Dynamic PET Research Articles

Modeling PET Data Acquired During Nonsteady Conditions: What If Brain Conditions Change During the Scan?

Researchers use dynamic PET imaging with target-selective tracer molecules to probe molecular processes. Kinetic models have been developed to describe these processes. The models are typically fitted to the measured PET data with the assumption that the brain is in a steady-state condition for the duration of the scan. The end results are quantitative parameters that characterize the molecular processes. The most common kinetic modeling endpoints are estimates of volume of distribution or the binding potential of a tracer. If the steady state is violated during the scanning period, the standard kinetic models may not apply. To address this issue, time-variant kinetic models have been developed for the characterization of dynamic PET data acquired while significant changes (e.g., short-lived neurotransmitter changes) are occurring in brain processes. These models are intended to extract a transient signal from data. This work in the PET field dates back at least to the 1990s. As interest has grown in imaging nonsteady events, development and refinement of time-variant models has accelerated. These new models, which we classify as belonging to the first, second, or third generation according to their innovation, have used the latest progress in mathematics, image processing, artificial intelligence, and statistics to improve the sensitivity and performance of the earliest practical time-variant models to detect and describe nonsteady phenomena. This review provides a detailed overview of the history of time-variant models in PET. It puts key advancements in the field into historical and scientific context. The sum total of the methods is an ongoing attempt to better understand the nature and implications of neurotransmitter fluctuations and other brief neurochemical phenomena.

PET mapping of receptor occupancy using joint direct parametric reconstruction.

In this work, we evaluate a novel joint direct parametric reconstruction framework to directly estimate distributions of RO and other kinetic parameters in the brain from a pair of baseline and postdrug injection dynamic PET scans. The proposed method combines the use of regularization on RO maps with alternating optimization to enable estimation of occupancy even in low binding regions. Simulation results demonstrate the quantitative improvement of this method over conventional approaches in terms of accuracy and precision of occupancy. The proposed method is also evaluated in preclinical in-vivo experiments using 11C-MK6884 and a muscarinic acetylcholine receptor 4 positive allosteric modulator drug, showing improved estimation of receptor occupancy as compared to traditional estimators. The proposed joint direct estimation framework improves RO estimation compared to conventional methods, especially in intermediate to low-binding regions. This work could potentially facilitate the evaluation of new drug candidates targeting the CNS.

Imaging Mutant Huntingtin Aggregates using [18F]CHDI-650 PET in a preclinical model of Huntington’s disease

Huntington’s disease (HD) is a fatal neurodegenerative disorder caused by a CAG repeat expansion in the huntingtin gene (HTT) that encodes pathogenic mutant huntingtin (mHTT) protein. Therapeutic strategies aimed at lowering mHTT would benefit from non-invasive PET-based methods to evaluate treatment response. The CHDI foundation developed the first-generation PET ligands labelled with 11C, which advanced to clinical evaluation. Further optimization generated an 18F radioligand with improved metabolic stability, brain exposure and specificity, shown by PET imaging in wild-type mice and autoradiography in HD brain samples1,2. Here, we characterised the PET radioligand [18F]CHDI-650 in the R6/1 mouse model of HD to assess its sensitivity for monitoring treatment response of mHTT lowering therapies. [18F]CHDI-650 was produced according to an established method3 using a TRACERlab system. Radiochemical purity/molar activity of the final [18F]CHDI-650 product was detected by reverse-phase HPLC analysis. Dynamic PET imaging was conducted using R6/1 mice and wild-type littermates at various disease stages. Image processing and kinetic modelling (2TCM) analysis were performed using PMOD software. Ex vivo brain radioactivity was measured using gamma counting. Brains were cryo-sectioned and processed for immunofluorescence to identify HTT load. [18F]CHDI-650 was produced (1.3 ± 0.2 GBq) with an average radiochemical purity of 99.9 ± 0.1 % and a molar activity of 32.4 ± 5.2 GBq/µmol (n = 9). The radioligand was able to discriminate R6/1 HET from WT mice at an early presymptomatic age for both dynamic PET imaging (striatal) and ex vivo whole brain gamma. A well-defined age associated increase was also evident using both measures. Dual immunofluorescence spatially defined the level of aggregated HTT in striatal and hippocampal regions across the age groups. [18F]CHDI-650 PET shows great potential as a non-invasive tool for visualising the development of mHTT pathology and as a biomarker for preclinical efficacy studies. Please click on the 'PDF' for the full abstract!

Using total-body PET to investigate relationships between excretory organs time activity curves and the metabolite fraction for [18F]SynVesT-1

Accurate quantification of dynamic PET data using kinetic modelling requires assessment of the metabolism of the tracer to obtain the quantity of unchanged parent tracer in the blood. Several image derived input functions methods have been demonstrated to be effective for kinetic modelling; however, currently no image derived metabolite correction method exists. Finding an image derived metabolite correction would remove the need for invasive blood sampling. This study uses 7 full body 18F-SynVesT-1 total body mouse scans. Initially, the time activity curves (TACs) for a range of organs including the liver, kidney and bladder were studied. Factor analysis (FA) was investigated to accurately separate contributions from the kidney – cortex, medulla and collecting duct. Following this, the relationships between each of the organ TACs and the parent plasma fraction (PPf) was investigated. FA analysis successfully discriminates between contributions from the cortex, medulla and collecting duct of the kidneys. In the context of total body scans, FA removes the need for manual drawing of volumes of interest allowing for more consistency amongst studies. By separating out these regions, a relationship between the kidney medulla and the metabolites also came to light. In addition, the average of the seven bladder time activity curves against the plasma parent fraction [Figure 1] shows a potential relationship between the excretion of the tracer and its metabolism. Combining excretory organ relationships with the parent fraction and potentially liver data opens the possibility for a model to be produced to fit a metabolite curve when we have access to a total body PET scan. While this research is in its early stages, it has shown relationships between excretory organ TACs and the metabolite fraction. This has the potential to allow for metabolite correction models to be created directly from the image data. Model architectures are under investigation. Please click on the 'PDF' for the full abstract!

Ultrashort Oncologic Whole-Body [18F]FDG Patlak Imaging Using LAFOV PET.

Methods to shorten [18F]FDG Patlak PET imaging procedures ranging from 65-90 to 20-30 min after injection, using a population-averaged input function (PIF) scaled to patient-specific image-derived input function (IDIF) values, were recently evaluated. The aim of the present study was to explore the feasibility of ultrashort 10-min [18F]FDG Patlak imaging at 55-65 min after injection using a PIF combined with direct Patlak reconstructions to provide reliable quantitative accuracy of lung tumor uptake, compared with a full-duration 65-min acquisition using an IDIF. Methods: Patients underwent a 65-min dynamic PET acquisition on a long-axial-field-of-view (LAFOV) Biograph Vision Quadra PET/CT scanner. Subsequently, direct Patlak reconstructions and image-based (with reconstructed dynamic images) Patlak analyses were performed using both the IDIF (time to relative kinetic equilibrium between blood and tissue concentration (t*) = 30 min) and a scaled PIF at 30-60 min after injection. Next, direct Patlak reconstructions were performed on the system console using only the last 10 min of the acquisition, that is, from 55 to 65 min after injection, and a scaled PIF using maximum crystal ring difference settings of both 85 and 322. Tumor lesion and healthy-tissue uptake was quantified and compared between the differently obtained parametric images to assess quantitative accuracy. Results: Good agreement was obtained between direct- and image-based Patlak analyses using the IDIF (t* = 30 min) and scaled PIF at 30-60 min after injection, performed using the different approaches, with no more than 8.8% deviation in tumor influx rate value (Ki ) (mean difference ranging from -0.0022 to 0.0018 mL/[min × g]). When direct Patlak reconstruction was performed on the system console, excellent agreement was found between the use of a scaled PIF at 30-60 min after injection versus 55-65 min after injection, with 2.4% deviation in tumor Ki (median difference, -0.0018 mL/[min × g]; range, -0.0047 to 0.0036 mL/[min × g]). For different maximum crystal ring difference settings using the scan time interval of 55-65 min after injection, only a 0.5% difference (median difference, 0.0000 mL/[min × g]; range, -0.0004 to 0.0013 mL/[min × g]) in tumor Ki was found. Conclusion: Ultrashort whole-body [18F]FDG Patlak imaging is feasible on an LAFOV Biograph Vision Quadra PET/CT system without loss of quantitative accuracy to assess lung tumor uptake compared with a full-duration 65-min acquisition. The ultrashort 10-min direct Patlak reconstruction with PIF allows for its implementation in clinical practice.

Assessment of dual time point protocols to produce parametric Ki images in FDG PET/CT: A virtual clinical study.

This simulation study investigated the feasibility of generating Patlak Ki images using a dual time point (DTP-Ki) scan protocol involving two 3-min/bed routine static PET scans and, subsequently, assessed DTP-Ki performance for an optimal DTP scan time frame combination, against conventional Patlak Ki estimated from complete 0-93min dynamic PET data. Six realistic heterogeneous tumors of different characteristic spatiotemporal [18F]FDG uptake distributions for three noise levels commonly found in clinical studies and 20 noise realizations (N=360 samples) were produced by analytic simulations of the XCAT phantom. Subsequently, DTP-Ki images were generated by performing standard linear indirect Patlak analysis with t* -min (Patlakt* = 12) using a scaled population-based input function (sPBIF) model on 66 combinations of early and late 3-min/bed static whole-body PET reconstructed images. All DTP-Ki images were evaluated against respective DTP-Ki images estimated with Patlakt* = 12 and 0-93min individual input functions (iIFs) and against gold standard Ki images estimated with Patlakt* = 12, 0-93min iIFs and tissue time activity curves from all reconstructed WB passes 12-93min post injection. The optimal combination of early and late frames, in terms of attaining the highest correlation between DTP-Ki with sPBIF and gold standard Ki was also determined from a set of 66 different combinations of 2-min early and late frames. Moreover, the performance of DTP-Ki with sPBIF was compared against that of the retention index (RI) in terms of their correlation to the gold standard Ki. Finally, the feasibility and practicality of DTP protocol in the clinic were assessed through the analysis of nine patients. High correlations(>0.9) were observed between DTP-Ki values from sPBIF and those from iIFs for all evaluated DTP protocols while the mean AUC difference between sPBIF and iIFs was less than 10%. The percentage difference of mean values between DTP-Ki from sPBIF and from iIFs was less than 1%. DTP Ki from sPBIF exhibited significantly higher correlation with gold standard Ki, in contrast to RI, across all 66 DTP protocols (p<0.05 using the two-tailed t-test by Williams) with the highest correlation attained for the 50-53-min early + 90-93-min late scan time frames (optimal DTP protocol). Feasibility of generating Patlak Ki [18F] FDG images from an early and a late post injection 3-min/bed routine static scan using a population-based input function model was demonstrated and an optimal DTP scan protocol was determined. The results indicated high correlations between DTP-Ki and gold-standard Ki images that are significantly larger than those between RI and gold-standard Ki.

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.

Heteroaryl derivatives of suvorexant as OX1R selective PET ligand candidates: Cu-mediated 18F-fluorination of boroxines, in vitro and initial in vivo evaluation

BackgroundThe orexin receptor (OXR) plays a role in drug addiction and is aberrantly expressed in colorectal tumors. Subtype-selective OXR PET ligands suitable for in vivo use have not yet been reported. This work reports the development of 18F-labeled OXR PET ligand candidates derived from the OXR antagonist suvorexant and the OX1R-selective antagonist JH112.ResultsComputational analysis predicted that fluorine substitution (1e) and introduction of the fluorobenzothiazole scaffold (1f) would be suitable for maintaining high OX1R affinity. After multi-step synthesis of 1a–1f, in vitro OXR binding studies confirmed the molecular dynamics calculations and revealed single-digit nanomolar OX1R affinities for 1a–f, ranging from 0.69 to 2.5 nM. The benzothiazole 1f showed high OX1R affinity (Ki = 0.69 nM), along with 77-fold subtype selectivity over OX2R. Cu-mediated 18F-fluorination of boroxine precursors allowed for a shortened reaction time of 5 min to provide the non-selective OXR ligand [18F]1c and its selective OX1R congener [18F]1f in activity yields of 14% and 22%, respectively, within a total synthesis time of 52–76 min. [18F]1c and [18F]1f were stable in plasma and serum in vitro, with logD7.4 of 2.28 ([18F]1c) and 2.37 ([18F]1f), and high plasma protein binding of 66% and 77%, respectively. Dynamic PET imaging in rats showed similar brain uptake of [18F]1c (0.17%ID/g) and [18F]1f (0.15%ID/g). However, preinjection of suvorexant did not significantly block [18F]1c or [18F]1f uptake in the rat brain. Pretreatment with cyclosporine A to study the role of P-glycoprotein (P-gp) in limiting brain accumulation moderately increased brain uptake of [18F]1c and [18F]1f. Accordingly, in vitro experiments demonstrated that the P-gp inhibitor zosuquidar only moderately inhibited polarized, basal to apical transport of 1c (p < 0.05) and had no effect on the transport of 1f, indicating that P-gp does not play a relevant role in brain accumulation of [18F]1c and [18F]1f in vivo.ConclusionsThe in vitro and in vivo results of [18F]1c and [18F]1f provide a solid basis for further development of suitable OXR PET ligands for brain imaging.

Whole-Body Multiparametric PET in Clinical Oncology: Current Status, Challenges, and Opportunities.

The interpretation of clinical oncologic PET studies has historically used static reconstructions based on SUVs. SUVs and SUV-based images have important limitations, including dependence on uptake times and reduced conspicuity of tracer-avid lesions in organs with high background uptake. The acquisition of dynamic PET images enables additional PET reconstructions via Patlak modeling, which assumes that a tracer is irreversibly trapped by tissues of interest. The resulting multiparametric PET images capture a tracer's net trapping rate (Ki) and apparent volume of distribution (VD), separating the contributions of bound and free tracer fractions to the PET signal captured in the SUV. Potential benefits of multiparametric PET include higher quantitative stability, superior lesion conspicuity, and greater accuracy for differentiating malignant and benign lesions. However, the imaging protocols necessary for multiparametric PET are inherently more complex and time-intensive, despite the recent introduction of automated or semiautomated scanner-based reconstruction packages. In this Review, we examine the current state of multiparametric PET in whole-body oncologic imaging. We summarize the Patlak methodology and relevant tracer kinetics, discuss clinical workflows and protocol considerations, and highlight clinical challenges and opportunities. We aim to help oncologic imagers make informed decisions about whether to implement multiparametric PET in their clinical practices.

Quantitative Total-Body Imaging of Blood Flow with High Temporal Resolution Early Dynamic 18F-Fluorodeoxyglucose PET Kinetic Modeling.

The first two minutes of dynamic PET scans were reconstructed at high temporal resolution (60×1 s, 30×2 s) to resolve the rapid passage of the radiotracer through blood vessels. In contrast to existing methods that use blood-to-tissue transport rate ( ) as a surrogate of blood flow, our method directly estimates blood flow using a distributed kinetic model (adiabatic approximation to the tissue homogeneity model; AATH). To validate our 18F-FDG measurements of blood flow against a flow radiotracer, we analyzed total-body dynamic PET images of six human participants scanned with both 18F-FDG and 11C-butanol. An additional thirty-four total-body dynamic 18F-FDG PET scans of healthy participants were analyzed for comparison against literature blood flow ranges. Regional blood flow was estimated across the body and total-body parametric imaging of blood flow was conducted for visual assessment. AATH and standard compartment model fitting was compared by the Akaike Information Criterion at different temporal resolutions. 18F-FDG blood flow was in quantitative agreement with flow measured from 11C-butanol across same-subject regional measurements (Pearson R=0.955, p<0.001; linear regression y=0.973x-0.012), which was visually corroborated by total-body blood flow parametric imaging. Our method resolved a wide range of blood flow values across the body in broad agreement with literature ranges (e.g., healthy cohort average: 0.51±0.12 ml/min/cm3 in the cerebral cortex and 2.03±0.64 ml/min/cm3 in the lungs, respectively). High temporal resolution (1 to 2 s) was critical to enabling AATH modeling over standard compartment modeling. Total-body blood flow imaging was feasible using early-dynamic 18F-FDG PET with high-temporal resolution kinetic modeling. Combined with standard 18F-FDG PET methods, this method may enable efficient single-tracer flow-metabolism imaging, with numerous research and clinical applications in oncology, cardiovascular disease, pain medicine, and neuroscience.

A radioligand for in vitro autoradiography of CSF1R in post-mortem CNS tissues

BackgroundReactive microglia and recruited peripheral macrophages contribute to the pathogenesis of Alzheimer’s dementia (AD). Monocytes, macrophages and microglia all express the marker colony-stimulating factor 1 receptor (CSF1R). 4-Cyano-N-(4-(4-methylpiperazin-1-yl)-2-(4-methylpiperidin-1-yl)phenyl)-1H-pyrrole-2-carboxamide (1) is a high-affinity antagonist for CSF1R. We report the radiosynthesis of both [3H]1 and [11C]1. The PET imaging properties of [11C]1 in mice and baboon were investigated. [3H]1 was studied in Bmax measurement in post-mortem autoradiography in the frontal cortex, inferior parietal cortex and hippocampus from donors diagnosed with AD and age-matched controls. In vitro binding affinity of 1 was measured commercially. Nor-methyl-1 precursor was radiolabeled with [11C]iodomethane or [3H]iodomethane to produce [11C]1 and [3H]1, respectively. Ex vivo brain biodistribution of [11C]1 was compared in normal mice versus lipopolysaccharide-administered (LPS) murine model of neuroinflammation. Dynamic PET imaging was performed in a healthy male Papio anubis baboon. Post-mortem autoradiography with [3H]1 was performed in frozen sections using a standard saturation binding technique.ResultsCompound 1 exhibits a high in vitro CSF1R binding affinity (0.59 nM). [11C]1 was synthesized with high yield. [3H]1 was synthesized similarly (commercially). Biodistribution of [11C]1 in healthy mice demonstrated moderate brain uptake. In LPS-treated mice the brain uptake of [11C]1 was ~ 50% specific for CSF1R. PET/CT [11C]1 study in baboon revealed low brain uptake (0.36 SUV) of [11C]1. Autoradiography with [3H]1 gave significantly elevated Bmax values in AD frontal cortex versus control (47.78 ± 26.80 fmol/mg vs. 12.80 ± 5.30 fmol/mg, respectively, P = 0.023) and elevated, but not significantly different binding in AD hippocampus grey matter and inferior parietal cortex (IPC) white matter.ConclusionsCompound 1 exhibits a high in vitro CSF1R binding affinity. [11C]1 specifically labels CSF1R in the mouse neuroinflammation, but lacks the ability to efficiently cross the blood–brain barrier in baboon PET. [3H]1 specifically labels CSF1R in post-mortem human brain. The binding of [3H]1 is significantly higher in the post-mortem frontal cortex of AD versus control subjects.

Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.

We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation correction, image enhancement, motion correction, kinetic modeling, and simulated data generation. (1) DL-based attenuation correction (DLAC) remains an area of limited exploration for pediatric whole-body PET/MR and lung-specific DLAC due to data shortages and technical limitations. (2) DL-based image enhancement approximating MR-guided regularized reconstruction with a high-resolution MR prior has shown promise in enhancing PET image quality. However, its clinical value has not been thoroughly evaluated across various radiotracers, and applications outside the head may pose challenges due to motion artifacts. (3) Robust training for DL-based motion correction requires pairs of motion-corrupted and motion-corrected PET/MR data. However, these pairs are rare. (4) DL-based approaches can address the limitations of dynamic PET, such as long scan durations that may cause patient discomfort and motion, providing new research opportunities. (5) Monte-Carlo simulations using anthropomorphic digital phantoms can provide extensive datasets to address the shortage of clinical data. This summary of technical/clinical challenges and potential solutions may provide research opportunities for the research community towards the clinical translation of DL solutions.

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.

Quantitative Assessments of Tumor Activity in a General Oncologic PET/CT Population: Which Metric Minimizes Tracer Uptake Time Dependence?

In oncologic PET, the SUV and standardized uptake ratio (SUR) of a viable tumor generally increase during the postinjection period. In contrast, the net influx rate (Ki ), which is derived from dynamic PET data, should remain relatively constant. Uptake-time-corrected SUV (cSUV) and SUR (cSUR) have been proposed as uptake-time-independent, static alternatives to Ki Our primary aim was to quantify the intrascan repeatability of Ki , SUV, cSUV, SUR, and cSUR among malignant lesions on PET/CT. An exploratory aim was to assess the ability of cSUR to estimate Ki Methods: This prospective, single-center study enrolled adults undergoing standard-of-care oncologic PET/CT. SUV and Ki images were reconstructed from dynamic PET data obtained before (∼35-50 min after injection) and after (∼75-90 min after injection) standard-of-care imaging. Tumors were manually segmented. Quantitative metrics were extracted. cSUVs and cSURs were calculated for a 60-min postinjection reference uptake time. The magnitude of the intrascan test-retest percent change (test-retest |%Δ|) was calculated. Coefficients of determination (R 2) and intraclass correlation coefficients (ICC) were also computed. Differences between metrics were assessed via the Wilcoxon signed-rank test (α, 0.05). Results: This study enrolled 78 subjects; 41 subjects (mean age, 63.8 y; 24 men) with 116 lesions were analyzed. For both tracers, SUVmax and maximum SUR (SURmax) had large early-to-late increases (i.e., poor intrascan repeatability). Among [18F]FDG-avid lesions (n = 93), there were no differences in intrascan repeatability (median test-retest |%Δ|; ICC) between the maximum Ki (Ki ,max) (13%; 0.97) and either the maximum cSUV (cSUVmax) (12%, P = 0.90; 0.96) or the maximum cSUR (cSURmax) (13%, P = 0.67; 0.94). For DOTATATE-avid lesions (n = 23), there were no differences in intrascan repeatability between the Ki ,max (11%; 0.98) and either the cSUVmax (13%, P = 0.41; 0.98) or the cSURmax (11%, P = 0.08; 0.94). The SUVmax, cSUVmax, SURmax, and cSURmax were all strongly correlated with the Ki ,max for both [18F]FDG (R 2, 0.81-0.92) and DOTATATE (R 2, 0.88-0.96), but the cSURmax provided the best agreement with the Ki ,max across early-to-late time points for [18F]FDG (ICC, 0.69-0.75) and DOTATATE (ICC, 0.90-0.91). Conclusion: Ki ,max, cSUVmax, and cSURmax had low uptake time dependence compared with SUVmax and SURmax The Ki ,max can be predicted from cSURmax.

A novel relative-equilibrium graphical plot for rapid reversible tracer studies in dynamic PET imaging

Objective. This study aims to address the issue of long scan durations required by traditional graphical analysis methods, such as the Logan plot and its variant, the reversible equilibrium (RE) Logan plot, for dynamic PET imaging of tracer kinetics. Approach. We propose a relative RE Logan model that builds on the principles of the Logan plot and its variant to significantly reduce scan time without compromising the accuracy of tracer kinetics analysis. The model is supported by theoretical evidence and experimental validations, including two computer simulations and one clinical data analysis. Main results. The proposed model demonstrates a significant linear relationship between the variable x and the slope DVT of the RE Logan plot, and the variable x′ and the slope DVT′ of the relative RE Logan plot. The Pearson correlation coefficients (r) of the linear fitting of the x′ to the x equal 0.9849 in the simulated data and 0.9912 in the clinical data. Similarly, the r values for the linear fitting of DVT′ to DVT equal 0.9989 and 0.9988 in the simulated data, and 0.9954 in the clinical data. Significance. These results demonstrate the model’s capability to maintain strong linear relationships and produce parametric images comparable to the traditional RE Logan plot, but with the considerable advantage of shorter scan durations. This innovation holds significant potential for enhancing the efficiency and feasibility of PET imaging in clinical settings.

First-in-human evaluation of 6-bromo-7-[11C]methylpurine, a PET tracer for assessing the function of multidrug resistance-associated proteins in different tissues

PurposeMultidrug resistance-associated protein 1 (MRP1) is a transport protein with a widespread tissue distribution, which has been implicated in the pathophysiology of Alzheimer’s and chronic respiratory disease. PET with 6-bromo-7-[11C]methylpurine ([11C]BMP) has been used to measure MRP1 function in rodents. In this study, [11C]BMP was for the first time characterised in humans to assess the function of MRP1 and other MRP subtypes in different tissues.MethodsThirteen healthy volunteers (7 men, 6 women) underwent dynamic whole-body PET scans on a long axial field-of-view (LAFOV) PET/CT system after intravenous injection of [11C]BMP. Three subjects of each sex were scanned a second time to assess reproducibility. Volumes of interest were outlined for MRP-expressing tissues (cerebral cortex, cerebellum, choroid plexus, retina, lungs, myocardium, kidneys, and liver). From the time-activity curves, the elimination rate constant (kE, h− 1) was derived as a parameter for tissue MRP function and its test-retest variability (TRTV, %) was calculated. Radiation dosimetry was calculated using the Medical Internal Radiation Dose (MIRD) methodology.ResultsMean kE and corresponding TRTV values were: cerebral cortex: 0.055 ± 0.010 h− 1 (− 4 ± 24%), cerebellum: 0.033 ± 0.009 h− 1 (1 ± 39%), choroid plexus: 0.292 ± 0.059 h− 1 (0.1 ± 16%), retina: 0.234 ± 0.045 h− 1 (30 ± 38%), lungs: 0.875 ± 0.095 h− 1 (− 3 ± 11%), myocardium: 0.641 ± 0.105 h− 1 (11 ± 25%), kidneys: 1.378 ± 0.266 h− 1 (14 ± 16%), and liver: 0.685 ± 0.072 h− 1 (7 ± 9%). Significant sex differences were found for kE in the cerebellum, lungs and kidneys. Effective dose was 4.67 ± 0.18 µSv/MBq for men and 4.55 ± 0.18 µSv/MBq for women.ConclusionLAFOV PET/CT with [11C]BMP potentially allows for simultaneous assessment of MRP function in multiple human tissues. Mean TRTV of kE in different tissues was in an acceptable range, except for the retina. The radiation dosimetry of [11C]BMP was in the typical range of 11C-tracers. LAFOV PET/CT holds great potential to assess at a whole-body, multi-tissue level molecular targets relevant for drug disposition in humans.Trial registrationEudraCT 2021-006348-29. Registered 15 December 2021.

Automated Quantitative Image-Derived Input Function for the Estimation of Cerebral Blood Flow Using Oxygen-15-Labelled Water on a Long-Axial Field-of-View PET/CT Scanner.

The accurate estimation of the tracer arterial blood concentration is crucial for reliable quantitative kinetic analysis in PET. In the current work, we demonstrate the automatic extraction of an image-derived input function (IDIF) from a CT AI-based aorta segmentation subsequently resliced to a dynamic PET series acquired on a Siemens Vision Quadra long-axial field of view scanner in 10 human subjects scanned with [15O]H2O. We demonstrate that the extracted IDIF is quantitative and in excellent agreement with a delay- and dispersion-corrected sampled arterial input function (AIF). Perfusion maps in the brain are calculated and compared from the IDIF and AIF, respectively, showed a high degree of correlation. The results demonstrate the possibility of defining a quantitatively correct IDIF compared with AIFs from the new-generation high-sensitivity and high-time-resolution long-axial field-of-view PET/CT scanners.

Noninvasive Quantification of Glucose Metabolism in Mice Myocardium Using the Spline Reconstruction Technique.

The spline reconstruction technique (SRT) is a fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The purpose of this study was to compare the SRT, filtered back-projection (FBP), and the Tera-Tomo 3D algorithm for various iteration numbers, using small-animal dynamic PET data obtained from a Mediso nanoScan® PET/CT scanner. For this purpose, Patlak graphical kinetic analysis was employed to noninvasively quantify the myocardial metabolic rate of glucose (MRGlu) in seven male C57BL/6 mice (n=7). All analytic reconstructions were performed via software for tomographic image reconstruction. The analysis of all PET-reconstructed images was conducted with PMOD software (version 3.506, PMOD Technologies LLC, Fällanden, Switzerland) using the inferior vena cava as the image-derived input function. Statistical significance was determined by employing the one-way analysis of variance test. The results revealed that the differences between the values of MRGlu obtained via SRT versus FBP, and the variants of he Tera-Tomo 3D algorithm were not statistically significant (p > 0.05). Overall, the SRT appears to perform similarly to the other algorithms investigated, providing a valid alternative analytic method for preclinical dynamic PET 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.

Development of a Radiolabeled Cyclin-Dependent Kinases 4 and 6 (CDK4/6) Inhibitor for Brain and Cancer PET Imaging.

The synthesis, biochemical evaluation and radiosynthesis of a cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitor and radioligand was performed. NT431, a newly synthesized 4-fluorobenzyl-abemaciclib, exhibited high potency to CDK4/6 and against four cancer cell lines with IC50 similar to that of the parent abemaciclib. We performed a two-step one-pot radiosynthesis to produce [18F]NT431 with good radiochemical yield (9.6 ± 3%, n = 3, decay uncorrected), high radiochemical purity (>95%), and high molar activity (>370 GBq/µmol (>10.0 Ci/µmol). In vitro autoradiography confirmed the specific binding of [18F]NT431 to CDK4/6 in brain tissues. Dynamic PET imaging supports that both [18F]NT431 and the parent abemaciclib crossed the BBB albeit with modest brain uptake. Therefore, we conclude that it is unlikely that NT431 or abemaciclib (FDA approved drug) can accumulate in the brain in sufficient concentrations to be potentially effective against breast cancer brain metastases or brain cancers. However, despite the modest BBB penetration, [18F]NT431 represents an important step towards the development and evaluation of a new generation of CDK4/6 inhibitors with superior BBB penetration for the treatment and visualization of CDK4/6 positive tumors in the CNS. Also, [18F]NT431 may have potential application in peripheral tumors such as breast cancer and other CDK4/6 positive tumors.