and 0-10min with 50-60min were 0.941. The LBRs of the 60min Ki, 5-10min with 40-45min Ki, 0-5min with 55-60min Ki, 0-10min with 50-60min Ki, SUVmean, and SUVmax images were 29.53 ± 27.33, 13.05 ± 15.28, 45.15 ± 53.11, 45.52 ± 70.31, 19.77 ± 23.43, and 25.06 ± 30.07, respectively. The 0-5min with 55-60min DTP parametric imaging exhibits a comparable Ki to 60min parametric imaging and remarkable image quality and contrast than SUV imaging, enhancing prostate cancer diagnosis while maintaining time efficiency.

Kinetic modeling of the monoamine oxidase-B radioligand [18F]SMBT-1 in human brain with positron emission tomography.

This paper describes pharmacokinetic analyses of the monoamine-oxidase-B (MAO-B) radiotracer [18F](S)-(2-methylpyrid-5-yl)-6-[(3-fluoro-2-hydroxy)propoxy]quinoline ([18F]SMBT-1) for positron emission tomography (PET) brain imaging. Brain MAO-B expression is widespread, predominantly within astrocytes. Reactive astrogliosis in response to neurodegenerative disease pathology is associated with MAO-B overexpression. Fourteen elderly subjects (8 control, 5 mild cognitive impairment, 1 Alzheimer's disease) with amyloid ([11C]PiB) and tau ([18F]flortaucipir) imaging assessments underwent dynamic [18F]SMBT-1 PET imaging with arterial input function determination. [18F]SMBT-1 showed high brain uptake and a retention pattern consistent with the known MAO-B distribution. A two-tissue compartment (2TC) model where the K1/k2 ratio was fixed to a whole brain value best described [18F]SMBT-1 kinetics. The 2TC total volume of distribution (VT) was well identified and highly correlated (r2∼0.8) with post-mortem MAO-B indices. Cerebellar grey matter (CGM) showed the lowest mean VT of any region and is considered the optimal pseudo-reference region. Simplified analysis methods including reference tissue models, non-compartmental models, and standard uptake value ratios (SUVR) agreed with 2TC outcomes (r2 > 0.9) but with varying bias. We found the CGM-normalized 70-90 min SUVR to be highly correlated (r2 = 0.93) with the 2TC distribution volume ratio (DVR) with acceptable bias (∼10%), representing a practical alternative for [18F]SMBT-1 analyses.

Non-invasive quantification of 18F-florbetaben with total-body EXPLORER PET

BackgroundKinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.Methods18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer’s disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND})$$\\end{document} was also calculated from the multi-reference tissue model (MRTM).ResultsAmyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND}$$\\end{document} analysis. \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND} $$\\end{document}and VT from kinetic models were correlated (r² = 0.46, P < 2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {e}^{-16})$$\\end{document} with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {r}^{2}$$\\end{document}= 0.65, P < 2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {e}^{-16}$$\\end{document}) with Logan graphical VT estimation.ConclusionNon-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {BP}_{ND} $$\\end{document}in amyloid-positive and amyloid-negative older individuals.

Differences in neuroinflammation in people who started antiretroviral treatment during primary versus chronic HIV infection: an 18kDa Translocator protein (TSPO) positron emission tomography (PET) study

Persistent inflammation is described in people with HIV (PWH) on antiretroviral treatment (ART). Early ART initiation is associated with reduced inflammation. We aimed to evaluate neuroinflammation, using translocator protein (TSPO) [11C]PBR28 PET neuroimaging in PWH who initiated ART during acute HIV (aPWH) versus chronic HIV infection (cPWH) versus a control population. This was a cross-sectional, observational study. All participants underwent [11C]PBR28 PET-CT neuroimaging. Using a two-tissue compartment model, total volume of distribution (VT) and distribution volume ratios (DVR) using cortical grey matter as a pseudo-reference region at 20 regions of interest (ROIs) were calculated. Differences in VT and DVR were compared between groups using the Kruskall-Wallis test. Seventeen neuro-asymptomatic male PWH on ART (9 aPWH, 8 cPWH) and 8 male control participants (CPs) were included. Median (interquartile range, IQR) age was 40 (30, 46), 44 (41, 47) and 21 (20, 25) years in aPWH, cPWH and CPs, respectively. Median (IQR) CD4 (cells/µL) and CD4:CD8 were 687 (652, 1014) and 1.37 (1.24, 1.42), and 700 (500, 720) and 0.67 (0.64, 0.82) in aPWH and cPWH, respectively. Overall, no significant difference in VT and DVR were observed between the three groups at any ROIs. cPWH demonstrated a trend towards higher mean VT compared with aPWH and CPs at most ROIs. No significant differences in neuroinflammation, using [11C]PBR28 binding as a proxy, were identified between cPWH, aPWH and CPs. A trend towards lower absolute [11C]PBR28 binding was seen amongst aPWH and CPs, suggesting early ART may mitigate neuroinflammation.

Clinical feasibility study of early 30-minute dynamic FDG-PET scanning protocol for patients with lung lesions

PurposeThis study aimed to evaluate the clinical feasibility of early 30-minute dynamic 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) scanning protocol for patients with lung lesions in comparison to the standard 65-minute dynamic FDG-PET scanning as a reference.MethodsDynamic 18F-FDG PET images of 146 patients with 181 lung lesions (including 146 lesions confirmed by histology) were analyzed in this prospective study. Dynamic images were reconstructed into 28 frames with a specific temporal division protocol for the scan data acquired 65 min post-injection. Ki images and quantitative parameters Ki based on two different acquisition durations [the first 30 min (Ki-30 min) and 65 min (Ki-65 min)] were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. The two acquisition durations were compared for Ki image quality (including visual score analysis and number of lesions detected) and Ki value (including accuracy of Ki, the value of differential diagnosis of lung lesions and prediction of PD-L1 status) by Wilcoxon’s rank sum test, Spearman’s rank correlation analysis, receiver operating characteristic (ROC) curve, and the DeLong test. The significant testing level (alpha) was set to 0.05.ResultsThe quality of the Ki-30 min images was not significantly different from the Ki-65 min images based on visual score analysis (P > 0.05). In terms of Ki value, among 181 lesions, Ki-65 min was statistically higher than Ki-30 min (0.027 ± 0.017 ml/g/min vs. 0.026 ± 0.018 ml/g/min, P < 0.05), while a very high correlation was obtained between Ki-65 min and Ki-30 min (r = 0.977, P < 0.05). In the differential diagnosis of lung lesions, ROC analysis was performed on 146 histologically confirmed lesions, the area under the curve (AUC) of Ki-65 min, Ki-30 min, and SUVmax was 0.816, 0.816, and 0.709, respectively. According to the Delong test, no significant differences in the diagnostic accuracies were found between Ki-65 min and Ki-30 min (P > 0.05), while the diagnostic accuracies of Ki-65 min and Ki-30 min were both significantly higher than that of SUVmax (P < 0.05). In 73 (NSCLC) lesions with definite PD-L1 expression results, the Ki-65 min, Ki-30 min, and SUVmax in PD-L1 positivity were significantly higher than that in PD-L1 negativity (P < 0.05). And no significant differences in predicting PD-L1 positivity were found among Ki-65 min, Ki-30 min, and SUVmax (AUC = 0.704, 0.695, and 0.737, respectively, P > 0.05), according to the results of ROC analysis and Delong test.ConclusionsThis study indicates that an early 30-minute dynamic FDG-PET acquisition appears to be sufficient to provide quantitative images with good-quality and accurate Ki values for the assessment of lung lesions and prediction of PD-L1 expression. Protocols with a shortened early 30-minute acquisition time may be considered for patients who have difficulty with prolonged acquisitions to improve the efficiency of clinical acquisitions.

Dynamic whole-body [18F]FES PET/CT increases lesion visibility in patients with metastatic breast cancer

BackgroundCorrect classification of estrogen receptor (ER) status is essential for prognosis and treatment planning in patients with breast cancer (BC). Therefore, it is recommended to sample tumor tissue from an accessible metastasis. However, ER expression can show intra- and intertumoral heterogeneity. 16α-[18F]fluoroestradiol ([18F]FES) Positron Emission Tomography/Computed Tomography (PET/CT) allows noninvasive whole-body (WB) identification of ER distribution and is usually performed as a single static image 60 min after radiotracer injection. Using dynamic whole-body (D-WB) PET imaging, we examine [18F]FES kinetics and explore whether Patlak parametric images (Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document}) are quantitative and improve lesion visibility.ResultsThis prospective study included eight patients with metastatic ER-positive BC scanned using a D-WB PET acquisition protocol. The kinetics of [18F]FES were best characterized by the irreversible two-tissue compartment model in tumor lesions and in the majority of organ tissues. Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} values from Patlak parametric images correlated with Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} values from the full kinetic analysis, r2 = 0.77, and with the semiquantitative mean standardized uptake value (SUVmean), r2 = 0.91. Furthermore, parametric Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} images had the highest target-to-background ratio (TBR) in 162/164 metastatic lesions and the highest contrast-to-noise ratio (CNR) in 99/164 lesions compared to conventional SUV images. TBR was 2.45 (95% confidence interval (CI): 2.25–2.68) and CNR 1.17 (95% CI: 1.08–1.26) times higher in Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} images compared to SUV images. These quantitative differences were seen as reduced background activity in the Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} images.Conclusion[18F]FES uptake is best described by an irreversible two-tissue compartment model. D-WB [18F]FES PET/CT scans can be used for direct reconstruction of parametric Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} images, with superior lesion visibility and Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} values comparable to Ki\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${K}_{i}$$\\end{document} values found from full kinetic analyses. This may aid correct ER classification and treatment decisions.Trial registration ClinicalTrials.gov: NCT04150731, https://clinicaltrials.gov/study/NCT04150731

Combined whole-body dynamic and static PET/CT with low-dose [18F]PSMA-1007 in prostate cancer patients

AimIn addition to significant improvements in sensitivity and image quality, the recent introduction of long axial field-of-view (LAFOV) PET/CT scanners has enabled dynamic whole-body imaging for the first time. We aim herein to determine an appropriate acquisition time range for static low-dose [18F]PSMA-1007 PET imaging and to investigate the whole-body pharmacokinetics of [18F]PSMA-1007 by dynamic PET with the LAFOV Biograph Vision Quadra PET/CT in a group of prostate cancer patients.MethodologyIn total, 38 prostate cancer patients were enrolled in the analysis for staging or re-staging purposes. Thirty-four patients underwent dynamic whole-body PET/CT (60 min) followed by static whole-body PET/CT and four patients underwent static whole-body PET/CT only. The activity applied was 2 MBq/kg [18F]PSMA-1007. The static PET images of 10-min duration (PET-10) were reconstructed and further split into 8-min (PET-8), 6-min (PET-6), 5-min (PET-5), 4-min (PET-4), and 2-min (PET-2) duration groups. Comparisons were made between the different reconstructed scan times in terms of lesion detection rate and image quality based on SUV calculations of tumor lesions and the spleen, which served as background. Analysis of the dynamic PET/CT data was based on a two-tissue compartment model using an image-derived input function obtained from the descending aorta.ResultsAnalysis of lesion detection rate showed no significant differences when reducing PET acquisitions from 10 up to 5 min. In particular, a total of 169 lesions were counted with PET-10, and the corresponding lesion detection rates (95% CI for the 90% quantile of the differences in tumor lesions) for shorter acquisitions were 100% (169/169) for PET-8 (95% CI: 0–0), 98.8% (167/169) for PET-6 (95% CI: 0–1), 95.9% (162/169) for PET-5 (95% CI: 0–3), 91.7% (155/169) for PET-4 (95% CI: 1–2), and 85.2% (144/169) for PET-2 (95% CI: 1–6). With the exception of PET-2, the differences observed between PET-10 and the other shorter acquisition protocols would have no impact on any patient in terms of clinical management. Objective evaluation of PET/CT image quality showed no significant decrease in tumor-to-background ratio (TBR) with shorter acquisition times, despite a gradual decrease in signal-to-noise ratio (SNR) in the spleen. Whole-body quantitative [18F]PSMA-1007 pharmacokinetic analysis acquired with full dynamic PET scanning was feasible in all patients. Two-tissue compartment modeling revealed significantly higher values for the parameter k3 in tumor lesions and parotid gland compared to liver and spleen, reflecting a higher specific tracer binding to the PSMA molecule and internalization rate in these tissues, a finding also supported by the respective time-activity curves. Furthermore, correlation analysis demonstrated a significantly strong positive correlation (r = 0.72) between SUV and k3 in tumor lesions.ConclusionsIn prostate cancer, low-dose (2 MBq/kg) [18F]PSMA-1007 LAFOV PET/CT can reduce static scan time by 50% without significantly compromising lesion detection rate and objective image quality. In addition, dynamic PET can elucidate molecular pathways related to the physiology of [18F]PSMA-1007 in both tumor lesions and normal organs at the whole-body level. These findings unfold many of the potentials of the new LAFOV PET/CT technology in the field of PSMA-based diagnosis and theranostics of prostate cancer.

Simultaneous estimation of a model-derived input function for quantifying cerebral glucose metabolism with [18F]FDG PET

BackgroundQuantification of the cerebral metabolic rate of glucose (CMRGlu) by dynamic [18F]FDG PET requires invasive arterial sampling. Alternatives to using an arterial input function (AIF) include the simultaneous estimation (SIME) approach, which models the image-derived input function (IDIF) by a series of exponentials with coefficients obtained by fitting time activity curves (TACs) from multiple volumes-of-interest. A limitation of SIME is the assumption that the input function can be modelled accurately by a series of exponentials. Alternatively, we propose a SIME approach based on the two-tissue compartment model to extract a high signal-to-noise ratio (SNR) model-derived input function (MDIF) from the whole-brain TAC. The purpose of this study is to present the MDIF approach and its implementation in the analysis of animal and human data.MethodsSimulations were performed to assess the accuracy of the MDIF approach. Animal experiments were conducted to compare derived MDIFs to measured AIFs (n = 5). Using dynamic [18F]FDG PET data from neurologically healthy volunteers (n = 18), the MDIF method was compared to the original SIME-IDIF. Lastly, the feasibility of extracting parametric images was investigated by implementing a variational Bayesian parameter estimation approach.ResultsSimulations demonstrated that the MDIF can be accurately extracted from a whole-brain TAC. Good agreement between MDIFs and measured AIFs was found in the animal experiments. Similarly, the MDIF-to-IDIF area-under-the-curve ratio from the human data was 1.02 ± 0.08, resulting in good agreement in grey matter CMRGlu: 24.5 ± 3.6 and 23.9 ± 3.2 mL/100 g/min for MDIF and IDIF, respectively. The MDIF method proved superior in characterizing the first pass of [18F]FDG. Groupwise parametric images obtained with the MDIF showed the expected spatial patterns.ConclusionsA model-driven SIME method was proposed to derive high SNR input functions. Its potential was demonstrated by the good agreement between MDIFs and AIFs in animal experiments. In addition, CMRGlu estimates obtained in the human study agreed to literature values. The MDIF approach requires fewer fitting parameters than the original SIME method and has the advantage that it can model the shape of any input function. In turn, the high SNR of the MDIFs has the potential to facilitate the extraction of voxelwise parameters when combined with robust parameter estimation methods such as the variational Bayesian approach.

Pharmacokinetic Analysis of [18F]FES PET in the Human Brain and Pituitary Gland

PurposeEstrogen receptors (ER) are implicated in psychiatric disorders. We assessed if ER availability in the human brain could be quantified using 16α-[18F]-fluoro-17β-estradiol ([18F]FES) positron emission tomography (PET).ProceduresSeven post‑menopausal women underwent a dynamic [18F]FES PET scan with arterial blood sampling. A T1-weighted MRI was acquired for anatomical information. After one week, four subjects received a selective ER degrader (SERD), four hours before the PET scan. Pharmacokinetic analysis was performed using a metabolite-corrected plasma curve as the input function. The optimal kinetic model was selected based on the Akaike information criterion and standard error of estimated parameters. Accuracy of Logan graphical analysis and standardized uptake value (SUV) was determined via correlational analyses.ResultsThe reversible two-tissue compartment model (2T4k) model with fixed K1/k2 was preferred. The total volume of distribution (VT) could be more reliably estimated than the binding potential (BPND). A high correlation of VT with Logan graphical analysis was observed, but only a moderate correlation with SUV. SERD administration resulted in a reduced VT in the pituitary gland, but not in other regions.ConclusionsThe optimal quantification method for [18F]FES was the 2T4k with fixed K1/k2 or Logan graphical analysis, but specific binding was only observed in the pituitary gland.

Comparison of tracer kinetic models for 68Ga-PSMA-11 PET in intermediate-risk primary prostate cancer patients

Background68Ga-PSMA-11 positron emission tomography enables the detection of primary, recurrent, and metastatic prostate cancer. Regional radiopharmaceutical uptake is generally evaluated in static images and quantified as standard uptake values (SUVs) for clinical decision-making. However, analysis of dynamic images characterizing both tracer uptake and pharmacokinetics may offer added insights into the underlying tissue pathophysiology. This study was undertaken to evaluate the suitability of various kinetic models for 68Ga-PSMA-11 PET analysis. Twenty-three lesions in 18 patients were included in a retrospective kinetic evaluation of 55-min dynamic 68Ga-PSMA-11 pre-prostatectomy PET scans from patients with biopsy-demonstrated intermediate- to high-risk prostate cancer. Three kinetic models—a reversible one-tissue compartment model, an irreversible two-tissue compartment model, and a reversible two-tissue compartment model, were evaluated for their goodness of fit to lesion and normal reference prostate time-activity curves. Kinetic parameters obtained through graphical analysis and tracer kinetic modeling techniques were compared for reference prostate tissue and lesion regions of interest.ResultsSupported by goodness of fit and information loss criteria, the irreversible two-tissue compartment model optimally fit the time-activity curves. Lesions exhibited significant differences in kinetic rate constants (K1, k2, k3, Ki) and semiquantitative measures (SUV and %ID/kg) when compared with reference prostatic tissue. The two-tissue irreversible tracer kinetic model was consistently appropriate across prostatic zones.ConclusionsAn irreversible tracer kinetic model is appropriate for dynamic analysis of 68Ga-PSMA-11 PET images. Kinetic parameters estimated by Patlak graphical analysis or full compartmental analysis can distinguish tumor from normal prostate tissue.

A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET.

In parametric PET, kinetic parameters are extracted from dynamic PET images. It is not commonly used in clinical practice because of long scan times and the requirement for an arterial input function (AIF). To address these limitations, we designed an 18F-fluorodeoxyglucose (18F-FDG) triple injection dynamic PET protocol for brain imaging with a standard field of view PET scanner using a 24-min imaging window and an input function modeled using measurements from a region of interest placed over the left ventricle. To test the protocol in 6 healthy participants, we examined the quality of voxel-based maps of kinetic parameters in the brain generated using the two-tissue compartment model and compared estimated parameter values with previously published values. We also utilized data from a 36-min validation imaging window to compare (1) the modeled AIF against the input function measured in the validation window; and (2) the net influx rate ([Formula: see text]) computed using parameter estimates from the short imaging window against the net influx rate obtained using Patlak analysis in the validation window. Compared to the AIF measured in the validation window, the input function estimated from the short imaging window achieved a mean area under the curve error of 9%. The voxel-wise Pearson's correlation between [Formula: see text] estimates from the short imaging window and the validation imaging window exceeded 0.95. The proposed 24-min triple injection protocol enables parametric 18F-FDG neuroimaging with noninvasive estimation of the AIF from cardiac images using a standard field of view PET scanner.