Raw PET Research Articles

Measuring animal exposure in Canada: Foodbook study, 2014-2015.

Animal companionship can have many physical and psychological benefits; however, animals can also be a source of zoonotic infection, including enteric illnesses; it has been estimated that in Canada, nearly 85,000 enteric illnesses due to eight pathogens occur each year related to animal contact. There is a lack of baseline data on animal-related exposures in Canada and around the world. This information is critical to inform quantitative and qualitative risk assessments to prioritize intervention efforts in public health and reduce the associated burden of enteric illness. To help address this issue and assist evaluation of the risks associated with animal contact, the Foodbook study, conducted in 2014-2015, assessed exposure to animals, animal food and animal-related venues within the last 7days among Canadians. Data were analysed by province and territory, age group and urban/rural residency. Overall, dogs and cats were the most commonly reported animal exposures (43.3% and 31.9%, respectively). The data suggest farm animal exposure occurs primarily at a farm/barn, and to a lesser extent at other animal-related venues (e.g., petting zoos or agricultural fairs). Approximately one in 25 respondents handled raw pet food within the last 7days; the majority of which had also been exposed to a dog (86.4%). Children aged 0-9years reported relatively high exposure to four types of high-risk animals: rodents (5.6%), poultry (4.0%), reptiles (2.1%) and amphibians (1.8%); with the most vulnerable children aged <5years also reporting exposure to many of these high-risk animals. These results highlight potential areas for targeted intervention that can focus on high-risk populations (e.g., young children) exhibiting potentially risky behaviour such as being exposed to certain high-risk animals, or handling pet food, treats and raw pet food diets. Additionally, these results support the need to better understand the burden of enteric illness associated with animals and their environments.

Pretreatment of low-grade poly(ethylene terephthalate) waste for effective depolymerization to monomers

Pretreatment process of silica-coated PET fabrics, a major low-grade PET waste, was developed using the reaction with NaOH solution. By destroying the structure of silica coating layer, impurities such as silica and pigment dyes could be removed. The removal of impurity was confirmed by X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDX). The pretreated PET fabric samples were used for depolymerization into its monomer, bis(2-hydroxylethyl) terephthalate (BHET), by glycolysis with ethylene glycol (EG), and zinc acetate (ZnAc) catalyst. The quality of BHET was confirmed by DSC, TGA, HPLC and NMR analyses. The highest BHET yield of 89.23% was obtained from pretreated PET fabrics, while glycolysis with raw PET fabric yielded 85.43%. The BHET yield from untreated silica-coated PET fabrics was 60.39%. The pretreatment process enhances the monomer yield by the removal of impurity and also improves the quality of the monomer.

Respiratory Motion Correction Using A Novel Positron Emission Particle Tracking Technique: A Framework Towards Individual Lesion-Based Motion Correction.

Respiratory motion during PET/CT imaging is a matter of concern due to degraded image quality and reduced quantitative accuracy caused by motion artifacts. One class of motion correction methods relies on hardware-based respiratory motion tracking systems in order to use respiratory cycles for correcting motion artifacts. Another class of hardware-free methods extract motion information from the reconstructed images or sinograms. Hardware-based methods, however, are limited by calibration requirement, patient discomfort, lack of adaptability during scanning, presence of electronic drift during respiratory monitoring etc. Extracting motion information from reconstructed images is also limited by the fact that the original raw information requires significant processing before it can be used. Hence the motivation behind this work is to introduce a software-based approach that can be applied on raw 64-bit listmode data. The basic design of the proposed method is based on the fundamentals of Positron Emission Particle Tracking (PEPT) with additional incorporation of Time of Flight (TOF) information. Respiratory motion of patients has been extracted from the raw PET data by tracking a point source attached to the patient in areas on and near the chest. The key objective of this work is to describe a new process by which this particle tracking based motion correction system can eventually be lesion specific and correct the motion for a particular lesion within the patient. This work thus serves as a framework for lesion specific motion correction.

NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

Companies seek food safety using a microbiome approach

In a pet food factory in Reno, NV, researchers from IBM Research and Mars, Inc. are conducting an experiment that may someday revolutionize food safety. For more than two years, they’ve taken regular samples of poultry meal—a protein-rich mash of chicken parts—as it enters the factory on its way to becoming pet food. Each sample of this raw material contains a vast community of living bacteria and viruses—the poultry meal’s microbiome—that either originated with the chicken parts or entered at some point along the food processing chain. The researchers then use genetic sequencing to determine the identity and relative quantities of each microbial species. Researchers with the Consortium for Sequencing the Food Supply Chain ultimately want to explore the microbiomes of food in each stage of the supply chain—from the farm, to the factory, to the supermarket. Image courtesy of Shutterstock/Alf Ribeiro. The hypothesis is that safe batches of poultry meal all have a fairly standard set of microbial residents. A shift in the microbiome, then, could signify that something is amiss—a pathogen has spiked, a toxin is present, or the item labeled poultry is actually from another animal altogether. By routinely sampling the microbiome of this raw pet food material, researchers could pinpoint and stop safety issues before the food leads to sick pets. And if a microbiome surveillance approach works for poultry meal, it might just work for the rest of the food supply. But if the approach is ever to replace more traditional food surveillance methods, the team must categorize a vast amount of bacterial diversity. Food suppliers and government agencies such as the Food and Drug Administration (FDA) and the US Department of Agriculture (USDA), regularly monitor food in the production chain to limit the spread of foodborne illnesses. And yet, roughly 48 million Americans get …

Raw pet food as a risk factor for shedding of extended-spectrum beta-lactamase-producing Enterobacteriaceae in household cats.

BackgroundClose contact between pets and owners provides the opportunity for transmission of antimicrobial resistant organisms like extended-spectrum beta-lactamase (ESBL)/AmpC beta-lactamase (AmpC)-producing Enterobacteriaceae, posing a risk to public health.ObjectivesTo investigate whether raw feed is a risk factor for household cats to shed ESBL-producing Enterobacteriaceae, a cohort study was designed. Additionally, raw and non-raw commercial pet food products were screened for the presence of ESBL-producing Enterobacteriaceae.MethodsWeekly fecal samples of 17 cats in the control group and 19 cats in the exposed group were collected for three weeks and analyzed for the presence of ESBL-producing Enterobacteriaceae. Questionnaires were obtained to determine additional risk factors. Fecal samples were cultured on MacConkey agar supplemented with 1 mg/L cefotaxime. PCR and sequence analysis was used for screening for ESBL genes in suspected isolates. Pet food samples were cultured in LB broth supplemented with 1 mg/L cefotaxime and processed as described above.ResultsIn the cohort study, ESBL-producing bacteria were isolated from 3 of 51 (5.9%) samples in the control group compared to 37 of 57 (89.5%) samples in the exposed group. A significant association was found between ESBL shedding and feeding raw pet food products (OR = 31.5). No other risk factors were identified in this study. ESBL-producing Enterobacteriaceae were isolated from 14 of 18 (77.8%) raw pet food products and 0 of 35 non-raw pet food products.ConclusionsThis study shows a strong association between shedding of ESBL-producing bacteria in household cats and feeding raw pet food. Raw pet food was often contaminated with ESBL-producing Enterobacteriaceae.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7–8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of , the tracer transport rate (ml · min−1 · ml−1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

Sign determination methods for the respiratory signal in data-driven PET gating

Patient respiratory motion during PET image acquisition leads to blurring in the reconstructed images and may cause significant artifacts, resulting in decreased lesion detectability, inaccurate standard uptake value calculation and incorrect treatment planning in radiation therapy. To reduce these effects data can be regrouped into (nearly) ‘motion-free’ gates prior to reconstruction by selecting the events with respect to the breathing phase. This gating procedure therefore needs a respiratory signal: on current scanners it is obtained from an external device, whereas with data driven (DD) methods it can be directly obtained from the raw PET data. DD methods thus eliminate the use of external equipment, which is often expensive, needs prior setup and can cause patient discomfort, and they could also potentially provide increased fidelity to the internal movement. DD methods have been recently applied on PET data showing promising results. However, many methods provide signals whose direction with respect to the physical motion is uncertain (i.e. their sign is arbitrary), therefore a maximum in the signal could refer either to the end-inspiration or end-expiration phase, possibly causing inaccurate motion correction. In this work we propose two novel methods, CorrWeights and CorrSino, to detect the correct direction of the motion represented by the DD signal, that is obtained by applying principal component analysis (PCA) on the acquired data. They only require the PET raw data, and they rely on the assumption that one of the major causes of change in the acquired data related to the chest is respiratory motion in the axial direction, that generates a cranio-caudal motion of the internal organs. We also implemented two versions of a published registration-based method, that require image reconstruction. The methods were first applied on XCAT simulations, and later evaluated on cancer patient datasets monitored by the Varian Real-time Position ManagementTM (RPM) device, selecting the lower chest bed positions. For each patient different time intervals were evaluated ranging from 50 to 300 s in duration. The novel methods proved to be generally more accurate than the registration-based ones in detecting the correct sign of the respiratory signal, and their failure rates are lower than 3% when the DD signal is highly correlated with the RPM. They also have the advantage of faster computation time, avoiding reconstruction. Moreover, CorrWeights is not specifically related to PCA and considering its simple implementation, it could easily be applied together with any DD method in clinical practice.

The Use of High Pressure Processing as a Pathogen Reduction Tool in Raw Pet Food

ObjectivesThe Food Safety Modernization Act (FSMA) has established a “zero tolerance” for Salmonella in pet food. The objective of this experiment was to evaluate the effectiveness of High Pressure Processing (HPP) and frozen storage time on the inactivation of non-pathogenic, surrogate bacteria populations in raw pet food.Materials and MethodsApproximately 18 kg of a raw beef pet food was inoculated to a target of 7 logs CFU/g with a 5 strain cocktail of non-pathogenic Escherichia coli (ATCC BAA 1427–31) which was previously validated as a surrogate for Salmonella. The inoculated product was packaged in 227 g individual roll stock packages and shipped to an external facility for HPP application. Inoculated samples were subjected to HPP at 600 mpa for 480 s. After HPP processing, samples were transported on ice to Colorado State University for determination of the remaining microbial population. The samples were randomly assigned to either sampling at 24-hours post-processing (n = 10) or following 5 d of frozen storage at -23°C (n = 10). Raw product samples were serially diluted in BPW and plated onto selective (Violet Red Bile Agar; VRBA; selective for coliforms) and non-selective (Tryptic Soy Agar; TSA) medias for enumeration.ResultsAt 24 h post-processing, following HPP, surviving colonies on VRBA totaled 1.8 logs CFU/g (4.9 log CFU/g reduction) following HPP and frozen storage, surviving colonies on VRBA totaled 0.48 logs CFU/g (6.2 log CFU/g reduction) with 90% of all samples under the detection limit. The TSA survivors totaled 4.8 logs CFU/g (2.1 log CFU/g reduction) 24 h post HPP and totaled 4.6 logs CFU/g (2.3 log CFU/g reduction) post HPP and frozen storage. Data were analyzed using the mixed procedure of SAS (version 9.3; SAS Inst. Inc., Cary, NC) and separated using the PDIFF statement with an ɑ of 0.05.ConclusionHigh Pressure Processing effectively kills pathogenic bacterial strains and causes substantial sub-lethal damage/injury to the bacterial cells, reducing the ability of the bacteria to recover and grow on selective media. Additionally, cellular injury leads to additional lethality in bacterial cells following frozen storage. Therefore, HPP and subsequent frozen storage are effective means of killing significant numbers of bacteria, but these methods do not achieve total death or sterilization. As a result, additional interventions must be investigated to achieve sterility and total destruction of Salmonella.

Isolation of Campylobacter spp. from Client-Owned Dogs and Cats, and Retail Raw Meat Pet Food in the Manawatu, New Zealand.

Campylobacter causes acute gastroenteritis in people worldwide and is frequently isolated from food, animals and the environment. The disease is predominately food-borne but many routes of transmission and sources of infection have been described, including contact with pets. The prevalence of Campylobacter spp. in dogs and cats varies widely, and data on New Zealand pets are limited. This study aimed to investigate the prevalence of Campylobacter spp. in dogs, cats and retail raw meat pet food products in New Zealand and to characterize Campylobacter jejuni isolates using multilocus sequence typing (MLST). Ninety dogs and 110 cats examined at the Massey University Veterinary Teaching Hospital for elective procedures, and fifty locally purchased retail raw meat pet diets were sampled. Two culture protocols combining Bolton broth enrichment and mCCDA and CAT agars in a microaerobic atmosphere at 42°C and 37°C with species identification using PCR were performed. The prevalence of Campylobacter spp., C.jejuni, Campylobacter upsaliensis and Campylobacter helveticus was 36%, 13%, 23% and 1% in dogs and 16%, 5%, 5% and 7% in cats, respectively. One dog had Campylobacter lari confirmed, and three dogs and one cat had multiple Campylobacter spp. detected. Significantly more animals tested positive using CAT than mCCDA agar (P<0.001). Being neutered, vaccinated for Bordetella bronchiseptica, fed dry diets and brought in for neutering were protective factors for dogs, whereas attendance for dental treatment was a risk factor for cats. Campylobacter spp. were isolated from 28%, C.jejuni 22%, C.lari 6% and Campylobacter coli 6% of food samples. Six isolates positive by Campylobacter genus PCR were identified as Arcobacter butzleri. Poultry meat was more likely to be positive than non-poultry meat (P=0.006). Of the 13 C.jejuni pet isolates with full MLST profiles, eight were of different sequence types (ST) and all nine food isolates were of different STs.

Bacteriophages safely reduce Salmonella contamination in pet food and raw pet food ingredients.

Contamination of pet food with Salmonella is a serious public health concern, and several disease outbreaks have recently occurred due to human exposure to Salmonella tainted pet food. The problem is especially challenging for raw pet foods (which include raw meats, seafood, fruits, and vegetables). These foods are becoming increasingly popular because of their nutritional qualities, but they are also more difficult to maintain Salmonella-free because they lack heat-treatment. Among various methods examined to improve the safety of pet foods (including raw pet food), one intriguing approach is to use bacteriophages to specifically kill Salmonella serotypes. At least 2 phage preparations (SalmoFresh® and Salmonelex™) targeting Salmonella are already FDA cleared for commercial applications to improve the safety of human foods. However, similar preparations are not yet available for pet food applications. Here, we report the results of evaluating one such preparation (SalmoLyse®) in reducing Salmonella levels in various raw pet food ingredients (chicken, tuna, turkey, cantaloupe, and lettuce). Application of SalmoLyse® in low (ca. 2-4×106 PFU/g) and standard (ca. 9×106 PFU/g) concentrations significantly (P < 0.01) reduced (by 60-92%) Salmonella contamination in all raw foods examined compared to control treatments. When SalmoLyse®-treated (ca. 2×107 PFU/g) dry pet food was fed to cats and dogs, it did not trigger any deleterious side effects in the pets. Our data suggest that the bacteriophage cocktail lytic for Salmonella can significantly and safely reduce Salmonella contamination in various raw pet food ingredients.

PET and SPECT of Neurobiological Systems

1805 Objectives A PET image reconstruction tool (Q.Clear®) has been recently introduced that allows more iterations of the raw PET data than the standard OSEM image reconstruction, to enable contrast recovery without amplifying noise. Here we qualitatively and semi-quantitatively compared Q.Clear® with the standard OSEM image reconstruction available on our clinical PET/CT scanners (GE Discovery 600 and 690) using patient data. Methods PET datasets from 30 previously acquired clinical research scans (16 68Ga-DOTA TATE, 11 18F-FPPRGD2, 1 18F-FLT, 2 18F-FSPG) were reconstructed using Q.Clear® (25 iterations with 3 different regularization strength or “beta” values) and compared to standard reconstruction for Discovery 600 (2 iterations and 32 subsets; with PSF modeling) and 690 (2 iterations and 24 subsets; with PSF modeling) scanners. Each of the 4 reconstructions/scan were reviewed blindly by 2 experienced nuclear medicine physicians and scored 1-5 (1 poor, 5 excellent quality). The SUVmax of the smallest lesion detected in each patient was also measured for comparison. The paired Welch t-test was used for statistical analysis. Results Significant differences (P Conclusions Q.Clear® with a higher number of iterations maintains image quality. Visual analysis confirmed that overall image quality is improved and may allow for improved detection of small lesions as compared to the image quality from the standard OSEM algorithm. Research Support GE Healthcare

Detecting and estimating head motion in brain PET acquisitions using raw time-of-flight PET data

Head motion during brain PET imaging is not uncommon and can negatively affect image quality. Motion correction techniques typically either use hardware to prospectively measure head motion, or they divide the acquisition into short fixed-frames and then align and combine these to produce a motion free image. The aim of this work was to retrospectively detect when motion occurred in PET data without the use of motion detection hardware, and then align the frames defined by these motion occurrences. We describe two methods that use either principal component analysis or the motion induced spatial displacements over time to detect motion in raw time-of-flight PET data. The points in time of motion then define the temporal boundaries of frames which are reconstructed without attenuation correction, aligned and combined. Phantom and [18F]-Fallypride patient acquisitions were used to validate and evaluate these approaches, which were compared with motion estimation using 60 s fixed-frames. Both methods identified all motion occurrences in phantom data, and unlike the fixed-frame approach did not exhibit intra-frame motion. With patient acquisitions, images corrected with the motion detection methods increased the average image sharpness by the same amount as the fixed-frame approach, but reduced the number of reconstructions and registrations by a factor of 3.4 on average. Detecting head motion in raw PET data alone is possible, allowing retrospective motion estimation of any listmode brain PET acquisition without additional hardware, subsequently decreasing data processing and potentially reducing intra-frame motion.

Melt Foamability of Poly(ethylene terephthalate)/Clay Nanocomposites Prepared by Extrusion Blending in the Presence of Pyromellitic Dianhydride

Exfoliated poly(ethylene terephthalate) (PET)/organoclay nanocomposites were prepared by extrusion blending method with different clay contents and molecular weights of raw PET. Pyromellitic dianhydride (PMDA) was extruded, together with PET and clay, to introduce long-chain branching to PET backbone and delaminate the clay layers. Although the molecular weights and viscoelastic properties of nanocomposites were much lower than those of foamable PMDA-modified PET, the melt foamability of nanocomposites was significantly improved by the well-dispersed clays due to the heterogeneous nucleation effect, enhanced nonisothermal crystallization rate, and so on. Foaming temperature windows with a width of 20–60 °C were explored for PET/clay nanocomposites with intrinsic viscosities of 0.67–0.94 dL/g, in which nanocomposites foams with cell diameters of 29–53 μm, cell densities of 6.5 × 107–6.9 × 108 cells/cm3, and expansion ratio of 10–50 could be controllably produced using supercritical CO2 as a blowing agent.

Direct 4D PET MLEM reconstruction of parametric images using the simplified reference tissue model with the basis function method for [11C]raclopride

This work assesses the one-step late maximum likelihood expectation maximization (OSL-MLEM) 4D PET reconstruction algorithm for direct estimation of parametric images from raw PET data when using the simplified reference tissue model with the basis function method (SRTM-BFM) for the kinetic analysis. To date, the OSL-MLEM method has been evaluated using kinetic models based on two-tissue compartments with an irreversible component. We extend the evaluation of this method for two-tissue compartments with a reversible component, using SRTM-BFM on simulated 3D + time data sets (with use of [11C]raclopride time-activity curves from real data) and on real data sets acquired with the high resolution research tomograph. The performance of the proposed method is evaluated by comparing voxel-level binding potential (BPND) estimates with those obtained from conventional post-reconstruction kinetic parameter estimation. For the commonly chosen number of iterations used in practice, our results show that for the 3D + time simulation, the direct method delivers results with lower %RMSE at the normal count level (decreases of 9–10 percentage points, corresponding to a 38–44% reduction), and also at low count levels (decreases of 17–21 percentage points, corresponding to a 26–36% reduction). As for the real 3D data set, the results obtained follow a similar trend, with the direct reconstruction method offering a 21% decrease in %CV compared to the post reconstruction method at low count levels. Thus, based on the results presented herein, using the SRTM-BFM kinetic model in conjunction with the OSL-MLEM direct 4D PET MLEM reconstruction method offers an improvement in performance when compared to conventional post reconstruction methods.

Practical PET Respiratory Motion Correction in Clinical PET/MR.

Respiratory motion during PET acquisition may lead to blurring in resulting images and underestimation of uptake parameters. The advent of integrated PET/MR scanners allows us to exploit the integration of modalities, using high spatial resolution and high-contrast MR images to monitor and correct PET images degraded by motion. We proposed a practical, anatomy-independent MR-based correction strategy for PET data affected by respiratory motion and showed that it can improve image quality both for PET acquired simultaneously to the motion-capturing MR and for PET acquired up to 1 h earlier during a clinical scan. To estimate the respiratory motion, our method needs only an extra 1-min dynamic MR scan, acquired at the end of the clinical PET/MR protocol. A respiratory signal was extracted directly from the PET list-mode data. This signal was used to gate the PET data and to construct a motion model built from the dynamic MR data. The estimated motion was then incorporated into the PET image reconstruction to obtain a single motion-corrected PET image. We evaluated our method in 2 steps. The PET-derived respiratory signal was compared with an MR measure of diaphragmatic displacement via a pencil-beam navigator. The motion-corrected images were compared with uncorrected images with visual inspection, line profiles, and standardized uptake value (SUV) in focally avid lesions. We showed a strong correlation between the PET-derived and MR-derived respiratory signals for 9 patients, with a mean correlation of 0.89. We then showed 4 clinical case study examples ((18)F-FDG and (68)Ga-DOTATATE) using the motion-correction technique, demonstrating improvements in image sharpness and reduction of respiratory artifacts in scans containing pancreatic, liver, and lung lesions as well as cardiac scans. The mean increase in peak SUV (SUV(peak)) and maximum SUV (SUV(max)) in a patient with 4 pancreatic lesions was 23.1% and 34.5% in PET acquired simultaneously with motion-capturing MR, and 17.6% and 24.7% in PET acquired 50 min before as part of the clinical scan. We showed that a respiratory signal can be obtained from raw PET data and that the clinical PET image quality can be improved using only a short additional PET/MR acquisition. Our method does not need external respiratory hardware or modification of the normal clinical MR sequences.

Extracting a respiratory signal from raw dynamic PET data that contain tracer kinetics

Data driven gating (DDG) methods provide an alternative to hardware based respiratory gating for PET imaging. Several existing DDG approaches obtain a respiratory signal by observing the change in PET-counts within specific regions of acquired PET data. Currently, these methods do not allow for tracer kinetics which can interfere with the respiratory signal and introduce error. In this work, we produced a DDG method for dynamic PET studies that exhibit tracer kinetics. Our method is based on an existing approach that uses frequency-domain analysis to locate regions within raw PET data that are subject to respiratory motion. In the new approach, an optimised non-stationary short-time Fourier transform was used to create a time-varying 4D map of motion affected regions. Additional processing was required to ensure that the relationship between the sign of the respiratory signal and the physical direction of movement remained consistent for each temporal segment of the 4D map. The change in PET-counts within the 4D map during the PET acquisition was then used to generate a respiratory curve. Using 26 min dynamic cardiac NH3 PET acquisitions which included a hardware derived respiratory measurement, we show that tracer kinetics can severely degrade the respiratory signal generated by the original DDG method. In some cases, the transition of tracer from the liver to the lungs caused the respiratory signal to invert. The new approach successfully compensated for tracer kinetics and improved the correlation between the data-driven and hardware based signals. On average, good correlation was maintained throughout the PET acquisitions.

Investigation of Listeria, Salmonella, and toxigenic Escherichia coli in various pet foods.

The Veterinary Laboratory Investigation and Response Network (Vet-LIRN), in collaboration with the Food Emergency Response Network (FERN) and its Microbiology Cooperative Agreement Program (MCAP) laboratories, conducted a study to evaluate the prevalence of selected microbial organisms in various types of pet foods. The goal of this blinded study was to help the Center for Veterinary Medicine prioritize potential future pet food-testing efforts. The study also increased the FERN laboratories' screening capabilities for foodborne pathogens in animal feed matrices, since such pathogens may also be a significant health risk to consumers who come into contact with pet foods. Six U.S. Food and Drug Administration FERN MCAP laboratories analyzed approximately 1056 samples over 2 years. Laboratories tested for Salmonella, Listeria, Escherichia coli O157:H7 enterohemorrhagic E. coli, and Shiga toxin-producing strains of E. coli (STEC). Dry and semimoist dog and cat foods purchased from local stores were tested during Phase 1. Raw dog and cat foods, exotic animal feed, and jerky-type treats purchased through the Internet were tested in Phase 2. Of the 480 dry and semimoist samples, only 2 tested positive: 1 for Salmonella and 1 for Listeria greyii. However, of the 576 samples analyzed during Phase 2, 66 samples were positive for Listeria (32 of those were Listeria monocytogenes) and 15 samples positive for Salmonella. These pathogens were isolated from raw foods and jerky-type treats, not the exotic animal dry feeds. This study showed that raw pet foods may harbor food safety pathogens, such as Listeria monocytogenes and Salmonella. Consumers should handle these products carefully, being mindful of the potential risks to human and animal health.

Gating, enhanced gating, and beyond: information utilization strategies for motion management, applied to preclinical PET

BackgroundRespiratory gating and gate optimization strategies present solutions for overcoming image degradation caused by respiratory motion in PET and traditionally utilize hardware systems and/or employ complex processing algorithms. In this work, we aimed to advance recently emerging data-driven gating methods and introduce a new strategy for optimizing the four-dimensional data based on information contained in that data. These algorithms are combined to form an automated motion correction workflow.MethodsSoftware-based gating methods were applied to a nonspecific population of 84 small-animal rat PET scans to create respiratory gated images. The gated PET images were then optimized using an algorithm we introduce as ‘gating+’ to reduce noise and optimize signal; the technique was also tested using simulations. Gating+ is based on a principle of only using gated information if and where it adds a net benefit, as evaluated in temporal frequency space. Motion-corrected images were assessed quantitatively and qualitatively.ResultsOf the small-animal PET scans, 71% exhibited quantifiable motion after software gating. The mean liver displacement was 3.25 mm for gated and 3.04 mm for gating+ images. The (relative) mean percent standard deviations measured in background ROIs were 1.53, 1.05, and 1.00 for the gated, gating+, and ungated values, respectively. Simulations confirmed that gating+ image voxels had a higher probability of being accurate relative to the corresponding ungated values under varying noise and motion scenarios. Additionally, we found motion mapping and phase decoupling models that readily extend from gating+ processing.ConclusionsRaw PET data contain information about motion that is not currently utilized. In our work, we showed that through automated processing of standard (ungated) PET acquisitions, (motion-) information-rich images can be constructed with minimal risk of noise introduction. Such methods have the potential for implementation with current PET technology in a robust and reproducible way.

External radioactive markers for PET data-driven respiratory gating in positron emission tomography

Respiratory gating is an established approach to overcoming respiration-induced image artefacts in PET. Of special interest in this respect are raw PET data-driven gating methods which do not require additional hardware to acquire respiratory signals during the scan. However, these methods rely heavily on the quality of the acquired PET data (statistical properties, data contrast, etc.). We therefore combined external radioactive markers with data-driven respiratory gating in PET/CT. The feasibility and accuracy of this approach was studied for [(18)F]FDG PET/CT imaging in patients with malignant liver and lung lesions. PET data from 30 patients with abdominal or thoracic [(18)F]FDG-positive lesions (primary tumours or metastases) were included in this prospective study. The patients underwent a 10-min list-mode PET scan with a single bed position following a standard clinical whole-body [(18)F]FDG PET/CT scan. During this scan, one to three radioactive point sources (either (22)Na or (18)F, 50-100kBq) in a dedicated holder were attached the patient's abdomen. The list mode data acquired were retrospectively analysed for respiratory signals using established data-driven gating approaches and additionally by tracking the motion of the point sources in sinogram space. Gated reconstructions were examined qualitatively, in terms of the amount of respiratory displacement and in respect of changes in local image intensity in the gated images. The presence of the external markers did not affect whole-body PET/CT image quality. Tracking of the markers led to characteristic respiratory curves in all patients. Applying these curves for gated reconstructions resulted in images in which motion was well resolved. Quantitatively, the performance of the external marker-based approach was similar to that of the best intrinsic data-driven methods. Overall, the gain in measured tumour uptake from the nongated to the gated images indicating successful removal of respiratory motion was correlated with the magnitude of the respiratory displacement of the respective tumour lesion, but not with lesion size. Respiratory information can be assessed from list-mode PET/CT through PET data-derived tracking of external radioactive markers. This information can be successfully applied to respiratory gating to reduce motion-related image blurring. In contrast to other previously described PET data-driven approaches, the external marker approach is independent of tumour uptake and thereby applicable even in patients with poor uptake and small tumours.