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Valdes-Cortez, C., Ballester, F., Vijande, J., Gimenez, V., Gimenez-Alventosa, V., Perez-Calatayud, J., et al. (2020). Depth-dose measurement corrections for the surface electronic brachytherapy beams of an Esteya(R) unit: a Monte Carlo study. Phys. Med. Biol., 65(24), 245026–12pp.
Abstract: Three different correction factors for measurements with the parallel-plate ionization chamber PTW T34013 on the Esteya electronic brachytherapy unit have been investigated. This chamber type is recommended by AAPM TG-253 for depth-dose measurements in the 69.5 kV x-ray beam generated by the Esteya unit. Monte Carlo simulations using the PENELOPE-2018 system were performed to determine the absorbed dose deposited in water and in the chamber sensitive volume at different depths with a Type A uncertainty smaller than 0.1%. Chamber-to-chamber differences have been explored performing measurements using three different chambers. The range of conical applicators available, from 10 to 30 mm in diameter, has been explored. Using a depth-independent global chamber perturbation correction factor without a shift of the effective point of measurement yielded differences between the absorbed dose to water and the corrected absorbed dose in the sensitive volume of the chamber of up to 1% and 0.6% for the 10 mm and 30 mm applicators, respectively. Calculations using a depth-dependent perturbation factor, including or excluding a shift of the effective point of measurement, resulted in depth-dose differences of about +/- 0.5% or less for both applicators. The smallest depth-dose differences were obtained when a shift of the effective point of measurement was implemented, being displaced 0.4 mm towards the center of the sensitive volume of the chamber. The correction factors were obtained with combined uncertainties of 0.4% (k = 2). Uncertainties due to chamber-to-chamber differences are found to be lower than 2%. The results emphasize the relevance of carrying out detailed Monte Carlo studies for each electronic brachytherapy device and ionization chamber used for its dosimetry.
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Valdes-Cortez, C., Mansour, I., Rivard, M. J., Ballester, F., Mainegra-Hing, E., Thomson, R. M., et al. (2021). A study of Type B uncertainties associated with the photoelectric effect in low-energy Monte Carlo simulations. Phys. Med. Biol., 66(10), 105014–14pp.
Abstract: Purpose. To estimate Type B uncertainties in absorbed-dose calculations arising from the different implementations in current state-of-the-art Monte Carlo (MC) codes of low-energy photon cross-sections (<200 keV). Methods. MC simulations are carried out using three codes widely used in the low-energy domain: PENELOPE-2018, EGSnrc, and MCNP. Three dosimetry-relevant quantities are considered: mass energy-absorption coefficients for water, air, graphite, and their respective ratios; absorbed dose; and photon-fluence spectra. The absorbed dose and the photon-fluence spectra are scored in a spherical water phantom of 15 cm radius. Benchmark simulations using similar cross-sections have been performed. The differences observed between these quantities when different cross-sections are considered are taken to be a good estimator for the corresponding Type B uncertainties. Results. A conservative Type B uncertainty for the absorbed dose (k = 2) of 1.2%-1.7% (<50 keV), 0.6%-1.2% (50-100 keV), and 0.3% (100-200 keV) is estimated. The photon-fluence spectrum does not present clinically relevant differences that merit considering additional Type B uncertainties except for energies below 25 keV, where a Type B uncertainty of 0.5% is obtained. Below 30 keV, mass energy-absorption coefficients show Type B uncertainties (k = 2) of about 1.5% (water and air), and 2% (graphite), diminishing in all materials for larger energies and reaching values about 1% (40-50 keV) and 0.5% (50-75 keV). With respect to their ratios, the only significant Type B uncertainties are observed in the case of the water-to-graphite ratio for energies below 30 keV, being about 0.7% (k = 2). Conclusions. In contrast with the intermediate (about 500 keV) or high (about 1 MeV) energy domains, Type B uncertainties due to the different cross-sections implementation cannot be considered subdominant with respect to Type A uncertainties or even to other sources of Type B uncertainties (tally volume averaging, manufacturing tolerances, etc). Therefore, the values reported here should be accommodated within the uncertainty budget in low-energy photon dosimetry studies.
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Zhang, X., Xiao, Y. T., & Gimeno, B. (2020). Multipactor Suppression by a Resonant Static Magnetic Field on a Dielectric Surface. IEEE Trans. Electron Devices, 67(12), 5723–5728.
Abstract: In this article, we study the suppression of the multipactor phenomenon on a dielectric surface by a resonant static magnetic field. A homemade Monte Carlo algorithm is developed for multipactor simulations on a dielectric surface driven by two orthogonal radio frequency (RF) electric field components. When the static magnetic field is perpendicular to the tangential and normal RF electric fields, it is shown that if the normal electric field lags the tangential electric field by pi/2, the superposition of the normal and tangential electric fields will trigger a gyro-acceleration of the electron cloud and restrain the multipactor discharge effectively. By contrast, when the normal electric field is in advance of the tangential electric field by pi/2, the difference between the normal and tangential electric fields drives gyro-motion of the electron cloud. Consequently, two enhanced discharge zones are inevitable. The suppression effects of the resonant static magnetic field that is parallel to the tangential RF electric field or to the normal RF electric field are also presented.
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Roser, J., Barrientos, L., Bernabeu, J., Borja-Lloret, M., Muñoz, E., Ros, A., et al. (2022). Joint image reconstruction algorithm in Compton cameras. Phys. Med. Biol., 67(15), 155009–15pp.
Abstract: Objective. To demonstrate the benefits of using an joint image reconstruction algorithm based on the List Mode Maximum Likelihood Expectation Maximization that combines events measured in different channels of information of a Compton camera. Approach. Both simulations and experimental data are employed to show the algorithm performance. Main results. The obtained joint images present improved image quality and yield better estimates of displacements of high-energy gamma-ray emitting sources. The algorithm also provides images that are more stable than any individual channel against the noisy convergence that characterizes Maximum Likelihood based algorithms. Significance. The joint reconstruction algorithm can improve the quality and robustness of Compton camera images. It also has high versatility, as it can be easily adapted to any Compton camera geometry. It is thus expected to represent an important step in the optimization of Compton camera imaging.
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Borys, D. et al, & Brzezinski, K. (2022). ProTheRaMon-a GATE simulation framework for proton therapy range monitoring using PET imaging. Phys. Med. Biol., 67(22), 224002–15pp.
Abstract: Objective. This paper reports on the implementation and shows examples of the use of the ProTheRaMon framework for simulating the delivery of proton therapy treatment plans and range monitoring using positron emission tomography (PET). ProTheRaMon offers complete processing of proton therapy treatment plans, patient CT geometries, and intra-treatment PET imaging, taking into account therapy and imaging coordinate systems and activity decay during the PET imaging protocol specific to a given proton therapy facility. We present the ProTheRaMon framework and illustrate its potential use case and data processing steps for a patient treated at the Cyclotron Centre Bronowice (CCB) proton therapy center in Krakow, Poland. Approach. The ProTheRaMon framework is based on GATE Monte Carlo software, the CASToR reconstruction package and in-house developed Python and bash scripts. The framework consists of five separated simulation and data processing steps, that can be further optimized according to the user's needs and specific settings of a given proton therapy facility and PET scanner design. Main results. ProTheRaMon is presented using example data from a patient treated at CCB and the J-PET scanner to demonstrate the application of the framework for proton therapy range monitoring. The output of each simulation and data processing stage is described and visualized. Significance. We demonstrate that the ProTheRaMon simulation platform is a high-performance tool, capable of running on a computational cluster and suitable for multi-parameter studies, with databases consisting of large number of patients, as well as different PET scanner geometries and settings for range monitoring in a clinical environment. Due to its modular structure, the ProTheRaMon framework can be adjusted for different proton therapy centers and/or different PET detector geometries. It is available to the community via github (Borys et al 2022).
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