This study aims to evaluate the dose sensitivity of MAGIC-f gel irradiated by high-energy photon beams, comparing quantification using different MRI sequences. Irradiation was performed using 6 MV photons with 600 cGy/min dose rate, field size of 20x20 cm², and 94 cm source-to-surface distance. Two gel batches were produced on different days and placed in vials. In the first batch, doses of 0, 2, 4, 6, 8, 10, 20, and 40 Gy were planned. The second batch was irradiated with doses of 0, 2, 4, 6, 10, 12, 14, and 16 Gy. MR images were acquired with Spin Echo (SE, TR=3 s) and Multi Spin Echo (MSE, TR = 3s or 10s, turbo factor 24) sequences. The dose is assessed via changes in the transverse relaxation time in the irradiated gel. In MSE, dose sensitivity in the first batch was 0.27 (TR=3 s) and 0.28 Gy-1s-1 (TR=10 s) and in the second batch, 0.31 and 0.31 Gy-1s-1 (TR = 3 s and TR = 10 s, respectively). In the SE sequence, dose sensitivity was 0.42 for the first batch and 0.43 Gy-1s-1 for the second batch. Linearity of dose-response was only obtained for doses below 10 Gy. Comparing the dose sensitivity extracted from MSE and SE sequences using TR= 3s, differences around 30% were found. Thus, although MSE-MRI offers a faster protocol of imaging acquisition it is less precise for quantification of relaxation times, as TE is not a well-defined quantity. The performance of the gel as a dosimeter is consequently sequence dependent.
To evaluate the amount of energy deposited in radiosensitive organs and tissues of the human body, when an anthropomorphic phantom is irradiated, researchers in numerical dosimetry use the so-called exposure computational models (ECMs). One can imagine an ECM as a virtual scene composed of a phantom in a mathematically defined position in relation to a radioactive source. The source in these ECMs produces the initial state of the simulation: the position, direction, and energy with which each particle enters the phantom are essential variables. For subsequent states of a particle history, robust Monte Carlo (MC) codes are used. For the subsequent states of a particle's history, robust Monte Carlo (MC) codes are used, which simulate the average free path that the particle performs without interacting, its interaction with the atoms in the medium and the amount of energy deposited per interaction. MC codes also evaluate normalization quantities, so the results are printed in text files in the form of conversion coefficients between the absorbed dose and the selected normalization quantity. From the 2000s, the authors have published ECMs where a voxel phantom is irradiated by photons in the environment of the MC code EGSnrc (EGS = Electron Gamma Shower; nrc = National Research Council Canada). The production of articles, dissertations and theses required the use of specific computational tools, such as the FANTOMAS, DIP (Digital Image Processing) and Monte Carlo applications, for the various steps of numerical dosimetry, which ranges from the preparation of input files to the execution from the ECM to the organization and graphical and numerical analysis of the results. This article reviews computational phantoms for dosimetry mainly those produced in DEN-UFPE dissertations and thesis.
Radiotherapy uses various techniques and equipment for local treatment of cancer. The equipment most often used in radiotherapy to the patient irradiation is linear accelerator (Linac). Among the many algorithms developed for evaluation of dose distributions in radiotherapy planning, the algorithms based on Monte Carlo (MC) methods have proven to be very promising in terms of accuracy by providing more realistic results. The MC simulations for applications in radiotherapy are divided into two parts. In the first, the simulation of the production of the radiation beam by the Linac is performed and then the phase-space is generated. In the second part the simulation of the transport of particles (sampled phase-space) in certain configurations of irradiation field is performed to assess the dose distribution. Accurate modeling of the Linac head is of particular interest in the calculation of dose distributions for intensity modulated radiation therapy (IMRT), where complex intensity distributions are delivered using a multileaf collimator (MLC). The objective of this work is to describe a methodology for modeling MC of MLCs using code Geant4. To exemplify this methodology, the Varian Millennium 120-leaf MLC was modeled. The dosimetric characteristics (i.e., penumbra, leakage, and tongue-and-groove effect) of this MLC were evaluated. The results agreed with data published in the literature concerning the same MLC.
Among the many algorithms developed for evaluation of dose distributions in radiotherapy, the Monte Carlo methods provide more realistic results. In intensity modulated radiation therapy, significant differences in dose distributions within the fields defined by multileaf collimator (MLC) could have significant radiobiology effects. Thus, it is important to model thoroughly the MLC to allow more accurate radiotherapy delivery. The objective of this work is to describe and to validate a methodology for modeling of MLCs using code Geant4. The Varian Millennium 120-leaf MLC was modeled using this methodology and it was experimentally verified. The leaves of the MLC were built using three types of solid (G4Box, G4Tubs and G4ExtrudeSolid) and the Boolean operation of subtraction (G4SubtractionSolid). Based on this methodology, it is possible to simulate other Varian MLC models and MLCs with similar design.
This work describes the development and validation of a simulation platform, called Quimera, based on the Monte Carlo (MC) code Geant4 for dose evaluation in radiotherapy. Quimera consists of two MC applications (qMATphantoms and qNCTphantoms) for dose evaluation from a phase-space and a graphical user interface (qGUI). qMATphantoms is aimed for modeling of physical phantoms used in quality control. NCT phantoms are built from computed tomography (CT) images of patient or physical phantom using a conversion method of CT numbers (NCT). qGUI has the function of creating or editing input files, running the MC applications and ana-lyzing results. MC applications were validated by comparison of dose distributions, whose results were in agreement with the quality assurance standards. qGUI is a differential concerning other Geant4 applications for radiotherapy and can be used for dose distribution analysis from other MC applications. Quimera can be used for research, simple treatment planning and quality assurance in photon beam radiotherapy
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.