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.

Relationship between neuroimaging and cognition in frontotemporal dementia: An FDG-PET and structural MRI study.

BACKGROUND AND PURPOSE: Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative condition with a prevalence comparable to Alzheimer's disease for patients under 65 years of age. Limited studies have examined the association between cognition and neuroimaging in FTD using different imaging modalities. METHODS: We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both gray matter (GM) volume and glucose metabolism using magnetic resonance imaging and fluorodeoxyglucose (FDG)-PET in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for FDG-PET. Partial volume correction was applied to PET data to account for disease-related atrophy. RESULTS: Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.46, p = .04). The association between whole-cortex FDG SUVR and MoCA scores was not significant (r = 0.37, p = .09). GM volumes of the frontal cortex (r = 0.54, p = .01), caudate (r = 0.62, p<.01), and insula (r = 0.57, p<.01) were also significantly correlated with MoCA, as were SUVR values of the insula (r = 0.51, p = .02), thalamus (r = 0.48, p = .03), and posterior cingulate cortex (PCC) (r = 0.47, p = .03). CONCLUSIONS: Whole-cortex atrophy is associated with cognitive dysfunction, and this association is larger than for whole-cortex hypometabolism as measured with FDG-PET. At the regional level, focal atrophy and/or hypometabolism in the frontal cortex, insula, PCC, thalamus, and caudate seem to be important for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways.

Relationship between Neuroimaging and Cognition in Frontotemporal Dementia: A [18 F]FDG PET and Structural MRI Study.

Background: Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous condition with a prevalence comparable to Alzheimer's Disease for patients under sixty-five years of age. Gray matter (GM) atrophy and glucose hypometabolism are important biomarkers for the diagnosis and evaluation of disease progression in FTD. However, limited studies have systematically examined the association between cognition and neuroimaging in FTD using different imaging modalities in the same patient group. Methods: We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both GM volume and glucose metabolism using structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography scanning ([18F]FDG PET) in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for [18F]FDG PET. Partial volume correction was applied to PET data to account for disease-related atrophy. Results: Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.461, p = 0.035). The association between whole-cortex [18F]FDG SUVR and MoCA scores was not Significant (r = 0.374, p = 0.094). GM volumes of the frontal cortex (r = 0.540, p = 0.011), caudate (r = 0.616, p = 0.002), and insula (r = 0.568, p = 0.007) were also Significantly correlated with MoCA, as were SUVR values of the insula (r = 0.508, p = 0.018), thalamus (r = 0.478, p = 0.028), and posterior cingulate cortex (PCC) (r = 0.472, p = 0.030). Discussion: Whole-cortex atrophy is associated with cognitive dysfunction, and this effect is larger than for cortical hypometabolism as measured with [18F]FDG PET. At the regional level, focal atrophy and/or hypometabolism in the frontal lobe, insula, PCC, thalamus, and caudate seem to imply the importance of these regions for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways. Our findings provide insight into the relationships between structural, metabolic, and cognitive changes due to FTD.

Markerless head motion tracking and event-by-event correction in brain PET.

Objective.Head motion correction (MC) is an essential process in brain positron emission tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based motion tracking (HMT) device, for PET head MC. However, this requires attachment of a marker to the subject's head. Markerless HMT (MLMT) methods are more convenient for clinical translation than HMT with external markers. In this study, we validated the United Imaging Healthcare motion tracking (UMT) MLMT system using phantom and human point source studies, and tested its effectiveness on eight18F-FPEB and four11C-LSN3172176 human studies, with frame-based region of interest (ROI) analysis. We also proposed an evaluation metric, registration quality (RQ), and compared it to a data-driven evaluation method, motion-corrected centroid-of-distribution (MCCOD).Approach.UMT utilized a stereovision camera with infrared structured light to capture the subject's real-time 3D facial surface. Each point cloud, acquired at up to 30 Hz, was registered to the reference cloud using a rigid-body iterative closest point registration algorithm.Main results.In the phantom point source study, UMT exhibited superior reconstruction results than the Vicra with higher spatial resolution (0.35 ± 0.27 mm) and smaller residual displacements (0.12 ± 0.10 mm). In the human point source study, UMT achieved comparable performance as Vicra on spatial resolution with lower noise. Moreover, UMT achieved comparable ROI values as Vicra for all the human studies, with negligible mean standard uptake value differences, while no MC results showed significant negative bias. TheRQevaluation metric demonstrated the effectiveness of UMT and yielded comparable results to MCCOD.Significance.We performed an initial validation of a commercial MLMT system against the Vicra. Generally, UMT achieved comparable motion-tracking results in all studies and the effectiveness of UMT-based MC was demonstrated.

An objective evaluation method for head motion estimation in PET-Motion corrected centroid-of-distribution.

Head motion presents a continuing problem in brain PET studies. A wealth of motion correction (MC) algorithms had been proposed in the past, including both hardware-based methods and data-driven methods. However, in most real brain PET studies, in the absence of ground truth or gold standard of motion information, it is challenging to objectively evaluate MC quality. For MC evaluation, image-domain metrics, e.g., standardized uptake value (SUV) change before and after MC are commonly used, but this measure lacks objectivity because 1) other factors, e.g., attenuation correction, scatter correction and parameters used in the reconstruction, will confound MC effectiveness; 2) SUV only reflects final image quality, and it cannot precisely inform when an MC method performed well or poorly during the scan time period; 3) SUV is tracer-dependent and head motion may cause increases or decreases in SUV for different tracers, so evaluating MC effectiveness is complicated. Here, we present a new algorithm, i.e., motion corrected centroid-of-distribution (MCCOD) to perform objective quality control for measured or estimated rigid motion information. MCCOD is a three-dimensional surrogate trace of the center of tracer distribution after performing rigid MC using the existing motion information. MCCOD is used to inform whether the motion information is accurate, using the PET raw data only, i.e., without PET image reconstruction, where inaccurate motion information typically leads to abrupt changes in the MCCOD trace. MCCOD was validated using simulation studies and was tested on real studies acquired from both time-of-flight (TOF) and non-TOF scanners. A deep learning-based brain mask segmentation was implemented, which is shown to be necessary for non-TOF MCCOD generation. MCCOD is shown to be effective in detecting abrupt translation motion errors in slowly varying tracer distribution caused by the motion tracking hardware and can be used to compare different motion estimation methods as well as to improve existing motion information.

Adaptive data-driven motion detection and optimized correction for brain PET.

Head motion during PET scans causes image quality degradation, decreased concentration in regions with high uptake and incorrect outcome measures from kinetic analysis of dynamic datasets. Previously, we proposed a data-driven method, center of tracer distribution (COD), to detect head motion without an external motion tracking device. There, motion was detected using one dimension of the COD trace with a semiautomatic detection algorithm, requiring multiple user defined parameters and manual intervention. In this study, we developed a new data-driven motion detection algorithm, which is automatic, self-adaptive to noise level, does not require user-defined parameters and uses all three dimensions of the COD trace (3DCOD). 3DCOD was first validated and tested using 30 simulation studies (18F-FDG, N = 15; 11C-raclopride (RAC), N = 15) with large motion. The proposed motion correction method was tested on 22 real human datasets, with 20 acquired from a high resolution research tomograph (HRRT) scanner (18F-FDG, N = 10; 11C-RAC, N = 10) and 2 acquired from the Siemens Biograph mCT scanner. Real-time hardware-based motion tracking information (Vicra) was available for all real studies and was used as the gold standard. 3DCOD was compared to Vicra, no motion correction (NMC), one-direction COD (our previous method called 1DCOD) and two conventional frame-based image registration (FIR) algorithms, i.e., FIR1 (based on predefined frames reconstructed with attenuation correction) and FIR2 (without attenuation correction) for both simulation and real studies. For the simulation studies, 3DCOD yielded -2.3 ± 1.4% (mean ± standard deviation across all subjects and 11 brain regions) error in region of interest (ROI) uptake for 18F-FDG (-3.4 ± 1.7% for 11C-RAC across all subjects and 2 regions) as compared to Vicra (perfect correction) while NMC, FIR1, FIR2 and 1DCOD yielded -25.4 ± 11.1% (-34.5 ± 16.1% for 11C- RAC), -13.4 ± 3.5% (-16.1 ± 4.6%), -5.7 ± 3.6% (-8.0 ± 4.5%) and -2.6 ± 1.5% (-5.1 ± 2.7%), respectively. For real HRRT studies, 3DCOD yielded -0.3 ± 2.8% difference for 18F-FDG (-0.4 ± 3.2% for 11C-RAC) as compared to Vicra while NMC, FIR1, FIR2 and 1DCOD yielded -14.9 ± 9.0% (-24.5 ± 14.6%), -3.6 ± 4.9% (-13.4 ± 14.3%), -0.6 ± 3.4% (-6.7 ± 5.3%) and -1.5 ± 4.2% (-2.2 ± 4.1%), respectively. In summary, the proposed motion correction method yielded comparable performance to the hardware-based motion tracking method for multiple tracers, including very challenging cases with large frequent head motion, in studies performed on a non-TOF scanner.

[89Zr]ZrDFO-CR011 PET Correlates with Response to Glycoprotein Nonmetastatic Melanoma B-targeted Therapy in Triple-negative Breast Cancer.

There is a need for prognostic markers to select patients most likely to benefit from antibody-drug conjugate (ADC) therapy. We quantified the relationship between pretreatment PET imaging of glycoprotein nonmetastatic melanoma B (gpNMB) with 89Zr-labeled anti-gpNMB antibody ([89Zr]ZrDFO-CR011) and response to ADC therapy (CDX-011) in triple-negative breast cancer. First, we compared different PET imaging metrics and found that standardized uptake values (SUV) and tumor-to-heart SUV ratios were sufficient to delineate differences in radiotracer uptake in the tumor of four different cell- and patient-derived tumor models and achieved high standardized effect sizes. These tumor models with varying levels of gpNMB expression were imaged with [89Zr]ZrDFO-CR011 followed by treatment with a single bolus injection of CDX-011. The percent change in tumor volume relative to baseline (% CTV) was then correlated with SUVmean of [89Zr]ZrDFO-CR011 uptake in the tumor. All gpNMB-positive tumor models responded to CDX-011 over 6 weeks of treatment, except one patient-derived tumor regrew after 4 weeks of treatment. As expected, the gpNMB-negative tumor increased in volume by 130 ± 59% at endpoint. The magnitude of pretreatment SUV had the strongest inverse correlation with the % CTV at 2-4 weeks after treatment with CDX-011 (Spearman ρ = -0.8). However, pretreatment PET imaging with [89Zr]ZrDFO-CR011 did not inform on which tumor types will regrow over time. Other methods will be needed to predict resistance to treatment.

Feasibility study of PET dynamic imaging of [18F]DHMT for quantification of reactive oxygen species in the myocardium of large animals.

OBJECTIVES: We aimed to develop a dynamic imaging technique for a novel PET superoxide tracer, [18F]DHMT, to allow for absolute quantification of myocardial reactive oxygen species (ROS) production in a large animal model. METHODS: Six beagle dogs underwent a single baseline dynamic [18F]DHMT PET study, whereas one animal underwent three serial dynamic studies over the course of chronic doxorubicin administration (1 mg·kg-1·week-1 for 15 weeks). During the scans, sequential arterial blood samples were obtained for plasma metabolite correction. The optimal compartment model and graphical analysis method were identified for kinetic modeling. Values for the left ventricular (LV) net influx rate, Ki, were reported for all the studies and compared with the LV standard uptake values (SUVs) and the LV-to-blood pool SUV ratios from the 60 to 90 minute static images. Parametric images were also generated. RESULTS: [18F]DHMT followed irreversible kinetics once oxidized within the myocardium in the presence of superoxide, as evidenced by the fitting generated by the irreversible two-tissue (2Ti) compartment model and the linearity of Patlak analysis. Myocardial Ki values showed a weak correlation with LV SUV (R2 = 0.27), but a strong correlation with LV-to-blood pool SUV ratio (R2 = 0.92). Generation of high-quality parametric images showed superior myocardial to blood contrast compared to static images. CONCLUSIONS: A dynamic PET imaging technique for [18F]DHMT was developed with full and simplified kinetic modeling for absolute quantification of myocardial superoxide production in a large animal model.

Assessment of population-based input functions for Patlak imaging of whole body dynamic 18F-FDG PET.

BACKGROUND: Arterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic 18F-FDG PET imaging. However, this procedure is invasive and not typically available in clinical environments. As an alternative, we compared AIFs to population-based input functions (PBIFs) using two normalization methods: area under the curve (AUC) and extrapolated initial plasma concentration (CP*(0)). To scale the PBIFs, we tested two methods: (1) the AUC of the image-derived input function (IDIF) and (2) the estimated CP*(0). The aim of this study was to validate IDIF and PBIF for FDG oncological WB PET studies by comparing to the gold standard arterial blood sampling. METHODS: The Feng 18F-FDG plasma concentration model was applied to estimate AIF parameters (n = 23). AIF normalization used either AUC(0-60 min) or CP*(0), estimated from an exponential fit. CP*(0) is also described as the ratio of the injected dose (ID) to initial distribution volume (iDV). iDV was modeled using the subject height and weight, with coefficients that were estimated in 23 subjects. In 12 oncological patients, we computed IDIF (from the aorta) and PBIFs with scaling by the AUC of the IDIF from 4 time windows (15-45, 30-60, 45-75, 60-90 min) (PBIFAUC) and estimated CP*(0) (PBIFiDV). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and Patlak Ki values. RESULTS: The IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC and Ki comparison, 30-60 min was the most accurate time window for PBIFAUC; later time windows for scaling underestimated Ki (- 6 ± 8 to - 13 ± 9%). Correlations of AUC between AIF and IDIF, PBIFAUC(30-60), and PBIFiDV were 0.91, 0.94, and 0.90, respectively. The bias of Ki was - 9 ± 10%, - 1 ± 8%, and 3 ± 9%, respectively. CONCLUSIONS: Both PBIF scaling methods provided good mean performance with moderate variation. Improved performance can be obtained by refining IDIF methods and by evaluating PBIFs with test-retest data.

Human adult and adolescent biodistribution and dosimetry of the synaptic vesicle glycoprotein 2A radioligand 11C-UCB-J.

The ability to quantify synaptic density in vivo in human adults and adolescents is of vital importance to understanding neuropsychiatric disorders. Here, we performed whole-body scans to determine organ radiation dosimetry of 11C-UCB-J in humans. METHODS: Dynamic whole-body PET scans were performed in four healthy adults after injection of 11C-UCB-J. Regions of interest (ROIs) were drawn manually for the brain, heart, stomach, kidneys, liver, pancreas, spleen, gallbladder, lungs, urinary bladder, and intestines. ROIs were applied to dynamic images to generate time-activity curves (TACs). Decay correction was removed from TACs, and the area under the curve (AUC) for each ROI was calculated. AUCs were then normalized by injected activity and organ volumes to produce radioligand residence times for each organ. These times were then used as input into the OLINDA/EXM 1.0 software to determine the total radiation dose in each organ and the effective dose for these OLINDA models: 55-kg female, 70-kg male, and 15-year-old adolescent. RESULTS: Visual evaluation detected high uptake in the liver, brain, gallbladder, gastrointestinal tract, and urinary bladder. The dose-limiting organ was the urinary bladder for adult males (0.0224 mSv/MBq) and liver for adult females (0.0248 mSv/MBq) with single-study dose limits of 2239 MBq and 2017 MBq 11C-UCB-J, respectively. For adolescents, the large intestine was the dose-limiting organ (0.0266 mSv/MBq) with a single-study dose limit of 188 MBq. CONCLUSIONS: 11C-UCB-J dosimetry in adults is consistent with those for many carbon-11-labeled ligands. Overall, 11C-UCB-J can be used safely in adolescents, as in adults, to measure synaptic density in various neuropsychiatric and other relevant disorders.

Data-Driven Motion Detection and Event-by-Event Correction for Brain PET: Comparison with Vicra.

Head motion degrades image quality and causes erroneous parameter estimates in tracer kinetic modeling in brain PET studies. Existing motion correction methods include frame-based image registration (FIR) and correction using real-time hardware-based motion tracking (HMT) information. However, FIR cannot correct for motion within 1 predefined scan period, and HMT is not readily available in the clinic since it typically requires attaching a tracking device to the patient. In this study, we propose a motion correction framework with a data-driven algorithm, that is, using the PET raw data itself, to address these limitations. Methods: We propose a data-driven algorithm, centroid of distribution (COD), to detect head motion. In COD, the central coordinates of the line of response of all events are averaged over 1-s intervals to generate a COD trace. A point-to-point change in the COD trace in 1 direction that exceeded a user-defined threshold was defined as a time point of head motion, which was followed by manually adding additional motion time points. All the frames defined by such time points were reconstructed without attenuation correction and rigidly registered to a reference frame. The resulting transformation matrices were then used to perform the final motion-compensated reconstruction. We applied the new COD framework to 23 human dynamic datasets, all containing large head motion, with 18F-FDG (n = 13) and 11C-UCB-J ((R)-1-((3-(11C-methyl-11C)pyridin-4-yl)methyl)-4-(3,4,5-trifluorophenyl)pyrrolidin-2-one) (n = 10) and compared its performance with FIR and with HMT using Vicra (an optical HMT device), which can be considered the gold standard. Results: The COD method yielded a 1.0% ± 3.2% (mean ± SD across all subjects and 12 gray matter regions) SUV difference for 18F-FDG (3.7% ± 5.4% for 11C-UCB-J) compared with HMT, whereas no motion correction (NMC) and FIR yielded -15.7% ± 12.2% (-20.5% ± 15.8%) and -4.7% ± 6.9% (-6.2% ± 11.0%), respectively. For 18F-FDG dynamic studies, COD yielded differences of 3.6% ± 10.9% in Ki value as compared with HMT, whereas NMC and FIR yielded -18.0% ± 39.2% and -2.6% ± 19.8%, respectively. For 11C-UCB-J, COD yielded 3.7% ± 5.2% differences in VT compared with HMT, whereas NMC and FIR yielded -20.0% ± 12.5% and -5.3% ± 9.4%, respectively. Conclusion: The proposed COD-based data-driven motion correction method outperformed FIR and achieved comparable or even better performance than the Vicra HMT method in both static and dynamic studies.

In Vivo Synaptic Density Imaging with 11C-UCB-J Detects Treatment Effects of Saracatinib in a Mouse Model of Alzheimer Disease.

11C-UCB-J is a new PET tracer for synaptic density imaging. Recently, we conducted 11C-UCB-J PET on patients with mild cognitive impairment or early Alzheimer disease (AD) and found a 41% decrease in specific binding in the hippocampus compared with healthy subjects. We hypothesized that 11C-UCB-J may have potential to be a general biomarker for evaluating AD treatment effects via monitoring of synaptic density changes. In this study, we performed longitudinal 11C-UCB-J PET on AD mice to measure the treatment effects of saracatinib, which previously demonstrated synaptic changes with postmortem methods. Methods: Nine wild-type (WT) mice and 9 amyloid precursor protein and presenilin 1 double-transgenic (APPswe/PS1ΔE9 [APP/PS1]) mice underwent 3 11C-UCB-J PET measurements: at baseline, after treatment, and during drug washout. After baseline measurements, saracatinib, a Fyn kinase inhibitor currently in clinical development for AD treatment, was administered by oral gavage for 41 ± 11 d. Treatment-phase measurements were performed on the last day of treatment, and washout-phase measurements occurred more than 27 d after the end of treatment. SUVs from 30 to 60 min after injection of 11C-UCB-J were calculated and normalized by the whole-brain (WB) or brain stem (BS) average values as SUV ratio (SUVR(WB) or SUVR-1(BS)). Results: Hippocampal SUVR(WB) at baseline was significantly lower in APP/PS1 than WT mice (APP/PS1: 1.11 ± 0.04, WT: 1.15 ± 0.02, P = 0.033, unpaired t test). Using SUVR-1(BS) in the hippocampus, there was also a significant difference at baseline (APP/PS1: 0.48 ± 0.13, WT: 0.65 ± 0.10, P = 0.017, unpaired t test). After treatment with saracatinib, hippocampal SUVR(WB) in APP/PS1 mice was significantly increased (P = 0.037, paired t test). A trend-level treatment effect was seen with hippocampal SUVR-1(BS). Saracatinib treatment effects may persist, as there were no significant differences between WT and APP/PS1 mice after drug washout. Conclusion: On the basis of the 11C-UCB-J PET results, hippocampal synaptic density was lower in APP/PS1 mice than in WT mice at baseline, and this deficit was normalized by treatment with saracatinib. These results support the use of 11C-UCB-J PET to identify disease-specific synaptic deficits and to monitor treatment effects in AD.

Data-driven voluntary body motion detection and non-rigid event-by-event correction for static and dynamic PET.

PET has the potential to perform absolute in vivo radiotracer quantitation. This potential can be compromised by voluntary body motion (BM), which degrades image resolution, alters apparent tracer uptakes, introduces CT-based attenuation correction mismatch artifacts and causes inaccurate parameter estimates in dynamic studies. Existing body motion correction (BMC) methods include frame-based image-registration (FIR) approaches and real-time motion tracking using external measurement devices. FIR does not correct for motion occurring within a pre-defined frame and the device-based method is generally not practical in routine clinical use, since it requires attaching a tracking device to the patient and additional device set up time. In this paper, we proposed a data-driven algorithm, centroid of distribution (COD), to detect BM. In this algorithm, the central coordinate of the time-of-flight (TOF) bin, which can be used as a reasonable surrogate for the annihilation point, is calculated for every event, and averaged over a certain time interval to generate a COD trace. We hypothesized that abrupt changes on the COD trace in lateral direction represent BMs. After detection, BM is estimated using non-rigid image registrations and corrected through list-mode reconstruction. The COD-based BMC approach was validated using a monkey study and was evaluated against FIR using four human and one dog studies with multiple tracers. The proposed approach successfully detected BMs and yielded superior correction results over conventional FIR approaches.

In Vivo Reactive Oxygen Species Detection With a Novel Positron Emission Tomography Tracer, 18F-DHMT, Allows for Early Detection of Anthracycline-Induced Cardiotoxicity in Rodents.

Reactive oxygen species (ROS) are involved in doxorubicin-induced cardiotoxicity. The authors investigated the efficacy of 18F-DHMT, a marker of ROS, for early detection of doxorubicin-induced cardiotoxicity in rats. Echocardiography was performed at baseline and 4, 6, and 8 weeks post-doxorubicin initiation, whereas in vivo superoxide production was measured at 4 and 6 weeks with 18F-DHMT positron emission tomography. Left ventricular ejection fraction (LVEF) was not significantly decreased until 6 weeks post-doxorubicin treatment, whereas myocardial superoxide production was significantly elevated at 4 weeks. 18F-DHMT imaging detected an elevation in cardiac superoxide production before a fall in LVEF in rodents and may allow for early cardiotoxicity detection in cancer patients.

Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data.

Respiratory motion degrades the detection and quantification capabilities of PET/CT imaging. Moreover, mismatch between a fast helical CT image and a time-averaged PET image due to respiratory motion results in additional attenuation correction artifacts and inaccurate localization. Current motion compensation approaches typically have 3 limitations: the mismatch among respiration-gated PET images and the CT attenuation correction (CTAC) map can introduce artifacts in the gated PET reconstructions that can subsequently affect the accuracy of the motion estimation; sinogram-based correction approaches do not correct for intragate motion due to intracycle and intercycle breathing variations; and the mismatch between the PET motion compensation reference gate and the CT image can cause an additional CT-mismatch artifact. In this study, we established a motion correction framework to address these limitations. Methods: In the proposed framework, the combined emission-transmission reconstruction algorithm was used for phase-matched gated PET reconstructions to facilitate the motion model building. An event-by-event nonrigid respiratory motion compensation method with correlations between internal organ motion and external respiratory signals was used to correct both intracycle and intercycle breathing variations. The PET reference gate was automatically determined by a newly proposed CT-matching algorithm. We applied the new framework to 13 human datasets with 3 different radiotracers and 323 lesions and compared its performance with CTAC and non-attenuation correction (NAC) approaches. Validation using 4-dimensional CT was performed for one lung cancer dataset. Results: For the 10 18F-FDG studies, the proposed method outperformed (P < 0.006) both the CTAC and the NAC methods in terms of region-of-interest-based SUVmean, SUVmax, and SUV ratio improvements over no motion correction (SUVmean: 19.9% vs. 14.0% vs. 13.2%; SUVmax: 15.5% vs. 10.8% vs. 10.6%; SUV ratio: 24.1% vs. 17.6% vs. 16.2%, for the proposed, CTAC, and NAC methods, respectively). The proposed method increased SUV ratios over no motion correction for 94.4% of lesions, compared with 84.8% and 86.4% using the CTAC and NAC methods, respectively. For the 2 18F-fluoropropyl-(+)-dihydrotetrabenazine studies, the proposed method reduced the CT-mismatch artifacts in the lower lung where the CTAC approach failed and maintained the quantification accuracy of bone marrow where the NAC approach failed. For the 18F-FMISO study, the proposed method outperformed both the CTAC and the NAC methods in terms of motion estimation accuracy at 2 lung lesion locations. Conclusion: The proposed PET/CT respiratory event-by-event motion-correction framework with motion information derived from matched attenuation-corrected PET data provides image quality superior to that of the CTAC and NAC methods for multiple tracers.

A 3D-printed modular device for imaging the brain of small birds.

BACKGROUND: One potential barrier to using in vivo imaging in any new animal species is solving the basic problem of how to hold animals safely and securely during scans. NEW METHOD: In this paper, we describe the design, fabrication, use, and positional reproducibility of a 3D-printed plastic device (the Avian Imaging Device, or AID) for imaging the brain of 1 or 2 small songbirds. We designed two different types of head cones to use with this device: one that was not contoured and designed for anesthesia induction, and one contoured to the shape of a house sparrow head, designed to be used with a pre-anesthetized animal. RESULTS: Compared to no holder, using the AID with both contoured and non-contoured head cones significantly reduced the amount of translation necessary to align the head in pairs of CT scans (by 78% and 90%, respectively); using the contoured head cone also significantly reduced the amount of rotation necessary for head alignment in registering pairs of scans (by 90%). COMPARISON WITH EXISTING METHOD(S): Using an animal holder that can not only securely hold animals but which has high positional reproducibility is essential to take advantage of the maximum resolution possible with small animal imaging. 3D-printed materials are also compatible with PET and CT, environmentally stable, and fast and inexpensive to make. CONCLUSIONS: Researchers can learn from the design of the AID and use our CAD models as a starting point for fabricating devices for multiple small-animal imaging needs.

Data-driven event-by-event respiratory motion correction using TOF PET list-mode centroid of distribution.

Data-driven respiratory gating techniques were developed to correct for respiratory motion in PET studies, without the help of external motion tracking systems. Due to the greatly increased image noise in gated reconstructions, it is desirable to develop a data-driven event-by-event respiratory motion correction method. In this study, using the Centroid-of-distribution (COD) algorithm, we established a data-driven event-by-event respiratory motion correction technique using TOF PET list-mode data, and investigated its performance by comparing with an external system-based correction method. Ten human scans with the pancreatic ß-cell tracer 18F-FP-(+)-DTBZ were employed. Data-driven respiratory motions in superior-inferior (SI) and anterior-posterior (AP) directions were first determined by computing the centroid of all radioactive events during each short time frame with further processing. The Anzai belt system was employed to record respiratory motion in all studies. COD traces in both SI and AP directions were first compared with Anzai traces by computing the Pearson correlation coefficients. Then, respiratory gated reconstructions based on either COD or Anzai traces were performed to evaluate their relative performance in capturing respiratory motion. Finally, based on correlations of displacements of organ locations in all directions and COD information, continuous 3D internal organ motion in SI and AP directions was calculated based on COD traces to guide event-by-event respiratory motion correction in the MOLAR reconstruction framework. Continuous respiratory correction results based on COD were compared with that based on Anzai, and without motion correction. Data-driven COD traces showed a good correlation with Anzai in both SI and AP directions for the majority of studies, with correlation coefficients ranging from 63% to 89%. Based on the determined respiratory displacements of pancreas between end-expiration and end-inspiration from gated reconstructions, there was no significant difference between COD-based and Anzai-based methods. Finally, data-driven COD-based event-by-event respiratory motion correction yielded comparable results to that based on Anzai respiratory traces, in terms of contrast recovery and reduced motion-induced blur. Data-driven event-by-event respiratory motion correction using COD showed significant image quality improvement compared with reconstructions with no motion correction, and gave comparable results to the Anzai-based method.

Quantification of myocardial blood flow with (82)Rb: Validation with (15)O-water using time-of-flight and point-spread-function modeling.

BACKGROUND: We quantified myocardial blood flow with (82)Rb PET using parameters of the generalized Renkin-Crone model estimated from (82)Rb and (15)O-water images reconstructed with time-of-flight and point spread function modeling. Previous estimates of rubidium extraction have used older-generation scanners without time-of-flight or point spread function modeling. We validated image-derived input functions with continuously collected arterial samples. METHODS: Nine healthy subjects were scanned at rest and under pharmacological stress on the Siemens Biograph mCT with (82)Rb and (15)O-water PET, undergoing arterial blood sampling with each scan. Image-derived input functions were estimated from the left ventricle cavity and corrected with tracer-specific population-based scale factors determined from arterial data. Kinetic parametric images were generated from the dynamic PET images by fitting the one-tissue compartment model to each voxel's time activity curve. Mean myocardial blood flow was determined from each subject's (15)O-water k 2 images. The parameters of the generalized Renkin-Crone model were estimated from these water-based flows and mean myocardial (82)Rb K 1 estimates. RESULTS: Image-derived input functions showed improved agreement with arterial measurements after a scale correction. The Renkin-Crone model fit (a = 0.77, b = 0.39) was similar to those previously published, though b was lower. CONCLUSIONS: We have presented parameter estimates for the generalized Renkin-Crone model of extraction for (82)Rb PET using human (82)Rb and (15)O-water PET from high-resolution images using a state-of-the-art time-of-flight-capable scanner. These results provide a state-of-the-art methodology for myocardial blood flow measurement with (82)Rb PET.

Evaluation of frame-based and event-by-event motion-correction methods for awake monkey brain PET imaging.

UNLABELLED: PET imaging of nonhuman primates (NHPs) requires correction of head motion if the subjects are scanned awake and their heads are unrestrained, because the NHPs move their heads faster and more frequently than human subjects. This work focuses on designing and validating 2 motion-correction algorithms for awake NHP brain PET imaging. METHODS: Two motion-correction methods were implemented for awake NHP brain PET imaging: multiacquisition frame (MAF) and event-by-event (EBE). Motion data were acquired from an external motion-tracking device. The MAF method divides scan data into short subframes, reconstructs each subframe individually, and registers them to a reference orientation. This method suffers from residual intraframe motion and data loss when motion is large because a minimum frame duration is often required. The EBE method, previously implemented for a human brain scanner and adapted for a small-animal PET scanner in this work, eliminates intraframe motion and should have a best accuracy. We first evaluated the accuracy of both motion-correction methods with moving phantom scans. Both motion-correction methods were then applied to awake NHP brain PET studies with a gamma-aminobutyric acid A-benzodiazepine receptor ligand, (11)C-flumazenil, and the reconstructed images were compared with those from a motion-free anesthetized study. RESULTS: The phantom studies showed that EBE motion correction recovers the contrast (within 3%) similarly to the static study, whereas MAF motion correction using the standard algorithm setting showed a 25% reduction in contrast from the static case. In awake NHP brain PET imaging, EBE motion correction better recovers the fine structures than the MAF method, as compared with anesthetized studies. CONCLUSION: The large magnitude and frequency of NHP head motion suggests that EBE motion correction with accurate externally measured motion data can noticeably alleviate image blurring due to the intraframe motion in the MAF motion-correction method.

Event-by-event respiratory motion correction for PET with 3D internal-1D external motion correlation.

PURPOSE: Respiratory motion during PET∕CT imaging can cause substantial image blurring and underestimation of tracer concentration for both static and dynamic studies. In this study, the authors developed an event-by-event respiratory motion correction method that used three-dimensional internal-one-dimensional external motion correlation (INTEX3D) in listmode reconstruction. The authors aim to fully correct for organ/tumor-specific rigid motion caused by respiration using all detected events to eliminate both intraframe and interframe motion, and investigate the quantitative improvement in static and dynamic imaging. METHODS: The positional translation of an internal organ or tumor during respiration was first determined from the reconstructions of multiple phase-gated images. A level set (active contour) method was used to segment the targeted internal organs/tumors whose centroids were determined. The mean displacement of the external respiratory signal acquired by the Anzai system that corresponded to each phase-gated frame was determined. Three linear correlations between the 1D Anzai mean displacements and the 3D centroids of the internal organ/tumor were established. The 3D internal motion signal with high temporal resolution was then generated by applying each of the three correlation functions to the entire Anzai trace (40 Hz) to guide event-by-event motion correction in listmode reconstruction. The reference location was determined as the location where CT images were acquired to facilitate phase-matched attenuation correction and anatomical-based postfiltering. The proposed method was evaluated with a NEMA phantom driven by a QUASAR respiratory motion platform, and human studies with two tracers: pancreatic beta cell tracer [(18)F]FP(+)DTBZ and tumor hypoxia tracer [(18)F]fluoromisonidazole (FMISO). An anatomical-based postreconstruction filter was applied to the motion-corrected images to reduce noise while preserving quantitative accuracy and organ boundaries in the patient studies. RESULTS: The INTEX3D method yielded an increase of 5%-9% and 32%-40% in contrast recovery coefficient on the hot spheres in the NEMA phantom, compared to the reconstructions with only 1D motion correction (INTEX1D) and no motion correction, respectively. The proposed method also increased the mean activities of the pancreas and kidney by 9.3% and 11.2%, respectively, across three subjects in the FPDTBZ studies, and the average lesion-to-blood ratio by 20% across three lesions in the FMISO study, compared to the reconstructions without motion correction. In addition, the proposed method reduced intragate motion as compared to phase-gated images. The application of the anatomical-based postreconstruction filter further reduced noise in the background by >50% compared to reconstructions without postfiltering, while preserving quantitative accuracy and organ boundaries. Finally, the measurements of the time-activity curves from a subject with FPDTBZ showed that INTEX3D yielded 18% and 11% maximum increases in tracer concentration in the pancreas and kidney cortex, respectively. CONCLUSIONS: These results suggest that the proposed method can effectively compensate for both intragate and intergate respiratory motion while preserving all the counts, and is applicable to dynamic studies.