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An accurate knowledge of in vivo proton dose distribution is key to fully utilizing the potential advantages of proton therapy. Two representative indirect methods for in vivo range verification, namely, prompt gamma (PG) imaging and positron emission tomography (PET), are available. This study proposes a PG-PET system that combines the advantages...
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Online ion range monitoring in hadron therapy can be performed via detection of secondary radiation, such as prompt γ-rays, emitted during treatment. The prompt γ emission profile is correlated with the ion depth-dose profile and can be reconstructed via Compton imaging. The line-cone reconstruction, using the intersection between the primary beam...
Citations
... The coded-aperture approach uses a multi-hole mask for the reconstruction of gamma imaging [69]. Coded-aperture imaging involves encoding and decoding processes. ...
Accurate in-vivo verification of beam range and dose distribution is crucial for the safety and effectiveness of particle therapy. Prompt gamma (PG) imaging, as a method for real-time verification, has gained prominence in this area. Currently, several PG imaging systems are under development, including gamma electron vertex imaging (GEVI), the Compton camera, the slit camera, and the multi-array type collimator camera. However, challenges persist in dose prediction accuracy, largely due to patient positioning uncertainty and anatomical changes. Although each system demonstrates potential in verifying PG range, further improvements in detection efficiency, spatial resolution, background reduction, and integration into clinical workflows are essential.
... A direct comparison of the performances of these three methods would be valuable to understand their advantages and disadvantages as well as to create possible combinations to compensate for the disadvantages of each method. In previous research, a system to measure prompt gamma photons and positron distribution was proposed (Choi L et al 2020, Parodi et al 2023 and a system to measure prompt x-ray and positron distribution was developed (Yamamoto et al 2023). ...
Objective. Prompt gamma photon, prompt x-ray, and induced positron imaging are possible methods for observing a proton beam’s shape from outside the subject. However, since these three types of images have not been measured simultaneously nor compared using the same subject, their advantages and disadvantages remain unknown for imaging beam shapes in therapy. To clarify these points, we developed a triple-imaging-modality system to simultaneously measure prompt gamma photons, prompt x-rays, and induced positrons during proton beam irradiation to a phantom. Approach. The developed triple-imaging-modality system consists of a gamma camera, an x-ray camera, and a dual-head positron emission tomography (PET) system. During 80 MeV proton beam irradiation to a polymethyl methacrylate (PMMA) phantom, imaging of prompt gamma photons was conducted by the developed gamma camera from one side of the phantom. Imaging of prompt x-rays was conducted by the developed x-ray camera from the other side. Induced positrons were measured by the developed dual-head PET system set on the upper and lower sides of the phantom. Main results. With the proposed triple-imaging-modality system, we could simultaneously image the prompt gamma photons and prompt x-rays during proton beam irradiation. Induced positron distributions could be measured after the irradiation by the PET system and the gamma camera. Among these imaging modalities, image quality was the best for the induced positrons measured by PET. The estimated ranges were actually similar to those imaged with prompt gamma photons, prompt x-rays and induced positrons measured by PET. Significance. The developed triple-imaging-modality system made possible to simultaneously measure the three different beam images. The system will contribute to increasing the data available for imaging in therapy and will contribute to better estimating the shapes or ranges of proton beam.
... Nuclear activation during irradiation generates positron emitter fragments which may be used for range verification (Kraan 2015, Bauert et al 2019, Masuda et al 2020. MC simulations of PET signals are required to have a reliable estimation of detector response and proton range reconstruction in clinical scenarios , Choi et al 2020, Onecha et al 2022. ...
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 @ 3.30GHz.
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 system response matrix estimation for complex scanners, or even MC iterative image reconstruction.
... Several solutions have been proposed to address the range verification in proton therapy to assess the compliance between the delivered and prescribed dose [5][6][7]. Instruments based on Prompt-Gamma (PG) detection have been investigated using Monte Carlo (MC) simulation for range verification in PT [8][9][10]. PG rays are promptly emitted after beam interactions with matter and have a wide energy spectrum ranging from 1 to 8 MeV [11]. ...
Purpose: Gamma cameras are one of the most promising technologies for in-vivo range monitoring in proton therapy. Monte Carlo (MC) simulation is a common calculation-based technique to design and optimize gamma cameras. However, it is prohibitively time-consuming. Analytical modeling speeds up the process of finding the optimal design. Materials and Methods: We proposed an analytical method using the efficiency-resolution trade-off for optimizing a knife-edge collimator based on the range retrieval precision of protons. Monte Carlo simulation was used for validation of obtained collimator efficiencies. Results: The model predicts that for the optimal range retrieval precision, the ratio of the source-to-detector distance to the source-to-collimator distance should be ranging from . For a special case, it was found that assuming an ideal detector , the falloff retrieval precision is optimal at independent of the collimator resolution. Moreover, using the optimized camera, the difference between the MC calculated range and the absolute range was 0.5 cm (the relative error is about 3%). Conclusion: It was found that the collimator parameters are in good agreement in comparison with that of the MC results reported in the literature. The analytical method studied in this work can be used to design and optimize imaging systems based on KE collimators in combination with new detectors in a fast and reliable way.
... The most prominent methods are based on prompt gamma (PG) detection, e.g., (Kurosawa et al. 2012;Smeets et al. 2012). There are also efforts to utilize neutrons (Clarke et al. 2016;Marafini et al. 2017), or a combination of modalities, e.g., PG and PET (Moteabbed et al. 2011;Choi et al. 2020). When using heavier ions for treatment, it is possible to use tracked secondary charged particles for in-situ range verification through interaction vertex imaging (Amaldi et al. 2010;Henriquet et al. 2012;Gwosch et al. 2013). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t ...
Objective. Proton therapy is highly sensitive to range uncertainties due to the nature of the dose deposition of charged particles. To ensure treatment quality, range verification methods can be used to verify that the individual spots in a pencil beam scanning treatment fraction match the treatment plan. This study introduces a novel metric for proton therapy quality control based on uncertainties in range verification of individual spots.
Approach. We employ uncertainty-aware deep neural networks to predict the Bragg peak depth in an anthropomorphic phantom based on secondary charged particle detection in a silicon pixel telescope designed for proton computed tomography. The subsequently predicted Bragg peak positions, along with their uncertainties, are compared to the treatment plan, rejecting spots which are predicted to be outside the 95% confidence interval. The such-produced spot rejection rate presents a metric for the quality of the treatment fraction.
Main results. The introduced spot rejection rate metric is shown to be well-defined for range predictors with well-calibrated uncertainties. Using this method, treatment errors in the form of lateral shifts can be detected down to 1 mm after around 1400 treated spots with spot intensities of 1·10 ⁷ protons. The range verification model used in this metric predicts the Bragg peak depth to a mean absolute error of 1.107 ± 0.015 mm.
Significance. Uncertainty-aware machine learning has potential applications in proton therapy quality control. This work presents the foundation for future developments in this area.
... A system of measuring prompt gamma photons and positron distribution was proposed, and simulation results were reported (Choi et al 2020). However, no real imaging system has been developed, nor have any images been measured. ...
Objective. Prompt x-ray imaging using a low-energy x-ray camera is a promising method for observing a proton beam's shape from outside the subject. Furthermore, imaging of positrons produced by nuclear reactions with protons is a possible method for observing the beam shape. However, it has not been possible to measure these two types of images with a single imaging system due to the limited imaging capability of existing systems. Imaging of both prompt x-rays and the distribution of positrons may compensate for the shortcomings of each method.Approach. We conducted imaging of the prompt x-ray using a pinhole x-ray camera during irradiation with protons in list mode. Then, after irradiation with protons, imaging of annihilation radiations from the produced positrons was conducted using the same pinhole x-ray camera in list mode. After this imaging, list-mode data were sorted to obtain prompt x-ray images and positron images.Main results. With the proposed procedure, we could measure both prompt x-ray images and induced positron images with a single irradiation by a proton beam. From the prompt x-ray images, ranges and widths of the proton beams could be estimated. The distributions of positrons were slightly wider than those of the prompt x-rays. From the time sequential positron images, we could derive the time activity curves of the produced positrons.Significance. Hybrid imaging of prompt x-rays and induced positrons using a pinhole x-ray camera was achieved. The proposed procedure would be useful for measuring prompt x-ray images during irradiation to estimate the beam structures as well as for measuring the induced positron images after irradiation to estimate the distributions and time activity curves of the induced positrons.
... 32 Several research groups have attempted to improve the poor detection efficiency through the construction of multi-head systems. 16,33 Choi et al. designed a hybrid PET-PG system, with parallel hole collimators, capable of 3D imaging from prompt gammas. 33 The collimator weight and the bulky detectors around the patient are a limiting factors in this PGI design. ...
... 16,33 Choi et al. designed a hybrid PET-PG system, with parallel hole collimators, capable of 3D imaging from prompt gammas. 33 The collimator weight and the bulky detectors around the patient are a limiting factors in this PGI design. The PET-PG system as a tomographic camera also suffers from this issue. ...
... 16 to collimator distance. 33 The collimator weight and the bulky detectors around the patient are limiting factors in these deigns. Alternatively, different types of collimators such as slit-slat (SS) can be optimized for 2D imaging. ...
Purpose
We investigated the design of a prompt gamma camera for real‐time dose delivery verification and the partial mitigation of range uncertainties.
Methods
A slit slat (SS) camera was optimized using the trade‐off between the signal‐to‐noise ratio and spatial resolution. Then, using the GATE Monte Carlo package, the camera performances were estimated by means of target shifts, beam position quantification, changing the camera distance from the beam, and air cavity inserting. A homogeneous PMMA phantom and the air gaps induced PMMA phantom were used. The air gaps ranged from 5 mm to 30 mm by 5 mm increments were positioned in the middle of the beam range. To reduce the simulation time, phase space scoring was used. The batch method with five realizations was used for stochastic error calculations.
Results
The system's detection efficiency was 1.1×10−4PGsEmittedPGs(1.8×10−5$1.1 \times {10}^{-4}\frac{{\rm PGs}}{{\rm Emitted}\ {\rm PGs}}\ (1.8 \times {10}^{-5}$ PGs/proton) for a 10 × 20 cm² detector (source‐to‐collimator distance = 15.0 cm). Axial and transaxial resolutions were 23 mm and 18 mm, respectively. The SS camera estimated the range as 69.0 ± 3.4 (relative stochastic error 1‐sigma is 5%) and 67.6 ± 1.8 mm (2.6%) for the real range of 67.0 mm for 10⁷ and 10⁸ protons of 100 MeV, respectively. Considering 160 MeV, these values are 155.5 ± 3.1 (2%) and 152.2 ± 2.0 mm (1.3%) for the real range of 152.0 mm for 10⁷ and 10⁸ protons, respectively. Considering phantom shift, for a 100 MeV beam, the precision of the quantification (1‐sigma) in the axial and lateral phantom shift estimation is 2.6 mm and 1 mm, respectively. Accordingly, the axial and lateral quantification precisions were 1.3 mm and 1 mm for a 160 MeV beam, respectively. Furthermore, the quantification of an air gap formulated as gapdet=0.98×gapreal${{\rm gap}}_{det}=0.98 \times {{\rm gap}}_{{\rm real}}$, where gapdet${{\rm gap}}_{det}$ and gapreal are the estimated and real air gap, respectively. The precision of the air gap quantification is 1.6 mm (1 sigma). Moreover, 2D PG images show the trajectory of the proton beam through the phantom.
Conclusion
The proposed slit‐slat imaging systems can potentially provide a real‐time, in‐vivo, and non‐invasive treatment monitoring method for proton therapy.
In our previous study, we proposed an integrated PG-PET-based imaging method to increase the prediction accuracy for patient dose distributions. The purpose of the present study is to experimentally validate the feasibility of the PG-PET system. Based on the detector geometry optimized in the previous study, we constructed a dual-head PG-PET system consisting of a 16 × 16 GAGG scintillator and KETEK SiPM arrays, BaSO4 reflectors, and an 8 × 8 parallel-hole tungsten collimator. The performance of this system as equipped with a proof of principle, we measured the PG and positron emission (PE) distributions from a 3 × 6 × 10 cm3 PMMA phantom for a 45 MeV proton beam. The measured depth was about 17 mm and the expected depth was 16 mm in the computation simulation under the same conditions as the measurements. In the comparison result, we can find a 1 mm difference between computation simulation and measurement. In this study, our results show the feasibility of the PG-PET system for in-vivo range verification. However, further study should be followed with the consideration of the typical measurement conditions in the clinic application.
