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.

18F-FDG gallbladder uptake: observation from a total-body PET/CT scanner.

BACKGROUND: Total-body positron emission tomography/computed tomography (PET/CT) scanners are characterized by higher signal collection efficiency and greater spatial resolution compared to conventional scanners, allowing for delayed imaging and improved image quality. These advantages may also lead to better detection of physiological processes that diagnostic imaging professionals should be aware of. The gallbladder (GB) is not usually visualized as an 18F-2-fluorodeoxyglucose (18F-FDG)-avid structure in routine clinical PET/CT studies; however, with the total-body PET/CT, we have been increasingly visualizing GB activity without it being involved in an inflammatory or neoplastic process. The aim of this study was to report visualization rates and characteristics of GB 18F-FDG uptake observed in both healthy and oncological subjects scanned on a total-body PET/CT system. MATERIALS AND METHODS: Scans from 73 participants (48 healthy and 25 with newly diagnosed lymphoma) who underwent 18F-FDG total-body PET/CT were retrospectively reviewed. Subjects were scanned at multiple timepoints up to 3 h post-injection. Gallbladder 18F-FDG activity was graded using liver uptake as a reference, and the pattern was qualified as present in the wall, lumen, or both. Participants' characteristics, such as age, sex, body-mass index, blood glucose, and other clinical parameters, were collected to assess for any significant correlation with GB 18F-FDG uptake. RESULTS: All 73 subjects showed GB uptake at one or more imaging timepoints. An increase in uptake intensity overtime was observed up until the 180-min scan, and the visualization rate of GB 18F-FDG uptake was 100% in the 120- and 180-min post-injection scans. GB wall uptake was detected in a significant number of patients (44/73, 60%), especially at early timepoint scans, whereas luminal activity was detected in 71/73 (97%) subjects, especially at later timepoint scans. No significant correlation was found between GB uptake intensity/pattern and subjects' characteristics. CONCLUSION: The consistent observation of GB 18F-FDG uptake recorded in this study in healthy participants and subjects with a new oncological diagnosis indicates that this is a normal physiologic finding rather than representing an exception.

Subsecond total-body imaging using ultrasensitive positron emission tomography.

A 194-cm-long total-body positron emission tomography/computed tomography (PET/CT) scanner (uEXPLORER), has been constructed to offer a transformative platform for human radiotracer imaging in clinical research and healthcare. Its total-body coverage and exceptional sensitivity provide opportunities for innovative studies of physiology, biochemistry, and pharmacology. The objective of this study is to develop a method to perform ultrahigh (100 ms) temporal resolution dynamic PET imaging by combining advanced dynamic image reconstruction paradigms with the uEXPLORER scanner. We aim to capture the fast dynamics of initial radiotracer distribution, as well as cardiac motion, in the human body. The results show that we can visualize radiotracer transport in the body on timescales of 100 ms and obtain motion-frozen images with superior image quality compared to conventional methods. The proposed method has applications in studying fast tracer dynamics, such as blood flow and the dynamic response to neural modulation, as well as performing real-time motion tracking (e.g., cardiac and respiratory motion, and gross body motion) without any external monitoring device (e.g., electrocardiogram, breathing belt, or optical trackers).

Avalanche photodetectors with photon trapping structures for biomedical imaging applications.

Enhancing photon detection efficiency and time resolution in photodetectors in the entire visible range is critical to improve the image quality of time-of-flight (TOF)-based imaging systems and fluorescence lifetime imaging (FLIM). In this work, we evaluate the gain, detection efficiency, and timing performance of avalanche photodiodes (APD) with photon trapping nanostructures for photons with 450 nm and 850 nm wavelengths. At 850 nm wavelength, our photon trapping avalanche photodiodes showed 30 times higher gain, an increase from 16% to >60% enhanced absorption efficiency, and a 50% reduction in the full width at half maximum (FWHM) pulse response time close to the breakdown voltage. At 450 nm wavelength, the external quantum efficiency increased from 54% to 82%, while the gain was enhanced more than 20-fold. Therefore, silicon APDs with photon trapping structures exhibited a dramatic increase in absorption compared to control devices. Results suggest very thin devices with fast timing properties and high absorption between the near-ultraviolet and the near infrared region can be manufactured for high-speed applications in biomedical imaging. This study paves the way towards obtaining single photon detectors with photon trapping structures with gains above 106 for the entire visible range.

Machine Learning in PET: from Photon Detection to Quantitative Image Reconstruction.

Machine learning has found unique applications in nuclear medicine from photon detection to quantitative image reconstruction. While there have been impressive strides in detector development for time-of-flight positron emission tomography, most detectors still make use of simple signal processing methods to extract the time and position information from the detector signals. Now with the availability of fast waveform digitizers, machine learning techniques have been applied to estimate the position and arrival time of high-energy photons. In quantitative image reconstruction, machine learning has been used to estimate various corrections factors, including scattered events and attenuation images, as well as to reduce statistical noise in reconstructed images. Here machine learning either provides a faster alternative to an existing time-consuming computation, such as in the case of scatter estimation, or creates a data-driven approach to map an implicitly defined function, such as in the case of estimating the attenuation map for PET/MR scans. In this article, we will review the abovementioned applications of machine learning in nuclear medicine.

Theoretical investigation of ultrasound-modulated Cerenkov luminescence imaging for higher-resolution imaging in turbid media.

Cerenkov luminescence imaging (CLI) is an optical technique for imaging radiolabeled molecules in vivo. It has demonstrated utility in both the clinical and preclinical settings and can serve as a substitute for nuclear imaging instrumentation in some cases. However, optical scattering fundamentally limits the resolution and depth of imaging that can be achieved with this modality. In this Letter, we report the numerical results that support the potential for ultrasound-modulated Cerenkov luminescence imaging (USCLI), a new imaging modality that can mitigate optical scattering. The technique uses an acoustic field to modulate the refractive index of the medium and, thus, the intensity of Cerenkov luminescence in a spatially precise manner. This mechanism of contrast has not been reported previously. For a physiologically compatible ultrasound peak pressure of 1 MPa, ∼0.1% of the Cerenkov signal can be modulated. Furthermore, our simulations show that USCLI can overcome the scattering limit of resolution for CLI and provide higher-resolution imaging. For an F18 point source centered in a 1 cm3 simulated tissue phantom with a scattering coefficient of µs'=10 cm-1, <2 mm full width at half-maximum lateral spatial resolution is possible, a resolution three times finer than the same phantom imaged with CLI.

Effects of pair bonding on dopamine D1 receptors in monogamous male titi monkeys (Callicebus cupreus).

Pair bonding leads to increases in dopamine D1 receptor (D1R) binding in the nucleus accumbens of monogamous prairie voles. In the current study, we hypothesized that there is similar up-regulation of D1R in a monogamous primate, the titi monkey (Callicebus cupreus). Receptor binding of the D1R antagonist [11 C]-SCH23390 was measured in male titi monkeys using PET scans before and after pairing with a female. We found that within-subject analyses of pairing show significant increases in D1R binding in the lateral septum, but not the nucleus accumbens, caudate, putamen, or ventral pallidum. The lateral septum is involved in a number of processes that may contribute to social behavior, including motivation, affect, reward, and reinforcement. This region also plays a role in pair bonding and paternal behavior in voles. Our observations of changes in D1R in the lateral septum, but not the nucleus accumbens, suggest that there may be broadly similar dopaminergic mechanisms underlying pair bonding across mammalian species, but that the specific changes to neural circuitry differ. This study is the first research to demonstrate neuroplasticity of the dopamine system following pair bonding in a non-human primate; however, substantial variability in the response to pairing suggests the utility of further research on the topic.

Persistent neuroinflammation and cognitive impairment in a rat model of acute diisopropylfluorophosphate intoxication.

BACKGROUND: Acute intoxication with organophosphorus (OP) cholinesterase inhibitors can trigger convulsions that progress to life-threatening status epilepticus. Survivors face long-term morbidity including mild-to-severe decline in memory. It is posited that neuroinflammation plays a key role in the pathogenesis of OP-induced neuropsychiatric deficits. Rigorous testing of this hypothesis requires preclinical models that recapitulate relevant phenotypic outcomes. Here, we describe a rat model of acute intoxication with the OP diisopropylfluorophosphate (DFP) that exhibits persistent neuroinflammation and cognitive impairment. METHODS: Neuroinflammation, neurodegeneration, and cognitive function were compared in adult male Sprague Dawley rats injected with an acutely toxic dose of DFP vs. vehicle controls at multiple time points up to 36 days post-exposure. Neuroinflammation was quantified using immunohistochemical biomarkers of microglia (ionized calcium-binding adapter molecule 1, IBA1) and activated astrocytes (glial fibrillary acidic protein, GFAP) and positron emission tomography (PET) imaging of [11C]-(R)-PK11195, a ligand for the 18-kDa mitochondrial membrane translocator protein (TSPO). FluoroJade-B staining was used to assess neurodegeneration; Pavlovian conditioning, to assess cognitive function. RESULTS: Animals exhibited moderate-to-severe seizures within minutes of DFP injection that continued for up to 6 h post-injection. As indicated by IBA1 and GFAP immunoreactivity and by PET imaging of TSPO, acute DFP intoxication triggered neuroinflammation in the hippocampus and cortex during the first 3 days that peaked at 7 days and persisted to 21 days post-exposure in most animals. Neurodegeneration was detected in multiple brain regions from 1 to 14 days post-exposure. All DFP-intoxicated animals exhibited significant deficits in contextual fear conditioning at 9 and 20 days post-exposure compared to vehicle controls. Whole-brain TSPO labeling positively correlated with seizure severity score, but did not correlate with performance in the contextual fear-conditioning task. CONCLUSIONS: We describe a preclinical model in which acute DFP intoxication causes seizures, persistent neuroinflammation, neurodegeneration, and memory impairment. The extent of the neuroinflammatory response is influenced by seizure severity. However, the observation that a subset of animals with moderate seizures and minimal TSPO labeling exhibited cognitive deficits comparable to those of animals with severe seizures and significant TSPO labeling suggests that DFP may impair learning and memory circuitry via mechanisms independent of seizures or neuroinflammation.

Characterization of Large-Area SiPM Array for PET Applications.

The performance of an 8 × 8 array of 6.0 × 6.0 mm2 (active area) SiPMs was evaluated for PET applications using crystal arrays with different pitch sizes (3.4 mm, 1.5 mm, 1.35 mm and 1.2 mm) and custom designed five-channel front-end readout electronics (four channels for position information and one channel for timing information). The total area of this SiPM array is 57.4 × 57.4 mm2, and the pitch size is 7.2 mm. It was fabricated using enhanced blue sensitivity SiPMs (MicroFB-60035-SMT) with peak spectral sensitivity at 420 nm. The performance of the SiPM array was characterized by measuring flood histogram decoding quality, energy resolution, timing resolution and saturation at several bias voltages (from 25.0 V to 30.0 V in 0.5 V intervals) and two different temperatures (5 °C and 20 °C). Results show that the best flood histogram was obtained at a bias voltage of 28.0 V and 5 °C and an array of polished LSO crystals with a pitch as small as 1.2 mm can be resolved. No saturation was observed up to a bias voltage of 29.5 V during the experiments, due to adequate light sharing between SiPMs. Energy resolution and timing resolution at 5 °C ranged from 12.7 ± 0.8% to 14.6 ± 1.4 % and 1.58 ± 0.13 ns to 2.50 ± 0.44 ns, for crystal array pitch sizes of 3.4 mm and 1.2 mm respectively. Superior flood histogram quality, energy resolution and timing resolution were obtained with larger crystal array pitch sizes and at lower temperature. Based on our findings, we conclude that this large-area SiPM array can serve as a suitable photodetector for high-resolution small-animal PET or dedicated human brain PET scanners.

A Study of Position-Sensitive Solid-State Photomultiplier Signal Properties.

We present an analysis of the signal properties of a position-sensitive solid-state photomultiplier (PS-SSPM) that has an integrated resistive network for position sensing. Attractive features of PS-SSPMs are their large area and ability to resolve small scintillator crystals. However, the large area leads to a high detector capacitance, and in order to achieve high spatial resolution a large network resistor value is required. These inevitably create a low-pass filter that drastically slows what would be a fast micro-cell discharge pulse. Significant changes in the signal shape of the PS-SSPM cathode output as a function of position are observed, which result in a position-dependent time delay when using traditional time pick-off methods such as leading edge discrimination and constant fraction discrimination. The timing resolution and time delay, as a function of position, were characterized for two different PS-SSPM designs, a continuous 10 mm × 10 mm PS-SSPM and a tiled 2 × 2 array of 5 mm × 5 mm PS-SSPMs. After time delay correction, the block timing resolution, measured with a 6 × 6 array of 1.3 × 1.3 × 20 mm3 LSO crystals, was 8.6 ns and 8.5 ns, with the 10 mm PS-SSPM and 5 mm PS-SSPM respectively. The effect of crystal size on timing resolution was also studied, and contrary to expectation, a small improvement was measured when reducing the crystal size from 1.3 mm to 0.5 mm. Digital timing methods were studied and showed great promise for allowing accurate timing by implementation of a leading edge time pick-off. Position-dependent changes in signal shape on the anode side also are present, which complicates peak height data acquisition methods used for positioning. We studied the effect of trigger position on signal amplitude, flood histogram quality, and depth-of-interaction resolution in a dual-ended readout detector configuration. We conclude that detector timing and positioning can be significantly improved by implementation of digital timing methods and by accounting for changes in the shape of the signals from PS-SSPMs.

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.

[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.

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.

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-minute PET scan on a Biograph mCT PET/CT scanner, starting at 60±5 minutes post-injection. The PET list-mode data were partitioned by subsampling without replacement, with 20 minutes used for image reconstruction using an in-house ordered subset expectation maximization algorithm and the remaining 2 minutes for cross-validation. Two penalty parameters, penalty strength ß and Fair penalty function parameter δ, 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: The δ value required to maximize the CVLL value was notably small (≤ 10-6 in this study). The influences of voxel size and scan duration on image optimization were investigated. A correlation analysis revealed a significant inverse relationship between optimal ß and 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.

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.

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.

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.

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.