Advanced Monte Carlo simulations of emission tomography imaging systems with GATE

Evaluation of lesion contrast in the walk-through long axial FOV PET scanner simulated with XCAT anthropomorphic phantoms

BACKGROUND

This study evaluates the lesion contrast in a cost-effective long axial field of view (FOV) PET scanner, called the walk-through PET (WT-PET). The scanner consists of two flat detector panels covering the entire torso and head, scanning patients in an upright position for increased throughput. High-resolution, depth-of-interaction capable, monolithic detector technology is used to provide good spatial resolution and enable detection of smaller lesions.

METHODS

Monte Carlo GATE simulations are used in conjunction with XCAT anthropomorphic phantoms to evaluate lesion contrast in lung, liver and breast for various lesion diameters (10, 7 and 5 mm), activity concentration ratios (8:1, 4:1 and 2:1) and patient BMIs (18-37). Images were reconstructed iteratively with listmode maximum likelihood expectation maximization, and contrast recovery coefficients (CRCs) were obtained for the reconstructed lesions.

RESULTS

Results shows notable variations in contrast recovery coefficients (CRC) across different lesion sizes and organ locations within the XCAT phantoms. Specifically, our findings reveal that 10 mm lesions consistently exhibit higher CRC compared to 7 mm and 5 mm lesions, with increases of approximately 54% and 330%, respectively, across all investigated organs. Moreover, high contrast recovery is observed in most liver lesions regardless of diameter or activity ratio (average CRC = 42%), as well as in the 10 mm lesions in the lung. Notably, for the 10 mm lesions, the liver demonstrates 42% and 62% higher CRC compared to the lung and breast, respectively. This trend remains consistent across lesion sizes, with the liver consistently exhibiting higher CRC values compared to the lung and breast: 7 mm lesions show an increase of 96% and 41%, while 5 mm lesions exhibit approximately 294% and 302% higher CRC compared to the lung and breast, respectively.

CONCLUSION

A comparison with a conventional pixelated LSO long axial FOV PET shows similar performance, achieved at a reduced cost for the WT-PET due to a reduction in required number of detectors.

A photon source model for alpha-emitter radionuclides

Objective.A Monte Carlo virtual source model named PHID (photon from Ion decay) that generates photons emitted in the complex decay chain process of alpha-emitter radionuclides is proposed, typically for use during the simulation of SPECT image acquisition.Approach.Given an alpha-emitter radionuclide, the PHID model extracts from Geant4 databases the photon emission lines from all decaying daughters for both isometric transition and atomic relaxation processes. According to a given time range, abundances and activities in the decay chain are considered thanks to the Bateman equations, taking into account the decay rates and the initial abundances.Main results.PHID is evaluated by comparison with analog Monte Carlo simulation. It generates photons with the correct energy and temporal distribution, avoiding the costly simulation of the complete decay chain thus decreasing the computation time. The exact time gain depends on the simulation setup. As an example, it is 30× faster for simulating 1 MBq of225Ac in water for 1 section Moreover, for225Ac, PHID was also compared to a simplified source model with the two main photon emission lines (218 and 440 keV). PHID shows that 2 times more particles are simulated and 60% more counts are detected in the images.Significance.PHID can simulate any alpha-emitter radionuclide available in the Geant4 database. As a limitation, photons emitted from Bremsstrahlung are ignored, but they represent only 0.7% of the photons above 30 keV and are not significant for SPECT imaging. PHID is open-source, available in GATE 10, and eases the investigation of imaging photon emission from alpha emitters.

Measurement of the12C(p,n)12N reaction cross section below 150 MeV

Objective. Proton therapy currently faces challenges from clinical complications on organs-at-risk due to range uncertainties. To address this issue, positron emission tomography (PET) of the proton-induced11C and15O activity has been used to provide feedback on the proton range. However, this approach is not instantaneous due to the relatively long half-lives of these nuclides. An alternative nuclide,12N (half-life 11 ms), shows promise for real-timein vivoproton range verification. Development of12N imaging requires better knowledge of its production reaction cross section.Approach. The12C(p,n)12N reaction cross section was measured by detecting positron activity of graphite targets irradiated with 66.5, 120, and 150 MeV protons. A pulsed beam delivery with 0.7-2 × 108protons per pulse was used. The positron activity was measured during the beam-off periods using a dual-head Siemens Biograph mCT PET scanner. The12N production was determined from activity time histograms.Main results. The cross section was calculated for 11 energies, ranging from 23.5 to 147 MeV, using information on the experimental setup and beam delivery. Through a comprehensive uncertainty propagation analysis, a statistical uncertainty of 2.6%-5.8% and a systematic uncertainty of 3.3%-4.6% were achieved. Additionally, a comparison between measured and simulated scanner sensitivity showed a scaling factor of 1.25 (±3%). Despite this, there was an improvement in the precision of the cross section measurement compared to values reported by the only previous study.Significance. Short-lived12N imaging is promising for real-timein vivoverification of the proton range to reduce clinical complications in proton therapy. The verification procedure requires experimental knowledge of the12N production cross section for proton energies of clinical importance, to be incorporated in a Monte Carlo framework for12N imaging prediction. This study is the first to achieve a precise measurement of the12C(p,n)12N nuclear cross section for such proton energies.

A time- and space-saving Monte Carlo simulation method using post-collimation generative adversarial network for dose calculation of an O-ring gantry Linac

PURPOSE

This study explores the feasibility of employing Generative Adversarial Networks (GANs) to model the RefleXion X1 Linac. The aim is to investigate the accuracy of dose simulation and assess the potential computational benefits.

METHODS

The X1 Linac is a new radiotherapy machine with a binary multi-leaf collimation (MLC) system, facilitating innovative biology-guided radiotherapy. A total of 34 GAN generators, each representing a desired MLC aperture, were developed. Each generator was trained using a phase space file generated underneath the corresponding aperture, enabling the generation of particles and serving as a beam source for Monte Carlo simulation. Dose distributions in water were simulated for each aperture using both the GAN and phase space sources. The agreement between dose distributions was evaluated. The computational time reduction from bypassing the collimation simulation and storage space savings were estimated.

RESULTS

The percentage depth dose at 10 cm, penumbra, and full-width half maximum of the GAN simulation agree with the phase space simulation, with differences of 0.4 % ± 0.2 %, 0.32 ± 0.66 mm, and 0.26 ± 0.44 mm, respectively. The gamma passing rate (1 %/1mm) for the planar dose exceeded 90 % for all apertures. The estimated time-saving for simulating an plan using 5766 beamlets was 530 CPU hours. The storage usage was reduced by a factor of 102.

CONCLUSION

The utilization of the GAN in simulating the X1 Linac demonstrated remarkable accuracy and efficiency. The reductions in both computational time and storage requirements make this approach highly valuable for future dosimetry studies and beam modeling.

Partial volume correction of PET image data using geometric transfer matrices based on uniform B-splines

Objective. Most methods for partial volume correction (PVC) of positron emission tomography (PET) data employ anatomical segmentation of images into regions of interest. This approach is not optimal for exploratory functional imaging beyond regional hypotheses. Here, we describe a novel method for unbiased voxel-wise PVC.Approach.B-spline basis functions were combined with geometric transfer matrices to enable a method (bsGTM) that provides PVC or alternatively provides smoothing with minimal regional crosstalk. The efficacy of the proposed method was evaluated using Monte Carlo simulations, human PET data, and murine functional PET data.Main results.In simulations, bsGTM provided recovery of partial volume signal loss comparable to iterative deconvolution, while demonstrating superior resilience to noise. In a real murine PET dataset, bsGTM yielded much higher sensitivity for detecting amphetamine-induced reduction of [11C]raclopride binding potential. In human PET data, bsGTM smoothing enabled increased signal-to-noise ratios with less degradation of binding potentials relative to Gaussian convolution or non-local means.Significance.bsGTM offers improved performance for PVC relative to iterative deconvolution, the current method of choice for voxel-wise PVC, especially in the common PET regime of low signal-to-noise ratio. The new method provides an anatomically unbiased way to compensate partial volume errors in cases where anatomical segmentation is unavailable or of questionable relevance or accuracy.

UMC-PET: a fast and flexible Monte Carlo PET simulator

Objective.The GPU-based Ultra-fast Monte Carlo positron emission tomography simulator (UMC-PET) incorporates the physics of the emission, transport and detection of radiation in PET scanners. It includes positron range, non-colinearity, scatter and attenuation, as well as detector response. The objective of this work is to present and validate UMC-PET as a a multi-purpose, accurate, fast and flexible PET simulator.Approach.We compared UMC-PET against PeneloPET, a well-validated MC PET simulator, both in preclinical and clinical scenarios. Different phantoms for scatter fraction (SF) assessment following NEMA protocols were simulated in a 6R-SuperArgus and a Biograph mMR scanner, comparing energy histograms, NEMA SF, and sensitivity for different energy windows. A comparison with real data reported in the literature on the Biograph scanner is also shown.Main results.NEMA SF and sensitivity estimated by UMC-PET where within few percent of PeneloPET predictions. The discrepancies can be attributed to small differences in the physics modeling. Running in a 11 GB GeForce RTX 2080 Ti GPU, UMC-PET is ∼1500 to ∼2000 times faster than PeneloPET executing in a single core Intel(R) Xeon(R) CPU W-2155 @ 3.30 GHz.Significance.UMC-PET employs a voxelized scheme for the scanner, patient adjacent objects (such as shieldings or the patient bed), and the activity distribution. This makes UMC-PET extremely flexible. Its high simulation speed allows applications such as MC scatter correction, faster SRM estimation for complex scanners, or even MC iterative image reconstruction.

A preliminary study of dynamic interactive simulation and computational CT scan of the ideal alveolus model

BACKGROUND

While the development of CT imaging technique has brought cognition of in vivo organs, the resolution of CT images and their static characteristics have gradually become barriers of microscopic tissue research.

PURPOSE

Previous research used the finite element method to study the airflow and gas exchange in the alveolus and acinar to show the fate of inhaled aerosols and studied the diffusive, convective, and sedimentation mechanisms. Our study combines these techniques with CT scan simulation to study the mechanisms of respiratory movement and its imaging appearance.

METHODS

We use 3D fluid-structure interaction simulation to study the movement of an ideal alveolus under regular and forced breathing situations and ill alveoli with different tissue elasticities. Additionally, we use the Monte Carlo algorithm within the OpenGATE platform to simulate the computational CT images of the dynamic process with different designated resolutions. The resolutions show the relationship between the kinematic model of the human alveolus and its imaging appearance.

RESULTS

The results show that the alveolus and the wall thickness can be seen with an image resolution smaller than 15.6 μm. With ordinary CT resolution, the alveolus is expressed with four voxels.

CONCLUSIONS

This is a preliminary study concerning the imaging appearance of the dynamic alveolus model. This technique will be used to study the imaging appearance of the dynamic bronchial tree and the lung lobe models in the future.

Energy-based scatter estimation in clinical PET

BACKGROUND

Scatter correction (SC) is essential in PET for accurate quantitative imaging. The state-of-the-art SC method is single-scatter simulation (SSS). Although this method is usually robust and accurate, it can fail in some situations, for example when there is motion between the CT and PET scans in PET/CT. Therefore, it is of interest to consider other SC methods.

PURPOSE

In this work, an energy-based scatter estimation (EBS) method is described in detail, tested in phantoms and patients, and compared to SSS.

METHODS

This version of EBS was developed for list-mode data from Biograph Vision-600 PET/CT scanner. EBS is based on digitized 2D energy histograms in each bin of a coarsely sampled PET sinogram, either with or without time of flight (TOF). The histograms are modeled as a noisy realization of a linear combination of nine basis functions whose parameters were derived from a measurement of the 511-keV photopeak spectrum as well as Monte-Carlo simulations of the scattering process. EBS uses an iterative expectation maximization approach to determine the coefficients in the linear combination, and from this estimates the scatter. The investigation was restricted to 18 F-based PET data in which the acquired number of counts was similar to the levels seen in oncological whole-body PET/CT scans. To evaluate the performance, phantom scans were used that involved the NEMA NU2-2018 protocol, a slab phantom, an NU 2-1994 phantom, a cardiac phantom in an anthropomorphic chest phantom, and a uniformly-filled torso phantom with a bladder phantom slightly outside the axial field of view. Contrast recovery (CR) and other parameters were evaluated in images reconstructed with SSS and EBS. Furthermore, FDG PET scans of seven lung cancer patients were used in the evaluation. Standardized uptake values (SUV) based on SSS and EBS were compared in 27 lesions.

RESULTS

EBS and SSS images were visually similar in all cases except the torso + bladder phantom, where the EBS was much closer to the expected uniform image. The NU2-2018 analysis indicated a 2% scatter residual in EBS images compared to 3% with SSS, and 10% higher background variability, which is a surrogate for image noise. The cardiac phantom scan showed that CR was 98.2% with EBS and 99.6% with SSS, and that the SSS sinogram had values greater than the net-true emission sinogram, indicating a slight overcorrection in the case of SSS. In the lesion SUV comparison in patient scans, EBS correlated strongly (R2  = 0.9973) with SSS, and SUV based on EBS were systematically 0.1 SUV lower. In the case of the torso + bladder phantom portion, the SSS image of the torso + bladder phantom was 299% times hotter than expected in one area, due to scatter estimation error, compared to 16% colder with EBS.

CONCLUSIONS

In evaluating clinically relevant parameters such as SUV in focal lesions, EBS and SSS give almost the same results. In phantoms, some scatter figures of merit were slightly improved by use of EBS, though an image variability figure of merit was slightly degraded. In typical oncological whole-body PET/CT, EBS may be a suitable replacement for SSS, especially when SSS fails due to technical problems during the scan.

A Metamodel-Based Multi-Scale Reliability Analysis of FRP Truss Structures under Hybrid Uncertainties

This study introduces a Radial Basis Function-Genetic Algorithm-Back Propagation-Importance Sampling (RBF-GA-BP-IS) algorithm for the multi-scale reliability analysis of Fiber-Reinforced Polymer (FRP) composite structures. The proposed method integrates the computationally powerful RBF neural network with GA, BP neural network and IS to efficiently calculate inner and outer optimization problems for reliability analysis with hybrid random and interval uncertainties. The investigation profoundly delves into incorporating both random and interval parameters in the reliability appraisal of FRP constructs, ensuring fluctuating parameters within designated boundaries are meticulously accounted for, thus augmenting analytic exactness. In application, the algorithm was subjected to diverse structural evaluations, including a seven-bar planar truss, an architectural space dome truss, and an intricate nonlinear truss bridge. Results demonstrate the algorithm's exceptional performance in terms of model invocation counts and accurate failure probability estimation. Specifically, within the seven-bar planar truss evaluation, the algorithm exhibited a deviation of 0.08% from the established failure probability benchmark.

A simulation study of the system characteristics for a long axial FOV PET design based on monolithic BGO flat panels compared with a pixelated LSO cylindrical design

BACKGROUND

Although a new generation of tomographs with a longer axial field-of-view called total-body PET have been developed, they are not widely utilized due to their high cost compared to conventional scanners. The newly designed walk-through total-body PET scanner is introduced as a high-throughput and cost-efficient alternative to total-body PET scanners, by making use of a flat panel geometry and lower cost, depth-of-interaction capable, monolithic BGO detectors. The main aim of the presented study is to evaluate through Monte Carlo simulation the system characteristics of the walk-through total-body PET scanner by comparing it with a Quadra-like total-body PET of similar attributes to the Siemens Biograph Vision Quadra.

METHODS

The walk-through total-body PET is comprised of two flat detector panels, spaced 50 cm apart. Each panel, 70 [Formula: see text] 106 cm[Formula: see text] in size, consists of 280 BGO-based monolithic detectors. The Quadra-like TB-PET has been simulated based on the characteristics of the Biograph Vision Quadra, one of the most common total-body PET scanners with 106 cm of axial field-of-view, which is constructed with pixelated LSO scintillation crystals. The spatial resolution, sensitivity, count rate performance, scatter fractions, and image quality of both scanners are simulated in the GATE simulation toolkit for comparison.

RESULTS

Due to the DOI-capable detectors used in the walk-through total-body PET, the values of the spatial resolution of this scanner were all below 2 mm along directions parallel to the panels, and reached a maximum of 3.36 mm in the direction perpendicular to the panels. This resolution is a large improvement compared to the values of the Quadra-like TB-PET. The walk-through total-body PET uses its maximum sensitivity (154 cps/kBq) for data acquisition and image reconstruction.

CONCLUSION

Based on the combination of very good spatial resolution and high sensitivity of the walk-through total-body PET, along with a 2.2 times lower scintillation crystal volume and 1.8 times lower SiPM surface, this scanner can be a very cost-efficient alternative for total-body PET scanners in cases where concomitant CT is not required.

Comparative studies of the sensitivities of sparse and full geometries of Total-Body PET scanners built from crystals and plastic scintillators

BACKGROUND

Alongside the benefits of Total-Body imaging modalities, such as higher sensitivity, single-bed position, low dose imaging, etc., their final construction cost prevents worldwide utilization. The main aim of this study is to present a simulation-based comparison of the sensitivities of existing and currently developed tomographs to introduce a cost-efficient solution for constructing a Total-Body PET scanner based on plastic scintillators.

METHODS

For the case of this study, eight tomographs based on the uEXPLORER configuration with different scintillator materials (BGO, LYSO), axial field-of-view (97.4 cm and 194.8 cm), and detector configurations (full and sparse) were simulated. In addition, 8 J-PET scanners with different configurations, such as various axial field-of-view (200 cm and 250 cm), different cross sections of plastic scintillator, and multiple numbers of plastic scintillator layers (2, 3, and 4), based on J-PET technology have been simulated by GATE software. Furthermore, Siemens' Biograph Vision has been simulated to compare the results with standard PET scans. Two types of simulations have been performed. The first one with a centrally located source with a diameter of 1 mm and a length of 250 cm, and the second one with the same source inside a water-filled cylindrical phantom with a diameter of 20 cm and a length of 183 cm.

RESULTS

With regards to sensitivity, among all the proposed scanners, the ones constructed with BGO crystals give the best performance ([Formula: see text] 350 cps/kBq at the center). The utilization of sparse geometry or LYSO crystals significantly lowers the achievable sensitivity of such systems. The J-PET design gives a similar sensitivity to the sparse LYSO crystal-based detectors while having full detector coverage over the body. Moreover, it provides uniform sensitivity over the body with additional gain on its sides and provides the possibility for high-quality brain imaging.

CONCLUSION

Taking into account not only the sensitivity but also the price of Total-Body PET tomographs, which till now was one of the main obstacles in their widespread clinical availability, the J-PET tomography system based on plastic scintillators could be a cost-efficient alternative for Total-Body PET scanners.

Adjustment of acquisition arc in cardiac malposition during myocardial perfusion SPECT imaging: computer simulation based on deterministic modeling

OBJECTIVES

To simulate cardiac malpositions, leftward and rightward shift and dextrocardia, and also to compare distribution of activity of septal and lateral walls of left ventricle acquired in standard acquisition arc and after relevant adjustment.

METHODS

In this study, digital phantoms with cardiac malpositions are designed and procedure of acquisition of scan in standard arc (from right anterior oblique to left posterior oblique) and adjusted acquisition arc is simulated. The three situations of malposition including leftward and rightward shift and dextrocardia are considered. For all types, acquisition is conducted in standard and then adjusted arcs (from anterior to posterior and also from right to left for leftward and rightward shifts, respectively, and for dextrocardia, from left anterior oblique to right posterior oblique). All obtained projections are reconstructed using the algorithm of filtered back projection. During forward projection to obtain sinograms, radiation attenuation is also modeled by incorporation of a simplified transmission map to emission map. The resulting tomographic slices of the LV (septum, apex, and lateral wall) are presented visually and are compared by plotting intensity profiles of the walls. Finally, normalized error images are also computed. All the computations are performed in MATLAB software package.

RESULTS

In transverse slice, septum and lateral wall are attenuated progressively from apex, which is closer to the camera, to the base in similar fashion. In tomographic slices of standard acquisition arc, the septum shows remarkably higher activity compared to lateral wall. However, after adjustment, both seems equally intense and progressively being attenuated from apex to base, similar to that found in phantom with normally positioned heart. Likewise, for the phantom with rightward shift, when the scanning was done in standard arc, the septum is more intense than the lateral wall. And similarly, adjustment of the arc renders both walls equally intense. In dextrocardia, level of attenuation of basal parts of septum and lateral wall is higher in 360° arc compared to adjusted 180° arc.

CONCLUSION

Adjustment of acquisition arc exerts perceptible changes in distribution of activity over LV walls which are more compatible with normally positioned heart.

Quantitative validation of Monte Carlo SPECT simulation: application to a Mediso AnyScan GATE simulation

BACKGROUND

Monte Carlo (MC) simulations are used in nuclear medicine imaging as they provide unparalleled insight into processes that are not directly experimentally measurable, such as scatter and attenuation in an acquisition. Whilst MC is often used to provide a 'ground-truth', this is only the case if the simulation is fully validated against experimental data. This work presents a quantitative validation for a MC simulation of a single-photon emission computed tomography (SPECT) system.

METHODS

An MC simulation model of the Mediso AnyScan SCP SPECT system installed at the UK National Physical Laboratory was developed in the GATE (Geant4 Application for Tomographic Emission) toolkit. Components of the detector head and two collimator configurations were modelled according to technical specifications and physical measurements. Experimental detection efficiency measurements were collected for a range of energies, permitting an energy-dependent intrinsic camera efficiency correction function to be determined and applied to the simulation on an event-by-event basis. Experimental data were collected in a range of geometries with [Formula: see text]Tc for comparison to simulation. The procedure was then repeated with [Formula: see text]Lu to determine how the validation extended to another isotope and set of collimators.

RESULTS

The simulation's spatial resolution, sensitivity, energy spectra and the projection images were compared with experimental measurements. The simulation and experimental uncertainties were determined and propagated to all calculations, permitting the quantitative agreement between simulated and experimental SPECT acquisitions to be determined. Statistical agreement was seen in sinograms and projection images of both [Formula: see text]Tc and [Formula: see text]Lu data. Average simulated and experimental sensitivity ratios of ([Formula: see text]) were seen for emission and scatter windows of [Formula: see text]Tc, and ([Formula: see text]) and ([Formula: see text]) for the 113 and 208 keV emissions of [Formula: see text]Lu, respectively.

CONCLUSIONS

MC simulations will always be an approximation of a physical system and the level of agreement should be assessed. A validation method is presented to quantify the level of agreement between a simulation model and a physical SPECT system.

Machine learning-based prediction of conversion coefficients for I-123 metaiodobenzylguanidine heart-to-mediastinum ratio

PURPOSE

We developed a method of standardizing the heart-to-mediastinal ratio in 123I-labeled meta-iodobenzylguanidine (MIBG) images using a conversion coefficient derived from a dedicated phantom. This study aimed to create a machine-learning (ML) model to estimate conversion coefficients without using a phantom.

METHODS

210 Monte Carlo (MC) simulations of 123I-MIBG images to obtain conversion coefficients using collimators that differed in terms of hole diameter, septal thickness, and length. Simulated conversion coefficients and collimator parameters were prepared as training datasets, then a gradient-boosting ML was trained to estimate conversion coefficients from collimator parameters. Conversion coefficients derived by ML were compared with those that were MC simulated and experimentally derived from 613 phantom images.

RESULTS

Conversion coefficients were superior when estimated by ML compared with the classical multiple linear regression model (root mean square deviations: 0.021 and 0.059, respectively). The experimental, MC simulated, and ML-estimated conversion coefficients agreed, being, respectively, 0.54, 0.55, and 0.55 for the low-; 0.74, 0.70, and 0.72 for the low-middle; and 0.88, 0.88, and 0.88 for the medium-energy collimators.

CONCLUSIONS

The ML model estimated conversion coefficients without the need for phantom experiments. This means that conversion coefficients were comparable when estimated based on collimator parameters and on experiments.

Transformation of PET raw data into images for event classification using convolutional neural networks

In positron emission tomography (PET) studies, convolutional neural networks (CNNs) may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, unprocessed PET coincidence data exist in tabular format. This paper develops the transformation of tabular data into n-dimensional matrices, as a preparation stage for classification based on CNNs. This method explicitly introduces a nonlinear transformation at the feature engineering stage and then uses principal component analysis to create the images. We apply the proposed methodology to the classification of simulated PET coincidence events originating from NEMA IEC and anthropomorphic XCAT phantom. Comparative studies of neural network architectures, including multilayer perceptron and convolutional networks, were conducted. The developed method increased the initial number of features from 6 to 209 and gave the best precision results (79.8) for all tested neural network architectures; it also showed the smallest decrease when changing the test data to another phantom.

Investigation of TG-43 Dosimetric Parameters for 192Ir Brachytherapy Source Using GATE Monte Carlo Code

Purpose

According to the revised Task Group number 43 recommendations, a brachytherapy source must be validated against a similar or identical source before its clinical application. The purpose of this investigation is to verify the dosimetric data of the high dose rate (HDR) BEBIG 192Ir source (Ir2.A85-2).

Materials and Methods

The HDR 192Ir encapsulated seed was simulated and its main dosimetric data were calculated using Geant4 Application for Tomographic Emission (GATE) simulation code. Cubic cells were used for the calculation of dose rate constant and radial dose function while for anisotropy function ring cells were used. DoseActors were simulated and attached to the respective cells to obtain the required data.

Results

The dose rate constant was obtained as 1.098 ± 0.003 cGy.h - 1.U - 1, differing by 1.0% from the reference value reported by Granero et al. Similarly, the calculated values for radial dose and anisotropy functions presented good agreement with the results obtained by Granero et al.

Conclusion

The results of this study suggest that the GATE Monte Carlo code is a valid toolkit for benchmarking brachytherapy sources and can be used for brachytherapy simulation-based studies and verification of brachytherapy treatment planning systems.

Simulation of X-ray projections on GPU: Benchmarking gVirtualXray with clinically realistic phantoms

BACKGROUND AND OBJECTIVES

This study provides a quantitative comparison of images created using gVirtualXray (gVXR) to both Monte Carlo (MC) and real images of clinically realistic phantoms. gVirtualXray is an open-source framework that relies on the Beer-Lambert law to simulate X-ray images in realtime on a graphics processor unit (GPU) using triangular meshes.

METHODS

Images are generated with gVirtualXray and compared with a corresponding ground truth image of an anthropomorphic phantom: (i) an X-ray projection generated using a Monte Carlo simulation code, (ii) real digitally reconstructed radiographs (DRRs), (iii) computed tomography (CT) slices, and (iv) a real radiograph acquired with a clinical X-ray imaging system. When real images are involved, the simulations are used in an image registration framework so that the two images are aligned.

RESULTS

The mean absolute percentage error (MAPE) between the images simulated with gVirtualXray and MC is 3.12%, the zero-mean normalised cross-correlation (ZNCC) is 99.96% and the structural similarity index (SSIM) is 0.99. The run-time is 10 days for MC and 23 ms with gVirtualXray. Images simulated using surface models segmented from a CT scan of the Lungman chest phantom were similar to (i) DRRs computed from the CT volume and (ii) an actual digital radiograph. CT slices reconstructed from images simulated with gVirtualXray were comparable to the corresponding slices of the original CT volume.

CONCLUSIONS

When scattering can be ignored, accurate images that would take days using MC can be generated in milliseconds with gVirtualXray. This speed of execution enables the use of repetitive simulations with varying parameters, e.g. to generate training data for a deep-learning algorithm, and to minimise the objective function of an optimisation problem in image registration. The use of surface models enables the combination of X-ray simulation with real-time soft-tissue deformation and character animation, which can be deployed in virtual reality applications.

Potential of Depth-of-Interaction-Based Detection Time Correction in Cherenkov Emitter Crystals for TOF-PET

Cherenkov light can improve the timing resolution of Positron Emission Tomography (PET) radiation detectors, thanks to its prompt emission. Coincidence time resolutions (CTR) of ~30 ps were recently reported when using 3.2 mm-thick Cherenkov emitters. However, sufficient detection efficiency requires thicker crystals, causing the timing resolution to be degraded by the optical propagation inside the crystal. We report on depth-of-interaction (DOI) correction to mitigate the time-jitter due to the photon time spread in Cherenkov-based radiation detectors. We simulated the Cherenkov and scintillation light generation and propagation in 3 × 3 mm2 lead fluoride, lutetium oxyorthosilicate, bismuth germanate, thallium chloride, and thallium bromide. Crystal thicknesses varied from 9 to 18 mm with a 3-mm step. A DOI-based time correction showed a 2-to-2.5-fold reduction of the photon time spread across all materials and thicknesses. Results showed that highly refractive crystals, though producing more Cherenkov photons, were limited by an experimentally obtained high-cutoff wavelength and refractive index, restricting the propagation and extraction of Cherenkov photons mainly emitted at shorter wavelengths. Correcting the detection time using DOI information shows a high potential to mitigate the photon time spread. These simulations highlight the complexity of Cherenkov-based detectors and the competing factors in improving timing resolution.

Dosimetric impact of 3D motion-compensated SPECT reconstruction for SIRT planning

BACKGROUND

In selective internal radiation therapy, ^99mTc SPECT images are used to optimize patient treatment planning, but they are affected by respiratory motion. In this study, we evaluated on patient data the dosimetric impact of motion-compensated SPECT reconstruction on several volumes of interest (VOI), on the tumor-to-normal liver (TN) ratio and on the activity to be injected.

METHODS

Twenty-nine patients with liver cancer or hepatic metastases treated by radioembolization were included in this study. The biodistribution of ⁹⁰Y is assumed to be the same as that of ^99mTc when predictive dosimetry is implemented. A total of 31 ^99mTc SPECT images were acquired and reconstructed with two methods: conventional OSEM (3D) and motion-compensated OSEM (3Dcomp). Seven VOI (liver, lungs, tumors, perfused liver, hepatic reserve, healthy perfused liver and healthy liver) were delineated on the CT or obtained by thresholding SPECT images followed by Boolean operations. Absorbed doses were calculated for each reconstruction using Monte Carlo simulations. Percentages of dose difference (PDD) between 3Dcomp and 3D reconstructions were estimated as well as the relative differences for TN ratio and activities to be injected. The amplitude of movement was determined with local rigid registration of the liver between the 3Dcomp reconstructions of the extreme phases of breathing.

RESULTS

The mean amplitude of the liver was 9.5 ± 2.7 mm. Medians of PDD were closed to zero for all VOI except for lungs (6.4%) which means that the motion compensation overestimates the absorbed dose to the lungs compared to the 3D reconstruction. The smallest lesions had higher PDD than the largest ones. Between 3D and 3Dcomp reconstructions, means of differences in lung dose and TN ratio were not statistically significant, but in some cases these differences exceed 1 Gy (4/31) and 8% (2/31). The absolute differences in activity were on average 3.1% ± 5.1% and can reach 22.8%.

CONCLUSION

The correction of respiratory motion mainly impacts the lung and tumor doses but only for some patients. The largest dose differences are observed for the smallest lesions.

Effect of detector geometry and surface finish on Cerenkov based time estimation in monolithic BGO detectors

Objective.Time-of-flight positron emission tomography based on bismuth germanate (BGO) detectors is made possible due to fast emission of Cerenkov light. Only around 17 Cerenkov photons are produced per 511 keV photoelectric event, making high photon collection efficiency crucial for obtaining good time-of-flight capabilities. In this study, we investigate how different lateral and back surface finishes affect the photon collection efficiency and Cerenkov based timing performance in monolithic BGO.Approach.The study is performed using GATE for gamma and optical photon modeling, with surface reflections of photons simulated by the LUT Davis model. We compare for different detector configurations (regarding size and surface finishes) the photon collection efficiency, detection delays of the first few optical photons and coincidence time resolution estimations obtained by modeling the SiPM signals and performing leading edge discrimination. An additional comparison is made to LYSO scintillators and pixelated detectors.Main results.Although Cerenkov photon emission is directional, many high incidence angle Cerenkov photons are emitted due to electron scattering in the crystal. Substituting a polished back (photodetector side) surface for a rough surface increases the collection efficiency of these high angle of incidence photons. Results show that for a monolithic 50 × 50 × 12 mm³BGO detector with reflective side surfaces, this leads to an overall increase in photon collection efficiency of 34%. Cerenkov photon collection efficiency is also improved, resulting in a reduction of the photon detection delays (and the variation therein) of the first few optical photons. This leads to a better coincidence time resolution, primarily achieved by a shortening of the tails in the time-of-flight kernel, with an 18% reduction in full width at tenth maximum.Significance.This study shows the importance of the photon collection efficiency for timing performance in Cerenkov based monolithic detectors, and how it can be improved with different surface finishes.

Monte-Carlo techniques for radiotherapy applications I: introduction and overview of the different Monte-Carlo codes

Introduction:

The dose calculation plays a crucial role in many aspects of contemporary clinical radiotherapy treatment planning process. It therefore goes without saying that the accuracy of the dose calculation is of very high importance. The gold standard for absorbed dose calculation is the Monte-Carlo algorithm.

Methods:

This first of two papers gives an overview of the main openly available and supported codes that have been widely used for radiotherapy simulations.

Results:

The paper aims to provide an overview of Monte-Carlo in the field of radiotherapy and point the reader in the right direction of work that could help them get started or develop their existing understanding and use of Monte-Carlo algorithms in their practice.

Conclusions:

It also serves as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Monte-Carlo techniques for radiotherapy applications II: equipment and source modelling, dose calculations and radiobiology

Introduction:

This is the second of two papers giving an overview of the use of Monte-Carlo techniques for radiotherapy applications.

Methods:

The first paper gave an introduction and introduced some of the codes that are available to the user wishing to model the different aspects of radiotherapy treatment. It also aims to serve as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Results and Conclusions:

This paper focuses on the application of Monte-Carlo to specific problems in radiotherapy. These include radiotherapy and imaging beam production, brachytherapy, phantom and patient dosimetry, detector modelling and track structure calculations for micro-dosimetry, nano-dosimetry and radiobiology.

Comparison and calibration of dose delivered by137Cs and x-ray irradiators in mice

Objective.The Office of Radiological Security, U.S. Department of Energy's National Nuclear Security Administration, is implementing a radiological risk reduction program which seeks to minimize or eliminate the use of high activity radiological sources, including¹³⁷Cs, by replacing them with non-radioisotopic technologies, such as x-ray irradiators. The main goal of this paper is to evaluate the equivalence of the dose delivered by gamma- and x-ray irradiators in mice using experimental measurements and Monte Carlo simulations. We also propose a novel biophantom as anin situdose calibration method.Approach.We irradiated mouse carcasses and 3D-printed mouse biophantoms in a¹³⁷Cs irradiator (Mark I-68) and an x-ray irradiator (X-Rad320) at three voltages (160 kVp, 225 kVp and 320 kVp) and measured the delivered radiation dose. A Geant4-based Monte Carlo model was developed and validated to provide a comprehensive picture of gamma- and x-ray irradiation in mice.Main Results.Our Monte Carlo model predicts a uniform dose delivered in soft-tissue for all the explored irradiation programs and in agreement with the absolute dose measurements. Our Monte Carlo model shows an energy-dependent difference between dose in bone and in soft tissue that decreases as photon energy increases. Dose rate depends on irradiator and photon energy. We observed a deviation of the measured dose from the target value of up to -9% for the Mark I-68, and up to 35% for the X-Rad320. The dose measured in the 3D-printed phantoms are equivalent to that in the carcasses within 6% uncertainty.Significance.Our results suggest that 320 kVp irradiation is a good candidate to substitute¹³⁷Cs irradiation barring a few caveats. There is a significant difference between measured and targeted doses for x-ray irradiation that suggests a strong need forin situcalibration, which can be achieved with 3D-printed mouse biophantoms. A dose correction is necessary for bone doses, which can be provided by a Monte Carlo calculation. Finally, the biological implications of the differences in dose rates and dose per photon for the different irradiation methods should be carefully assessed for each small-animal irradiation experiment.

Autonomous digitizer calibration of a Monte Carlo detector model through evolutionary simulation

Simulating the response of a radiation detector is a modelling challenge due to the stochastic nature of radiation, often complex geometries, and multi-stage signal processing. While sophisticated tools for Monte Carlo simulation have been developed for radiation transport, emulating signal processing and data loss must be accomplished using a simplified model of the electronics called the digitizer. Due to a large number of free parameters, calibrating a digitizer quickly becomes an optimisation problem. To address this, we propose a novel technique by which evolutionary algorithms calibrate a digitizer autonomously. We demonstrate this by calibrating six free parameters in a digitizer model for the ADAC Forte. The accuracy of solutions is quantified via a cost function measuring the absolute percent difference between simulated and experimental coincidence count rates across a robust characterisation data set, including three detector configurations and a range of source activities. Ultimately, this calibration produces a count rate response with 5.8% mean difference to the experiment, improving from 18.3% difference when manually calibrated. Using evolutionary algorithms for model calibration is a notable advancement because this method is novel, autonomous, fault-tolerant, and achieved through a direct comparison of simulation to reality. The software used in this work has been made freely available through a GitHub repository.

Deep learning-based segmentation in prostate radiation therapy using Monte Carlo simulated cone-beam computed tomography

PURPOSE

Segmenting organs in cone-beam CT (CBCT) images would allow to adapt the radiotherapy based on the organ deformations that may occur between treatment fractions. However, this is a difficult task because of the relative lack of contrast in CBCT images, leading to high inter-observer variability. Deformable image registration (DIR) and deep-learning based automatic segmentation approaches have shown interesting results for this task in the past years. However, they are either sensitive to large organ deformations, or require to train a convolutional neural network (CNN) from a database of delineated CBCT images, which is difficult to do without improvement of image quality. In this work, we propose an alternative approach: to train a CNN (using a deep learning-based segmentation tool called nnU-Net) from a database of artificial CBCT images simulated from planning CT, for which it is easier to obtain the organ contours.

METHODS

Pseudo-CBCT (pCBCT) images were simulated from readily available segmented planning CT images, using the GATE Monte Carlo simulation. CT reference delineations were copied onto the pCBCT, resulting in a database of segmented images used to train the neural network. The studied segmentation contours were: bladder, rectum, and prostate contours. We trained multiple nnU-Net models using different training: (1) segmented real CBCT, (2) pCBCT, (3) segmented real CT and tested on pseudo-CT (pCT) generated from CBCT with cycleGAN, and (4) a combination of (2) and (3). The evaluation was performed on different datasets of segmented CBCT or pCT by comparing predicted segmentations with reference ones thanks to Dice similarity score and Hausdorff distance. A qualitative evaluation was also performed to compare DIR-based and nnU-Net-based segmentations.

RESULTS

Training with pCBCT was found to lead to comparable results to using real CBCT images. When evaluated on CBCT obtained from the same hospital as the CT images used in the simulation of the pCBCT, the model trained with pCBCT scored mean DSCs of 0.92 ± 0.05, 0.87 ± 0.02, and 0.85 ± 0.04 and mean Hausdorff distance 4.67 ± 3.01, 3.91 ± 0.98, and 5.00 ± 1.32 for the bladder, rectum, and prostate contours respectively, while the model trained with real CBCT scored mean DSCs of 0.91 ± 0.06, 0.83 ± 0.07, and 0.81 ± 0.05 and mean Hausdorff distance 5.62 ± 3.24, 6.43 ± 5.11, and 6.19 ± 1.14 for the bladder, rectum, and prostate contours, respectively. It was also found to outperform models using pCT or a combination of both, except for the prostate contour when tested on a dataset from a different hospital. Moreover, the resulting segmentations demonstrated a clinical acceptability, where 78% of bladder segmentations, 98% of rectum segmentations, and 93% of prostate segmentations required minor or no corrections, and for 76% of the patients, all structures of the patient required minor or no corrections.

CONCLUSION

We proposed to use simulated CBCT images to train a nnU-Net segmentation model, avoiding the need to gather complex and time-consuming reference delineations on CBCT images.

Evaluation of a method based on synthetic data inserted into raw data prior to reconstruction for the assessment of PET scanners

Background

Performance assessment of positron emission tomography (PET) scanners is crucial to guide clinical practice with efficiency. Even though clinical data are the final target, their use to characterize systems response is constrained by the lack of ground truth. Phantom tests overcome this limitation by controlling the object of study, but remain simple and are not representative of patient complexity. The objective of this study is to evaluate the accuracy of a simulation method using synthetic spheres inserted into acquired raw data prior to reconstruction, simulating multiple scenarios in comparison with equivalent physical experiments.

Methods

We defined our experimental framework using the National Electrical Manufacturers Association NU-2 2018 Image Quality standard, but replaced the standard sphere set with more appropriate sizes (4, 5, 6, 8, 10 and 13 mm) better suited to current PET scanner performance. Four experiments, with different spheres-to-background ratios (2:1, 4:1, 6:1 and 8:1), were performed. An additional dataset was acquired with a radioactive background but no activity within the spheres (water only) to establish a baseline. Then, we artificially simulated radioactive spheres to reproduce other experiments using synthetic data inserted into the original sinogram. Images were reconstructed following standard guidelines using ordered subset expectation maximization algorithm along with a Bayesian penalized likelihood algorithm. We first visually compared experimental and simulated images. Afterward, we measured the activity concentration values into the spheres to calculate the mean and maximum recovery coefficients (RC_mean and RC_max) which we used in a quantitative analysis.

Results

No significant visual differences were identified between experimental and simulated series. Mann–Whitney U tests comparing simulated and experimental distributions showed no statistical differences for both RC_mean (P value = 0.611) and RC_max (P value = 0.720). Spearman tests revealed high correlation for RC_mean (ρ = 0.974, P value < 0.001) and RC_max (ρ = 0.974, P value < 0.001) between both datasets. From Bland–Altman plots, we highlighted slight shifts in RC_mean and RC_max of, respectively, 2.1 ± 16.9% and 3.3 ± 22.3%.

Conclusions

We evaluated the efficiency of our hybrid method in faithfully mimicking practical situations producing satisfactory results compared to equivalent experimental data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-022-00496-6.

The OpenGATE ecosystem for Monte Carlo simulation in medical physics

This paper reviews the ecosystem of GATE, an open-source Monte Carlo toolkit for medical physics. Based on the shoulders of Geant4, the principal modules (geometry, physics, scorers) are described with brief descriptions of some key concepts (Volume, Actors, Digitizer). The main source code repositories are detailed together with the automated compilation and tests processes (Continuous Integration). We then described how the OpenGATE collaboration managed the collaborative development of about one hundred developers during almost 20 years. The impact of GATE on medical physics and cancer research is then summarized, and examples of a few key applications are given. Finally, future development perspectives are indicated.

Development of a digital zebrafish phantom and its application to dedicated small-fish PET

Objective. We are developing a small-fish positron emission tomography (PET) scanner dedicated to small aquatic animals relevant for biomedical and biological research, e.g. zebrafish. We plan to use Monte Carlo simulations to optimize its configuration and the required water-filled imaging chambers. Our objectives were: (1) to create a digital 3D zebrafish phantom using conventional micro-CT, (2) include the phantom into a simulated PET environment based on the framework GATE, and (3) investigate the effects of the water environment on the reconstructed images. Approach. To create the phantom, we performed ex vivo measurements of zebrafish specimen using a tabletop micro-CT and compared three methods to fixate the specimen. From segmented micro-CT images we created digital emission and transmission phantoms which were incorporated in GATE via tessellated volumes. Two chamber sizes were considered. For reference, a simulation with the zebrafish in air was implemented. The simulated data were reconstructed using CASToR. For attenuation correction, we used the exact attenuation information or a uniform distribution (only water). Several realizations of each scenario were performed; the reconstructed images were quantitatively evaluated. Main results. Fixation in formalin led to the best soft-tissue contrast at the cost of some specimen deformation. After attenuation correction, no significant differences were found between the reconstructed images. The PET images reflected well the higher uptake simulated in the brain and heart, despite their small size and surrounding background activity; the swim bladder (no activity) was clearly identified. The simplified attenuation map, consisting only of water, slightly worsened the images. Significance. A conventional micro-CT can provide sufficient image quality to generate numerical phantoms of small fish without contrast media. Such phantoms are useful to evaluate in-silico small aquatic animal imaging concepts and develop imaging protocols. Our results support the feasibility of zebrafish PET with an aqueous environment.

Towards efficient Monte Carlo N-Particle simulation of a positron emission tomography (PET) via source volume definition

Monte Carlo N-Particle (MCNP) simulation has been extensively proven in nuclear medicine imaging systems, most notably in designing and optimizing new medical imaging tools. It enables more complicated geometries and the simulation of particles passing through and interacting with materials. However, a relatively long simulation time is a drawback of Monte Carlo simulation, mainly when complex geometry exists. The current study presents an alternative variance reduction technique for a modeled positron emission tomography (PET) camera by reducing the height of the source volume definition while maintaining the geometry of the simulated model. The National Electrical Manufacturers Association (NEMA) of the International Electrotechnical Commission (IEC) PET's phantom was used with a 1 cm diameter and 7 cm height of line source placed in the middle. The first geometry was fully filled the line source with 0.50 mCi radioactivity. In contrast, the second geometry decreased the source definition to 2.4 cm in height, covering 1 cm above and below the sub-block detector level. The source volume definition approach led to a 71% reduction in the total photons to be simulated. Results showed that the proposed variance reduction strategy could produce spatial resolution as precise as fully filled geometry and sped up the simulation time by approximately 65%. Hence, this strategy can be utilized for further PET optimizing simulation studies.

The Accuracy of Cerenkov Photons Simulation in Geant4/Gate Depends on the Parameterization of Primary Electron Propagation

Energetic electrons traveling in a dispersive medium can produce Cerenkov radiation. Cerenkov photons' prompt emission, combined with their predominantly forward emission direction with respect to the parent electron, makes them extremely promising to improve radiation detector timing resolution. Triggering gamma detections based on Cerenkov photons to achieve superior timing resolution is challenging due to the low number of photons produced per interaction. Monte Carlo simulations are fundamental to understanding their behavior and optimizing their pathway to detection. Therefore, accurately modeling the electron propagation and Cerenkov photons emission is crucial for reliable simulation results. In this work, we investigated the physics characteristics of the primary electrons (velocity, energy) and those of all emitted Cerenkov photons (spatial and timing distributions) generated by 511 keV photoelectric interactions in a bismuth germanate crystal using simulations with Geant4/GATE. Geant4 uses a stepwise particle tracking approach, and users can limit the electron velocity change per step. Without limiting it (default Geant4 settings), an electron mean step length of ~250 μm was obtained, providing only macroscopic modeling of electron transport, with all Cerenkov photons emitted in the forward direction with respect to the incident gamma direction. Limiting the electron velocity change per step reduced the electron mean step length (~0.200 μm), leading to a microscopic approach to its transport which more accurately modeled the electron physical properties in BGO at 511 keV. The electron and Cerenkov photons rapidly lost directionality, affecting Cerenkov photons' transport and, ultimately, their detection. Results suggested that a deep understanding of low energy physics is crucial to perform accurate optical Monte Carlo simulations and ultimately use them in TOF PET detectors.

Precision dosimetry in yttrium-90 radioembolization through CT imaging of radiopaque microspheres in a rabbit liver model

PURPOSE

To perform precision dosimetry in yttrium-90 radioembolization through CT imaging of radiopaque microspheres in a rabbit liver model and to compare extracted dose metrics to those produced from conventional PET-based dosimetry.

MATERIALS AND METHODS

A CT calibration phantom was designed containing posts with nominal microsphere concentrations of 0.5 mg/mL, 5.0 mg/mL, and 25.0 mg/mL. The mean Hounsfield unit was extracted from the post volumes to generate a calibration curve to relate Hounsfield units to microsphere concentration. A nominal bolus of 40 mg of microspheres was administered to the livers of eight rabbits, followed by PET/CT imaging. A CT-based activity distribution was calculated through the application of the calibration curve to the CT liver volume. Post-treatment dosimetry was performed through the convolution of yttrium-90 dose-voxel kernels and the PET- and CT-based cumulated activity distributions. The mean dose to the liver in PET- and CT-based dose distributions was compared through linear regression, ANOVA, and Bland-Altman analysis.

RESULTS

A linear least-squares fit to the average Hounsfield unit and microsphere concentration data from the calibration phantom confirmed a strong correlation (r2 > 0.999) with a slope of 14.13 HU/mg/mL. A poor correlation was found between the mean dose derived from CT and PET (r2 = 0.374), while the ANOVA analysis revealed statistically significant differences (p < 10-12) between the MIRD-derived mean dose and the PET- and CT-derived mean dose. Bland-Altman analysis predicted an offset of 15.0 Gy between the mean dose in CT and PET. The dose within the liver was shown to be more heterogeneous in CT than in PET with an average coefficient of variation equal to 1.99 and 1.02, respectively.

CONCLUSION

The benefits of a CT-based approach to post-treatment dosimetry in yttrium-90 radioembolization include improved visualization of the dose distribution, reduced partial volume effects, a better representation of dose heterogeneity, and the mitigation of respiratory motion effects. Post-treatment CT imaging of radiopaque microspheres in yttrium-90 radioembolization provides the means to perform precision dosimetry and extract accurate dose metrics used to refine the understanding of the dose-response relationship, which could ultimately improve future patient outcomes.

Using inverse Laplace transform in positronium lifetime imaging

Positronium (Ps) lifetime imaging is gaining attention to bring out additional biomedical information from positron emission tomography (PET). The lifetime of Psin vivocan change depending on the physical and chemical environments related to some diseases. Due to the limited sensitivity, Ps lifetime imaging may require merging some voxels for statistical accuracy. This paper presents a method for separating the lifetime components in the voxel to avoid information loss due to averaging. The mathematics for this separation is the inverse Laplace transform (ILT), and the authors examined an iterative numerical ILT algorithm using Tikhonov regularization, namely CONTIN, to discriminate a small lifetime difference due to oxygen saturation. The separability makes it possible to merge voxels without missing critical information on whether they contain abnormally long or short lifetime components. The authors conclude that ILT can compensate for the weaknesses of Ps lifetime imaging and extract the maximum amount of information.

Monte Carlo evaluation of hypothetical long axial field-of-view PET scanner using GE discovery MI PET front-end architecture

PURPOSE

The development of total-body PET scanners is of growing interest in the PET community. Investigation into the imaging properties of a hypothetical extended axial field-of-view (AFOV) GE Healthcare SiPM-based Discovery MI (DMI) system architecture has not yet been performed. In this work, we assessed its potential as a whole-body scanner using Monte Carlo simulations. The aim of this work was to (1) develop and validate a Monte Carlo model of a 4-ring scanner and (2) extend its AFOV up to 2 m to evaluate performance gain through NEMA-based evaluation.

METHODS

The DMI 4-ring geometry and its pulse digitization scheme were modeled within the GATE Monte Carlo platform using published literature. The GATE scanner model was validated by comparing results against published NEMA performance measurements. Following the validation of the 4-ring model, the model was extended to simulate 8, 20, 30, and 40-ring systems. Spatial resolution, sensitivity, NECR, and scatter fraction were characterized with modified NEMA NU-2 2018 standards; however, the image quality measurements were not acquired due to computational limitations. Spatial resolutions were simulated for all scanner ring configurations using point sources to examine the effects of parallax errors. NEMA count rates were estimated using a standard 70 cm scatter phantom and an extended version of scatter phantom of length 200 cm with (1-800) MBq of ¹⁸ F for all scanners. Sensitivity was evaluated using NEMA methods with a 70 cm standard and a 200 cm long line source.

RESULTS

The average FWHM of the radial/tangential/axial spatial resolution reconstructed with filtered back-projection at 1 and 10 cm from the scanner center were 3.94/4.10/4.41 mm and 5.29/4.89/5.90 mm for the 4-ring scanner. Sensitivity was determined to be 14.86 cps/kBq at the center of the FOV for the 4-ring scanner using a 70 cm line source. Sensitivity enhancement up to 21-fold and 60-fold were observed for 1 m and 2 m AFOV scanners compared to 4-ring scanner using a 200 cm long line source. Spatial resolution simulations in a 2 m AFOV scanner suggest a maximum degradation of ∼23.8% in the axial resolution compared to the 4-ring scanner. However, the transverse resolution was found to be relatively constant when increasing the axial acceptance angle up to ±70°. The peak NECR was 212.92 kcps at 22.70 kBq/mL with a scatter fraction of 38.9% for a 4-ring scanner with a 70 cm scatter phantom. Comparison of peak NECR using the 200 cm long scatter phantom relative to the 4-ring scanner resulted in a NECR gain of 15 for the 20-ring and 28 for the 40-ring geometry. Spatial resolution, sensitivity, and scatter fraction showed an agreement within ∼7% compared with published measured values.

CONCLUSIONS

The 4-ring DMI scanner simulation was successfully validated against published NEMA measurements. Sensitivity and NECR performance of extended 1 and 2 meters AFOV scanners based upon the DMI architecture were subsequently simulated. Increases in sensitivity and count-rate performance are consistent with prior simulation studies utilizing extensions of the Siemens mCT architecture and published NEMA measurements with the uEXPLORER system. This article is protected by copyright. All rights reserved.

Ultrafast timing enables reconstruction-free positron emission imaging

X-ray and gamma-ray photons are widely used for imaging but require a mathematical reconstruction step, known as tomography, to produce cross-sectional images from the measured data. Theoretically, the back-to-back annihilation photons produced by positron-electron annihilation can be directly localized in three-dimensional space using time-of-flight information without tomographic reconstruction. However, this has not yet been demonstrated due to the insufficient timing performance of available radiation detectors. Here, we develop techniques based on detecting prompt Cerenkov photons, which when combined with a convolutional neural network for timing estimation resulted in an average timing precision of 32 picoseconds, corresponding to a spatial precision of 4.8 mm. We show this is sufficient to produce cross-sectional images of a positron-emitting radionuclide directly from the detected coincident annihilation photons, without using any tomographic reconstruction algorithm. The reconstruction-free imaging demonstrated here directly localizes positron emission, and frees the design of an imaging system from the geometric and sampling constraints that normally present for tomographic reconstruction.

Integration of polarization in the LUTDavis model for optical Monte Carlo simulation in radiation detectors

OBJECTIVE

Cerenkov photons have distinctive features from scintillation photons. Among them is their polarization: their electric field is always perpendicular to the direction of propagation of light and parallel to the plane of incidence. Scintillation photons are instead considered unpolarized.

APPROACH

This study aims at understanding and optimizing the reflectance of polarized Cerenkov photons for optical Monte Carlo simulation of scintillation detectors with Geant4/GATE. First, the Cerenkov emission spectrum and polarization were implemented in the previously developed look-up-table Davis model of crystal reflectance. Next, we modified Geant4/GATE source code to account for scintillation and Cerenkov photons LUTs simultaneously. Then, we performed optical Monte Carlo simulations in BGO using GATE to show the effect of Cerenkov features on the photons' momentum at the photodetector face, using two surface finishes, with and without reflector.

MAIN RESULTS

In this work, we describe the new features added to the algorithm and GATE. We showed that Cerenkov characteristics affect their probability to be reflected/refracted and thus their travel path within a material.

SIGNIFICANCE

We showed the importance of accounting for accurate Cerenkov photons reflectance while performing advanced optical Monte Carlo simulations.

Simulating NEMA characteristics of the modular total-body J-PET scanner-an economic total-body PET from plastic scintillators

The purpose of the presented research is estimation of the performance characteristics of the economic total-body Jagiellonian-PET system (TB-J-PET) constructed from plastic scintillators. The characteristics are estimated according to the NEMA NU-2-2018 standards utilizing the GATE package. The simulated detector consists of 24 modules, each built out of 32 plastic scintillator strips (each with cross section of 6 mm times 30 mm and length of 140 or 200 cm) arranged in two layers in regular 24-sided polygon circumscribing a circle with the diameter of 78.6 cm. For the TB-J-PET with an axial field-of-view (AFOV) of 200 cm, a spatial resolutions (SRs) of 3.7 mm (transversal) and 4.9 mm (axial) are achieved. The noise equivalent count rate (NECR) peak of 630 kcps is expected at 30 kBq cc^-1. Activity concentration and the sensitivity at the center amounts to 38 cps kBq^-1. The scatter fraction (SF) is estimated to 36.2 %. The values of SF and SR are comparable to those obtained for the state-of-the-art clinical PET scanners and the first total-body tomographs: uExplorer and PennPET. With respect to the standard PET systems with AFOV in the range from 16 to 26 cm, the TB-J-PET is characterized by an increase in NECR approximately by factor of 4 and by the increase of the whole-body sensitivity by factor of 12.6 to 38. The time-of-flight resolution for the TB-J-PET is expected to be at the level of CRT = 240 ps full width at half maximum. For the TB-J-PET with an AFOV of 140 cm, an image quality of the reconstructed images of a NEMA IEC phantom was presented with a contrast recovery coefficient and a background variability parameters. The increase of the whole-body sensitivity and NECR estimated for the TB-J-PET with respect to current commercial PET systems makes the TB-J-PET a promising cost-effective solution for the broad clinical applications of total-body PET scanners. TB-J-PET may constitute an economic alternative for the crystal TB-PET scanners, since plastic scintillators are much cheaper than BGO or LYSO crystals and axial arrangement of the strips significantly reduces the costs of readout electronics and SiPMs.

High-throughput, accurate Monte Carlo simulation on CPU hardware for PET applications

Monte Carlo simulations (MCS) represent a fundamental approach to modelling the photon interactions in Positron Emission Tomography (PET). A variety of PET-dedicated MCS tools are available to assist and improve PET imaging applications. Of these, GATE has evolved into one of the most popular software for PET MCS because of its accuracy and flexibility. However, simulations are extremely time-consuming. The use of graphics processing units (GPU) has been proposed as a solution to this, with reported acceleration factors about 400-800. These factors refer to GATE benchmarks performed on a single CPU core. Consequently, CPU-based MCS can also be easily accelerated by one order of magnitude or beyond when exploiting multi-threading on powerful CPUs. Thus, CPU-based implementations become competitive when further optimisations can be achieved. In this context, we have developed a novel, CPU-based software called the PET Physics Simulator (PPS), which combines several efficient methods to significantly boost the performance. PPS flexibly applies GEANT4 cross-sections as a pre-calculated database, thus obtaining results equivalent to GATE. This is demonstrated for an elaborated PET scanner with 3-layer block detectors. All code optimisations yield an acceleration factor of  20 (single core). Multi-threading on a high-end CPU workstation (96 cores) further accelerates the PPS by a factor of 80. This results in a total speed-up factor of 1600, which outperforms comparable GPU-based MCS by a factor of  2. Optionally, the proposed method of coincidence multiplexing can further enhance the throughput by an additonal factor of 15. The combination of all optimisations corresponds to an acceleration factor of  24000. In this way, the PPS can simulate complex PET detector systems with an effective throughput of photon pairs in less than 10 milliseconds.