A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator
Currently, commercial treatment planning systems are validated against Monte Carlo (MC) simulation in medical physics research. MC is the current gold standard to model the transport of radiation. In this study, a Monte Carlo package, Electron Gamma Shower from the National Research Council Canada (...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/68602 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-68602 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-686022023-02-28T23:13:19Z A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator Tan, Lloyd Kuan Rui James C L Lee School of Physical and Mathematical Sciences National Cancer Centre Singapore Roger Soh DRNTU::Science Currently, commercial treatment planning systems are validated against Monte Carlo (MC) simulation in medical physics research. MC is the current gold standard to model the transport of radiation. In this study, a Monte Carlo package, Electron Gamma Shower from the National Research Council Canada (EGSnrc), is chosen to calculate the dose distribution for photon beams under standard reference and small field conditions and validated against measured data. In a MC simulation of photon beam, 2 key components are needed; First, a photon beam source and second, a target medium. External beam radiotherapy is the most common form of radiotherapy for treating cancer, and a linear accelerator (LINAC) is used to deliver the radiation. A target medium can be of any material of interest for study or a human body for clinical application. EGSnrc is able to model a LINAC through its subroutine BEAMnrc. BEAMnrc models the geometry and materials of a commercial LINAC. However, the exact modeling of a commercial linac in BEAMnrc may not yield the best or optimal clinical beam distribution against actual measured data. As such, a few key LINAC parameters in BEAMnrc will have to be varied and simulated in a water phantom to produce a depth dose and lateral dose profile to match clinically measured results. Various parameters will be adjusted in the BEAMnrc LINAC model to derive a set of optimal parameters that produces the closest match between simulation and measured. They are the electron energy, the full width half maximum or FWHM of the electron beam and the jaw thickness. The results of the study has shown that optimal parameters differs between different field sizes for the LINAC, contrary to recommendations by previous studies. Bachelor of Science in Physics 2016-05-30T01:52:08Z 2016-05-30T01:52:08Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68602 en 63 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Science |
spellingShingle |
DRNTU::Science Tan, Lloyd Kuan Rui A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator |
description |
Currently, commercial treatment planning systems are validated against Monte Carlo (MC) simulation in medical physics research. MC is the current gold standard to model the transport of radiation. In this study, a Monte Carlo package, Electron Gamma Shower from the National Research Council Canada (EGSnrc), is chosen to calculate the dose distribution for photon beams under standard reference and small field conditions and validated against measured data.
In a MC simulation of photon beam, 2 key components are needed; First, a photon beam source and second, a target medium. External beam radiotherapy is the most common form of radiotherapy for treating cancer, and a linear accelerator (LINAC) is used to deliver the radiation. A target medium can be of any material of interest for study or a human body for clinical application.
EGSnrc is able to model a LINAC through its subroutine BEAMnrc. BEAMnrc models the geometry and materials of a commercial LINAC. However, the exact modeling of a commercial linac in BEAMnrc may not yield the best or optimal clinical beam distribution against actual measured data. As such, a few key LINAC parameters in BEAMnrc will have to be varied and simulated in a water phantom to produce a depth dose and lateral dose profile to match clinically measured results. Various parameters will be adjusted in the BEAMnrc LINAC model to derive a set of optimal parameters that produces the closest match between simulation and measured. They are the electron energy, the full width half maximum or FWHM of the electron beam and the jaw thickness.
The results of the study has shown that optimal parameters differs between different field sizes for the LINAC, contrary to recommendations by previous studies. |
author2 |
James C L Lee |
author_facet |
James C L Lee Tan, Lloyd Kuan Rui |
format |
Final Year Project |
author |
Tan, Lloyd Kuan Rui |
author_sort |
Tan, Lloyd Kuan Rui |
title |
A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator |
title_short |
A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator |
title_full |
A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator |
title_fullStr |
A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator |
title_full_unstemmed |
A study to determine the optimal input parameters for the Monte Carlo simulation of a clinical linear accelerator |
title_sort |
study to determine the optimal input parameters for the monte carlo simulation of a clinical linear accelerator |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/68602 |
_version_ |
1759854501796249600 |