Accurate modeling of a DOI capable small animal PET scanner using GATE

Hybrid model of photon propagation based on the analytical and Monte Carlo methods for a dual-head PET system

The construction of photon propagation has a close relationship with the quality of reconstructed images. The classical Monte Carlo (MC) based method can model the photon propagation precisely, but it is time-consuming. The analytical method can often quickly construct a model, but its precision is a problem. How to fully exploit the advantages of the MC simulation and analytical model is an open problem. Inspired by the characteristics of the depth of interaction (DOI) detectors, which can help confirm the deposited position of a photon with DOI-encoding technology, we virtually discretize each crystal into several subcrystals to obtain the statistical distribution by MC-based simulation. Then, the statistical distribution is combined with a spatially variant solid-angle model. This combination strategy provides a hybrid model to describe photon propagation with relatively high accuracy and low computational cost. Three discretization schemes are compared to optimize the constructed photon propagation model. Several experiments are carried out to evaluate the performance of the proposed hybrid method. The metrics of full width at half maximum (FWHM), contrast recovery (CR), and coefficient of variation (COV) are adopted to quantitate the imaging results. The classical MC-based method is compared as a gold-standard reference. When a crystal is divided into two discretized positions, the convergent tendencies of CRs and COVs are consistent with that based on MC simulation method, respectively. In terms of FWHMs, the resolutions of using the MC-based model and the proposed hybrid model are 0.71 mm and 0.68 mm in the direction parallel to the detector head, respectively. This indicates the potential of the proposed method in positron emission tomography imaging.

Advanced Monte Carlo simulations of emission tomography imaging systems with GATE

Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.

Monte Carlo simulation and performance assessment of GE Discovery 690 VCT positron emission tomography/computed tomography scanner

The aim of this study is to simulate GE Discovery 690 VCT positron emission tomography/computed tomography (PET/CT) scanner using Geant4 Application for Tomographic Emission (GATE) simulation package (version 8). Then, we assess the performance of scanner by comparing measured and simulated parameter results. Detection system and geometry of PET scanner that consists of 13,824 LYSO crystals designed in 256 blocks and 24 ring detectors were modeled. In order to achieve a precise model, we verified scanner model. Validation was based on a comparison between simulation data and experimental results obtained with this scanner in the same situation. Parameters used for validation were sensitivity, spatial resolution, and contrast. Image quality assessment was done based on comparing the contrast recovery coefficient (CRC) of simulated and measured images. The findings demonstrate that the mean difference between simulated and measured sensitivity is <7%. The simulated spatial resolution agreed to within <5.5% of the measured values. Contrast results had a slight divergence within the range below 4%. The image quality validation study demonstrated an acceptable agreement in CRC for 8:1 and 2:1 source-to-background activity ratio. Validated performance parameters showed good agreement between experimental data and simulated results and demonstrated that GATE is a valid simulation tool for simulating this scanner model. The simulated model of this scanner can be used for future studies regarding optimization of image reconstruction algorithms and emission acquisition protocols.

Detective quantum efficiency (DQE) in PET scanners: A simulation study

The aim of the present study is to introduce the detective quantum efficiency (DQE) for the image quality assessment of positron emission tomography (PET) scanners. For this purpose, a thin layer chromatography (TLC) plane source was simulated using a previously validated, scanner and source geometry, Monte Carlo (MC) model. The model was developed with the Geant4 application for tomographic emission (GATE) MC package and reconstructed images obtained with the software for tomographic image reconstruction (STIR), with cluster computing. The GE Discovery ST PET scanner was simulated by using a previously validated code. A plane source consisting of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrate, immersed in 18F-FDG bath solution (1MBq). Image quality was assessed in terms of the modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) in order to obtain the detective quantum efficiency (DQE). MTF curves were estimated from transverse reconstructed images of the plane source, whereas the NNPS data were estimated from the corresponding coronal images. Images were reconstructed by the maximum likelihood estimation ordered subsets maximum a posteriori one step late (MLE)-OS-MAP-OSL algorithm, by using various subsets 1-21) and iterations 1-20). MTF values were found to increase up to the 12th iteration whereas remain almost constant thereafter. However, the range of the increase in the MTF is limited as the number of subsets increases. The noise levels were found to increase with the corresponding increase of both the number of iterations and subsets. The maximum NNPS value (0.517mm²) was observed for the 420 MLEM-equivalent iterations reconstructed image at 0cycles/mm. Finally DQE values were found to increase for spatial frequencies up to 0.038cycles/mm and to decrease thereafter with the corresponding increase in both number of iterations and subsets. The maximum DQE value (0.48 at 0.038cycles/mm) was obtained for the 8 MLEM-equivalent iterations image. The simulated PET evaluation method based on the TLC plane source can be useful in the quality control and in the further development of PET and SPECT scanners though GATE simulations.

Influences of 3D PET scanner components on increased scatter evaluated by a Monte Carlo simulation

Monte Carlo simulation is widely applied to evaluate the performance of three-dimensional positron emission tomography (3D-PET). For accurate scatter simulations, all components that generate scatter need to be taken into account. The aim of this work was to identify the components that influence scatter. The simulated geometries of a PET scanner were: a precisely reproduced configuration including all of the components; a configuration with the bed, the tunnel and shields; a configuration with the bed and shields; and the simplest geometry with only the bed. We measured and simulated the scatter fraction using two different set-ups: (1) as prescribed by NEMA-NU 2007 and (2) a similar set-up but with a shorter line source, so that all activity was contained only inside the field-of-view (FOV), in order to reduce influences of components outside the FOV. The scatter fractions for the two experimental set-ups were, respectively, 45% and 38%. Regarding the geometrical configurations, the former two configurations gave simulation results in good agreement with the experimental results, but simulation results of the simplest geometry were significantly different at the edge of the FOV. From the simulation of the precise configuration, the object (scatter phantom) was the source of more than 90% of the scatter. This was also confirmed by visualization of photon trajectories. Then, the bed and the tunnel were mainly the sources of the rest of the scatter. From the simulation results, we concluded that the precise construction was not needed; the shields, the tunnel, the bed and the object were sufficient for accurate scatter simulations.

Optimization of the Energy Window for PETbox4, a Preclinical PET Tomograph With a Small Inner Diameter

Small animal positron emission tomography (PET) systems are often designed by employing close geometry configurations. Due to the different characteristics caused by geometrical factors, these tomographs require data acquisition protocols that differ from those optimized for conventional large diameter ring systems. In this work we optimized the energy window for data acquisitions with PETbox4, a 50 mm detector separation (box-like geometry) pre-clinical PET scanner, using the Geant4 Application for Tomographic Emission (GATE). The fractions of different types of events were estimated using a voxelized phantom including a mouse as well as its supporting chamber, mimicking a realistic mouse imaging environment. Separate code was developed to extract additional information about the gamma interactions for more accurate event type classification. Three types of detector backscatter events were identified in addition to the trues, phantom scatters and randoms. The energy window was optimized based on the noise equivalent count rate (NECR) and scatter fraction (SF) with lower-level discriminators (LLD) corresponding to energies from 150 keV to 450 keV. The results were validated based on the calculated image uniformity, spillover ratio (SOR) and recovery coefficient (RC) from physical measurements using the National Electrical Manufacturers Association (NEMA) NU-4 image quality phantom. These results indicate that when PETbox4 is operated with a more narrow energy window (350-650 keV), detector backscatter rejection is unnecessary. For the NEMA NU-4 image quality phantom, the SOR for the water chamber decreases by about 45% from 15.1% to 8.3%, and the SOR for the air chamber decreases by 31% from 12.0% to 8.3% at the LLDs of 150 and 350 keV, without obvious change in uniformity, further supporting the simulation based optimization. The optimization described in this work is not limited to PETbox4, but also applicable or helpful to other small inner diameter geometry scanners.

Cold wall effect eliminating method to determine the contrast recovery coefficient for small animal PET scanners using the NEMA NU-4 image quality phantom

The contrast recovery coefficients (CRC) were evaluated for five different small animal PET scanners: GE Explore Vista, Genisys4, MiniPET-2, nanoScan PC and Siemens Inveon. The NEMA NU-4 2008 performance test with the suggested image quality phantom (NU4IQ) does not allow the determination of the CRC values for the hot regions in the phantom. This drawback of NU4IQ phantom motivated us to develop a new method for this purpose. The method includes special acquisition and reconstruction protocols using the original phantom, and results in an artificially merged image enabling the evaluation of CRC values. An advantageous feature of this method is that it stops the cold wall effect from distorting the CRC calculation. Our suggested protocol results in a set of CRC values contributing to the characterization of small animal PET scanners. GATE simulations were also performed to validate the new method and verify the evaluated CRC values. We also demonstrated that the numerical values of this parameter depend on the actual object contrast of the hot region(s) and this mainly comes from the spillover effect. This effect was also studied while analysing the background activity level around the hot rods. We revealed that the calculated background mean values depended on the target contrast in a scanner specific manner. Performing the artificially merged imaging procedure and additional simulations using the micro hollow sphere (MHS) phantom geometry, we also proved that the inactive wall around the hot spheres can have a remarkable impact on the calculated CRC. In conclusion, we have shown that the proposed artificial merging procedure and the commonly used NU4IQ phantom prescribed by the NEMA NU-4 can easily deliver reliable CRC data otherwise unavailable for the NU4IQ phantom in the conventional protocol or the MHS phantom.