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Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit
Our institution delivers TBI using a modified Theratron 780 [Formula: see text] unit. Due to limitations of our treatment planning system in calculating dose for this treatment, we have developed a fast Monte Carlo code to calculate dose distributions within the patient. The algorithm is written in...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5714420/ https://www.ncbi.nlm.nih.gov/pubmed/23652253 http://dx.doi.org/10.1120/jacmp.v14i3.4214 |
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author | Liu, Xiaodong Lack, Danielle Rakowski, Joseph T. Knill, Cory Snyder, Michael |
author_facet | Liu, Xiaodong Lack, Danielle Rakowski, Joseph T. Knill, Cory Snyder, Michael |
author_sort | Liu, Xiaodong |
collection | PubMed |
description | Our institution delivers TBI using a modified Theratron 780 [Formula: see text] unit. Due to limitations of our treatment planning system in calculating dose for this treatment, we have developed a fast Monte Carlo code to calculate dose distributions within the patient. The algorithm is written in C and uses voxel density information from CT images to calculate dose in heterogeneous media. To test the algorithm, film‐based dose measurements were made separately in a simple water phantom with a high‐density insert and a RANDO phantom and then compared to doses calculated by the Monte Carlo algorithm. In addition, a separate simulation in GEANT4 was run for the RANDO phantom and compared to both film and the in‐house simulation. All results were analyzed using RIT113 film analysis software. Simulations in the water phantom accurately predict the depth of maximum dose in the phantom at 0.5 cm. The measured PDD along the central axis of the beam closely matches the PDD generated from the Monte Carlo code, deviating on average by only 3% along the depth of the water phantom. Dose measured at planes inside the high‐density insert had a mean difference of 4.9% on cross‐profile measurement. In the RANDO phantom, gamma pass rates vary between 91% and 99% at 3 mm, 3%, and were [Formula: see text] at 5 mm, 5% for the four film planes measured. Profiles taken across the film and both simulations resulted in mean relative differences of [Formula: see text] for all profiles in each slice measured. The Monte Carlo algorithm presented here is potentially a viable method for calculating dose distributions delivered in TBI treatments at our center. While not yet refined enough to be the primary method of treatment planning, the algorithm at its current resolution determines the dose distribution for one patient within a few hours, and provides clinically useful information in planning TBI. With appropriate optimization, the Monte Carlo method presented here could potentially be implemented as a first‐line treatment planning option for [Formula: see text] TBI. PACS number: 87.10.Rt |
format | Online Article Text |
id | pubmed-5714420 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57144202018-04-02 Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit Liu, Xiaodong Lack, Danielle Rakowski, Joseph T. Knill, Cory Snyder, Michael J Appl Clin Med Phys Radiation Oncology Physics Our institution delivers TBI using a modified Theratron 780 [Formula: see text] unit. Due to limitations of our treatment planning system in calculating dose for this treatment, we have developed a fast Monte Carlo code to calculate dose distributions within the patient. The algorithm is written in C and uses voxel density information from CT images to calculate dose in heterogeneous media. To test the algorithm, film‐based dose measurements were made separately in a simple water phantom with a high‐density insert and a RANDO phantom and then compared to doses calculated by the Monte Carlo algorithm. In addition, a separate simulation in GEANT4 was run for the RANDO phantom and compared to both film and the in‐house simulation. All results were analyzed using RIT113 film analysis software. Simulations in the water phantom accurately predict the depth of maximum dose in the phantom at 0.5 cm. The measured PDD along the central axis of the beam closely matches the PDD generated from the Monte Carlo code, deviating on average by only 3% along the depth of the water phantom. Dose measured at planes inside the high‐density insert had a mean difference of 4.9% on cross‐profile measurement. In the RANDO phantom, gamma pass rates vary between 91% and 99% at 3 mm, 3%, and were [Formula: see text] at 5 mm, 5% for the four film planes measured. Profiles taken across the film and both simulations resulted in mean relative differences of [Formula: see text] for all profiles in each slice measured. The Monte Carlo algorithm presented here is potentially a viable method for calculating dose distributions delivered in TBI treatments at our center. While not yet refined enough to be the primary method of treatment planning, the algorithm at its current resolution determines the dose distribution for one patient within a few hours, and provides clinically useful information in planning TBI. With appropriate optimization, the Monte Carlo method presented here could potentially be implemented as a first‐line treatment planning option for [Formula: see text] TBI. PACS number: 87.10.Rt John Wiley and Sons Inc. 2013-05-06 /pmc/articles/PMC5714420/ /pubmed/23652253 http://dx.doi.org/10.1120/jacmp.v14i3.4214 Text en © 2013 The Authors. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/3.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Radiation Oncology Physics Liu, Xiaodong Lack, Danielle Rakowski, Joseph T. Knill, Cory Snyder, Michael Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit |
title | Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit |
title_full | Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit |
title_fullStr | Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit |
title_full_unstemmed | Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit |
title_short | Fast Monte Carlo simulation for total body irradiation using a [Formula: see text] teletherapy unit |
title_sort | fast monte carlo simulation for total body irradiation using a [formula: see text] teletherapy unit |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5714420/ https://www.ncbi.nlm.nih.gov/pubmed/23652253 http://dx.doi.org/10.1120/jacmp.v14i3.4214 |
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