PICASSO: a universal brain phantom for positron emission tomography based on the activity painting technique.

Objective. This study presents a universal phantom for positron emission tomography (PET) that allows arbitrary static and dynamic activity distributions of various complexities to be generated using a single PET acquisition.Approach. We collected a high-statistics dataset (with a total of 22.4 × 109prompt coincidences and an event density of 2.75 × 106events mm-3) by raster-scanning a single plane with a22Na point source mounted on a robotic arm in the field-of-view of the uEXPLORER PET/CT scanner. The source position was determined from the reconstructed dynamic frames. Uniquely, true coincidences were separated from scattered and random events based on the distance between their line-of-response and the known source location. Finally, we randomly sampled the dataset to generate the desired activity distributions modeling several different phantoms.Main results. Overall, the target and the reconstructed phantom images had good agreement. The analysis of a simple geometric distribution showed high quantitative accuracy of the phantom, with mean error of <-3.0% relative to the ground truth for activity concentrations ranging from 5.3 to 47.7 kBq ml-1. The model of a high-resolution18F-fluorodeoxyglucose distribution in the brain illustrates the usefulness of the technique in simulating realistic static neuroimaging studies. A dynamic18F-florbetaben study was modeled based on the time-activity curves of a human study and a segmented brain phantom with no coincidences repeating between frames. For all time points, the mean voxel-wise errors ranged from -4.4% to -0.7% in grey matter and from -3.9% to +2.8% in white matter.Significance. The proposed phantom technique is highly flexible and allows modeling of static and dynamic brain PET studies with high quantitative accuracy. It overcomes several key limitations of the existing phantoms and has many promising applications for the purposes of image reconstruction, data correction methods, and system performance evaluation, particularly for new high-performance dedicated brain PET scanners.

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

Quantitative total-body PET imaging of blood flow can be performed with freely diffusible flow radiotracers such as 15O-water and 11C-butanol, but their short half-lives necessitate close access to a cyclotron. Past efforts to measure blood flow with the widely available radiotracer 18F-fluorodeoxyglucose (FDG) were limited to tissues with high 18F-FDG extraction fraction. In this study, we developed an early-dynamic 18F-FDG PET method with high temporal resolution kinetic modeling to assess total-body blood flow based on deriving the vascular transit time of 18F-FDG and conducted a pilot comparison study against a 11C-butanol reference. Methods: 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 ( K 1 ) 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. Results: 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. Conclusions: 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.

Quantitative PET imaging and modeling of molecular blood-brain barrier permeability.

Blood-brain barrier (BBB) disruption is involved in the pathogenesis and progression of many neurological and systemic diseases. Non-invasive assessment of BBB permeability in humans has mainly been performed with dynamic contrast-enhanced magnetic resonance imaging, evaluating the BBB as a structural barrier. Here, we developed a novel non-invasive positron emission tomography (PET) method in humans to measure the BBB permeability of molecular radiotracers that cross the BBB through different transport mechanisms. Our method uses high-temporal resolution dynamic imaging and kinetic modeling to jointly estimate cerebral blood flow and tracer-specific BBB transport rate from a single dynamic PET scan and measure the molecular permeability-surface area (PS) product of the radiotracer. We show our method can resolve BBB PS across three PET radiotracers with greatly differing permeabilities, measure reductions in BBB PS of 18F-fluorodeoxyglucose (FDG) in healthy aging, and demonstrate a possible brain-body association between decreased FDG BBB PS in patients with metabolic dysfunction-associated steatotic liver inflammation. Our method opens new directions to efficiently study the molecular permeability of the human BBB in vivo using the large catalogue of available molecular PET tracers.

Total-Body Parametric Imaging Using Relative Patlak Plot.

Standard Patlak plot is widely used to describe FDG kinetics for dynamic PET imaging. Whole-body Patlak parametric imaging remains constrained due to the need for a full-time input function. Here, we demonstrate the Relative Patlak (RP) plot, which eliminates the need for the early-time input function, for total-body parametric imaging and its application to clinical 20-min scan acquired in list-mode. We demonstrated that the RP intercept b' is equivalent to a ratio of standardized uptake value relative to the blood, while the RP slope Ki' is equal to the standard Patlak Ki multiplied by a global scaling factor for each subject. One challenge in applying RP to a short scan duration (20 min) is the high noise in parametric images. We applied a deep kernel method for noise reduction. Using the standard Patlak plot as the reference, the RP method was evaluated for lesion quantification, lesion-to-background contrast, and myocardial visualization in total-body parametric imaging with uEXPLORER in 22 human subjects who underwent a 1-h dynamic 18F-FDG scan. The RP method was also applied to the dynamic data regenerated from a clinical standard 20-min scan either at 1-h or 2-h post-injection for two cancer patients. We demonstrated that it is feasible to obtain high-quality parametric images from 20-min dynamic scans using the RP plot with a self-supervised deep-kernel noise reduction strategy. The RP Ki' highly correlated with Ki in lesions and major organs, demonstrating its quantitative potential across subjects. Compared to conventional SUVs, the Ki' images significantly improved lesion contrast and enabled visualization of the myocardium for potential cardiac assessment. The application of RP parametric imaging to two clinical scans also showed similar benefits. Total-body PET with the RP plot is feasible to generate parametric images from the dynamic data of a 20-min clinical scan.

Total-Body Dynamic Imaging and Kinetic Modeling of [18F]F-AraG in Healthy Individuals and a Non-Small Cell Lung Cancer Patient Undergoing Anti-PD-1 Immunotherapy.

Immunotherapies, especially checkpoint inhibitors such as anti-programmed cell death protein 1 (anti-PD-1) antibodies, have transformed cancer treatment by enhancing the immune system's capability to target and kill cancer cells. However, predicting immunotherapy response remains challenging. 18F-arabinosyl guanine ([18F]F-AraG) is a molecular imaging tracer targeting activated T cells, which may facilitate therapy response assessment by noninvasive quantification of immune cell activity within the tumor microenvironment and elsewhere in the body. The aim of this study was to obtain preliminary data on total-body pharmacokinetics of [18F]F-AraG as a potential quantitative biomarker for immune response evaluation. Methods: The study consisted of 90-min total-body dynamic scans of 4 healthy subjects and 1 non-small cell lung cancer patient who was scanned before and after anti-PD-1 immunotherapy. Compartmental modeling with Akaike information criterion model selection was used to analyze tracer kinetics in various organs. Additionally, 7 subregions of the primary lung tumor and 4 mediastinal lymph nodes were analyzed. Practical identifiability analysis was performed to assess the reliability of kinetic parameter estimation. Correlations of the SUVmean, the tissue-to-blood SUV ratio (SUVR), and the Logan plot slope (K Logan) with the total volume of distribution (V T) were calculated to identify potential surrogates for kinetic modeling. Results: Strong correlations were observed between K Logan and SUVR with V T, suggesting that they can be used as promising surrogates for V T, especially in organs with a low blood-volume fraction. Moreover, practical identifiability analysis suggested that dynamic [18F]F-AraG PET scans could potentially be shortened to 60 min, while maintaining quantification accuracy for all organs of interest. The study suggests that although [18F]F-AraG SUV images can provide insights on immune cell distribution, kinetic modeling or graphical analysis methods may be required for accurate quantification of immune response after therapy. Although SUVmean showed variable changes in different subregions of the tumor after therapy, the SUVR, K Logan, and V T showed consistent increasing trends in all analyzed subregions of the tumor with high practical identifiability. Conclusion: Our findings highlight the promise of [18F]F-AraG dynamic imaging as a noninvasive biomarker for quantifying the immune response to immunotherapy in cancer patients. Promising total-body kinetic modeling results also suggest potentially wider applications of the tracer in investigating the role of T cells in the immunopathogenesis of diseases.

Refining penalty parameter selection in whole-body PET image reconstruction for lung cancer patients using the cross-validation log-likelihood method.

Objective.Penalty parameters in penalized likelihood positron emission tomography (PET) reconstruction are typically determined empirically. The cross-validation log-likelihood (CVLL) method has been introduced to optimize these parameters by maximizing a CVLL function, which assesses the likelihood of reconstructed images using one subset of a list-mode dataset based on another subset. This study aims to validate the efficacy of the CVLL method in whole-body imaging for cancer patients using a conventional clinical PET scanner.Approach.Fifteen lung cancer patients were injected with 243.7 ± 23.8 MBq of [18F]FDG and underwent a 22 min PET scan on a Biograph mCT PET/CT scanner, starting at 60 ± 5 min post-injection. The PET list-mode data were partitioned by subsampling without replacement, with 20 minutes of data for image reconstruction using an in-house ordered subset expectation maximization algorithm and the remaining 2 minutes of data for cross-validation. Two penalty parameters, penalty strengthßand Fair penalty function parameterδ, were subjected to optimization. Whole-body images were reconstructed, and CVLL values were computed across various penalty parameter combinations. The optimal image corresponding to the maximum CVLL value was selected by a grid search for each patient.Main results.Theδvalue required to maximize the CVLL value was notably small (⩽10-6in this study). The influences of voxel size and scan duration on image optimization were investigated. A correlation analysis revealed a significant inverse relationship between optimalßand scan count level, with a correlation coefficient of -0.68 (p-value = 3.5 × 10-5). The optimal images selected by the CVLL method were compared with those chosen by two radiologists based on their diagnostic preferences. Differences were observed in the selection of optimal images.Significance.This study demonstrates the feasibility of incorporating the CVLL method into routine imaging protocols, potentially allowing for a wide range of combinations of injected radioactivity amounts and scan durations in modern PET imaging.

[Direct Positron Emission Imaging Using Ultrafast Timing Performance Detectors].

This is an explanatory paper on Sun Il Kwon et al., Nat. Photon. 15: 914-918, 2021 and some parts of this manuscript are translated from the paper. Medical imaging modalities such as X-ray computed tomography, Magnetic resonance imaging, positron emission tomography (PET), and single photon emission computed tomography, require image reconstruction processes, consequently constraining them to form cylindrical shapes. However, among them, only PET can use additional information, so called time of flight, on an event-by-event basis. If coincidence time resolution (CTR) of PET detectors improved to 30 ps, which corresponds to spatial resolution of 4.5 mm, directly localizing electron-positron annihilation point is possible, allowing us to circumvent image reconstruction processes and free us from the geometric constraint. We call this concept direct positron emission imaging (dPEI). We have developed ultrafast radiation detectors by focusing on Cherenkov photon detection. Furthermore, the CTR of 32 ps being equivalent to 4.8 mm spatial resolution is achieved by combining deep learning-based signal processing with the detectors. In this article, we explain how we developed the detectors and demonstrated the first dPEI using different types of phantoms, how we will tackle limitations to be addressed to make the dPEI more practical, and how dPEI will emerge as an imaging modality in nuclear medicine.

Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager.

The collaboration of Yale, the University of California, Davis, and United Imaging Healthcare has successfully developed the NeuroEXPLORER, a dedicated human brain PET imager with high spatial resolution, high sensitivity, and a built-in 3-dimensional camera for markerless continuous motion tracking. It has high depth-of-interaction and time-of-flight resolutions, along with a 52.4-cm transverse field of view (FOV) and an extended axial FOV (49.5 cm) to enhance sensitivity. Here, we present the physical characterization, performance evaluation, and first human images of the NeuroEXPLORER. Methods: Measurements of spatial resolution, sensitivity, count rate performance, energy and timing resolution, and image quality were performed adhering to the National Electrical Manufacturers Association (NEMA) NU 2-2018 standard. The system's performance was demonstrated through imaging studies of the Hoffman 3-dimensional brain phantom and the mini-Derenzo phantom. Initial 18F-FDG images from a healthy volunteer are presented. Results: With filtered backprojection reconstruction, the radial and tangential spatial resolutions (full width at half maximum) averaged 1.64, 2.06, and 2.51 mm, with axial resolutions of 2.73, 2.89, and 2.93 mm for radial offsets of 1, 10, and 20 cm, respectively. The average time-of-flight resolution was 236 ps, and the energy resolution was 10.5%. NEMA sensitivities were 46.0 and 47.6 kcps/MBq at the center and 10-cm offset, respectively. A sensitivity of 11.8% was achieved at the FOV center. The peak noise-equivalent count rate was 1.31 Mcps at 58.0 kBq/mL, and the scatter fraction at 5.3 kBq/mL was 36.5%. The maximum count rate error at the peak noise-equivalent count rate was less than 5%. At 3 iterations, the NEMA image-quality contrast recovery coefficients varied from 74.5% (10-mm sphere) to 92.6% (37-mm sphere), and background variability ranged from 3.1% to 1.4% at a contrast of 4.0:1. An example human brain 18F-FDG image exhibited very high resolution, capturing intricate details in the cortex and subcortical structures. Conclusion: The NeuroEXPLORER offers high sensitivity and high spatial resolution. With its long axial length, it also enables high-quality spinal cord imaging and image-derived input functions from the carotid arteries. These performance enhancements will substantially broaden the range of human brain PET paradigms, protocols, and thereby clinical research applications.

Optimization-derived blood input function using a kernel method and its evaluation with total-body PET for brain parametric imaging.

Dynamic PET allows quantification of physiological parameters through tracer kinetic modeling. For dynamic imaging of brain or head and neck cancer on conventional PET scanners with a short axial field of view, the image-derived input function (ID-IF) from intracranial blood vessels such as the carotid artery (CA) suffers from severe partial volume effects. Alternatively, optimization-derived input function (OD-IF) by the simultaneous estimation (SIME) method does not rely on an ID-IF but derives the input function directly from the data. However, the optimization problem is often highly ill-posed. We proposed a new method that combines the ideas of OD-IF and ID-IF together through a kernel framework. While evaluation of such a method is challenging in human subjects, we used the uEXPLORER total-body PET system that covers major blood pools to provide a reference for validation. METHODS: The conventional SIME approach estimates an input function using a joint estimation together with kinetic parameters by fitting time activity curves from multiple regions of interests (ROIs). The input function is commonly parameterized with a highly nonlinear model which is difficult to estimate. The proposed kernel SIME method exploits the CA ID-IF as a priori information via a kernel representation to stabilize the SIME approach. The unknown parameters are linear and thus easier to estimate. The proposed method was evaluated using 18F-fluorodeoxyglucose studies with both computer simulations and 20 human-subject scans acquired on the uEXPLORER scanner. The effect of the number of ROIs on kernel SIME was also explored. RESULTS: The estimated OD-IF by kernel SIME showed a good match with the reference input function and provided more accurate estimation of kinetic parameters for both simulation and human-subject data. The kernel SIME led to the highest correlation coefficient (R = 0.97) and the lowest mean absolute error (MAE = 10.5 %) compared to using the CA ID-IF (R = 0.86, MAE = 108.2 %) and conventional SIME (R = 0.57, MAE = 78.7 %) in the human-subject evaluation. Adding more ROIs improved the overall performance of the kernel SIME method. CONCLUSION: The proposed kernel SIME method shows promise to provide an accurate estimation of the blood input function and kinetic parameters for brain PET parametric imaging.

Dose Reduction in Pediatric Oncology Patients with Delayed Total-Body [18F]FDG PET/CT.

Our aim was to define a lower limit of reduced injected activity in delayed [18F]FDG total-body (TB) PET/CT in pediatric oncology patients. Methods: In this single-center prospective study, children were scanned for 20 min with TB PET/CT, 120 min after intravenous administration of a 4.07 ± 0.49 MBq/kg dose of [18F]FDG. Five randomly subsampled low-count reconstructions were generated using », ⅛, [Formula: see text], and [Formula: see text] of the counts in the full-dose list-mode reference standard acquisition (20 min), to simulate dose reduction. For the 2 lowest-count reconstructions, smoothing was applied. Background uptake was measured with volumes of interest placed on the ascending aorta, right liver lobe, and third lumbar vertebra body (L3). Tumor lesions were segmented using a 40% isocontour volume-of-interest approach. Signal-to-noise ratio, tumor-to-background ratio, and contrast-to-noise ratio were calculated. Three physicians identified malignant lesions independently and assessed the image quality using a 5-point Likert scale. Results: In total, 113 malignant lesions were identified in 18 patients, who met the inclusion criteria. Of these lesions, 87.6% were quantifiable. Liver SUVmean did not change significantly, whereas a lower signal-to-noise ratio was observed in all low-count reconstructions compared with the reference standard (P < 0.0001) because of higher noise rates. Tumor uptake (SUVmax), tumor-to-background ratio, and total lesion count were significantly lower in the reconstructions with [Formula: see text] and [Formula: see text] of the counts of the reference standard (P < 0.001). Contrast-to-noise ratio and clinical image quality were significantly lower in all low-count reconstructions than with the reference standard. Conclusion: Dose reduction for delayed [18F]FDG TB PET/CT imaging in children is possible without loss of image quality or lesion conspicuity. However, our results indicate that to maintain comparable tumor uptake and lesion conspicuity, PET centers should not reduce the injected [18F]FDG activity below 0.5 MBq/kg when using TB PET/CT in pediatric imaging at 120 min after injection.

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

BACKGROUND: Kinetic 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. METHODS: 18F-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 ([Formula: see text] was also calculated from the multi-reference tissue model (MRTM). RESULTS: Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula: see text] analysis. [Formula: see text]and VT from kinetic models were correlated (r² = 0.46, P < 2[Formula: see text] with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated ([Formula: see text]= 0.65, P < 2[Formula: see text]) with Logan graphical VT estimation. CONCLUSION: Non-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 [Formula: see text]in amyloid-positive and amyloid-negative older individuals.

Super-resolution reconstruction of γ-ray CT images for PET-enabled dual-energy CT imaging.

Dual-energy computed tomography (DECT) enables material decomposition for tissues and produces additional information for PET/CT imaging to potentially improve the characterization of diseases. PET-enabled DECT (PDECT) allows the generation of PET and DECT images simultaneously with a conventional PET/CT scanner without the need for a second x-ray CT scan. In PDECT, high-energy γ-ray CT (GCT) images at 511 keV are obtained from time-of-flight (TOF) PET data and are combined with the existing x-ray CT images to form DECT imaging. We have developed a kernel-based maximum-likelihood attenuation and activity (MLAA) method that uses x-ray CT images as a priori information for noise suppression. However, our previous studies focused on GCT image reconstruction at the PET image resolution which is coarser than the image resolution of the x-ray CT. In this work, we explored the feasibility of generating super-resolution GCT images at the corresponding CT resolution. The study was conducted using both phantom and patient scans acquired with the uEXPLORER total-body PET/CT system. GCT images at the PET resolution with a pixel size of 4.0 mm × 4.0 mm and at the CT resolution with a pixel size of 1.2 mm × 1.2 mm were reconstructed using both the standard MLAA and kernel MLAA methods. The results indicated that the GCT images at the CT resolution had sharper edges and revealed more structural details compared to the images reconstructed at the PET resolution. Furthermore, images from the kernel MLAA method showed substantially improved image quality compared to those obtained with the standard MLAA method.

High-Temporal-Resolution Kinetic Modeling of Lung Tumors with Dual-Blood Input Function Using Total-Body Dynamic PET.

The lungs are supplied by both the pulmonary arteries carrying deoxygenated blood originating from the right ventricle and the bronchial arteries carrying oxygenated blood downstream from the left ventricle. However, this effect of dual blood supply has never been investigated using PET, partially because the temporal resolution of conventional dynamic PET scans is limited. The advent of PET scanners with a long axial field of view, such as the uEXPLORER total-body PET/CT system, permits dynamic imaging with high temporal resolution (HTR). In this work, we modeled the dual-blood input function (DBIF) and studied its impact on the kinetic quantification of normal lung tissue and lung tumors using HTR dynamic PET imaging. Methods: Thirteen healthy subjects and 6 cancer subjects with lung tumors underwent a dynamic 18F-FDG scan with the uEXPLORER for 1 h. Data were reconstructed into dynamic frames of 1 s in the early phase. Regional time-activity curves of lung tissue and tumors were analyzed using a 2-tissue compartmental model with 3 different input functions: the right ventricle input function, left ventricle input function, and proposed DBIF, all with time delay and dispersion corrections. These models were compared for time-activity curve fitting quality using the corrected Akaike information criterion and for differentiating lung tumors from lung tissue using the Mann-Whitney U test. Voxelwise multiparametric images by the DBIF model were further generated to verify the regional kinetic analysis. Results: The effect of dual blood supply was pronounced in the high-temporal-resolution time-activity curves of lung tumors. The DBIF model achieved better time-activity curve fitting than the other 2 single-input models according to the corrected Akaike information criterion. The estimated fraction of left ventricle input was low in normal lung tissue of healthy subjects but much higher in lung tumors (∼0.04 vs. ∼0.3, P < 0.0003). The DBIF model also showed better robustness in the difference in 18F-FDG net influx rate [Formula: see text] and delivery rate [Formula: see text] between lung tumors and normal lung tissue. Multiparametric imaging with the DBIF model further confirmed the differences in tracer kinetics between normal lung tissue and lung tumors. Conclusion: The effect of dual blood supply in the lungs was demonstrated using HTR dynamic imaging and compartmental modeling with the proposed DBIF model. The effect was small in lung tissue but nonnegligible in lung tumors. HTR dynamic imaging with total-body PET can offer a sensitive tool for investigating lung diseases.

Feasibility of PET-enabled dual-energy CT imaging: First physical phantom and patient results.

X-ray computed tomography (CT) in PET/CT is commonly operated with a single energy, resulting in a limitation of lacking tissue composition information. Dual-energy (DE) spectral CT enables material decomposition by using two different x-ray energies and may be combined with PET for improved multimodality imaging, but would either require hardware upgrade or increase radiation dose due to the added second x-ray CT scan. Recently proposed PET-enabled DECT method allows dual-energy spectral imaging using a conventional PET/CT scanner without the need for a second x-ray CT scan. A gamma-ray CT (gCT) image at 511 keV can be generated from the existing time-of-flight PET data with the maximum-likelihood attenuation and activity (MLAA) approach and is then combined with the low-energy x-ray CT image to form dual-energy spectral imaging. To improve the image quality of gCT, a kernel MLAA method was further proposed by incorporating x-ray CT as a priori information. The concept of this PET-enabled DECT has been validated using simulation studies, but not yet with 3D real data. In this work, we developed a general open-source implementation for gCT reconstruction from PET data and use this implementation for the first real data validation with both a physical phantom study and a human subject study on a uEXPLORER total-body PET/CT system. These results have demonstrated the feasibility of this method for spectral imaging and material decomposition.

Development of a Monte Carlo-based scatter correction method for total-body PET using the uEXPLORER PET/CT scanner.

Objective.This study presents and evaluates a robust Monte Carlo-based scatter correction (SC) method for long axial field of view (FOV) and total-body positron emission tomography (PET) using the uEXPLORER total-body PET/CT scanner.Approach.Our algorithm utilizes the Monte Carlo (MC) tool SimSET to compute SC factors in between individual image reconstruction iterations within our in-house list-mode and time-of-flight-based image reconstruction framework. We also introduced a unique scatter scaling technique at the detector block-level for optimal estimation of the scatter contribution in each line of response. First image evaluations were derived from phantom data spanning the entire axial FOV along with image data from a human subject with a large body mass index. Data was evaluated based on qualitative inspections, and contrast recovery, background variability, residual scatter removal from cold regions, biases and axial uniformity were quantified and compared to non-scatter-corrected images.Main results.All reconstructed images demonstrated qualitative and quantitative improvements compared to non-scatter-corrected images: contrast recovery coefficients improved by up to 17.2% and background variability was reduced by up to 34.3%, and the residual lung error was between 1.26% and 2.08%. Low biases throughout the axial FOV indicate high quantitative accuracy and axial uniformity of the corrections. Up to 99% of residual activity in cold areas in the human subject was removed, and the reliability of the method was demonstrated in challenging body regions like in the proximity of a highly attenuating knee prosthesis.Significance.The MC SC method employed was demonstrated to be accurate and robust in TB-PET. The results of this study can serve as a benchmark for optimizing the quantitative performance of future SC techniques.

Numerical investigation reveals challenges in measuring the contrast recovery coefficients in PET.

Objective.Contrast recovery coefficient (CRC) is essential for image quality (IQ) assessment in positron emission tomography (PET), typically measured according to the National Electrical Manufacturers Association (NEMA) NU 2 standard. This study quantifies systematic uncertainties of the CRC measurement by a numerical investigation of the effects from scanner-independent parameters like voxel size, region-of-interest (ROI) misplacement, and sphere position on the underlying image grid.Approach.CRC measurements with 2D and 3D ROIs were performed on computer-generated images of a NEMA IQ-like phantom, using voxel sizes of 1-4 mm for sphere diameters of 5-40 mm-first in absence of noise and blurring, then with simulated spatial resolution and image noise with varying noise levels. The systematic uncertainties of the CRC measurement were quantified from above variations of scanner-independent parameters. Subsampled experimental images of a NEMA IQ phantom were additionally used to investigate the impact of ROI misplacement at different noise levels.Main results.In absence of noise and blurring, systematic uncertainties were up to 28.8% and 31.0% with 2D and 3D ROIs, respectively, for the 10 mm sphere, with the highest impact from ROI misplacement. In all cases, smaller spheres showed higher uncertainties with larger voxels. Contrary to prior assumptions, the use of 3D ROIs did not exhibit less susceptibility for parameter changes. Experimental and computer-generated images both demonstrated considerable variations on individual CRC measurements when background coefficient-of-variation exceeded 20%, despite negligible effects on mean CRC.Significance.This study underscores the effect of scanner-independent parameters on reliability, reproducibility, and comparability of CRC measurements. Our findings highlight the trade-off between the benefits of smaller voxel sizes and noise-induced CRC fluctuations, which is not considered in the current version of the NEMA IQ standards. The results furthermore warrant adjustments to the standard to accommodate the advances in sensitivity and spatial resolution of current-generation PET scanners.

First-in-human immunoPET imaging of COVID-19 convalescent patients using dynamic total-body PET and a CD8-targeted minibody.

With most of the T cells residing in the tissue, not the blood, developing noninvasive methods for in vivo quantification of their biodistribution and kinetics is important for studying their role in immune response and memory. This study presents the first use of dynamic positron emission tomography (PET) and kinetic modeling for in vivo measurement of CD8+ T cell biodistribution in humans. A 89Zr-labeled CD8-targeted minibody (89Zr-Df-Crefmirlimab) was used with total-body PET in healthy individuals (N = 3) and coronavirus disease 2019 (COVID-19) convalescent patients (N = 5). Kinetic modeling results aligned with T cell-trafficking effects expected in lymphoid organs. Tissue-to-blood ratios from the first 7 hours of imaging were higher in bone marrow of COVID-19 convalescent patients compared to controls, with an increasing trend between 2 and 6 months after infection, consistent with modeled net influx rates and peripheral blood flow cytometry analysis. These results provide a promising platform for using dynamic PET to study the total-body immune response and memory.

Total-body Dynamic Imaging and Kinetic Modeling of 18F-AraG in Healthy Individuals and a Non-Small Cell Lung Cancer Patient Undergoing Anti-PD-1 Immunotherapy.

Immunotherapies, especially the checkpoint inhibitors such as anti-PD-1 antibodies, have transformed cancer treatment by enhancing immune system's capability to target and kill cancer cells. However, predicting immunotherapy response remains challenging. 18F-AraG is a molecular imaging tracer targeting activated T cells, which may facilitate therapy response assessment by non-invasive quantification of immune cell activity within tumor microenvironment and elsewhere in the body. The aim of this study was to obtain preliminary data on total-body pharmacokinetics of 18F-AraG, as a potential quantitative biomarker for immune response evaluation. Methods: The study consisted of 90-min total-body dynamic scans of four healthy subjects and one non-small cell lung cancer (NSCLC) patient, scanned before and after anti-PD-1 immunotherapy. Compartmental modeling with Akaike information criterion model selection were employed to analyze tracer kinetics in various organs. Additionally, seven sub-regions of the primary lung tumor and four mediastinal lymph nodes were analyzed. Practical identifiability analysis was performed to assess reliability of kinetic parameter estimation. Correlations of SUVmean, SUVR (tissue-to-blood ratio), and Logan plot slope KLogan with total volume-of-distribution VT were calculated to identify potential surrogates for kinetic modeling. Results: Strong correlations were observed between KLogan and SUVR values with VT, suggesting that they can be used as promising surrogates for VT, especially in organs with low blood-volume fraction. Moreover, the practical identifiability analysis suggests that the dynamic 18F-AraG PET scans could potentially be shortened to 60 minutes, while maintaining quantification accuracy for all organs-of-interest. The study suggests that although 18F-AraG SUV images can provide insights on immune cell distribution, kinetic modeling or graphical analysis methods may be required for accurate quantification of immune response post-therapy. While SUVmean showed variable changes in different sub-regions of the tumor post-therapy, the SUVR, KLogan, and VT showed consistent increasing trends in all analyzed sub-regions of the tumor with high practical identifiability. Conclusion: Our findings highlight the promise of 18F-AraG dynamic imaging as a non-invasive biomarker for quantifying the immune response to immunotherapy in cancer patients. The promising total-body kinetic modeling results also suggest potentially wider applications of the tracer in investigating the role of T cells in the immunopathogenesis of diseases.

Total-Body Positron Emission Tomography: Adding New Perspectives to Cardiovascular Research.

The recent advent of positron emission tomography (PET) scanners that can image the entire human body opens up intriguing possibilities for cardiovascular research and future clinical applications. These new systems permit radiotracer kinetics to be measured in all organs simultaneously. They are particularly well suited to study cardiovascular disease and its effects on the entire body. They could also play a role in quantitatively measuring physiologic, metabolic, and immunologic responses in healthy individuals to a variety of stressors and lifestyle interventions, and may ultimately be instrumental for evaluating novel therapeutic agents and their molecular effects across different tissues. In this review, we summarize recent progress in PET technology and methodology, discuss several emerging cardiovascular applications for total-body PET, and place this in the context of multiorgan and systems medicine. Finally, we discuss opportunities that will be enabled by the technology, while also pointing to some of the challenges that still need to be addressed.

Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of Coronavirus Disease 2019 Recovery.

Conventional whole-body static 18F-FDG PET imaging provides a semiquantitative evaluation of overall glucose metabolism without insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods: The study included 13 healthy subjects and 12 recovering COVID-19 subjects within 8 wk of confirmed diagnosis. Each subject had a 1-h dynamic 18F-FDG scan on the uEXPLORER total-body PET/CT system. Semiquantitative SUV and the SUV ratio relative to blood (SUVR) were calculated for different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify the microparametric blood-to-tissue 18F-FDG delivery rate [Formula: see text] and the phosphorylation rate k 3, as well as the macroparametric 18F-FDG net influx rate ([Formula: see text]). Statistical tests were performed to examine differences between healthy subjects and recovering COVID-19 subjects. The effect of COVID-19 vaccination was also investigated. Results: We detected no significant difference in lung SUV but significantly higher lung SUVR and [Formula: see text] in COVID-19 recovery, indicating improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k 3 but not with [Formula: see text], which suggests that glucose phosphorylation, rather than glucose delivery, drives the observed difference of glucose metabolism. Meanwhile, there was no or little difference in bone marrow 18F-FDG metabolism measured with SUV, SUVR, and [Formula: see text] but a significantly higher bone marrow [Formula: see text] in the COVID-19 group, suggesting a difference in glucose delivery. Vaccinated COVID-19 subjects had a lower lung [Formula: see text] and a higher spleen [Formula: see text] than unvaccinated COVID-19 subjects. Conclusion: Higher lung glucose metabolism and bone marrow glucose delivery were observed with total-body multiparametric 18F-FDG PET in recovering COVID-19 subjects than in healthy subjects, implying continued inflammation during recovery. Vaccination demonstrated potential protection effects. Total-body multiparametric PET of 18F-FDG can provide a more sensitive tool and more insights than conventional whole-body static 18F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.