Impact of secondary particles on microdistribution of deposited dose in biological tissue in the presence of gold and gadolinium nanoparticles under photon beam irradiation

It is experimentally proven that nanoparticles of high-Z materials can be used as radiosensitizers for photon beam therapy. In the authors' opinion, data available as of today on the impact of secondary particles (electrons, photons and positrons generated in biological tissue by penetrating beam of primary photons) on the distribution of deposited dose during photon beam therapy in the presence of nanoparticles, are insufficient. Investigation of this impact constituted the main goal of this work. Two-stage simulation was performed using Geant4 platform. During the first stage a layer of biological tissue (water) was irradiated by monoenergetic photon sources with energies ranging from 10 keV to 6 MeV. As the result of this modeling spectra of electrons, photons and positrons were obtained at the depth of 5 cm. During the second stage the obtained photon spectra were used to irradiate gold, gadolinium and water nanoparticles. Radial distributions of energy deposited around nanoparticles were obtained as the result of this modeling. Radial DEF (Dose Enhancement Factor) values around nanoparticles of gold and gadolinium positioned in water at the depth of 5 cm were obtained after processing the collected data. Contributions from primary photons and secondary particles (electrons, photons and positrons generated in the layer of water with 5-cm thickness by the penetrating beam of primary photons) in the additional dose deposited around the nanoparticles were calculated as well. It was demonstrated that layer of biological tissue placed between the source of photons and nanoparticles considerably changes the initial spectrum of photons and this change is significant in the analysis of mechanism of radiosensitization of biological tissues by nanoparticles for all energies of photon sources (up to 6 MeV). It was established that interaction of electrons and positrons with nanoparticles does not lead to significant increase of additional dose in the vicinity of their surfaces and can be most likely excluded from consideration in the analysis of radiosensitization mechanism of nanoparticles

An implementation of discrete electron transport models for gold in the Geant4 simulation toolkit

Gold nanoparticle (GNP) boosted radiation therapy can enhance the biological effectiveness of radiation treatments by increasing the quantity of direct and indirect radiation-induced cellular damage. As the physical effects of GNP boosted radiotherapy occur across energy scales that descend down to 10 eV, Monte Carlo simulations require discrete physics models down to these very low energies in order to avoid underestimating the absorbed dose and secondary particle generation. Discrete physics models for electron transportation down to 10 eV have been implemented within the Geant4-DNA low energy extension of Geant4. Such models allow the investigation of GNP effects at the nanoscale. At low energies, the new models have better agreement with experimental data on the backscattering coefficient, and they show similar performance for transmission coefficient data as the Livermore and Penelope models already implemented in Geant4. These new models are applicable in simulations focussed towards estimating the relative biological effectiveness of radiation in GNP boosted radiotherapy applications with photon and electron radiation sources

An implementation of discrete electron transport models for gold in the Geant4 simulation toolkit

Gold nanoparticle (GNP) boosted radiation therapy can enhance the biological effectiveness of radiation treatments by increasing the quantity of direct and indirect radiation-induced cellular damage. As the physical effects of GNP boosted radiotherapy occur across energy scales that descend down to 10 eV, Monte Carlo simulations require discrete physics models down to these very low energies in order to avoid underestimating the absorbed dose and secondary particle generation. Discrete physics models for electron transportation down to 10 eV have been implemented within the Geant4-DNA low energy extension of Geant4. Such models allow the investigation of GNP effects at the nanoscale. At low energies, the new models have better agreement with experimental data on the backscattering coefficient, and they show similar performance for transmission coefficient data as the Livermore and Penelope models already implemented in Geant4. These new models are applicable in simulations focussed towards estimating the relative biological effectiveness of radiation in GNP boosted radiotherapy applications with photon and electron radiation sources

Geometric Algorithms and Data Structures for Simulating Diffusion Limited Reactions

Radiation therapy is one of the most effective means for treating cancers. An important calculation in radiation therapy is the estimation of dose distribution in the treated patient, which is key to determining the treatment outcome and potential side effects of the therapy. Biological dose — the level of biological damage (e.g., cell killing ratio, DNA damage, etc.) inflicted by the radiation is the best measure of treatment quality, but it is very difficult to calculate. Therefore, most clinics today use physical dose - the energy deposited by incident radiation per unit body mass - for planning radiation therapy, which can be calculated accurately using kinetic Monte Carlo simulations. Studies have found that physical dose correlates with biological dose, but exhibits a very complex relationship that is not yet well understood. Generally speaking, the calculation of biological dose involves four steps: (1) the calculation of physical dose distribution, (2) the generation of radiochemicals based on the physical dose distribution, (3) the simulation of interactions between radiochemicals and bio-matter in the body, and (4) the estimation of biological damage based on the distribution of radiochemicals. This dissertation focuses on the development of a more efficient and effective simulation algorithm to speed up step (3). The main contribution of this research is the development of an efficient and effective kinetic Monte Carlo (KMC) algorithm for simulating diffusion-limited chemical reactions in the context of radiation therapy. The central problem studied is - given n particles distributed among a small number of particle species, all allowed to diffuse and chemically react according to a small number of chemical reaction equations - predict the radiochemical yield over time. The algorithm presented makes use of a sparse grid structure, with one grid per species per radiochemical reactant used to group particles in a way that makes the nearest neighbor search efficient, where particles are stored only once, yet are represented in grids of all appropriate reaction radii. A kinetic data structure is used as the time stepping mechanism, which provides spatially local updates to the simulation at a frequency which captures all events - retaining accuracy. A serial and three parallel versions of the algorithm have been developed. The parallel versions implement the kinetic data structure using both a standard priority queue and a treap data structure in order to investigate the algorithms scalability. The treap provides a way for each thread of execution to do more work in a particular region of space. A comparison with a spatial discretization variant of the algorithm is also provided

Mechanistic Modelling of Radiation Responses

Radiobiological modelling has been a key part of radiation biology and therapy for many decades, and many aspects of clinical practice are guided by tools such as the linear-quadratic model. However, most of the models in regular clinical use are abstract and empirical, and do not provide significant scope for mechanistic interpretation or making predictions in novel cell lines or therapies. In this review, we will discuss the key areas of ongoing mechanistic research in radiation biology, including physical, chemical, and biological steps, and review a range of mechanistic modelling approaches which are being applied in each area, highlighting the possible opportunities and challenges presented by these techniques

Desarrollo de algoritmos Monte Carlo track – structure para estudiar el efecto de la Interacción de la radiación ionizante con tejido biológico

"Propósito: Extender los códigos Monte Carlo de estructura de track Geant4-DNA y TOPAS-nBio para que sean capaces de recrear y predecir el daño al ADN debido a la radiación ionizante utilizando plásmidos de ADN. Reproducir la respuesta del daño al ADN como función de la concentración de ADN, concentración de DMSO, torcimiento del ADN, y dosis impartida. Metodología: Se llevo a cabo una validación en diferentes etapas de los códigos Monte Carlo Geant4-DNA y TOPAS-nBio para asegurar estos pueden simular de forma exitosa el daño al ADN en plásmidos. En una primera etapa se analizó la respuesta del medio ante diferentes fuentes de radiación (valores G en función de la LET), posteriormente se validaron los algoritmos para su uso a tiempos mayores a los de la química inhomogenea en agua pura (> 1µs), desarrollando los modelos de ADN, finalmente se incorporaron todos los algoritmos implementados en una sola simulación"

Estudo do dano direto e indireto induzido ao DNA pela radiação ionizante usando o método de Monte Carlo

Orientador: Mario Antonio Bernal RodriguezTese (doutorado) - Universidade Estadual de Campinas, Instituto de Física Gleb WataghinResumo: A simulação por Monte Carlo (MC) é uma poderosa ferramenta para estudar os efeitos biológicos induzidos pela radiação ionizante em seres vivos. Vários códigos MC, com diferentes níveis de complexidade, são comumente usados em campos de pesquisa como nanodosimetria, radioterapia, proteção radiológica e areoespacial. Este trabalho apresenta uma ampliação de um modelo existente [1] para fins radiobiológicos, a fim de levar em conta o dano indireto e mixto induzido no DNA por radiações ionizantes. O kit de ferramentas de simulação GEANT4-DNA foi usado para simular a etapa física, pré-química e química do dano inicial no DNA induzidos por prótons e partículas alfa. O meio usado nas simulações foi a água líquida. Foram gerados dois arquivos de saída, um contendo eventos de deposição de energia dentro da região de interesse (ROI), e outro com a posição das espécies químicas produzidas pela radiólise d¿água, de 0,1 ps até 1 ns. As informações contidas nos dois arquivos foram sobrepostas em um modelo de material genético com resolução atômica, consistindo de várias cópias de fibras de cromatina de 30 nm. A configuração do B-DNA foi usada. O foco deste trabalho foi o dano indireto produzido pelo ataque do radical hidroxilo (?OH) ao grupo açucar-fosfato, normalmente através da abstração do hidrogênio. A abordagem seguida para explicar o dano indireto no DNA foi o mesmo usado por outros códigos radiobiológicos [2, 3]. O parâmetro crítico aqui considerado foi o raio de reação, calculado a partir da equação de difusão de Smoluchowski. Os rendimentos de quebra de cadeia simples, dupla e total produzidos por mecanismos diretos, indiretos e mistos são relatados. Resultados consistentes com outros trabalhos de simulações e experimentais foram encontrados, mesmo sem seguir qualquer processo de ajuste. Até aonde nós sabemos, esta é a primeira vez que o código GEANT4-DNA é combinado com um modelo atômico do DNA para estudar o dano químico induzido por radiações ionizantesAbstract: Monte Carlo (MC) simulation is a powerful tool to study biological effects induced by ionizing radiation on living beings. Several MC codes, with different level of complexity, are commonly used in research fields such as nanodosimetry, radiotherapy, radiation protection, and space radiation. This work presents an enhancement of an existing model [1] for radiobiological purposes, in order to account for the indirect and mixed DNA damage induced by ionizing particles. The GEANT4-DNA simulation toolkit was used to simulate physical, pre-chemical and chemical stages of the early DNA damage induced by protons and alpha particles. Liquid water was used as the medium for simulations. Two phase-space files were generated, one containing energy deposition events inside the region of interest (ROI), and another one with the position of chemical species produced by water radiolysis from 0.1 ps up to 1 ns. The information contained in both files was superposed on a genetic material model with atomic-resolution, consisting of several copies of 30-nm chromatin fibers. The B-DNA configuration was used. This work focused on the indirect damage produced by the hydroxyl radical (?OH) attack on the sugar-phosphate, normally through hydrogen abstraction. The approach followed to account for the indirect damage in DNA was the same used by other radiobiological codes [2, 3]. The critical parameter considered here was the reaction radius, which was calculated from the Smoluchowski¿s diffusion equation. Single, double, and total strand break yields produced by direct, indirect and mixed mechanisms are reported. Results consistent with simulated and experimental works were found, even without following any fitting process. To the best of our knowledge, this is the first time the GEANT4-DNA code is used in conjunction with a DNA atomic resolution model for studying the chemical damage induced by ionizing radiationsDoutoradoFísicaDoutora em Ciências190154/2013-6CNP