Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Incorporating Microdosimetry Into Radiation Therapy Treatment Planning With Multi Scale Monte Carlo Simulations PDF full book. Access full book title Incorporating Microdosimetry Into Radiation Therapy Treatment Planning With Multi Scale Monte Carlo Simulations.
| Author | : Joseph Lucido |
| Publisher | : |
| Total Pages | : |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
| Author | : H. Zaidi |
| Publisher | : CRC Press |
| Total Pages | : 441 |
| Release | : 2002-09-01 |
| Genre | : Medical |
| ISBN | : 1000687686 |
Therapeutic Applications of Monte Carlo Calculations in Nuclear Medicine examines the applications of Monte Carlo (MC) calculations in therapeutic nuclear medicine, from basic principles to computer implementations of software packages and their applications in radiation dosimetry and treatment planning. With chapters written by recognized authorit
| Author | : Andrew William Alexander |
| Publisher | : |
| Total Pages | : |
| Release | : 2012 |
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Within the field of medical physics, Monte Carlo radiation transport simulations are considered to be the most accurate method for the determination of dose distributions in patients. The McGill Monte Carlo treatment planning system (MMCTP), provides a flexible software environment to integrate Monte Carlo simulations with current and new treatment modalities. A developing treatment modality called energy and intensity modulated electron radiotherapy (MERT) is a promising modality, which has the fundamental capabilities to enhance the dosimetry of superficial targets. An objective of this work is to advance the research and development of MERT with the end goal of clinical use. To this end, we present the MMCTP system with an integrated toolkit for MERT planning and delivery of MERT fields. Delivery is achieved using an automated "few leaf electron collimator" (FLEC) and a controller. Aside from the MERT planning toolkit, the MMCTP system required numerous...
| Author | : Pablo Cirrone |
| Publisher | : CRC Press |
| Total Pages | : 528 |
| Release | : 2023-11-08 |
| Genre | : Science |
| ISBN | : 1000987655 |
This book explores the current difficulties and unsolved problems in the field of particle therapy and, after analysing them, discusses how (and if) innovative Monte Carlo approaches can be used to solve them. Each book chapter is dedicated to a different sub-discipline, including multi-ion treatments, flash-radiotherapy, laser-accelerated beams, nanoparticles effects, binary reactions to enhance radiobiology, and space-related issues. This is the first book able to provide a comprehensive insight into this exciting field and the growing use of Monte Carlo in medical physics. It will be of interest to graduate students in medicine and medical physics, in addition to researchers and clinical staff. Key Features: Explores the exciting and interdisciplinary topic of Monte Carlo in particle therapy and medicine. Addresses common challenges in the field. Edited by an authority on the subject, with chapter contributions from specialists. Pablo Cirrone is a medical physicist and researcher at the Laboratori Nazionali del Sud of INFN, Italy, where he supports and coordinates various experimental groups. Dr. Cirrone is an expert in the use of proton and ion in radiation treatment and of absolute and relative dosimetry in electron, photon and ion beam. He is an expert in the development and test of detectors for medical applications, of the production and use of laser-driven beams for medical and multidisciplinary applications and recipient of the Michael Gotein Award. He is active on many scientific committees and organizes national and international conferences. Giada Petringa is a researcher at the Laboratori Nazionali del Sud of INFN, Italy. Dr. Petringa has a professional experience in the field of Monte Carlo simulations for medical applications, dosimetry, microdosimetry, and diagnostics with conventional and laser-driven proton beams. In 2019 she had a MSCA-IF-2019 (Marie Sklodowska-Curie Actions-Individual Fellowship) grant funded by the European Community in the framework of the H2020 program. She is a member of the Editorial Board of the international journal Physica Medica - European Journal of Medical. She organized more than fifteen international Geant4 Schools. She is an official member of the Geant4 code Collaboration at CERN since 2019. She is a code developer, and she collaborates to maintain two of the official examples of the code.
| Author | : Wanbao Gao |
| Publisher | : |
| Total Pages | : 200 |
| Release | : 1996 |
| Genre | : Monte Carlo method |
| ISBN | : |
| Author | : Yuhe Wang |
| Publisher | : |
| Total Pages | : 120 |
| Release | : 2017 |
| Genre | : Electronic dissertations |
| ISBN | : |
Monte Carlo (MC) simulation is generally considered to be the most accurate method for dose calculation in radiation therapy. However, it suffers from the low simulation efficiency (hours to days) and complex configuration, which impede its applications in clinical studies. The recent rise of MRI-guided radiation platform (e.g. ViewRay's MRIdian system) brings urgent need of fast MC algorithms because the introduced strong magnetic field may cause big errors to other algorithms. My dissertation focuses on resolving the conflict between accuracy and efficiency of MC simulations through 4 different approaches: (1) GPU parallel computation, (2) Transport mechanism simplification, (3) Variance reduction, (4) DVH constraint. Accordingly, we took several steps to thoroughly study the performance and accuracy influence of these methods. As a result, three Monte Carlo simulation packages named gPENELOPE, gDPMvr and gDVH were developed for subtle balance between performance and accuracy in different application scenarios. For example, the most accurate gPENELOPE is usually used as "golden standard" for radiation meter model, while the fastest gDVH is usually used for quick in-patient dose calculation, which significantly reduces the calculation time from 5 hours to 1.2 minutes (250 times faster) with only 1% error introduced. In addition, a cross-platform GUI integrating simulation kernels and 3D visualization was developed to make the toolkit more user-friendly. After the fast MC infrastructure was established, we successfully applied it to four radiotherapy scenarios: (1) Validate the vender provided Co60 radiation head model by comparing the dose calculated by gPENELOPE to experiment data; (2) Quantitatively study the effect of magnetic field to dose distribution and proposed a strategy to improve treatment planning efficiency; (3) Evaluate the accuracy of the build-in MC algorithm of MRIdian's treatment planning system. (4) Perform quick quality assurance (QA) for the "online adaptive radiation therapy" that doesn't permit enough time to perform experiment QA. Many other time-sensitive applications (e.g. motional dose accumulation) will also benefit a lot from our fast MC infrastructure.
| Author | : Michael C. Lee |
| Publisher | : |
| Total Pages | : 276 |
| Release | : 2002 |
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| Author | : D. Nigg |
| Publisher | : |
| Total Pages | : 28 |
| Release | : 2004 |
| Genre | : |
| ISBN | : |
The aim of this project is to extend accurate and patient-specific treatment planning to new treatment modalities, such as molecular targeted radiation therapy, incorporating previously crafted and proven Monte Carlo and deterministic computation methods. A flexible software environment is being created that allows planning radiation treatment for these new modalities and combining different forms of radiation treatment with consideration of biological effects. The system uses common input interfaces, medical image sets for definition of patient geometry, and dose reporting protocols. Previously, the Idaho National Engineering and Environmental Laboratory (INEEL), Montana State University (MSU), and Lawrence Livermore National Laboratory (LLNL) had accrued experience in the development and application of Monte Carlo-based, three-dimensional, computational dosimetry and treatment planning tools for radiotherapy in several specialized areas. In particular, INEEL and MSU have developed computational dosimetry systems for neutron radiotherapy and neutron capture therapy, while LLNL has developed the PEREGRINE computational system for external beam photon-electron therapy. Building on that experience, the INEEL and MSU are developing the MINERVA (Modality Inclusive Environment for Radiotherapeutic Variable Analysis) software system as a general framework for computational dosimetry and treatment planning for a variety of emerging forms of radiotherapy. In collaboration with this development, LLNL has extended its PEREGRINE code to accommodate internal sources for molecular targeted radiotherapy (MTR), and has interfaced it with the plug-in architecture of MINERVA. Results from the extended PEREGRINE code have been compared to published data from other codes, and found to be in general agreement (EGS4 - 2%, MCNP - 10%)(Descalle et al. 2003). The code is currently being benchmarked against experimental data. The interpatient variability of the drug pharmacokinetics in MTR can only be properly accounted for by image-based, patient-specific treatment planning as has been common in external beam radiation therapy for many years. MINERVA offers 3D Monte Carlo based MTR treatment planning as its first integrated operational capability. The new MINERVA system will ultimately incorporate capabilities for a comprehensive list of radiation therapies. In progress are modules for external beam photon-electron therapy and Boron Neutron Capture Therapy (BNCT). Brachytherapy and Protontherapy are planned. Through the open Application Programming Interface (API) other groups can add their own modules and share them with the community.
| Author | : Miguel Antonio Cortés-Giraldo |
| Publisher | : Frontiers Media SA |
| Total Pages | : 167 |
| Release | : 2022-08-19 |
| Genre | : Science |
| ISBN | : 2889761053 |
| Author | : Mat Mustafa Tamimi |
| Publisher | : |
| Total Pages | : 163 |
| Release | : 2014 |
| Genre | : Cancer |
| ISBN | : |
A successful radiation therapy treatment aims at conforming (i.e., concentrating) radiation dose to the entire tumor volume (i.e., diseased area) while avoiding surrounding normal tissue (i.e., healthy non-diseased areas). This objective is achieved clinically by finding a set of radiation beam parameters that successfully deliver the desired dose distribution. In this project, a hybrid forward/adjoint Monte Carlo based absorbed dose computation method is developed and tested, aimed at eventual implementation in a radiation therapy external beam treatment planning system to predict the absorbed dose produced by a medical linear accelerator. This absorbed dose calculational engine was designed to be:1. Efficient. This is achieved by incorporating several Monte Carlo techniques used in the Nuclear Engineering field for deep penetration and reactor analysis problem. 2. Flexible. This is achieved by using a Cartesian grid and a voxelized material map. Currently most of the absorbed dose calculation algorithms in radiotherapy are 3-D based predictive models. The use of such algorithms results in treatment planning quality that depends tremendously on the planner’s experience and knowledge base. This dependence, along with inaccuracy in predicting absorbed dose due to the assumptions and simplifications used in these algorithms, can result in a predicted absorbed dose that under- or over-predicts the delivered dose. As an alternative, forward and adjoint Monte Carlo absorbed dose computation methods have been used and validated by several authors (Difilippo, 1998; Goldstein & Regev, 1999; Jeraj & Keall, 1999). However, in the “pure” forward or adjoint methods, each change in the radiation beam parameters requires its own time-consuming 3D calculation; for the hybrid technique developed in this research, a single 3D calculation for each desired dose region (tumor or healthy organ) is all that is required. This project also improves the Monte Carlo methodology by incorporating the use of voxelized fictitious scattering and surface forward/adjoint coupling. The accuracy is demonstrated through comparison with forward and adjoint MCNP calculations of a simple beam/patient sample problem.
