Dynamic Positron Emission Tomography Data Research Articles

Exact parameter identification in PET pharmacokinetic modeling using the irreversible two tissue compartment model.

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.

Signal separation of simultaneous dual-tracer PET imaging based on global spatial information and channel attention

BackgroundSimultaneous dual-tracer positron emission tomography (PET) imaging efficiently provides more complete information for disease diagnosis. The signal separation has long been a challenge of dual-tracer PET imaging. To predict the single-tracer images, we proposed a separation network based on global spatial information and channel attention, and connected it to FBP-Net to form the FBPnet-Sep model.ResultsExperiments using simulated dynamic PET data were conducted to: (1) compare the proposed FBPnet-Sep model to Sep-FBPnet model and currently existing Multi-task CNN, (2) verify the effectiveness of modules incorporated in FBPnet-Sep model, (3) investigate the generalization of FBPnet-Sep model to low-dose data, and (4) investigate the application of FBPnet-Sep model to multiple tracer combinations with decay corrections. Compared to the Sep-FBPnet model and Multi-task CNN, the FBPnet-Sep model reconstructed single-tracer images with higher structural similarity, peak signal-to-noise ratio and lower mean squared error, and reconstructed time-activity curves with lower bias and variation in most regions. Excluding the Inception or channel attention module resulted in degraded image qualities. The FBPnet-Sep model showed acceptable performance when applied to low-dose data. Additionally, it could deal with multiple tracer combinations. The qualities of predicted images, as well as the accuracy of derived time-activity curves and macro-parameters were slightly improved by incorporating a decay correction module.ConclusionsThe proposed FBPnet-Sep model was considered a potential method for the reconstruction and signal separation of simultaneous dual-tracer PET imaging.

Advancing 6-bromo-7-[11C]methylpurine to clinical use: improved regioselective radiosynthesis, non-clinical toxicity data and human dosimetry estimates

Background6-Bromo-7-[11C]methylpurine ([11C]BMP) is a radiotracer for positron emission tomography (PET) to measure multidrug resistance-associated protein 1 (MRP1) transport activity in different tissues. Previously reported radiosyntheses of [11C]BMP afforded a mixture of 7- and 9-[11C]methyl regioisomers. To prepare for clinical use, we here report an improved regioselective radiosynthesis of [11C]BMP, the results of a non-clinical toxicity study as well as human dosimetry estimates based on mouse PET data.Results[11C]BMP was synthesised by regioselective N7-methylation of 6-bromo-7H-purine (prepared under good manufacturing practice) with [11C]methyl triflate in presence of 2,2,6,6-tetramethylpiperidine magnesium chloride in a TRACERlab™ FX2 C synthesis module. [11C]BMP was obtained within a total synthesis time of approximately 43 min in a decay-corrected radiochemical yield of 20.5 ± 5.2%, based on starting [11C]methyl iodide, with a radiochemical purity > 99% and a molar activity at end of synthesis of 197 ± 130 GBq/μmol (n = 28). An extended single-dose toxicity study conducted in male and female Wistar rats under good laboratory practice after single intravenous (i.v.) administration of unlabelled BMP (2 mg/kg body weight) revealed no test item related adverse effects. Human dosimetry estimates, based on dynamic whole-body PET data in female C57BL/6J mice, suggested that an i.v. injected activity amount of 400 MBq of [11C]BMP will deliver an effective dose in the typical range of 11C-labelled radiotracers.Conclusions[11C]BMP can be produced in sufficient amounts and acceptable quality for clinical use. Data from the non-clinical safety evaluation showed no adverse effects and suggested that the administration of [11C]BMP will be safe and well tolerated in humans.

Dynamic neuroreceptor positron emission tomography in non-anesthetized rats using point source based motion correction: A feasibility study with [11C]ABP688.

To prevent motion artifacts in small animal positron emission tomography (PET), animals are routinely scanned under anesthesia or physical restraint. Both may potentially alter metabolism and neurochemistry. This study investigates the feasibility of fully awake acquisition and subsequent absolute quantification of dynamic brain PET data via pharmacokinetic modelling in moving rats using the glutamate 5 receptor radioligand [11C]ABP688 and point source based motion correction. Five male rats underwent three dynamic [11C]ABP688 PET scans: two test-retest awake PET scans and one scan under anesthesia for comparison. Specific radioligand binding was determined via the simplified reference tissue model (reference: cerebellum) and outcome parameters BPND and R1 were evaluated in terms of stability and reproducibility. Test-retest measurements in awake animals gave reliable results with high correlations of BPND (y = 1.08 × -0.2, r = 0.99, p < 0.01) and an acceptable variability (mean over all investigated regions 15.7 ± 2.4%). Regional [11C]ABP688 BPNDs under awake and anesthetized conditions were comparable although in awake scans, absolute radioactive peak uptakes were lower and relative blood flow in terms of R1 was higher. Awake small animal PET with absolute quantification of neuroreceptor availability is technically feasible and reproducible thereby providing a suitable alternative whenever effects of anesthesia are undesirable, e.g. in sleep research.

ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages

BackgroundThe indirect method for generating parametric images in positron emission tomography (PET) involves the acquisition and reconstruction of dynamic images and temporal modelling of tissue activity given a measured arterial input function. This approach is not robust, as noise in each dynamic image leads to a degradation in parameter estimation. Direct methods incorporate into the image reconstruction step both the kinetic and noise models, leading to improved parametric images. These methods require extensive computational time and large computing resources. Machine learning methods have demonstrated significant potential in overcoming these challenges. But they are limited by the requirement of a paired training dataset. A further challenge within the existing framework is the use of state-of-the-art arterial input function estimation via temporal arterial blood sampling, which is an invasive procedure, or an additional magnetic resonance imaging (MRI) scan for selecting a region where arterial blood signal can be measured from the PET image. We propose a novel machine learning approach for reconstructing high-quality parametric brain images from histoimages produced from time-of-flight PET data without requiring invasive arterial sampling, an MRI scan, or paired training data from standard field-of-view scanners.ResultThe proposed is tested on a simulated phantom and five oncological subjects undergoing an 18F-FDG-PET scan of the brain using Siemens Biograph Vision Quadra. Kinetic parameters set in the brain phantom correlated strongly with the estimated parameters (K1, k2 and k3, Pearson correlation coefficient of 0.91, 0.92 and 0.93) and a mean squared error of less than 0.0004. In addition, our method significantly outperforms (p < 0.05, paired t-test) the conventional nonlinear least squares method in terms of contrast-to-noise ratio. At last, the proposed method was found to be 37% faster than the conventional method.ConclusionWe proposed a direct non-invasive DL-based reconstruction method and produced high-quality parametric maps of the brain. The use of histoimages holds promising potential for enhancing the estimation of parametric images, an area that has not been extensively explored thus far. The proposed method can be applied to subject-specific dynamic PET data alone.

Imaging the brain's immune response to alcohol with [11C]PBR28 TSPO Positron Emission Tomography.

In humans, the negative effects of alcohol are linked to immune dysfunction in both the periphery and the brain. Yet acute effects of alcohol on the neuroimmune system and its relationships with peripheral immune function are not fully understood. To address this gap, immune response to an alcohol challenge was measured with positron emission tomography (PET) using the radiotracer [11C]PBR28, which targets the 18-kDa translocator protein, a marker sensitive to immune challenges. Participants (n = 12; 5 F; 25-45 years) who reported consuming binge levels of alcohol (>3 drinks for females; >4 drinks for males) 1-3 months before scan day were enrolled. Imaging featured a baseline [11C]PBR28 scan followed by an oral laboratory alcohol challenge over 90 min. An hour later, a second [11C]PBR28 scan was acquired. Dynamic PET data were acquired for at least 90 min with arterial blood sampling to measure the metabolite-corrected input function. [11C]PBR28 volume of distributions (VT) was estimated in the brain using multilinear analysis 1. Subjective effects, blood alcohol levels (BAL), and plasma cytokines were measured during the paradigm. Full completion of the alcohol challenge and data acquisition occurred for n = 8 (2 F) participants. Mean peak BAL was 101 ± 15 mg/dL. Alcohol significantly increased brain [11C]PBR28 VT (n = 8; F(1,49) = 34.72, p > 0.0001; Cohen's d'=0.8-1.7) throughout brain by 9-16%. Alcohol significantly altered plasma cytokines TNF-α (F(2,22) = 17.49, p < 0.0001), IL-6 (F(2,22) = 18.00, p > 0.0001), and MCP-1 (F(2,22) = 7.02, p = 0.004). Exploratory analyses identified a negative association between the subjective degree of alcohol intoxication and changes in [11C]PBR28 VT. These findings provide, to our knowledge, the first in vivo human evidence for an acute brain immune response to alcohol.

Glucose uptake and distribution across the human skeleton using state-of-the-art total-body PET/CT

A growing number of studies have demonstrated that the skeleton is an endocrine organ that is involved in glucose metabolism and plays a significant role in human glucose homeostasis. However, there is still a limited understanding of the in vivo glucose uptake and distribution across the human skeleton. To address this issue, we aimed to elucidate the detailed profile of glucose uptake across the skeleton using a total-body positron emission tomography (PET) scanner. A total of 41 healthy participants were recruited. Two of them received a 1-hour dynamic total-body 18F-fluorodeoxyglucose (18F-FDG) PET scan, and all of them received a 10-minute static total-body 18F-FDG PET scan. The net influx rate (Ki) and standardized uptake value normalized by lean body mass (SUL) were calculated as indicators of glucose uptake from the dynamic and static PET data, respectively. The results showed that the vertebrae, hip bone and skull had relatively high Ki and SUL values compared with metabolic organs such as the liver. Both the Ki and SUL were higher in the epiphyseal, metaphyseal and cortical regions of long bones. Moreover, trends associated with age and overweight with glucose uptake (SULmax and SULmean) in bones were uncovered. Overall, these results indicate that the skeleton is a site with significant glucose uptake, and skeletal glucose uptake can be affected by age and dysregulated metabolism.

Spatiotemporal Learning of Dynamic Positron Emission Tomography Data Improves Diagnostic Accuracy in Breast Cancer

Positron emission tomography (PET) is a noninvasive imaging technology able to assess the metabolic or functional state of healthy and/or pathological tissues. In clinical practice, PET data are usually acquired statically and normalized for the evaluation of the standardized uptake value (SUV). In contrast, dynamic PET acquisitions provide information about radiotracer delivery to tissue, its interaction with the target and its physiological washout. The shape of the time activity curves (TACs) embeds tissue-specific biochemical properties. Conventionally, TACs are employed along with information about blood plasma activity concentration, i.e., the arterial input function, and tracer-specific compartmental models to obtain a full quantitative analysis of PET data. This method’s primary disadvantage is the requirement for invasive arterial blood sample collection throughout the whole PET scan. In this study, we employ a variety of deep learning models to illustrate the diagnostic potential of dynamic PET acquisitions of varying lengths for discriminating breast cancer lesions in the absence of arterial blood sampling compared to static PET only. Our findings demonstrate that the use of TACs, even in the absence of arterial blood sampling and even when using only a share of all timeframes available, outperforms the discriminative ability of conventional SUV analysis.

Time course of neuroinflammation after human stroke – a pilot study using co-registered PET and MRI

BackgroundMicroglial activation contributes to both inflammatory damage and repair in experimental ischemic stroke. However, because of the logistical challenges, there have been few clinical imaging studies directly describing inflammatory activation and its resolution after stroke. The purpose of our pilot study was to describe the spatio-temporal profile of brain inflammation after stroke using 18kD translocator protein (TSPO) positron emission tomography (PET) with magnetic resonance (MR) co-registration in the subacute and chronic stage after stroke.MethodsThree patients underwent magnetic resonance imaging (MRI) and PET scans with TSPO ligand [11C]PBR28 15 ± 3 and 90 ± 7 days after an ischaemic stroke. Regions of interest (ROI) were defined on MRI images and applied to the dynamic PET data to derive regional time-activity curves. Regional uptake was quantified as standardised uptake values (SUV) over 60 to 90 min post-injection. ROI analysis was applied to identify binding in the infarct, and in frontal, temporal, parietal, and occipital lobes and cerebellum excluding the infarcted area.ResultsThe mean age of participants was 56 ± 20.4 years and mean infarct volume was 17.9 ± 18.1 ml. [11C]PBR28 showed increased tracer signal in the infarcted area compared to non-infarcted areas of the brain in the subacute phase of stroke (Patient 1 SUV 1.81; Patient 2 SUV 1.15; Patient 3 SUV 1.64). [11C]PBR28 uptake returned to the level of non-infarcted areas at 90 days Patient 1 SUV 0.99; Patient 3 SUV 0.80). No additional upregulation was detected elsewhere at either time point.ConclusionsThe neuroinflammatory reaction after ischaemic stroke is limited in time and circumscribed in space suggesting that post-ischaemic inflammation is tightly controlled but regulatory mechanisms.

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

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

Spatiotemporal learning of dynamic positron emission tomography data improves diagnostic accuracy in breast cancer.

Positron emission tomography (PET) can reveal metabolic activity in a voxelwise manner. PET analysis is commonly performed in a static manner by analyzing the standardized uptake value (SUV) obtained from the plateau region of PET acquisitions. A dynamic PET acquisition can provide a map of the spatiotemporal concentration of the tracer in vivo, hence conveying information about radiotracer delivery to tissue, its interaction with the target and washout. Therefore, tissue-specific biochemical properties are embedded in the shape of time activity curves (TACs), which are generally used for kinetic analysis. Conventionally, TACs are employed along with information about blood plasma activity concentration, i.e., the arterial input function (AIF), and specific compartmental models to obtain a full quantitative analysis of PET data. The main drawback of this approach is the need for invasive procedures requiring arterial blood sample collection during the whole PET scan. In this paper, we address the challenge of improving PET diagnostic accuracy through an alternative approach based on the analysis of time signal intensity patterns. Specifically, we demonstrate the diagnostic potential of tissue TACs provided by dynamic PET acquisition using various deep learning models. Our framework is shown to outperform the discriminative potential of classical SUV analysis, hence paving the way for more accurate PET-based lesion discrimination without additional acquisition time or invasive procedures. Clinical Relevance- The diagnostic accuracy of dynamic PET data exploited by deep-learning based time signal intensity pattern analysis is superior to that of static SUV imaging.

Dictionary Learning Constrained Direct Parametric Estimation in Dynamic Myocardial Perfusion PET.

In myocardial perfusion imaging with dynamic positron emission tomography (PET), direct parametric reconstruction from the projection data allows accurate modeling of the Poisson noise in the projection domain to provide more reliable estimate of the parametric images. In this study, we propose to incorporate a superior denoiser to efficiently suppress the unfavorable noise propagation during the direct reconstruction. The dictionary learning (DL) based sparse representation serves as a regularization term to constrain the intermediate K1 estimation. We rewrite the DL regularizer into a voxel-separable form to facilitate the decoupling of a DL penalized curve fitting from the reconstruction of dynamic frames. The nonlinear fitting is then solved by a damped Newton method with uniform initialization. Using simulated and patient 82Rb dynamic PET data, we study the performance of the proposed DL direct algorithm and quantitatively compare it with the indirect method with or without post-filtering, the direct reconstruction without regularization, and the quadratic penalty regularized direct algorithm. The DL regularized direct reconstruction achieves improved noise versus bias performance in the reconstructed K1 images as well as superior recovery of a reduced myocardial blood flow defect. The dictionary learned from a 3D self-created hollow sphere image yields comparable results to those using the dictionary learned from the corresponding magnetic resonance image. The uniform initializations converge to K1 estimations similar to the result from initializing with the indirect reconstruction. To summarize, we demonstrate the potential of the proposed DL constrained direct parametric reconstruction in improving quantitative dynamic PET imaging.

Assessing different approaches to estimate single-subject metabolic connectivity from dynamic [18F]fluorodeoxyglucose Positron Emission Tomography data.

Metabolic connectivity is conventionally calculated in terms of correlation of static positron emission tomography (PET) measurements across subjects. There is increasing interest in deriving metabolic connectivity at the single-subject level from dynamic PET data, in a similar way to functional magnetic resonance imaging. However, the strong multicollinearity among region-wise PET time-activity curves (TACs), their non-Gaussian distribution, and the choice of the best strategy for TAC standardization before metabolic connectivity estimation, are non-trivial methodological issues to be tackled.In this work we test four different approaches to estimate sparse inverse covariance matrices, as well as three similarity-based methods to derive adjacency matrices. These approaches, combined with three different TAC standardization strategies, are employed to quantify metabolic connectivity from dynamic [18F]fluorodeoxyglucose ([18F]FDG) PET data in four healthy subjects.

Voxelwise Principal Component Analysis of Dynamic [S-Methyl-11C]Methionine PET Data in Glioma Patients.

Simple SummaryRecent works on dynamic amino acid positron emission tomography (PET) imaging of gliomas have highlighted characteristic behaviors of time-activity curves (TACs) extracted from the whole tumor w.r.t. the grade, genotype, and outcome. However, gliomas are known to be highly heterogeneous tumors. Here, we aim at highlighting similar dynamic behaviors at the voxel level within the tumor volume in [S-methyl-11C]methionine PET data of 33 glioma patients using principal component analysis (PCA). The PCA model was derived from TACs of 20 patients and subsequently applied to 13 other patients in whom our approach was shown to outperform classical pharmacokinetic modeling to this end. Our parameter-free approach provides additional parametric maps from dynamic methionine PET scans with little modification of the routine protocol and no arterial sampling. This early methodological work paves the way for various clinical studies on glioma heterogeneity with applications for treatment planning and response evaluation.Recent works have demonstrated the added value of dynamic amino acid positron emission tomography (PET) for glioma grading and genotyping, biopsy targeting, and recurrence diagnosis. However, most of these studies are based on hand-crafted qualitative or semi-quantitative features extracted from the mean time activity curve within predefined volumes. Voxelwise dynamic PET data analysis could instead provide a better insight into intra-tumor heterogeneity of gliomas. In this work, we investigate the ability of principal component analysis (PCA) to extract relevant quantitative features from a large number of motion-corrected [S-methyl-11C]methionine ([11C]MET) PET frames. We first demonstrate the robustness of our methodology to noise by means of numerical simulations. We then build a PCA model from dynamic [11C]MET acquisitions of 20 glioma patients. In a distinct cohort of 13 glioma patients, we compare the parametric maps derived from our PCA model to these provided by the classical one-compartment pharmacokinetic model (1TCM). We show that our PCA model outperforms the 1TCM to distinguish characteristic dynamic uptake behaviors within the tumor while being less computationally expensive and not requiring arterial sampling. Such methodology could be valuable to assess the tumor aggressiveness locally with applications for treatment planning and response evaluation. This work further supports the added value of dynamic over static [11C]MET PET in gliomas.

Evaluation of Arterial Spin Labeling MRI-Comparison with 15O-Water PET on an Integrated PET/MR Scanner.

Cerebral blood flow (CBF) measurements are of high clinical value and can be acquired non-invasively with no radiation exposure using pseudo-continuous arterial spin labeling (ASL). The aim of this study was to evaluate accordance in resting state CBF between ASL (CBFASL) and 15O-water positron emission tomography (PET) (CBFPET) acquired simultaneously on an integrated 3T PET/MR system. The data comprised ASL and dynamic 15O-water PET data with arterial blood sampling of eighteen subjects (eight patients with focal epilepsy and ten healthy controls, age 21 to 61 years). 15O-water PET parametric CBF images were generated using a basis function implementation of the single tissue compartment model. Cortical and subcortical regions were automatically segmented using Freesurfer. Average CBFASL and CBFPET in grey matter were 60 ± 20 and 75 ± 22 mL/100 g/min respectively, with a relatively high correlation (r = 0.78, p < 0.001). Bland-Altman analysis revealed poor agreement (bias = −15 mL/100 g/min, lower and upper limits of agreements = −16 and 45 mL/100 g/min, respectively) with a negative relationship. Accounting for the negative relationship, the width of the limits of agreement could be narrowed from 61 mL/100 g/min to 35 mL/100 g/min using regression-based limits of agreements. Although a high correlation between CBFASL and CBFPET was found, the agreement in absolute CBF values was not sufficient for ASL to be used interchangeably with 15O-water PET.

Real-Time Positron Emission Tomography Evaluation of Topotecan Brain Kinetics after Ultrasound-Mediated Blood-Brain Barrier Permeability.

Glioblastoma (GBM) is the most common primary adult brain malignancy with an extremely poor prognosis and a median survival of fewer than two years. A key reason for this high mortality is that the blood–brain barrier (BBB) significantly restricts systemically delivered therapeutics to brain tumors. High-intensity focused ultrasound (HIFU) with microbubbles is a methodology being used in clinical trials to noninvasively permeabilize the BBB for systemic therapeutic delivery to GBM. Topotecan is a topoisomerase inhibitor used as a chemotherapeutic agent to treat ovarian and small cell lung cancer. Studies have suggested that topotecan can cross the BBB and can be used to treat brain metastases. However, pharmacokinetic data demonstrated that topotecan peak concentration in the brain extracellular fluid after systemic injection was ten times lower than in the blood, suggesting less than optimal BBB penetration by topotecan. We hypothesize that HIFU with microbubbles treatment can open the BBB and significantly increase topotecan concentration in the brain. We radiolabeled topotecan with 11C and acquired static and dynamic positron emission tomography (PET) scans to quantify [11C] topotecan uptake in the brains of normal mice and mice after HIFU treatment. We found that HIFU treatments significantly increased [11C] topotecan brain uptake. Moreover, kinetic analysis of the [11C] topotecan dynamic PET data demonstrated a substantial increase in [11C] topotecan volume of distribution in the brain. Furthermore, we found a decrease in [11C] topotecan brain clearance, confirming the potential of HIFU to aid in the delivery of topotecan through the BBB. This opens the potential clinical application of [11C] topotecan as a tool to predict topotecan loco-regional brain concentration in patients with GBMs undergoing experimental HIFU treatments.

Synthesis and preclinical evaluation of [11C]MTP38 as a novel PET ligand for phosphodiesterase 7 in the brain

PurposePhosphodiesterase (PDE) 7 is a potential therapeutic target for neurological and inflammatory diseases, although in vivo visualization of PDE7 has not been successful. In this study, we aimed to develop [11C]MTP38 as a novel positron emission tomography (PET) ligand for PDE7.Methods[11C]MTP38 was radiosynthesized by 11C-cyanation of a bromo precursor with [11C]HCN. PET scans of rat and rhesus monkey brains and in vitro autoradiography of brain sections derived from these species were conducted with [11C]MTP38. In monkeys, dynamic PET data were analyzed with an arterial input function to calculate the total distribution volume (VT). The non-displaceable binding potential (BPND) in the striatum was also determined by a reference tissue model with cerebellar reference. Finally, striatal occupancy of PDE7 by an inhibitor was calculated in monkeys according to changes in BPND.Results[11C]MTP38 was synthesized with radiochemical purity ≥99.4% and molar activity of 38.6 ± 12.6 GBq/μmol. Autoradiography revealed high radioactivity in the striatum and its reduction by non-radiolabeled ligands, in contrast with unaltered autoradiographic signals in other regions. In vivo PET after radioligand injection to rats and monkeys demonstrated that radioactivity was rapidly distributed to the brain and intensely accumulated in the striatum relative to the cerebellum. Correspondingly, estimated VT values in the monkey striatum and cerebellum were 3.59 and 2.69 mL/cm3, respectively. The cerebellar VT value was unchanged by pretreatment with unlabeled MTP38. Striatal BPND was reduced in a dose-dependent manner after pretreatment with MTP-X, a PDE7 inhibitor. Relationships between PDE7 occupancy by MTP-X and plasma MTP-X concentration could be described by Hill’s sigmoidal function.ConclusionWe have provided the first successful preclinical demonstration of in vivo PDE7 imaging with a specific PET radioligand. [11C]MTP38 is a feasible radioligand for evaluating PDE7 in the brain and is currently being applied to a first-in-human PET study.

Acute acetate administration increases endogenous opioid levels in the human brain: A [11C]carfentanil molecular imaging study.

Introduction:A recent study has shown that acetate administration leads to a fourfold increase in the transcription of proopiomelanocortin (POMC) mRNA in the hypothalamus. POMC is cleaved to peptides, including β-endorphin, an endogenous opioid (EO) agonist that binds preferentially to the µ-opioid receptor (MOR). We hypothesised that an acetate challenge would increase the levels of EO in the human brain. We have previously demonstrated that increased EO release in the human brain can be detected using positron emission tomography (PET) with the selective MOR radioligand [11C]carfentanil. We used this approach to evaluate the effects of an acute acetate challenge on EO levels in the brain of healthy human volunteers.Methods:Seven volunteers each completed a baseline [11C]carfentanil PET scan followed by an administration of sodium acetate before a second [11C]carfentanil PET scan. Dynamic PET data were acquired over 90 minutes, and corrected for attenuation, scatter and subject motion. Regional [11C] carfentanil BPND values were then calculated using the simplified reference tissue model (with the occipital grey matter as the reference region). Change in regional EO concentration was evaluated as the change in [11C]carfentanil BPND following acetate administration.Results:Following sodium acetate administration, 2.5–6.5% reductions in [11C]carfentanil regional BPND were seen, with statistical significance reached in the cerebellum, temporal lobe, orbitofrontal cortex, striatum and thalamus.Conclusions:We have demonstrated that an acute acetate challenge has the potential to increase EO release in the human brain, providing a plausible mechanism of the central effects of acetate on appetite in humans.

Dynamic PET Image Reconstruction Incorporating Multiscale Superpixel Clusters

Dynamic positron emission tomography (PET) image reconstruction is challenging due to the low-count statistics of individual frames. This study proposes a novel reconstruction framework aiming to enhance the quantitative accuracy of individual dynamic frames via the introduction of priors based on multiscale superpixel clusters. The clusters are derived from pre-reconstruction composite images using superpixel clustering followed by fuzzy c-means (FCM) clustering. A multiscale aggregation is exploited during the superpixel clustering to generate multiscale superpixel clusters. Then, maximum a posteriori (MAP) PET reconstruction with different-scale clusters is separately applied to individual frame and fused to generate the final result. Using realistic simulated dynamic brain PET data, the quantitative performance of the proposed method is investigated and compared with the maximum-likelihood expectation-maximization (MLEM), Bowsher method, and kernelized expectation-maximization (the kernel method). The proposed method achieves substantial improvements in both visual and quantitative accuracy (in terms of the signal-to-noise ratio and contrast versus noise performances). The method is also tested with a 60 min 18F-FDG rat study performed with an Inveon small animal PET scanner. The proposed method is shown to outperform the other methods via improvements in visual and quantitative accuracy (in terms of noise versus the mean intensity of the region of interest).

Can B Washout Rate be a Biomarker of Tumor Viability in Charged Particle Therapy? A Rat In-beam PET Study

Positron emission tomography (PET) is a practical tool for range verification in charged particle therapy. We aimed to apply in-beam PET imaging for tracking the evolution of irradiated particles in living tissue. The quantitative biological washout rate of the positron emitters has a potential usefulness as a diagnostic index that provides a unique opportunity to probe the status of tumor viability, but the modeling for this has not been established. Therefore, we measured biological washout rates of tumor-bearing nude rat and performed kinetic analysis on dynamic PET data to explore the biological washout mechanism. C6 rat glioma cells were implanted into right shoulder subcutaneous regions of six nude rats. Tumors volume reached to about 3 cm3 on day 14 after implantation. Tumor tissue (right shoulder) and normal tissue (left shoulder) were irradiated by 11C radioactive ion beam. Time activity curves (TACs) of the irradiated field were acquired by our original PET prototype. The biological washout rate was quantified based on the two-washout model assuming medium decay rate (k2m) and slow decay rate (k2s). In this model, k2m is speculated as the component which spread out via interstitial fluid, and k2s is speculated as the trapping component by the stable molecules in the tissue. After irradiation and PET dynamic scan, pathological morphology of tumor tissue (Hematoxylin & Eosin staining) was observed under microscope. The two-washout model fitted the experimental TACs well for five of six nude-rats irradiation studies. The observed k2m of tumor irradiation was 0.31+/-0.04 min-1, which was consistent with the normal tissue irradiation. While k2s of tumor irradiation was faster (0.017 +/-0.002 min-1) than that of normal tissue irradiation (0.006 +/-0.002 min-1). These results suggested that the component, which was trapped in normal tissue, diffused out more smoothly from tumor tissue due to vascular hyperpermeability which characterizes pathological tumor-angiogenesis. For one of six nude rats, only slow washout component (k2s = 0.014 +/-0.003 min-1) was observed in tumor irradiation study. Necrosis in tumor was observed in pathological tissue sample of this nude rat. It is also suggested that the decrease of washout rate was caused by the decrease of blood flow in the necrotic region. We measured the biological washout rate of irradiated 11C ion beam in tumor tissue and normal tissue. The physiological difference of tissue condition reflected the biological washout rates. This effect may be used as a clinical diagnostic index to monitor the dose response of the tumors in individual patients as well as the observation of the functional metabolism of tumor.