1
|
Chacon A, Rutherford H, Hamato A, Nitta M, Nishikido F, Iwao Y, Tashima H, Yoshida E, Akamatsu G, Takyu S, Kang HG, Franklin DR, Parodi K, Yamaya T, Rosenfeld A, Guatelli S, Safavi-Naeini M. A quantitative assessment of Geant4 for predicting the yield and distribution of positron-emitting fragments in ion beam therapy. Phys Med Biol 2024; 69:125015. [PMID: 38776943 DOI: 10.1088/1361-6560/ad4f48] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/22/2024] [Indexed: 05/25/2024]
Abstract
Objective.To compare the accuracy with which different hadronic inelastic physics models across ten Geant4 Monte Carlo simulation toolkit versions can predict positron-emitting fragments produced along the beam path during carbon and oxygen ion therapy.Approach.Phantoms of polyethylene, gelatin, or poly(methyl methacrylate) were irradiated with monoenergetic carbon and oxygen ion beams. Post-irradiation, 4D PET images were acquired and parent11C,10C and15O radionuclides contributions in each voxel were determined from the extracted time activity curves. Next, the experimental configurations were simulated in Geant4 Monte Carlo versions 10.0 to 11.1, with three different fragmentation models-binary ion cascade (BIC), quantum molecular dynamics (QMD) and the Liege intranuclear cascade (INCL++) - 30 model-version combinations. Total positron annihilation and parent isotope production yields predicted by each simulation were compared between simulations and experiments using normalised mean squared error and Pearson cross-correlation coefficient. Finally, we compared the depth of the maximum positron annihilation yield and the distal point at which the positron yield decreases to 50% of peak between each model and the experimental results.Main results.Performance varied considerably across versions and models, with no one version/model combination providing the best prediction of all positron-emitting fragments in all evaluated target materials and irradiation conditions. BIC in Geant4 10.2 provided the best overall agreement with experimental results in the largest number of test cases. QMD consistently provided the best estimates of both the depth of peak positron yield (10.4 and 10.6) and the distal 50%-of-peak point (10.2), while BIC also performed well and INCL generally performed the worst across most Geant4 versions.Significance.The best predictions of the spatial distribution of positron annihilations and positron-emitting fragment production along the beam path during carbon and oxygen ion therapy was obtained using Geant4 10.2.p03 with BIC or QMD. These version/model combinations are recommended for future heavy ion therapy research.
Collapse
Affiliation(s)
- Andrew Chacon
- Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW, Australia
| | - Harley Rutherford
- Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW, Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Akram Hamato
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Munetaka Nitta
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | | | - Yuma Iwao
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Hideaki Tashima
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Eiji Yoshida
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Go Akamatsu
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Sodai Takyu
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Han Gyu Kang
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Daniel R Franklin
- School of Electrical and Data Engineering, University of Technology Sydney, Ultimo, Australia
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Garching b, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Taiga Yamaya
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Anatoly Rosenfeld
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW 2522, Australia
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Susanna Guatelli
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW 2522, Australia
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia
| | - Mitra Safavi-Naeini
- Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW, Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW 2522, Australia
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| |
Collapse
|
2
|
Rutherford H, Saha Turai R, Chacon A, Franklin DR, Mohammadi A, Tashima H, Yamaya T, Parodi K, Rosenfeld AB, Guatelli S, Safavi-Naeini M. An inception network for positron emission tomography based dose estimation in carbon ion therapy. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac88b2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 08/10/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective. We aim to evaluate a method for estimating 1D physical dose deposition profiles in carbon ion therapy via analysis of dynamic PET images using a deep residual learning convolutional neural network (CNN). The method is validated using Monte Carlo simulations of 12C ion spread-out Bragg peak (SOBP) profiles, and demonstrated with an experimental PET image. Approach. A set of dose deposition and positron annihilation profiles for monoenergetic 12C ion pencil beams in PMMA are first generated using Monte Carlo simulations. From these, a set of random polyenergetic dose and positron annihilation profiles are synthesised and used to train the CNN. Performance is evaluated by generating a second set of simulated 12C ion SOBP profiles (one 116 mm SOBP profile and ten 60 mm SOBP profiles), and using the trained neural network to estimate the dose profile deposited by each beam and the position of the distal edge of the SOBP. Next, the same methods are used to evaluate the network using an experimental PET image, obtained after irradiating a PMMA phantom with a 12C ion beam at QST’s Heavy Ion Medical Accelerator in Chiba facility in Chiba, Japan. The performance of the CNN is compared to that of a recently published iterative technique using the same simulated and experimental 12C SOBP profiles. Main results. The CNN estimated the simulated dose profiles with a mean relative error (MRE) of 0.7% ± 1.0% and the distal edge position with an accuracy of 0.1 mm ± 0.2 mm, and estimate the dose delivered by the experimental 12C ion beam with a MRE of 3.7%, and the distal edge with an accuracy of 1.7 mm. Significance. The CNN was able to produce estimates of the dose distribution with comparable or improved accuracy and computational efficiency compared to the iterative method and other similar PET-based direct dose quantification techniques.
Collapse
|
3
|
Ahmed AM, Chacon A, Rutherford H, Akamatsu G, Mohammadi A, Nishikido F, Tashima H, Yoshida E, Yamaya T, Franklin DR, Rosenfeld A, Guatelli S, Safavi-Naeini M. A validated Geant4 model of a whole-body PET scanner with four-layer DOI detectors. ACTA ACUST UNITED AC 2020; 65:235051. [DOI: 10.1088/1361-6560/abaa24] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
|
4
|
Kang HG, Yamamoto S, Takyu S, Nishikido F, Mohammadi A, Akamatsua G, Sato S, Yamaya T. Energy spread estimation of radioactive oxygen ion beams using optical imaging. Phys Med Biol 2020; 65. [DOI: 10.1088/1361-6560/abc304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 10/20/2020] [Indexed: 11/12/2022]
Abstract
Abstract
Radioactive ion (RI) beams combined with in-beam positron emission tomography enable accurate in situ beam range verification in heavy ion therapy. However, the energy spread of the radioactive beams generated as secondary beams is wider than that of conventional stable heavy ion beams which causes Bragg peak region and distal falloff region broadening. Therefore, the energy spread of the RI beams should be measured carefully for their quality control. Here, we proposed an optical imaging technique for the energy spread estimation of radioactive oxygen ion beams. A polymethyl methacrylate phantom (10.0 × 10.0 × 9.9 cm3) was irradiated with an 15O beam (mean energy = 247.7 MeV u−1, standard deviation = 6.8 MeV u−1) in the Heavy Ion Medical Accelerator in Chiba. Three different momentum acceptances of 1%, 2% and 4% were used to get energy spreads of 1.9 MeV u−1, 3.4 MeV u−1 and 5.5 MeV u−1, respectively. The in-beam luminescence light and offline beam Cerenkov light images were acquired with an optical system consisting of a lens and a cooled charge-coupled device camera. To estimate the energy spread of the 15O ion beams, we proposed three optical parameters: (1) distal-50% falloff length of the prompt luminescence signals; (2) full-width at half maximum of the Cerenkov light signals in the beam direction; and (3) positional difference between the peaks of the Cerenkov light and the luminescence signals. These parameters estimated the energy spread with the respective mean squared errors of 2.52 × 10−3 MeV u−1, 5.91 × 10−3 MeV u−1, and 0.182 MeV u−1. The distal-50% falloff length of the luminescence signals provided the lowest mean squared error among the optical parameters. From the findings, we concluded optical imaging using luminescence and Cerenkov light signals offers an accurate energy spread estimation of 15O ion beams. In the future, the proposed optical parameters will be used for energy spread estimation of other RI beams as well as stable ion beams.
Collapse
|
5
|
Rutherford H, Chacon A, Mohammadi A, Takyu S, Tashima H, Yoshida E, Nishikido F, Hofmann T, Pinto M, Franklin DR, Yamaya T, Parodi K, Rosenfeld AB, Guatelli S, Safavi-Naeini M. Dose quantification in carbon ion therapy using in-beam positron emission tomography. ACTA ACUST UNITED AC 2020; 65:235052. [DOI: 10.1088/1361-6560/abaa23] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
|
6
|
Usta M, Aydın G. Use of Gaussian-type functions for flux-based dose calculations in carbon ion therapy. RADIATION AND ENVIRONMENTAL BIOPHYSICS 2020; 59:511-522. [PMID: 32561981 DOI: 10.1007/s00411-020-00856-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 06/08/2020] [Indexed: 06/11/2023]
Abstract
In radiation therapy, it is very important to ensure that the radiation dose is correctly delivered to the patient. This is achieved by obtaining quantitative dose measurements for beam calibration in the treatment planning system. Dose calculations should be performed with the required accuracy to a degree of uncertainty of less than 1%. The measurement of the absorbed dose in and around body tissues irradiated with carbon ions requires careful use of materials selected from established phantom and radiation detectors. The main advantage of such materials is that when information on the energy and nature of charged particles at the desired point is incomplete or inaccurate, they can allow determination of the absorbed dose. In general, radiation interactions in a tissue representation caused by carbon ions can be characterized by calculating the linear stopping power. Carbon ions have a limited penetration depth within human tissues that depends on the energy and stopping power of these ions as they penetrate into the body. The purpose of the present study was to calculate the stopping power, range and dose to intestinal and prostate tissues of carbon ions. The stopping power values of these tissues were specified by the effective charge approach method. The 5ZaPa-NR-CV, pcemd-4 and pcSseg-4 sets of Gaussian-type functions were employed for the calculation of electronic charge density. Range calculations were made by means of the Gaussian quadrature method, making use of the continuous slowing down approximation. Flux-based dose calculations were also carried out in accordance with the Bragg-Gray theorem using the Geant4 and FLUKA simulation toolkits. The results were compared with each other and with the SRIM and CasP datasets. Then, depth-dose distributions and range values were verified by positron emission activity using the GATE toolkit. Among the different types of Gaussian functions used here, the best semi-analytical result was found for the 5ZaPa-NR-CV set. The results obtained in the present study can be used for dose verification and dose reconstruction in charged particle radiotherapy and for radiation research on the interaction of radiation with matter. The results calculated here will be useful for quantifying uncertainties associated with stopping power, range, and reconstruction of dose in charged particle therapy.
Collapse
Affiliation(s)
- Metin Usta
- Department of Physics, Faculty of Arts and Sciences, Mustafa Kemal University, 31034, Hatay, Turkey.
| | - Güral Aydın
- Department of Physics, Faculty of Arts and Sciences, Mustafa Kemal University, 31034, Hatay, Turkey
| |
Collapse
|
7
|
Pinto M, Kröniger K, Bauer J, Nilsson R, Traneus E, Parodi K. A filtering approach for PET and PG predictions in a proton treatment planning system. Phys Med Biol 2020; 65:095014. [PMID: 32191932 DOI: 10.1088/1361-6560/ab8146] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Positron emission tomography (PET) and prompt gamma (PG) detection are promising proton therapy monitoring modalities. Fast calculation of the expected distributions is desirable for comparison to measurements and to develop/train algorithms for automatic treatment error detection. A filtering formalism was used for positron-emitter predictions and adapted to allow for its use for the beamline of any proton therapy centre. A novel approach based on a filtering formalism was developed for the prediction of energy-resolved PG distributions for arbitrary tissues. The method estimates PG yields and their energy spectra in the entire treatment field. Both approaches were implemented in a research version of the RayStation treatment planning system. The method was validated against PET monitoring data and Monte Carlo simulations for four patients treated with scanned proton beams. Longitudinal shifts between profiles from analytical and Monte Carlo calculations were within -1.7 and 0.9 mm, with maximum standard deviation of 0.9 mm and 1.1 mm, for positron-emitters and PG shifts, respectively. Normalized mean absolute errors were within 1.2 and 5.3%. When comparing measured and predicted PET data, the same more complex case yielded an average shift of 3 mm, while all other cases were below absolute average shifts of 1.1 mm. Normalized mean absolute errors were below 7.2% for all cases. A novel solution to predict positron-emitter and PG distributions in a treatment planning system is proposed, enabling calculation times of only a few seconds to minutes for entire patient cases, which is suitable for integration in daily clinical routine.
Collapse
Affiliation(s)
- M Pinto
- Department for Medical Physics, Ludwig-Maximilians-Universität München, Garching, Germany
| | | | | | | | | | | |
Collapse
|