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Mapping of the position map to DOIs via look-up table. For example, all the position responses that are at (or near) the red rectangular dots are identified as occuring in layer 4.
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The purpose of this work is to develop a validated Geant4 simulation model of a whole-body prototype PET scanner constructed from the four-layer depth-of-interaction detectors developed at the National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Japan. The simulation model emulates th...
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... Overall, it is important to optimize all these parameters for obtaining good quality reconstructed image. Considering the challenges involved in optimization of these parameters experimentally, it is advantageous to use Monte Carlo simulations to understand the response of the detector setup for nuclear radiation and then to optimize the imaging parameters [1]. A variety of simulation toolkits, such as GATE, SimSET, GAMOS, PeneloPET are available for this purpose. ...
Positrons emitted from radioisotope quickly annihilates to two collinear photons that are captured by the array of scintillator detectors to infer about the origin of radioactivity. Coincidence collection of pair of points from the detector modules makes a line of response, their large number reveals a radioactive region of interest. Most of the medical diagnostic research is conducted with position sensitive imaging device whose performance strongly depends on the optical light collection efficiency. A versatile Lutetium–Yttrium Oxyorthosilicate (LYSO) scintillator is used to mimic the optical photon production and transport processes followed by the light collection with Silicon PhotoMultiplier sensor. Charge spectrum from a 2 × 2 × 10 mm ³ single LYSO bar is obtained in GEANT4, and reproduces well the scintillation characteristics of LYSO along with photons incidence angle distribution with a single SiPM pad. This excercise is followed by the simulation performance of two PET modules comprises of 12 × 12 SiPM tile coupled with mesh of LYSO bars. The preliminarly results shows the transverse position resolution (FWHM) as 7.82 mm for a point source. Objective of this study is to search for a cheaper detector solution which will have equivalent imaging performance.
... Two main procedures in nuclear imaging are single-photon emission computed tomography (SPECT) and Compton imaging systems, both of which use gamma-ray emitting radioactive nuclei [1,2]. Positron emission tomography (PET) uses positron-emitting radioisotopes as radioactive materials [3]. ...
Compton cameras detect scattered gamma rays and estimate the distribution of gamma-ray sources. Nonetheless, crafting a camera tailored to a specific application presents formidable challenges, often necessitating the implementation of diverse image reconstruction techniques. Delving into the factors influencing these cameras can pave the way for design optimization and performance enhancement. This study introduces an inventive detector design for Compton imaging systems, building upon the achievements of prior designs. The proposed system contains eight scatterer detectors and a semiconductor absorber detector, spaced at 1 mm and 30 mm intervals, respectively. The source-to-first-scatterer-detector distance is 5 mm, with scatterer and absorber detector plates measuring 70× 70× 2.125 mm3 and 70× 70× 10 mm3, respectively. Geant4 simulation toolkit models the Compton imaging system, and an analytical method reconstructs Compton camera images. Unlike more straightforward techniques, the analytical method directly reconstructs Compton camera images by solving the equation relating to the reflected image data. This approach is implemented in the C++ programming language. The study's findings reveal that the analytical method discerns optimal conditions and parameters that significantly influence efficiency, yielding a full width at half maximum (FWHM) of 3.7 mm with an angular uncertainty of approximately 2.7 degrees at an energy level of 0.662 MeV. Compared to another experimental design employing the analytical image reconstruction approach, the FWHM value decreased by 0.7 mm. This study presents an innovative detector design and an analytical reconstruction method for Compton imaging systems, showcasing improved efficiency and accuracy.
... In addition to detector development, Monte Carlo simulations are widely used to simulate complete clinical and preclinical imaging systems (Ricci et al 2019, Ahmed et al 2020, Sarrut et al 2021a, Sanaat et al 2022, Zaidi and Andreo 2022. Detailed and complete system optical simulations of these systems, often composed of hundreds or thousands of scintillators, are computationally prohibitive and thus are always limited to the analysis of the first interaction gamma points to study the system performance (Gu et al 2015, Abbaszadeh et al 2018, Borghi et al 2018, Surti and Karp 2018. ...
Detailed simulation of optical photon transport and detection in radiation detectors is often used for crystal-based gamma detector optimization. However, the time and memory burden associated with the track-wise approach to particle transport and detection in commonly used Monte Carlo codes makes optical simulation prohibitive at a system level, where hundreds to thousands of scintillators must be modeled. Consequently, current large system simulations do not include detailed detector models to analyze the potential performance gain with new radiation detector technologies. Generative Adversarial Networks are explored as a tool to speed up the optical simulation of crystal-based detectors. These networks learn training datasets made of high-dimensional data distributions. Once trained, the resulting model can produce distributions belonging to the training data probability distribution. In this work, we present the proof of concept of using a Generative Adversarial Network to enable high-fidelity optical simulations of nuclear medicine systems, mitigating their computational complexity. The architecture of the first network version and high-fidelity training dataset is discussed. The latter is generated through accurate optical simulation with GATE/Geant4, and contains the position, direction, and energy distributions of the optical photons emitted by 511 keV gamma rays in bismuth germanate and detected on the photodetector face. We compare the GAN and simulation-generated distributions in terms of similarity using the Jensen-Shannon distance. Excellent agreement was found with similarity values higher than 93.5% for all distributions. Moreover, the GAN speeded the optical photon distribution generation by up to 2 orders of magnitude. These very promising results have the potential to drastically change the use of nuclear imaging system optical simulations by enabling high-fidelity system-level simulations in reasonable computation times. The ultimate is to integrate the GAN within GATE/Geant4 since numerous applications (large detectors, bright scintillators, Cerenkov-based timing positron emission tomography) can benefit from these improvements.
... Several MC toolkits and applications have been developed to support various geometry modeling and scoring functions (Rogers et al 1995, Agostinelli et al 2003, Forster et al 2004, Battistoni et al 2007. Among these, Geant4 is a general-purpose toolkit with well-established physics models, which has been widely used in medical applications (Spiga et al 2007, Sardari et al 2010, Ahmed et al 2020. However, comprehensive programming knowledge is required to build and run simulations using Geant4. ...
Objective: The TOol for PArticle Simulation (TOPAS) is a Geant4-based Monte Carlo software application that has been used for both research and clinical studies in medical physics. So far, most users of TOPAS have focused on radiotherapy-related studies, such as modeling radiation therapy delivery systems or patient dose calculation. Here, we present the first set of TOPAS extensions to make it easier for TOPAS users to model medical imaging systems.
Approach: We used the extension system of TOPAS to implement pre-built, user-configurable geometry components such as detectors (e.g., flat-panel and multi-planar detectors) for various imaging modalities and pre-built, user-configurable scorers for medical imaging systems (e.g., digitizer chain).
Main Results: We developed a flexible set of extensions that can be adapted to solve research questions for a variety of imaging modalities. We then utilized these extensions to model specific examples of cone-beam CT (CBCT), positron emission tomography (PET), and prompt gamma (PG) systems. The first of these new geometry components, the FlatImager, was used to model example CBCT and PG systems. Detected signals were accumulated in each detector pixel to obtain the intensity of X-rays penetrating objects or prompt gammas from proton-nuclear interaction. The second of these new geometry components, the RingImager, was used to model an example PET system. Positron-electron annihilation signals were recorded in crystals of the RingImager and coincidences were detected. The simulated data were processed using corresponding post-processing algorithms for each modality and obtained results in good agreement with the expected true signals or experimental measurement.
Significance: The newly developed extension is a first step to making it easier for TOPAS users to build and simulate medical imaging systems. Together with existing TOPAS tools, this extension can help integrate medical imaging systems with radiotherapy simulations for image-guided radiotherapy.
... For instance, these simulations can help optimize clinical protocols and assess the impact of scanner parameters on the resulting image quality. [4][5][6] The advantage of using simulations is that these types of tests can be run without the associated costs of taking physical measurements. ...
... 6 Lastly, Geant4 simulations were validated when modeling a whole-body PET scanner prototype that was constructed from four-layer depth-of -interaction detectors. 5 To develop a large PET dataset for the purpose of testing deep learning data manipulation techniques, a GATE simulation of a PET system was developed. Due to the wide accessibility of a Biograph 40 mCT PET/CT system (Siemens Healthineers), this scanner was modeled so that future developments can be transferred to the available clinical data. ...
Background: Monte Carlo (MC) simulations are a powerful tool to model medical imaging systems. However, before simulations can be considered the ground truth, they have to be validated with experiments.
Purpose: To provide a pipeline that models a clinical positron emission tomography (PET)/CT system using MC simulations after extensively validating the results against experimental measurements.
Methods: A clinical four‐ring PET imaging system was modeled using Geant4 application for tomographic emission (v. 9.0). To validate the simulations, PET images were acquired of a cylindrical phantom, point source, and image quality phantom with the modeled system and the simulations of the experimental procedures. For the purpose of validating the quantification capabilities and image quality provided by the simulation pipeline, the simulations were compared against the measurements in terms of their count rates and sensitivity as well as their image uniformity, resolution, recovery coefficients (RCs), coefficients of variation, contrast, and background variability.
Results: When compared to the measured data, the number of true detections in the MC simulations was within 5%. The scatter fraction was found to be 30.0% ± 2.2% and 28.8% ± 1.7% in the measured and simulated scans, respectively. Analyzing the measured and simulated sinograms, the sensitivities were found to be 8.2 and 7.8 cps/kBq, respectively. The fraction of random coincidences were 19% in the measured data and 25% in the simulation. When calculating the image uniformity within the axial slices, the measured image exhibited a uniformity of 0.015 ± 0.005, whereas the simulated image had a uniformity of 0.029 ± 0.011. In the axial direction, the uniformity was measured to be 0.024 ± 0.006 and 0.040 ± 0.015 for the measured and simulated data, respectively. Comparing the image resolution, an average percentage difference of 2.9% was found between the measurements and simulations. The RCs calculated in both the measured and simulated images were found to be within the EARL ranges, except for that of the simulation of the smallest sphere. The coefficients of variation for the measured and simulated images were found to be 12% and 13%, respectively. Lastly, the background variability was consistent between the measurements and simulations, whereas the average percentage difference in the sphere contrasts was found to be 8.8%.
Conclusion: The clinical PET/CT system was modeled and validated to provide a simulation pipeline for the community. The pipeline and the validation procedures have been made available (https://github.com/teaghan/PET_MonteCarlo).
... The pitch size of the GSOZ arrays is 2.85 mm, and Hamamatsu H8500 position-sensitive PMTs are used as photodetectors. Depth of interaction is determined using a light-sharing method in which the optical photon distributions arriving at the PMT are modified via the insertion of radial reflectors in the crystal array with different patterns for each layer, providing a 7.5 mm DOI information [54,55]. The measured sensitivity is 16.7% at the center of the scanner using a 400-600 keV energy window. ...
Positron emission tomography (PET) is the most sensitive in vivo molecular imaging technique available. Small animal PET has been widely used in studying pharmaceutical biodistribution and disease progression over time by imaging a wide range of biological processes. However, it remains true that almost all small animal PET studies using mouse or rat as preclinical models are either limited by the spatial resolution or the sensitivity (especially for dynamic studies), or both, reducing the quantitative accuracy and quantitative precision of the results. Total-body small animal PET scanners, which have axial lengths longer than the nose-to-anus length of the mouse/rat and can provide high sensitivity across the entire body of mouse/rat, can realize new opportunities for small animal PET. This article aims to discuss the technical opportunities and challenges in developing total-body small animal PET scanners for mice and rats.
... Single-photon emission computed tomography (SPECT) and Compton imaging systems are two well-known examples of single-photon imaging of radioactive nuclei that decay by emitting gamma rays [1,2]. Positron emission tomography (PET) uses positron-emitting radioisotopes as radioactive materials [3]. ...
In recent years, Compton cameras that use electronic collimators have become common. One or more scatterer detectors and an absorber detector make up the Compton camera, which is sensitive to the energy and location of scattered gamma rays. It predicts the distribution of gamma-ray sources by reflecting all valid events in the image space using conical surfaces. Compton cameras are designed for specific applications and image reconstruction using various methods.
Based on studies on the efficiency of the Compton camera, the current work provides a novel detector design that includes scatterer and absorber detectors. This design includes eight scatterer detectors spaced 1 mm apart and an absorber detector 30 mm from the last scatterer detector. The distance between the source and the first scatterer detector was 5 mm. The scatterer and absorber detector plates were 70*70*2.125mm³ and 70*70*10mm³, respectively. The Compton imaging system is simulated using the GEANT4 toolkit.
In addition, this study uses an analytical method to reconstruct Compton camera images. The method used for analytical reconstruction in the Compton imaging system differs slightly from simple restoration methods used in other imaging systems. In the analytical method, the equation related to the data reflected by the image must be solved to reconstruct the image directly. This method, the C++ code was developed to reconstruct Compton camera images.
According to the results, using the analytical method to identify the best circumstances and the parameters impacting efficiency, the value of FWHM achieved was 3.7 mm with an angular uncertainty of about 2.7 at an energy of 0.662 MeV. Furthermore, the FWHM value decreased by 0.7 mm, compared to another (experimental) design that employed the analytical image reconstruction approach.
... Single-photon emission computed tomography (SPECT) and Compton imaging systems are two well-known examples of single-photon imaging of radioactive nuclei that decay by emitting gamma rays [1,2]. Positron emission tomography (PET) uses positron-emitting radioisotopes as radioactive materials [3]. ...
In recent years, Compton cameras that use electronic collimators have become common. One or more scatterer detectors and an absorber detector make up the Compton camera, which is sensitive to the energy and location of scattered gamma rays. It predicts the distribution of gamma-ray sources by reflecting all valid events in the image space using conical surfaces. Compton cameras are designed for specific applications and image reconstruction using various methods.
Based on studies on the efficiency of the Compton camera, the current work provides a novel detector design that includes scatterer and absorber detectors. This design includes eight scatterer detectors spaced 1 mm apart and an absorber detector 30 mm from the last scatterer detector. The distance between the source and the first scatterer detector was 5 mm. The scatterer and absorber detector plates were 70x70x2.125mm³ and 70x70x10mm³, respectively. The Compton imaging system is simulated using the GEANT4 toolkit.
In addition, this study uses an analytical method to reconstruct Compton camera images. The method used for analytical reconstruction in the Compton imaging system differs slightly from simple restoration methods used in other imaging systems. In the analytical method, the equation related to the data reflected by the image must be solved to reconstruct the image directly. This method, the C + + code was developed to reconstruct Compton camera images.
According to the results, using the analytical method to identify the best circumstances and the parameters impacting efficiency, the value of FWHM achieved was 3.7 mm with an angular uncertainty of about 2.7 at an energy of 0.662 MeV. Furthermore, the FWHM value decreased by 0.7 mm, compared to another (experimental) design that employed the analytical image reconstruction approach.
... Single-photon emission computed tomography (SPECT) and the Compton imaging system are two well-known examples of single-photon imaging of radioactive nuclei that decay by emitting a gamma-ray [1,2]. Another method, positron emission tomography (PET), uses positron-emitting radioisotopes as radioactive material [3]. ...
Compton cameras have become widespread in recent years because it uses electronic collimators. One or more scatterer detectors and an absorber detector make up the Compton camera, which is sensitive to the energy and location of scattered gamma rays. It predicts the distribution of gamma-ray sources by reflecting all valid events in the image space using conical surfaces. Compton cameras are designed for specific applications and image reconstruction using various methods.
Based on studies of the efficiency of the Compton camera, the current work provides a novel detector design that includes scatterer and absorber detectors. The Compton imaging system is simulated using the GEANT4 toolkit.
In addition, this research uses an analytical method to reconstruct the Compton camera image. The method used for analytical reconstruction in the Compton imaging system differs slightly from the simple restoration methods used in other imaging systems. In the analytical method, the equation related to the data reflected by the image must be solved to reconstruct the image directly. In this method, C + + code required development to reconstruct images using the Compton camera.
According to the results, using the analytical method to identify the best circumstances and the parameters impacting efficiency, the value of FWHM achieved was 3.7 mm with an angular uncertainty of about 2.7 at an energy of 0.662 MeV. Furthermore, the value of FWHM was decreased by 0.7 mm, compared to another (experimental) design that employed the analytical image reconstruction approach.
... Single-photon emission computed tomography (SPECT) and Compton imaging systems are two well-known examples of single-photon imaging of radioactive nuclei that decay by emitting gamma rays [1,2]. Positron emission tomography (PET) uses positron-emitting radioisotopes as radioactive materials [3]. ...
In recent years, Compton cameras that use electronic collimators have become common. One or more scatterer detectors and an absorber detector make up the Compton camera, which is sensitive to the energy and location of scattered gamma rays. It predicts the distribution of gamma-ray sources by reflecting all valid events in the image space using conical surfaces. Compton cameras are designed for specific applications and image reconstruction using various methods.
Based on studies on the efficiency of the Compton camera, the current work provides a novel detector design that includes scatterer and absorber detectors. This design includes eight scatterer detectors spaced 1 mm apart and an absorber detector 30 mm from the last scatterer detector. The distance between the source and the first scatterer detector was 5 mm. The scatterer and absorber detector plates were 70x70x2.125mm³ and 70x70x10mm³, respectively. The Compton imaging system is simulated using the GEANT4 toolkit.
In addition, this study uses an analytical method to reconstruct Compton camera images. The method used for analytical reconstruction in the Compton imaging system differs slightly from simple restoration methods used in other imaging systems. In the analytical method, the equation related to the data reflected by the image must be solved to reconstruct the image directly. This method, the C + + code was developed to reconstruct Compton camera images.
According to the results, using the analytical method to identify the best circumstances and the parameters impacting efficiency, the value of FWHM achieved was 3.7 mm with an angular uncertainty of about 2.7 at an energy of 0.662 MeV. Furthermore, the FWHM value decreased by 0.7 mm, compared to another (experimental) design that employed the analytical image reconstruction approach.
