Dosimetry applications in GATE Monte Carlo toolkit
- PMID: 28236558
- DOI: 10.1016/j.ejmp.2017.02.005
Dosimetry applications in GATE Monte Carlo toolkit
Abstract
Purpose: Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies.
Methods: GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy.
Results: GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms.
Conclusions: Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment.
Keywords: Dosimetry; GATE; Monte Carlo simulations; Radiotherapy.
Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Similar articles
-
A dose point kernel database using GATE Monte Carlo simulation toolkit for nuclear medicine applications: comparison with other Monte Carlo codes.Med Phys. 2012 Aug;39(8):5238-47. doi: 10.1118/1.4737096. Med Phys. 2012. PMID: 22894448
-
A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications.Med Phys. 2014 Jun;41(6):064301. doi: 10.1118/1.4871617. Med Phys. 2014. PMID: 24877844 Review.
-
A framework for prediction of personalized pediatric nuclear medical dosimetry based on machine learning and Monte Carlo techniques.Phys Med Biol. 2023 Apr 7;68(8). doi: 10.1088/1361-6560/acc4a5. Phys Med Biol. 2023. PMID: 36921349
-
Preclinical voxel-based dosimetry through GATE Monte Carlo simulation using PET/CT imaging of mice.Phys Med Biol. 2019 Apr 26;64(9):095007. doi: 10.1088/1361-6560/ab134b. Phys Med Biol. 2019. PMID: 30913544
-
Monte Carlo simulations in radiotherapy dosimetry.Radiat Oncol. 2018 Jun 27;13(1):121. doi: 10.1186/s13014-018-1065-3. Radiat Oncol. 2018. PMID: 29945636 Free PMC article. Review.
Cited by
-
Influence of dosimetry method on bone lesion absorbed dose estimates in PSMA therapy: application to mCRPC patients receiving Lu-177-PSMA-I&T.EJNMMI Phys. 2021 Mar 12;8(1):26. doi: 10.1186/s40658-021-00369-4. EJNMMI Phys. 2021. PMID: 33709253 Free PMC article.
-
Standardization and Validation of Brachytherapy Seeds' Modelling Using GATE and GGEMS Monte Carlo Toolkits.Cancers (Basel). 2021 Oct 22;13(21):5315. doi: 10.3390/cancers13215315. Cancers (Basel). 2021. PMID: 34771479 Free PMC article.
-
DosePatch: physics-inspired cropping layout for patch-based Monte Carlo simulations to provide fast and accurate internal dosimetry.EJNMMI Phys. 2024 Jun 26;11(1):51. doi: 10.1186/s40658-024-00646-y. EJNMMI Phys. 2024. PMID: 38922372 Free PMC article.
-
Monte Carlo methods for medical imaging research.Biomed Eng Lett. 2024 Sep 5;14(6):1195-1205. doi: 10.1007/s13534-024-00423-x. eCollection 2024 Nov. Biomed Eng Lett. 2024. PMID: 39465109 Free PMC article. Review.
-
Efficient full Monte Carlo modelling and multi-energy generative model development of an advanced X-ray device.Z Med Phys. 2023 May;33(2):135-145. doi: 10.1016/j.zemedi.2022.04.006. Epub 2022 Jun 7. Z Med Phys. 2023. PMID: 35688672 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources