Spillover Ratio Research Articles

Animal PET scanner with a large field of view is suitable for high-throughput scanning of rodents.

In preclinical studies, high-throughput positron emission tomography (PET) imaging, known as simultaneous multiple animal scanning, can reduce the time spent on animal experiments, the cost of PET tracers, and the risk of synthesis of PET tracers. It is well known that the image quality acquired by high-throughput imaging depends on the PET system. Herein, we investigated the influence of large field of view (FOV) PET scanner on high-throughput imaging. We investigated the influence of scanning four objects using a small animal PET scanner with a large FOV. We compared the image quality acquired by four objects scanned with the one acquired by one object scanned using phantoms and animals. We assessed the image quality with uniformity, recovery coefficient (RC), and spillover ratio (SOR), which are indicators of image noise, spatial resolution, and quantitative precision, respectively. For the phantom study, we used the NEMA NU 4-2008 image quality phantom and evaluated uniformity, RC, and SOR, and for the animal study, we used Wistar rats and evaluated the spillover in the heart and kidney. In the phantom study, four phantoms had little effect on imaging quality, especially SOR compared with that for one phantom. In the animal study as well, four rats had little effect on spillover from the heart muscle and kidney cortex compared with that for one rat. This study demonstrated that an animal PET scanner with a large FOV was suitable for high-throughput imaging. Thus, the large FOV PET scanner can support drug discovery and bridging research through rapid pharmacological and pathological evaluation.

Image quality evaluation for a clinical organ-targeted PET camera.

A newly developed clinical organ-targeted Positron Emission Tomography (PET) system (also known as Radialis PET) is tested with a set of standardized and custom tests previously used to evaluate the performance of Positron Emission Mammography (PEM) systems. Imaging characteristics impacting standardized uptake value (SUV) and detectability of small lesions, namely spatial resolution, linearity, uniformity, and recovery coefficients, are evaluated. In-plane spatial resolution was measured as 2.3 mm ± 0.1 mm, spatial accuracy was 0.1 mm, and uniformity measured with flood field and NEMA NU-4 phantom was 11.7% and 8.3% respectively. Selected clinical images are provided as reference to the imaging capabilities under different clinical conditions such as reduced activity of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (18F-FDG) and time-delayed acquisitions. SUV measurements were performed for selected clinical acquisitions to demonstrate a capability for quantitative image assessment of different types of cancer including for invasive lobular carcinoma with comparatively low metabolic activity. Quantitative imaging performance assessment with phantoms demonstrates improved contrast recovery and spill-over ratio for this PET technology when compared to other commercial organ-dedicated PET systems with similar spatial resolution. Recovery coefficients were measured to be 0.21 for the 1 mm hot rod and up to 0.89 for the 5 mm hot rod of NEMA NU-4 Image Quality phantom. Demonstrated ability to accurately reconstruct activity in tumors as small as 5 mm suggests that the Radialis PET technology may be well suited for emerging clinical applications such as image guided assessment of response to neoadjuvant systemic treatment (NST) in lesions smaller than 2 cm. Also, our results suggest that, while spatial resolution greatly influences the partial volume effect which degrades contrast recovery, optimized count rate performance and image reconstruction workflow may improve recovery coefficients for systems with comparable spatial resolution. We emphasize that recovery coefficient should be considered as a primary performance metric when a PET system is used for accurate lesion size or radiotracer uptake assessments.

Comparative analysis of image quality parameters and spatial resolution of three Small Animal PET scanner in Brazil

This study evaluated Image Quality (IQ) parameters and spatial resolution (SR) of Triumph® LabPET systems installed in three different Brazilian preclinical molecular imaging centers. A comprehensive evaluation of the PET scanner intrinsic parameters is important to optimize the acquired images, providing more reliable qualitative and quantitative analyses. Experiments were carried out at the centers: C1 - Molecular Imaging Laboratory of the CDTN/CNEN; C2 - Laboratory of Nuclear Medicine of HCFMUSP; C3 - Preclinical Research Center of the Brain Institute at PUC-RS. IQ phantom PET images were acquired as recommended in NEMA NU 4-2008 standard. Image reconstructions were performed in each system using the same reconstruction protocol. Data was processed using PMOD® software. The IQ parameters: (i) uniformity, (ii) spill-over ratio (SOR) and (iii) recovery coefficients (RC) were evaluated and compared. For Uniformity test, the percentage standard deviations of mean activity concentration were 7.8%; 7.3% and 6.4% for Centers 1, 2 and 3 respectively. Cold chambers RSO values in the systems 1, 2 and 3 were respectively 0.16, 0.19 and 0.21 for water; 0.26; 0.28 and 0.30 for air. The RC’s for rod diameters from 1 to 5 mm ranged from 0.08 to 0.91 for the three centers. Results revealed that the three PET systems have appropriate quality parameters for pre-clinical studies, presenting values compatible with international standards. This study was able to reveals the performance of preclinical PET system of different Brazilian imaging centers and may support the standardization of a National Quality Control Program for Small Animal PET scanners.

Residual 3D convolutional neural network to enhance sinograms from small-animal positron emission tomography images

Positron emission tomography (PET) has been widely used in nuclear medicine to diagnose cancer. PET images suffer from degradation because of the scanner's physical limitations, the radiotracer's reduced dose, and the acquisition time. In this work, we propose a residual three-dimensional (3D) and convolutional neural network (CNN) to enhance sinograms acquired from a small-animal PET scanner. The network comprises three convolutional layers created with 3D filters of sizes 9, 5, and 5, respectively. For training, we extracted 15250 3D patches from low- and high-count sinograms to build the low- and high-resolution pairs. After training and prediction, the image was reconstructed from the enhanced sinogram using the ordered subset expectation maximization (OSEM) algorithm. The results revealed that the proposed network improves the spillover ratio by up to 4.5% and the uniformity by 55% compared to the U-Net. The NEMA phantom data were obtained in a simulation environment. The network was tested on acquired real data from a mouse. The reconstructed images and the profiles of maximum intensity projection show that the proposed method visually yields sharper images.2023 Elsevier Ltd. All rights reserved.

Performance evaluation of SimPET-L and SimPET-XL: MRI-compatible small-animal PET systems with rat-body imaging capability

BackgroundSimPET-L and SimPET-XL have recently been introduced with increased transaxial fields of view (FOV) compared with their predecessors (SimPET™ and SimPET-X), enabling whole-body positron emission tomography (PET) imaging of rats. We conducted performance evaluations of SimPET-L and SimPET-XL and rat-body imaging with SimPET-XL to demonstrate the benefits of increased axial and transaxial FOVs.ProceduresThe detector blocks in SimPET-L and SimPET-XL consist of two 4 × 4 silicon photomultiplier arrays coupled with 20 × 9 array lutetium oxyorthosilicate crystals. SimPET-L and SimPET-XL have an inner diameter (bore size) of 7.6 cm, and they are composed of 40 and 80 detector blocks yielding axial lengths of 5.5 and 11 cm, respectively. Each system was evaluated according to the National Electrical Manufacturers Association NU4-2008 protocol. Rat imaging studies, such as 18F-NaF and 18F-FDG PET, were performed using SimPET-XL.ResultsThe radial resolutions at the axial center measured using the filtered back projection, 3D ordered-subset expectation maximization (OSEM), and 3D OSEM with point spread functions correction were 1.7, 0.82, and 0.82 mm FWHM in SimPET-L and 1.7, 0.91, and 0.91 mm FWHM in SimPET-XL, respectively. The peak sensitivities of SimPET-L and SimPET-XL were 6.30% and 10.4% for an energy window of 100–900 keV and 4.44% and 7.25% for a window of 250–750 keV, respectively. The peak noise equivalent count rate with an energy window of 250–750 keV was 249 kcps at 44.9 MBq for SimPET-L and 349 kcps at 31.3 MBq for SimPET-XL. In SimPET-L, the uniformity was 4.43%, and the spill-over ratios in air- and water-filled chambers were 5.54% and 4.10%, respectively. In SimPET-XL, the uniformity was 3.89%, and the spill-over ratio in the air- and water-filled chambers were 3.56% and 3.60%. Moreover, SimPET-XL provided high-quality images of rats.ConclusionSimPET-L and SimPET-XL show adequate performance compared with other SimPET systems. In addition, their large transaxial and long axial FOVs provide imaging capability for rats with high image quality.

DH-Mammo PET: a dual-head positron emission mammography system for breast imaging

Objective. To develop a simultaneous positron emission tomography-Optical (OPET) breast imaging dual-head PET subsystem, called DH-Mammo PET, for accurate, early diagnosis and efficacy assessment of breast cancer with high resolution and sensitivity. Approach. We developed a breast-dedicated PET based on LYSO crystal, silicon photomultiplier array and multi-voltage threshold sampling technique. It consists of two detector heads, each with a detection area of 216 mm × 145.5 mm. The distance between the detector heads is fixed at 120 mm. In order to extract coincidences and correct data, GPU-based software coincidence processing, random, scatter, normalization, gap-filling and attenuation corrections were applied in turn. The images were reconstructed using maximum likelihood expectation maximization with depth of interaction (DOI) modeling. The performance of DH-Mammo PET was evaluated referring to NEMA NU 4–2008, NU 2–2007 and Chinese industry recommended standard YY/T 1835–2022. Besides, several clinical patient images of DH-Mammo PET were compared with those of a whole-body PET/CT. Main results. The energy resolution was 14.5%, and time resolution was < 1.31 ns. Indicated by the 22Na point source imaging, its spatial resolution was 2.60 mm (5.40 mm), 1.00 mm (1.04 mm), and 0.96 mm (0.93 mm) in the X, Y and Z directions, respectively, using the system response matrix with (without) DOI modeling. Indicated by the Derenzo phantom imaging, the spatial resolution was ∼3.0 mm, <1.2 mm, and <1.2 mm in the X, Y and Z directions. The system sensitivity was 6.87%, 4.89% and 3.37% with an energy window of 100–800, 250–750 and 350–650 keV, respectively. The scatter fraction was 26.43%, and the peak NECR was 162.6 kcps at 24.1 MBq for the modified rat-like phantom. As for the recovery coefficients, they ranged from 0.15 to 1.04 for rods between 1 and 5 mm obtained with a NEMA image quality phantom. The spill-over ratio for the air-filled and water-filled chamber was 0.05 and 0.11, respectively. DH-Mammo PET can provide more image details in clinical experiments and fulfil a fast scan with 60–120 s acquisition time. Significance. Good spatial resolution and high sensitivity of DH-Mammo PET would enable fast and accurate PET imaging of the breast. Besides, combining the DH-Mammo PET with the diffuse optical tomography would make full use of tumor metabolic imaging and tissue endogenous optical imaging, which would improve the accuracy of early clinical diagnosis of small lesions of breast cancers.

Feasibility of positron range correction in 82-Rubidium cardiac PET/CT

BackgroundMyocardial perfusion imaging (MPI) using positron emission tomography (PET) tracers is an essential tool in investigating diseases and treatment responses in cardiology. 82Rubidium (82Rb)-PET imaging is advantageous for MPI due to its short half-life, but cannot be used for small animal research due to the long positron range. We aimed to correct for this, enabling MPI with 82Rb-PET in rats.MethodsThe effect of positron range correction (PRC) on 82Rb-PET was examined using two phantoms and in vivo on rats. A NEMA NU-4-inspired phantom was used for image quality evaluation (%standard deviation (%SD), spillover ratio (SOR) and recovery coefficient (RC)). A cardiac phantom was used for assessing spatial resolution. Two rats underwent rest 82Rb-PET to optimize number of iterations, type of PRC and respiratory gating.ResultsNEMA NU-4 metrics (no PRC vs PRC): %SD 0.087 versus 0.103; SOR (air) 0.022 versus 0.002, SOR (water) 0.059 versus 0.019; RC (3 mm) 0.219 versus 0.584, RC (4 mm) 0.300 versus 0.874, RC (5 mm) 0.357 versus 1.197. Cardiac phantom full width at half maximum (FWHM) and full width at tenth maximum (FWTM) (no PRC vs. PRC): FWTM 6.73 mm versus 3.26 mm (true: 3 mm), FWTM 9.27 mm versus 7.01 mm. The in vivo scans with respiratory gating had a homogeneous myocardium clearly distinguishable from the blood pool.ConclusionPRC improved the spatial resolution for the phantoms and in vivo at the expense of slightly more noise. Combined with respiratory gating, the spatial resolution achieved using PRC should allow for quantitative MPI in small animals.

Performance Evaluation of a PET of 7T Bruker Micro-PET/MR Based on NEMA NU 4-2008 Standards

Purpose: This study aimed to measure the performance evaluation of the Bruker sequential micro-positron emission tomography/magnetic resonance imaging (PET/MRI) scanner by following National Electrical Manufacturers Association (NEMA) NU 4-2008 standards’ protocol. The system consists of a high-performance silicon photomultiplier (SiPM) advanced technology detector and a continuous lutetium-yttrium oxyorthosilicate (LYSO) crystal. Methods: A 22Na (sodium-22) point source was utilized to assess the spatial resolution and system sensitivity, and the Micro-PET scatter phantom measurements were conducted to measure count rate measurements and scatter fractions (SF). A mouse-like Micro-PET image quality (IQ) phantom was utilized as a model to analyze the uniformity, recovery coefficient (RC), and spillover ratio (SOR). A small animal PET/MRI imaging study was performed in a rat. Results: We calculated the spatial resolutions of filtered back-projection (FBP), and used 3D-MLEM to reconstruct PET images at the axial center and ¼ of the axial field of view (FOV) in axial, radial, and tangential directions. The best observed spatial resolutions in both reconstructed images were obtained in the tangential direction, and the values were 0.80 mm in 3D-MLEM and 0.94 mm in FBP. The peak noise equivalent count rate (NECR) in the 358–664 keV energy window was 477.30 kcps at 95.83 MBq and 774.45 kcps at 103.6 MBq for rat and mouse-sized scatter phantoms, respectively. The rat and mouse-sized phantoms scatter fractions (SF) were 14.2% and 6.9%, respectively. Conclusions: According to our results, the performance characteristics of the scanner are high sensitivity, good spatial resolution, low scatter fraction, and good IQ, indicating that it is suitable for preclinical imaging studies.

Reconstruction of Preclinical PET Images via Chebyshev Polynomial Approximation of the Sinogram

Over the last decades, there has been an increasing interest in dedicated preclinical imaging modalities for research in biomedicine. Especially in the case of positron emission tomography (PET), reconstructed images provide useful information of the morphology and function of an internal organ. PET data, stored as sinograms, involve the Radon transform of the image under investigation. The analytical approach to PET image reconstruction incorporates the derivative of the Hilbert transform of the sinogram. In this direction, in the present work we present a novel numerical algorithm for the inversion of the Radon transform based on Chebyshev polynomials of the first kind. By employing these polynomials, the computation of the derivative of the Hilbert transform of the sinogram is significantly simplified. Extending the mathematical setting of previous research based on Chebyshev polynomials, we are able to efficiently apply our new Chebyshev inversion scheme for the case of analytic preclinical PET image reconstruction. We evaluated our reconstruction algorithm on projection data from a small-animal image quality (IQ) simulated phantom study, in accordance with the NEMA NU 4-2008 standards protocol. In particular, we quantified our reconstructions via the image quality metrics of percentage standard deviation, recovery coefficient, and spill-over ratio. The projection data employed were acquired for three different Poisson noise levels: 100% (NL1), 50% (NL2), and 20% (NL3) of the total counts, respectively. In the uniform region of the IQ phantom, Chebyshev reconstructions were consistently improved over filtered backprojection (FBP), in terms of percentage standard deviation (up to 29% lower, depending on the noise level). For all rods, we measured the contrast-to-noise-ratio, indicating an improvement of up to 68% depending on the noise level. In order to compare our reconstruction method with FBP, at equal noise levels, plots of recovery coefficient and spill-over ratio as functions of the percentage standard deviation were generated, after smoothing the NL3 reconstructions with three different Gaussian filters. When post-smoothing was applied, Chebyshev demonstrated recovery coefficient values up to 14% and 42% higher, for rods 1–3 mm and 4–5 mm, respectively, compared to FBP, depending on the smoothing sigma values. Our results indicate that our Chebyshev-based analytic reconstruction method may provide PET reconstructions that are comparable to FBP, thus yielding a good alternative to standard analytic preclinical PET reconstruction methods.

Evaluation of the spline reconstruction technique for preclinical PET imaging

Background and ObjectiveThe Spline Reconstruction Technique (SRT) is a fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The purpose of this study is to provide a comparison between SRT, Filtered Back-Projection (FBP), Ordered Subset Expectation Maximization 2D (2D-OSEM), and the Tera-Tomo 3D algorithm, using phantom data at various acquisition durations as well as small-animal data obtained from the Mediso nanoScan® PET/CT scanner. MethodsFor this purpose, the “NEMA NU 4–2008 standards” protocol was employed at five different realizations and acquisition durations. In addition to the image quality metrics described by the NEMA protocol, Cold Region Contrast was also considered as a figure-of-merit. Furthermore, Cold Region Contrast was measured in the myocardial infarction region of six male Wistar rats. The volumetric defect quantification was assessed with dedicated computer software. Lastly, plots of Recovery Coefficient and Spill-Over Ratio as a function of the Percentage Standard Deviation were generated, after smoothing the phantom reconstructions with four different Gaussian filters. Statistical significance was determined by employing the Kruskal-Wallis test or One-way Analysis of Variance depending on the normality of the variable's distribution. ResultsThe present study revealed that, at the expense of slightly increased noise in the reconstructed images, SRT resulted in higher Recovery Coefficient values for small hot regions of interest, when compared with FBP and 2D-OSEM at all acquisition durations. Furthermore, SRT reconstructed images exhibit higher Recovery Coefficient values, for all hot regions of interest, when compared to the other 2D algorithms at short acquisition durations. In both phantom and animal studies, SRT achieved a significant improvement over 2D-OSEM for the Spill-Over Ratio and the Cold Region Contrast. These advantages were maintained even after comparing the algorithms at equal noise levels. The Tera-Tomo 3D algorithm (4 subsets, iterations≥ 13) performed significantly better compared to the other algorithms for all figures-of-merit. No statistically significant differences regarding the myocardial defect size were observed between the algorithms investigated. ConclusionsOverall, SRT appears that could be useful for the quantification of small hot regions of interest, cold regions of interest, as well as in low-count imaging applications.

Compensating Positron Range Effects of Ga-68 in Preclinical PET Imaging by Using Convolutional Neural Network: A Monte Carlo Simulation Study.

This study aimed to investigate the feasibility of positron range correction based on three different convolutional neural network (CNN) models in preclinical PET imaging of Ga-68. The first model (CNN1) was originally designed for super-resolution recovery, while the second model (CNN2) and the third model (CNN3) were originally designed for pseudo CT synthesis from MRI. A preclinical PET scanner and 30 phantom configurations were modeled in Monte Carlo simulations, where each phantom configuration was simulated twice, once for Ga-68 (CNN input images) and once for back-to-back 511-keV gamma rays (CNN output images) with a 20 min emission scan duration. The Euclidean distance was used as the loss function to minimize the difference between CNN input and output images. According to our results, CNN3 outperformed CNN1 and CNN2 qualitatively and quantitatively. With regard to qualitative observation, it was found that boundaries in Ga-68 images became sharper after correction. As for quantitative analysis, the recovery coefficient (RC) and spill-over ratio (SOR) were increased after correction, while no substantial increase in coefficient of variation of RC (CVRC) or coefficient of variation of SOR (CVSOR) was observed. Overall, CNN3 should be a good candidate architecture for positron range correction in Ga-68 preclinical PET imaging.

Influence of image reconstruction protocols on the image quality of a small animal PET scanner using 18F and 11C

The small animal positron emission tomography (PET) scanner from Molecular Imaging Laboratory (LIM/CDTN) is dedicated to pre-clinical studies on new 18F and 11C-based radiopharmaceuticals and to development of novel applications for well-known radiopharmaceuticals. Thus, quality control tests recommended by the publication NEMA NU 4-2008 are routinely carried out to ensure the proper performance of PET scanner. The aim of this work was to evaluate the influence of image reconstruction protocols on the image quality, accuracy of attenuation and scatter corrections parameters for 18F and 11C PET images. PET images of the image quality phantom filed with 18F-FDG or 11C-PK1122 were acquired and then reconstructed using different reconstruction protocols. The reconstruction variables evaluated were the algorithms (FBP, MLEM-3D, OSEM-3D), the resolution mode (high/standard) and the number of iterations (10 to 150). Uniformity, spill-over ratio (SOR) and recovery coefficients (RC) tests were performed for each reconstructed image according NEMA NU 4-2008. PMOD software was used for image analysis. FBP based protocol generated noisier images compared to iterative algorithms (MLEM-3D or OSEM-3D) based protocols. The increase in the number of iterations resulted in higher standard deviation of the analyzed parameters for all reconstructed images. MLEM-3D and OSEM-3D based protocols generates similar results when number of iterations and resolution mode were identical. SOR and RC mean values remained stable when the number of iterations ranged from 40 to 150. This study allowed the evaluation of different image reconstruction protocols on important parameters of 18F and 11C PET image quality. Additionally, standard image reconstruction protocols to be adopted in LIM/CDTN laboratorial routine for 18F and 11C images reconstruction in preclinical studies were defined.

Assessment of MicroPET Image Quality Based on Reconstruction Methods and Post-Filtering

The accuracy of positron emission tomography (PET) imaging is hampered by the partial volume effect (PVE), which causes image blurring and sampling. The PVE produces spillover phenomena, making PET analysis difficult. Generally, the PVE values vary based on reconstruction methods and filtering. Thus, selection of the proper reconstruction and filtering method can ensure accurate and high-quality PET images. This study compared the values of factors (recovery coefficient (RC), uniformity, and spillover ratio (SOR)) associated with different reconstruction and post-filtering methods using a mouse image quality phantom (NEMA NU 4), and we present an effective approach for microPET images. The PET images were obtained using a microPET scanner (Inveon, Siemens Medical Solutions, Malvern, PA, USA). PET data were reconstructed and/or post-filtered. For tumors smaller than 3 mm, iterative reconstruction methods provided better image quality. For tumor sizes bigger than 3 mm, reconstruction methods without post-filtering showed better results.

Avian cross-habitat spillover as a bidirectional process modulated by matrix type, forest cover and fragment size

Cross-habitat spillover (i.e. the movement of individuals between different habitat types) occurs very often in agricultural landscapes, following temporary crop resource pulses that work as complementary resources for biodiversity. We tested how avian spillover at edges of forest fragments is affected by the adjacent agricultural matrix contrast (sun coffee plantations or pastures), forest fragment size, and forest cover at the landscape scale. We performed paired mist netting at forest edges (forest/sun coffee plantations and forest/pastures; N = 24) and estimated the spillover ratio and the dissimilarity of birds moving in- and out- forest fragments. We found that avian spillover in highly fragmented landscapes is a bidirectional process regardless of species habitat association or feeding guild. Matrix type is a key driver of spillover, and most spillover occurred when the matrix is of less contrast (i.e. sun coffee plantations). Spillover ratio at coffee interfaces increased with forest cover and also with fragment size, meanwhile at pasture interfaces spillover only increased at high values of forest cover and fragment size. Finally, we found that the dissimilarity between bird species entering and leaving the fragments was higher in pasture matrices, while at coffee interfaces the dissimilarity was lower. Landscape management aimed at reducing the contrast between matrix and habitat, increasing habitat cover and maintaining large fragments can intensify spillover movements across natural and anthropogenic habitats, and potentially, promote more ecosystem service provision by those species that are performing spillover movements.

Quality control phantom using 3D-printing technology in a multi-modality system

In this paper, we proposed a design for a preclinical and clinical quality control (QC) phantom system and validated the performance of the multi-modality system. The QC phantom system can be easily built with complicated shapes using three-dimensional (3D)-printing technology. An Objet Eden 3D printer (Stratasys Ltd., USA) was used to fabricate a 3D multi-material phantom. The 3D-printed phantom composed of two main parts with QC disk units to support both X-ray imaging and nuclear imaging, which were imaged on a Inveon PET system (Siemens Medical Solutions, Knoxville, USA) and a micro-CT system (Nano Focus Ray co. Ltd. Polaris-G90, South Korea) scanner and reconstructed. The spillover ratio (SOR), non-uniformity, recover coefficients (RC) and spatial resolution were assessed using NEMA NU 4-2008 image quality phantom to compare the pixel-value statistics. Finally, the uniformity and the Hounsfield Units (HU) for computed tomography (CT) were assessed by examining a disk-type phantom. A custom phantom was created using a 3D printer. This phantom offered efficient control of the multi-modality system (CT/PET/SPECT) and was able to accommodate the flexibility of changing quality parameters for a multi-modality system by changing the QC disk in a standard manner. A further refinement of the phantom construction process is needed for routine use.

Evaluation of image quality with four positron emitters and three preclinical PET/CT systems

BackgroundWe investigated the image quality of 11C, 68Ga, 18F and 89Zr, which have different positron fractions, physical half-lifes and positron ranges. Three small animal positron emission tomography/computed tomography (PET/CT) systems were used in the evaluation, including the Siemens Inveon, RAYCAN X5 and Molecubes β-cube. The evaluation was performed on a single scanner level using the national electrical manufacturers association (NEMA) image quality phantom and analysis protocol. Acquisitions were performed with the standard NEMA protocol for 18F and using a radionuclide-specific acquisition time for 11C, 68Ga and 89Zr. Images were assessed using percent recovery coefficient (%RC), percentage standard deviation (%STD), image uniformity (%SD), spill-over ratio (SOR) and evaluation of image quantification.Results68Ga had the lowest %RC (< 62%) across all systems. 18F had the highest maximum %RC (> 85%) and lowest %STD for the 5 mm rod across all systems. For 11C and 89Zr, the maximum %RC was close (> 76%) to the %RC with 18F. A larger SOR were measured in water with 11C and 68Ga compared to 18F on all systems. SOR in air reflected image reconstruction and data correction performance. Large variation in image quantification was observed, with maximal errors of 22.73% (89Zr, Inveon), 17.54% (89Zr, RAYCAN) and − 14.87% (68Ga, Molecubes).ConclusionsThe systems performed most optimal in terms of NEMA image quality parameters when using 18F, where 11C and 89Zr performed slightly worse than 18F. The performance was least optimal when using 68Ga, due to large positron range. The large quantification differences prompt optimization not only by terms of image quality but also quantification. Further investigation should be performed to find an appropriate calibration and harmonization protocol and the evaluation should be conducted on a multi-scanner and multi-center level.

Image quality analysis of 44Sc on two preclinical PET scanners: a comparison to 68Ga

Background44Sc has been increasingly investigated as a potential alternative to 68Ga in the development of tracers for positron emission tomography (PET). The lower mean positron energy of 44Sc (0.63 MeV) compared to 68Ga (0.83 MeV) can result in better spatial image resolutions. However, high-energy γ-rays (1157 keV) are emitted at high rates (99.9%) during 44Sc decay, which can reduce image quality. Therefore, we investigated the impact of these physical properties and performed an unbiased performance evaluation of 44Sc and 68Ga with different imaging phantoms (image quality phantom, Derenzo phantom, and three-rod phantom) on two preclinical PET scanners (Mediso nanoScan PET/MRI, Siemens microPET Focus 120).ResultsDespite the presence of high-energy γ-rays in 44Sc decay, a higher image resolution of small structures was observed with 44Sc when compared to 68Ga. Structures as small as 1.3 mm using the Mediso system, and as small as 1.0 mm using the Siemens system, could be visualized and analyzed by calculating full width at half maximum. Full widths at half maxima were similar for both isotopes. For image quality comparison, we calculated recovery coefficients in 1–5 mm rods and spillover ratios in either air, water, or bone-equivalent material (Teflon). Recovery coefficients for 44Sc were significantly higher than those for 68Ga. Despite the lower positron energy, 44Sc-derived spillover ratio (SOR) values were similar or slightly higher to 68Ga-derived SOR values. This may be attributed to the higher background caused by the additional γ-rays. On the Siemens system, an overestimation of scatter correction in the central part of the phantom was observed causing a virtual disappearance of spillover inside the three-rod phantom.ConclusionBased on these findings, 44Sc appears to be a suitable alternative to 68Ga. The superior image resolution makes it an especially strong competitor in preclinical settings. The additional γ-emissions have a small impact on the imaging resolution but cause higher background noises and can effect an overestimation of scatter correction, depending on the PET system and phantom.

Effect of Aerosol Particles on Orographic Clouds: Sensitivity to Autoconversion Schemes

Aerosol particles can serve as cloud condensation nuclei (CCN) to influence orographic clouds. Autoconversion, which describes the initial formation of raindrops from the collision of cloud droplets, is an important process for aerosol-cloud-precipitation systems. In this study, seven autoconversion schemes are used to investigate the impact of CCN on orographic warm-phase clouds. As the initial cloud droplet concentration is increased from 100 cm−3 to 1000 cm−3 (to represent an increase in CCN), the cloud water increases and then the rainwater is suppressed due to a decrease in the autoconversion rate, leading to a spatial shift in surface precipitation. Intercomparison of the results from the autoconversion schemes show that the sensitivity of cloud water, rainwater, and surface precipitation to a change in the concentration of CCN is different from scheme to scheme. In particular, the decrease in orographic precipitation due to increasing CCN is found to range from −87% to −10% depending on the autoconversion scheme. Moreover, the surface precipitation distribution also changes significantly by scheme or CCN concentration, and the increase in the spillover (ratio of precipitation on the leeward side to total precipitation) induced by increased CCN ranges from 10% to 55% under different autoconversion schemes. The simulations suggest that autoconversion parameterization schemes should not be ignored in the interaction of aerosol and orographic cloud.

Improved Quantification of 18F-FDG PET during 131I-Rituximab Therapy on Mouse Lymphoma Models after 131I Prompt Emission Correction.

18F-FDG Positron Emission Tomography (PET) is used to monitor tumor response to 131I-therapy, but is confounded by prompt emissions (284, 364, 637, and 723 keV) from 131I, particularly in animal PET imaging. We propose a method for correcting this emission in 18F-FDG PET. The 131I prompt emission effect was assessed within various energy windows and various activities. We applied a single gamma correction method to a phantom and in vivo mouse model. The 131I prompt emission fraction was 12% when 300 µCi of 131I and 100 µCi of FDG were administered, and increased exponentially with escalating 131I activity for all energy windows. The difference in spill-over ratio was reduced to <5% after 131I prompt emission correction. In the mouse model, the standard uptake value (SUV) did not differ significantly between FDG PET only (gold standard) and FDG PET after 131I prompt emission-correction, whereas it was overestimated by 38% before correction. Contrast was improved by 18% after 131I prompt emission correction. We first found that count contamination on 18F-FDG follow-up scans due to 131I spilled-over count after 131I rituximab tumor targeted therapy. Our developed 131I prompt emission-correction method increased accuracy during measurement of standard uptake values on 18F-FDG PET.

Implementation of cylindrical PET scanners with block detector geometry in STIR

BackgroundSoftware for Tomographic Image Reconstruction (STIR) is an open-source library for PET and SPECT image reconstruction, implementing iterative reconstruction as well as 2D- and 3D-filtered back projection. Quantitative reconstruction of PET data requires the knowledge of the scanner geometry. Typical scanners, clinical as well as pre-clinical ones, use a block-type geometry. Several rectangular blocks of crystals are arranged into regular polygons. Multiple of such polygons are arranged along the scanner axis. However, the geometrical representation of a scanner provided by STIR is a cylinder made of rings of individual crystals equally distributed in axial and transaxial directions. The data of realistic scanners are projected onto such virtual scanners prior to image reconstruction. This results in reduced quality of the reconstructed image. In this study, we implemented the above-described block geometry into the STIR library, permitting the image reconstruction without the interpolation step. In order to evaluate the difference in image quality, we performed Monte Carlo simulation studies of three different scanner designs: two scanners with multiple crystals per block and one with a single crystal per block. Simulated data were reconstructed using the standard STIR method and the newly implemented block geometry.ResultsVisual comparison between the images reconstructed by the two models for the block-type scanners shows that the new implementation enhances the image quality to the extent that the results before normalization correction are comparable with those after normalization correction. The simulation result of a uniform cylinder shows that the coefficient of variation decreases from 25.8% to 20.9% by using the new implementation in STIR. Spatial resolution is enhanced resulting in a lower partial loss of intensity in sources of small size, e.g., the spill-over ratio for spherical sources of 1.8 mm diameter is 0.19 in the block and 0.34 in the cylindrical model.ConclusionsResults indicate a significant improvement for the new model in comparison with the old one which mapped the polygonal geometry into a cylinder. The new implementation was tested and is available for use via the library of Swiss Federal Institute of Technology in Zurich (ETH).