Sequential deep learning image enhancement models improve diagnostic confidence, lesion detectability, and image reconstruction time in PET.

BACKGROUND: Investigate the potential benefits of sequential deployment of two deep learning (DL) algorithms namely DL-Enhancement (DLE) and DL-based time-of-flight (ToF) (DLT). DLE aims to enhance the rapidly reconstructed ordered-subset-expectation-maximisation algorithm (OSEM) images towards block-sequential-regularised-expectation-maximisation (BSREM) images, whereas DLT aims to improve the quality of BSREM images reconstructed without ToF. As the algorithms differ in their purpose, sequential application may allow benefits from each to be combined. 20 FDG PET-CT scans were performed on a Discovery 710 (D710) and 20 on Discovery MI (DMI; both GE HealthCare). PET data was reconstructed using five combinations of algorithms:1. ToF-BSREM, 2. ToF-OSEM + DLE, 3. OSEM + DLE + DLT, 4. ToF-OSEM + DLE + DLT, 5. ToF-BSREM + DLT. To assess image noise, 30 mm-diameter spherical VOIs were drawn in both lung and liver to measure standard deviation of voxels within the volume. In a blind clinical reading, two experienced readers rated the images on a five-point Likert scale based on lesion detectability, diagnostic confidence, and image quality. RESULTS: Applying DLE + DLT reduced noise whilst improving lesion detectability, diagnostic confidence, and image reconstruction time. ToF-OSEM + DLE + DLT reconstructions demonstrated an increase in lesion SUVmax of 28 ± 14% (average ± standard deviation) and 11 ± 5% for data acquired on the D710 and DMI, respectively. The same reconstruction scored highest in clinical readings for both lesion detectability and diagnostic confidence for D710. CONCLUSIONS: The combination of DLE and DLT increased diagnostic confidence and lesion detectability compared to ToF-BSREM images. As DLE + DLT used input OSEM images, and because DL inferencing was fast, there was a significant decrease in overall reconstruction time. This could have applications to total body PET.

The Unusual Cosubstrate Specificity of NQO2: Conservation Throughout the Amniotes and Implications for Cellular Function.

Human Quinone Reductase 2 (NQO2) is a pharmacological target and has appeared in numerous screening efforts as an off-target interactor with kinase-targeted drugs. However the cellular functions of NQO2 are not known. To gain insight into the potential cellular functions of NQO2, we have carried out a detailed evolutionary analysis. One of the most striking characteristics of NQO2 is that it uses conventional dihydronicotinamide cosubstrates, NADH and NADPH, extremely inefficiently, raising questions about an enzymatic function in cells. To characterize the ability of NQO2 to serve as an enzyme, the NQO2 gene was disrupted in HCT116 cells. These NQO2 knockouts along with the parental cells were used to demonstrate that cellular NQO2 is unable to catalyze the activation of the DNA cross-linking reagent, CB1954, without the addition of exogenous dihydronicotinamide riboside (NRH). To find whether the unusual cosubstrate specificity of NQO2 has been conserved in the amniotes, recombinant NQO2 from a reptile, Alligator mississippiensis, and a bird, Anas platyrhynchos, were cloned, purified, and their catalytic activity characterized. Like the mammalian enzymes, the reptile and bird NQO2 were efficient catalysts with the small and synthetic cosubstrate N-benzyl-1,4-dihydronicotinamide but were inefficient in their use of NADH and NADPH. Therefore, the unusual cosubstrate preference of NQO2 appears to be conserved throughout the amniotes; however, we found that NQO2 is not well-conserved in the amphibians. A phylogenetic analysis indicates that NQO1 and NQO2 diverged at the time, approximately 450 MYA, when tetrapods were beginning to evolve.

Deep learning-based time-of-flight (ToF) image enhancement of non-ToF PET scans.

PURPOSE: To improve the quantitative accuracy and diagnostic confidence of PET images reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image enhancement (DL-ToF). METHODS: A total of 273 [18F]-FDG PET scans were used, including data from 6 centres equipped with GE Discovery MI ToF scanners. PET data were reconstructed using the block-sequential-regularised-expectation-maximisation (BSREM) algorithm with and without ToF. The images were then split into training (n = 208), validation (n = 15), and testing (n = 50) sets. Three DL-ToF models were trained to transform non-ToF BSREM images to their target ToF images with different levels of DL-ToF strength (low, medium, high). The models were objectively evaluated using the testing set based on standardised uptake value (SUV) in 139 identified lesions, and in normal regions of liver and lungs. Three radiologists subjectively rated the models using testing sets based on lesion detectability, diagnostic confidence, and image noise/quality. RESULTS: The non-ToF, DL-ToF low, medium, and high methods resulted in - 28 ± 18, - 28 ± 19, - 8 ± 22, and 1.7 ± 24% differences (mean; SD) in the SUVmax for the lesions in testing set, compared to ToF-BSREM image. In background lung VOIs, the SUVmean differences were 7 ± 15, 0.6 ± 12, 1 ± 13, and 1 ± 11% respectively. In normal liver, SUVmean differences were 4 ± 5, 0.7 ± 4, 0.8 ± 4, and 0.1 ± 4%. Visual inspection showed that our DL-ToF improved feature sharpness and convergence towards ToF reconstruction. Blinded clinical readings of testing sets for diagnostic confidence (scale 0-5) showed that non-ToF, DL-ToF low, medium, and high, and ToF images scored 3.0, 3.0, 4.1, 3.8, and 3.5 respectively. For this set of images, DL-ToF medium therefore scored highest for diagnostic confidence. CONCLUSION: Deep learning-based image enhancement models may provide converged ToF-equivalent image quality without ToF reconstruction. In clinical scoring DL-ToF-enhanced non-ToF images (medium and high) on average scored as high as, or higher than, ToF images. The model is generalisable and hence, could be applied to non-ToF images from BGO-based PET/CT scanners.

Effects of Respiratory Motion on Y-90 PET Dosimetry for SIRT.

Respiratory motion degrades the quantification accuracy of PET imaging by blurring the radioactivity distribution. In the case of post-SIRT PET-CT verification imaging, respiratory motion can lead to inaccuracies in dosimetric measures. Using an anthropomorphic phantom filled with 90Y at a range of clinically relevant activities, together with a respiratory motion platform performing realistic motions (10-15 mm amplitude), we assessed the impact of respiratory motion on PET-derived post-SIRT dosimetry. Two PET scanners at two sites were included in the assessment. The phantom experiments showed that device-driven quiescent period respiratory motion correction improved the accuracy of the quantification with statistically significant increases in both the mean contrast recovery (+5%, p = 0.003) and the threshold activities corresponding to the dose to 80% of the volume of interest (+6%, p < 0.001). Although quiescent period gating also reduces the number of counts and hence increases the noise in the PET image, its use is encouraged where accurate quantification of the above metrics is desired.

Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise.

PURPOSE: To enhance the image quality of oncology [18F]-FDG PET scans acquired in shorter times and reconstructed by faster algorithms using deep neural networks. METHODS: List-mode data from 277 [18F]-FDG PET/CT scans, from six centres using GE Discovery PET/CT scanners, were split into ¾-, ½- and »-duration scans. Full-duration datasets were reconstructed using the convergent block sequential regularised expectation maximisation (BSREM) algorithm. Short-duration datasets were reconstructed with the faster OSEM algorithm. The 277 examinations were divided into training (n = 237), validation (n = 15) and testing (n = 25) sets. Three deep learning enhancement (DLE) models were trained to map full and partial-duration OSEM images into their target full-duration BSREM images. In addition to standardised uptake value (SUV) evaluations in lesions, liver and lungs, two experienced radiologists scored the quality of testing set images and BSREM in a blinded clinical reading (175 series). RESULTS: OSEM reconstructions demonstrated up to 22% difference in lesion SUVmax, for different scan durations, compared to full-duration BSREM. Application of the DLE models reduced this difference significantly for full-, ¾- and ½-duration scans, while simultaneously reducing the noise in the liver. The clinical reading showed that the standard DLE model with full- or ¾-duration scans provided an image quality substantially comparable to full-duration scans with BSREM reconstruction, yet in a shorter reconstruction time. CONCLUSION: Deep learning-based image enhancement models may allow a reduction in scan time (or injected activity) by up to 50%, and can decrease reconstruction time to a third, while maintaining image quality.

Advances in PET/CT Technology: An Update.

This article reviews the current evolution and future directions in PET/CT technology focusing on three areas: time of flight, image reconstruction, and data-driven gating. Image reconstruction is considered with advances in point spread function modelling, Bayesian penalised likelihood reconstruction, and artificial intelligence approaches. Data-driven gating is examined with reference to respiratory motion, cardiac motion, and head motion. For each of these technological advancements, theory will be briefly discussed, benefits of their use in routine practice will be detailed and potential future developments will be discussed. Representative clinical cases will be presented, demonstrating the huge opportunities given to the PET community by hardware and software advances in PET technology when it comes to lesion detection, disease characterization, accurate quantitation and quicker scans. Through this review, hospitals are encouraged to embrace, evaluate and appropriately implement the wide range of new PET technologies that are available now or in the near future, for the improvement of patient care.

Data-Driven Respiratory Gating Outperforms Device-Based Gating for Clinical 18F-FDG PET/CT.

A data-driven method for respiratory gating in PET has recently been commercially developed. We sought to compare the performance of the algorithm with an external, device-based system for oncologic 18F-FDG PET/CT imaging. Methods: In total, 144 whole-body 18F-FDG PET/CT examinations were acquired, with a respiratory gating waveform recorded by an external, device-based respiratory gating system. In each examination, 2 of the bed positions covering the liver and lung bases were acquired with a duration of 6 min. Quiescent-period gating retaining approximately 50% of coincidences was then able to produce images with an effective duration of 3 min for these 2 bed positions, matching the other bed positions. For each examination, 4 reconstructions were performed and compared: data-driven gating (DDG) (we use the term DDG-retro to distinguish that we did not use the real-time R-threshold-based application of DDG that is available within the manufacturer's product), external device-based gating (real-time position management (RPM)-gated), no gating but using only the first 3 min of data (ungated-matched), and no gating retaining all coincidences (ungated-full). Lesions in the images were quantified and image quality scored by a radiologist who was masked to the method of data processing. Results: Compared with the other reconstruction options, DDG-retro increased the SUVmax and decreased the threshold-defined lesion volume. Compared with RPM-gated, DDG-retro gave an average increase in SUVmax of 0.66 ± 0.1 g/mL (n = 87, P < 0.0005). Although the results from the masked image evaluation were most commonly equivalent, DDG-retro was preferred over RPM-gated in 13% of examinations, whereas the opposite occurred in just 2% of examinations. This was a significant preference for DDG-retro (P = 0.008, n = 121). Liver lesions were identified in 23 examinations. Considering this subset of data, DDG-retro was ranked superior to ungated-full in 6 of 23 (26%) cases. Gated reconstruction using the external device failed in 16% of examinations, whereas DDG-retro always provided a clinically acceptable image. Conclusion: In this clinical evaluation, DDG-retro provided performance superior to that of the external device-based system. For most examinations the performance was equivalent, but DDG-retro had superior performance in 13% of examinations, leading to a significant preference overall.

An interbacterial toxin inhibits target cell growth by synthesizing (p)ppApp.

Bacteria have evolved sophisticated mechanisms to inhibit the growth of competitors1. One such mechanism involves type VI secretion systems, which bacteria can use to inject antibacterial toxins directly into neighbouring cells. Many of these toxins target the integrity of the cell envelope, but the full range of growth inhibitory mechanisms remains unknown2. Here we identify a type VI secretion effector, Tas1, in the opportunistic pathogen Pseudomonas aeruginosa. The crystal structure of Tas1 shows that it is similar to enzymes that synthesize (p)ppGpp, a broadly conserved signalling molecule in bacteria that modulates cell growth rate, particularly in response to nutritional stress3. However, Tas1 does not synthesize (p)ppGpp; instead, it pyrophosphorylates adenosine nucleotides to produce (p)ppApp at rates of nearly 180,000 molecules per minute. Consequently, the delivery of Tas1 into competitor cells drives rapid accumulation of (p)ppApp, depletion of ATP, and widespread dysregulation of essential metabolic pathways, thereby resulting in target cell death. Our findings reveal a previously undescribed mechanism for interbacterial antagonism and demonstrate a physiological role for the metabolite (p)ppApp in bacteria.

Evaluation of data-driven respiratory gating waveforms for clinical PET imaging.

BACKGROUND: We aimed to evaluate the clinical robustness of a commercially developed data-driven respiratory gating algorithm based on principal component analysis, for use in routine PET imaging. METHODS: One hundred fifty-seven adult FDG PET examinations comprising a total of 1149 acquired bed positions were used for the assessment. These data are representative of FDG scans currently performed at our institution. Data were acquired for 4 min/bed position (3 min/bed for legs). The data-driven gating (DDG) algorithm was applied to each bed position, including those where minimal respiratory motion was expected. The algorithm provided a signal-to-noise measure of respiratory-like frequencies within the data, denoted as R. Qualitative evaluation was performed by visual examination of the waveforms, with each waveform scored on a 3-point scale by two readers and then averaged (score S of 0 = no respiratory signal, 1 = some respiratory-like signal but indeterminate, 2 = acceptable signal considered to be respiratory). Images were reconstructed using quiescent period gating and compared with non-gated images reconstructed with a matched number of coincidences. If present, the SUVmax of a well-defined lesion in the thorax or abdomen was measured and compared between the two reconstructions. RESULTS: There was a strong (r = 0.86) and significant correlation between R and scores S. Eighty-six percent of waveforms with R ≥ 15 were scored as acceptable for respiratory gating. On average, there were 1.2 bed positions per patient examination with R ≥ 15. Waveforms with high R and S were found to originate from bed positions corresponding to the thorax and abdomen: 90% of waveforms with R ≥ 15 had bed centres in the range 5.6 cm superior to 27 cm inferior from the dome of the liver. For regions where respiratory motion was expected to be minimal, R tended to be < 6 and S tended to be 0. The use of DDG significantly increased the SUVmax of focal lesions, by an average of 11% when considering lesions in bed positions with R ≥ 15. CONCLUSIONS: The majority of waveforms with high R corresponded to the part of the patient where respiratory motion was expected. The waveforms were deemed suitable for respiratory gating when assessed visually, and when used were found to increase SUVmax in focal lesions.

Single Inflammatory Trigger Leads to Neuroinflammation in LRRK2 Rodent Model without Degeneration of Dopaminergic Neurons.

BACKGROUND: Leucine-rich repeat kinase 2 (LRRK2) mutations are the most common genetic risk factor for Parkinson's disease (PD). While the corresponding pathogenic mechanisms remain largely unknown, LRRK2 has been implicated in the immune system. OBJECTIVE: To assess whether LRRK2 mutations alter the sensitivity to a single peripheral inflammatory trigger, with ultimate impact on dopaminergic integrity, using a longitudinal imaging-based study design. METHODS: Rats carrying LRRK2 p.G2019S and non-transgenic (NT) littermates were treated peripherally with lipopolysaccharide (LPS). They were monitored over 10 months with PET markers for neuroinflammation and dopaminergic integrity, and with behavioral testing. Tyrosine hydroxylase and CD68 expression were assessed postmortem, 12 months after LPS treatment, in the striatum and substantia nigra. RESULTS: Longitudinal [11C]PBR28 PET imaging revealed that LPS treatment caused inflammation in the brain, increasing over time, as compared to saline (corrected p = 0.008). LPS treated LRRK2 animals exhibited significantly increased neuroinflammation in the cortex and ventral-regions compared to saline treated animals (LRRK2 and NT) at 10 months post treatment, with the increase in [11C]PBR28 binding from baseline averaging 0.128±0.045 g/mL. For LPS treated NT animals, the increase was not significant. CD68 immunohistochemistry data supported the imaging results, but without reaching statistical significance. No dopaminergic degeneration was observed. CONCLUSION: A single peripheral inflammatory trigger elicited long lasting, progressive neuroinflammation. A trend for an exacerbated inflammatory response in LRRK2 animals compared to NT controls was observed. Translationally, this implies that repeated exposure to inflammatory triggers may be needed for LRRK2 mutation carriers to develop active PD.

Evaluation of principal component analysis-based data-driven respiratory gating for positron emission tomography.

OBJECTIVE: Respiratory motion can degrade PET image quality and lead to inaccurate quantification of lesion uptake. Such motion can be mitigated via respiratory gating. Our objective was to evaluate a data-driven gating (DDG) technique that is being developed commercially for clinical PET/CT. METHODS: A data-driven respiratory gating algorithm based on principal component analysis (PCA) was applied to phantom and FDG patient data. An anthropomorphic phantom and a NEMA IEC Body phantom were filled with 18F, placed on a respiratory motion platform, and imaged using a PET/CT scanner. Motion waveforms were measured using an infrared camera [the Real-time Position Management™ system (RPM)] and also extracted from the PET data using the DDG algorithm. The waveforms were compared via calculation of Pearson's correlation coefficients. PET data were reconstructed using quiescent period gating (QPG) and compared via measurement of recovery percentage and background variability. RESULTS: Data-driven gating had similar performance to the external gating system, with correlation coefficients in excess of 0.97. Phantom and patient images were visually clearer with improved contrast when QPG was applied as compared to no motion compensation. Recovery coefficients in the phantoms were not significantly different between DDG- and RPM-based QPG, but were significantly higher than those found for no motion compensation (p < 0.05). CONCLUSION: A PCA-based DDG algorithm was evaluated and found to provide a reliable respiratory gating signal in anthropomorphic phantom studies and in example patients. Advances in knowledge: The prototype commercial DDG algorithm may enable reliable respiratory gating in routine clinical PET-CT.

Phantom and clinical evaluation of the effect of full Monte Carlo collimator modelling in post-SIRT yttrium-90 Bremsstrahlung SPECT imaging.

BACKGROUND: Post-therapy SPECT/CT imaging of 90Y microspheres delivered to hepatic malignancies is difficult, owing to the continuous, high-energy Bremsstrahlung spectrum emitted by 90Y. This study aimed to evaluate the utility of a commercially available software package (HybridRecon, Hermes Medical Solutions AB) which incorporates full Monte Carlo collimator modelling. Analysis of image quality was performed on both phantom and clinical images in order to ultimately provide a recommendation of an optimum reconstruction for post-therapy 90Y microsphere SPECT/CT imaging. A 3D-printed anthropomorphic liver phantom was filled with 90Y with a sphere-to-background ratio of 4:1 and imaged on a GE Discovery 670 SPECT/CT camera. Datasets were reconstructed using ordered-subsets expectation maximization (OSEM) 1-7 iterations in order to identify the optimal OSEM reconstruction (5 iterations, 15 subsets). Quantitative analysis was subsequently carried out on phantom datasets obtained using four reconstruction algorithms: the default OSEM protocol (2 iterations, 10 subsets) and the optimised OSEM protocol, both with and without full Monte Carlo collimator modelling. The quantitative metrics contrast recovery (CR) and background variability (BV) were calculated. The four algorithms were then used to retrospectively reconstruct 10 selective internal radiation therapy (SIRT) patient datasets which were subsequently blind scored for image quality by a consultant radiologist. RESULTS: The optimised OSEM reconstruction (5 iterations, 15 subsets with full MC collimator modelling) increased the CR by 42% (p < 0.001) compared to the default OSEM protocol (2 iterations, 10 subsets). The use of full Monte Carlo collimator modelling was shown to further improve CR by 14% (30 mm sphere, CR = 90%, p < 0.05). The consultant radiologist had a significant preference for the optimised OSEM over the default OSEM protocol (p < 0.001), with the optimised OSEM being the favoured reconstruction in every one of the 10 clinical cases presented. CONCLUSIONS: OSEM (5 iterations, 15 subsets) with full Monte Carlo collimator modelling is quantitatively the optimal image reconstruction for post-SIRT 90Y Bremsstrahlung SPECT/CT imaging. The use of full Monte Carlo collimator modelling for correction of image-degrading effects significantly increases contrast recovery without degrading clinical image quality.

[11C]PBR28 PET imaging is sensitive to neuroinflammation in the aged rat.

Neuroinflammation in the aging rat brain was investigated using [(11)C]PBR28 microPET (positron emission tomography) imaging. Normal rats were studied alongside LRRK2 p.G2019S transgenic rats; this mutation increases the risk of Parkinson's disease in humans. Seventy [(11)C]PBR28 PET scans were acquired. Arterial blood sampling enabled tracer kinetic modeling and estimation of VT. In vitro autoradiography was also performed. PBR28 uptake increased with age, without differences between nontransgenic and transgenic rats. In 12 months of aging (4 to 16 months), standard uptake value (SUV) increased by 56% from 0.44 to 0.69 g/mL, whereas VT increased by 91% from 30 to 57 mL/cm(3). Standard uptake value and VT were strongly correlated (r = 0.52, 95% confidence interval (CI) = 0.31 to 0.69, n = 37). The plasma free fraction, fp, was 0.21 ± 0.03 (mean ± standard deviation, n = 53). In vitro binding increased by 19% in 16 months of aging (4 to 20 months). The SUV was less variable across rats than VT; coefficients of variation were 13% (n = 27) and 29% (n = 12). The intraclass correlation coefficient for SUV was 0.53, but was effectively zero for VT. These data show that [(11)C]PBR28 brain uptake increases with age, implying increased microglial activation in the aged brain.

Commentary: an eye on PET quantification.

Positron emission tomography (PET) is generally considered to be a quantitative imaging modality, allowing assessment of regional differences in radiotracer accumulation and the derivation of quantitative physiological information. Due to the increasing complexity of PET technology, the quantitative accuracy of PET images has to be continually reassessed if PET is to maintain its quantitative reputation. In this commentary, we discuss the results from a recent inter-scanner study in which the quantitative outcome measures from human studies were compared for three different radiotracers. The approach is a useful complement to standard phantom tests such as those prescribed by NEMA, but the resulting data are more difficult to interpret.

The discovery of I-BET726 (GSK1324726A), a potent tetrahydroquinoline ApoA1 up-regulator and selective BET bromodomain inhibitor.

Through their function as epigenetic readers of the histone code, the BET family of bromodomain-containing proteins regulate expression of multiple genes of therapeutic relevance, including those involved in tumor cell growth and inflammation. BET bromodomain inhibitors have profound antiproliferative and anti-inflammatory effects which translate into efficacy in oncology and inflammation models, and the first compounds have now progressed into clinical trials. The exciting biology of the BETs has led to great interest in the discovery of novel inhibitor classes. Here we describe the identification of a novel tetrahydroquinoline series through up-regulation of apolipoprotein A1 and the optimization into potent compounds active in murine models of septic shock and neuroblastoma. At the molecular level, these effects are produced by inhibition of BET bromodomains. X-ray crystallography reveals the interactions explaining the structure-activity relationships of binding. The resulting lead molecule, I-BET726, represents a new, potent, and selective class of tetrahydroquinoline-based BET inhibitors.

Behavioral deficits and striatal DA signaling in LRRK2 p.G2019S transgenic rats: a multimodal investigation including PET neuroimaging.

BACKGROUND: A major risk-factor for developing Parkinson's disease (PD) is genetic variability in leucine-rich repeat kinase 2 (LRRK2), most notably the p.G2019S mutation. Examination of the effects of this mutation is necessary to determine the etiology of PD and to guide therapeutic development. OBJECTIVE: Assess the behavioral consequences of LRRK2 p.G2019S overexpression in transgenic rats as they age and test the functional integrity of the nigro-striatal dopamine system. Conduct positron emission tomography (PET) neuroimaging to compare transgenic rats with previous data from human LRRK2 mutation carriers. METHODS: Rats overexpressing human LRRK2 p.G2019S were generated by BAC transgenesis and compared to non-transgenic (NT) littermates. Motor skill tests were performed at 3, 6 and 12 months-of-age. PET, performed at 12 months, assessed the density of dopamine and vesicular monoamine transporters (DAT and VMAT2, respectively) and measured dopamine synthesis, storage and availability. Brain tissue was assayed for D2, DAT, dopamine and cAMP-regulated phosphoprotein (DARPP32) and tyrosine hydroxylase (TH) expression by Western blot, and TH by immunohistochemistry. RESULTS: Transgenic rats had no abnormalities in measures of striatal dopamine function at 12 months. A behavioral phenotype was present, with LRRK2 p.G2019S rats performing significantly worse on the rotarod than non-transgenic littermates (26% reduction in average running duration at 6 months), but with normal performance in other motor tests. CONCLUSIONS: Neuroimaging using dopaminergic PET did not recapitulate prior studies in human LRRK2 mutation carriers. Consistently, LRRK2 p.G2019S rats do not develop overt neurodegeneration; however, they do exhibit behavioral abnormalities.

Performance assessment of a preclinical PET scanner with pinhole collimation by comparison to a coincidence-based small-animal PET scanner.

UNLABELLED: PET imaging of rodents is increasingly used in preclinical research, but its utility is limited by spatial resolution and signal-to-noise ratio of the images. A recently developed preclinical PET system uses a clustered-pinhole collimator, enabling high-resolution, simultaneous imaging of PET and SPECT tracers. Pinhole collimation strongly departs from traditional electronic collimation achieved via coincidence detection in PET. We investigated the potential of such a design by direct comparison to a traditional PET scanner. METHODS: Two small-animal PET scanners, 1 with electronic collimation and 1 with physical collimation using clustered pinholes, were used to acquire data from Jaszczak (hot rod) and uniform phantoms. Mouse brain imaging using (18)F-FDG PET was performed on each system and compared with quantitative ex vivo autoradiography as a gold standard. Bone imaging using (18)F-NaF allowed comparison of imaging in the mouse body. Images were visually and quantitatively compared using measures of contrast and noise. RESULTS: Pinhole PET resolved the smallest rods (diameter, 0.85 mm) in the Jaszczak phantom, whereas the coincidence system resolved 1.1-mm-diameter rods. Contrast-to-noise ratios were better for pinhole PET when imaging small rods (<1.1 mm) for a wide range of activity levels, but this reversed for larger rods. Image uniformity on the coincidence system (<3%) was superior to that on the pinhole system (5%). The high (18)F-FDG uptake in the striatum of the mouse brain was fully resolved using the pinhole system, with contrast to nearby regions equaling that from autoradiography; a lower contrast was found using the coincidence PET system. For short-duration images (low-count), the coincidence system was superior. CONCLUSION: In the cases for which small regions need to be resolved in scans with reasonably high activity or reasonably long scan times, a first-generation clustered-pinhole system can provide image quality in terms of resolution, contrast, and the contrast-to-noise ratio superior to a traditional PET system.

Measuring dopaminergic function in the 6-OHDA-lesioned rat: a comparison of PET and microdialysis.

BACKGROUND: [18 F]fluorodopa (FDOPA) positron emission tomography (PET) allows assessment of levodopa (LDOPA) metabolism and is widely used to study Parkinson's disease. We examined how [18 F]FDOPA PET-derived kinetic parameters relate the dopamine (DA) and DA metabolite content of extracellular fluid measured by microdialysis to aid in the interpretation of data from both techniques. METHODS: [18 F]FDOPA PET imaging and microdialysis measurements were performed in unilaterally 6-hydroxydopamine-lesioned rats (n = 8) and normal control rats (n = 3). Microdialysis testing included baseline measurements and measurements following acute administration of LDOPA. PET imaging was also performed using [11C]dihydrotetrabenazine (DTBZ), which is a ligand for the vesicular monoamine transporter marker and allowed assessment of denervation severity. RESULTS: The different methods provided highly correlated data. Lesioned rats had reduced DA metabolite concentrations ipsilateral to the lesion (p < 0.05 compared to controls), with the concentration being correlated with FDOPA's effective distribution volume ratio (EDVR; r = 0.86, p < 0.01) and DTBZ's binding potential (BPND; r = 0.89, p < 0.01). The DA metabolite concentration in the contralateral striatum of severely (>80%) lesioned rats was lower (p < 0.05) than that of less severely lesioned rats (<80%) and was correlated with the ipsilateral PET measures (r = 0.89, p < 0.01 for BPND) but not with the contralateral PET measures. EDVR and BPND in the contralateral striatum were not different from controls and were not correlated with the denervation severity. CONCLUSIONS: The demonstrated strong correlations between the PET and microdialysis measures can aid in the interpretation of [18 F]FDOPA-derived kinetic parameters and help compare results from different studies. The contralateral striatum was affected by the lesioning and so cannot always serve as an unaffected control.

In-vivo measurement of LDOPA uptake, dopamine reserve and turnover in the rat brain using [18F]FDOPA PET.

Longitudinal measurements of dopamine (DA) uptake and turnover in transgenic rodents may be critical when developing disease-modifying therapies for Parkinson's disease (PD). We demonstrate methodology for such measurements using [(18)F]fluoro-3,4-dihydroxyphenyl-L-alanine ([(18)F]FDOPA) positron emission tomography (PET). The method was applied to 6-hydroxydopamine lesioned rats, providing the first PET-derived estimates of DA turnover for this species. Control (n=4) and unilaterally lesioned (n=11) rats were imaged multiple times. Kinetic modeling was performed using extended Patlak, incorporating a k(loss) term for metabolite washout, and modified Logan methods. Dopaminergic terminal loss was measured via [(11)C]-(+)-dihydrotetrabenazine (DTBZ) PET. Clear striatal [(18)F]FDOPA uptake was observed. In the lesioned striatum the effective DA turnover increased, shown by a reduced effective distribution volume ratio (EDVR) for [(18)F]FDOPA. Effective distribution volume ratio correlated (r>0.9) with the [(11)C]DTBZ binding potential (BP(ND)). The uptake and trapping rate (k(ref)) decreased after lesioning, but relatively less so than [(11)C]DTBZ BP(ND). For normal controls, striatal estimates were k(ref)=0.037±0.005 per minute, EDVR=1.07±0.22 and k(loss)=0.024±0.003 per minute (30 minutes turnover half-time), with repeatability (coefficient of variation) ≤11%. [(18)F]fluoro-3,4-dihydroxyphenyl-L-alanine PET enables measurements of DA turnover in the rat, which is useful for developing novel therapies for PD.