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Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator

PURPOSE AND AIM: The Vero4DRT (Brainlab AG) linear accelerator is capable of dynamic tumor tracking (DTT) by panning/tilting the radiation beam to follow respiratory-induced tumor motion in real time. In this study, the panning/tilting motion is modeled in Monte Carlo (MC) for quality assurance (QA)...

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Autores principales: Carpentier, Emilie E., Mcdermott, Ronan L., Su, Shiqin, Rostamzadeh, Maryam, Popescu, I. Antoniu, Bergman, Alanah M., Mestrovic, Ante
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10277301/
https://www.ncbi.nlm.nih.gov/pubmed/37342609
http://dx.doi.org/10.4103/jmp.jmp_108_22
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author Carpentier, Emilie E.
Mcdermott, Ronan L.
Su, Shiqin
Rostamzadeh, Maryam
Popescu, I. Antoniu
Bergman, Alanah M.
Mestrovic, Ante
author_facet Carpentier, Emilie E.
Mcdermott, Ronan L.
Su, Shiqin
Rostamzadeh, Maryam
Popescu, I. Antoniu
Bergman, Alanah M.
Mestrovic, Ante
author_sort Carpentier, Emilie E.
collection PubMed
description PURPOSE AND AIM: The Vero4DRT (Brainlab AG) linear accelerator is capable of dynamic tumor tracking (DTT) by panning/tilting the radiation beam to follow respiratory-induced tumor motion in real time. In this study, the panning/tilting motion is modeled in Monte Carlo (MC) for quality assurance (QA) of four-dimensional (4D) dose distributions created within the treatment planning system (TPS). MATERIALS AND METHODS: Step-and-shoot intensity-modulated radiation therapy plans were optimized for 10 previously treated liver patients. These plans were recalculated on multiple phases of a 4D computed tomography (4DCT) scan using MC while modeling panning/tilting. The dose distributions on each phase were accumulated to create a respiratory-weighted 4D dose distribution. Differences between the TPS and MC modeled doses were examined. RESULTS: On average, 4D dose calculations in MC showed the maximum dose of an organ at risk (OAR) to be 10% greater than the TPS’ three-dimensional dose calculation (collapsed cone [CC] convolution algorithm) predicted. MC’s 4D dose calculations showed that 6 out of 24 OARs could exceed their specified dose limits, and calculated their maximum dose to be 4% higher on average (up to 13%) than the TPS’ 4D dose calculations. Dose differences between MC and the TPS were greatest in the beam penumbra region. CONCLUSION: Modeling panning/tilting for DTT has been successfully modeled with MC and is a useful tool to QA respiratory-correlated 4D dose distributions. The dose differences between the TPS and MC calculations highlight the importance of using 4D MC to confirm the safety of OAR doses before DTT treatments.
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spelling pubmed-102773012023-06-20 Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator Carpentier, Emilie E. Mcdermott, Ronan L. Su, Shiqin Rostamzadeh, Maryam Popescu, I. Antoniu Bergman, Alanah M. Mestrovic, Ante J Med Phys Original Article PURPOSE AND AIM: The Vero4DRT (Brainlab AG) linear accelerator is capable of dynamic tumor tracking (DTT) by panning/tilting the radiation beam to follow respiratory-induced tumor motion in real time. In this study, the panning/tilting motion is modeled in Monte Carlo (MC) for quality assurance (QA) of four-dimensional (4D) dose distributions created within the treatment planning system (TPS). MATERIALS AND METHODS: Step-and-shoot intensity-modulated radiation therapy plans were optimized for 10 previously treated liver patients. These plans were recalculated on multiple phases of a 4D computed tomography (4DCT) scan using MC while modeling panning/tilting. The dose distributions on each phase were accumulated to create a respiratory-weighted 4D dose distribution. Differences between the TPS and MC modeled doses were examined. RESULTS: On average, 4D dose calculations in MC showed the maximum dose of an organ at risk (OAR) to be 10% greater than the TPS’ three-dimensional dose calculation (collapsed cone [CC] convolution algorithm) predicted. MC’s 4D dose calculations showed that 6 out of 24 OARs could exceed their specified dose limits, and calculated their maximum dose to be 4% higher on average (up to 13%) than the TPS’ 4D dose calculations. Dose differences between MC and the TPS were greatest in the beam penumbra region. CONCLUSION: Modeling panning/tilting for DTT has been successfully modeled with MC and is a useful tool to QA respiratory-correlated 4D dose distributions. The dose differences between the TPS and MC calculations highlight the importance of using 4D MC to confirm the safety of OAR doses before DTT treatments. Wolters Kluwer - Medknow 2023 2023-04-18 /pmc/articles/PMC10277301/ /pubmed/37342609 http://dx.doi.org/10.4103/jmp.jmp_108_22 Text en Copyright: © 2023 Journal of Medical Physics https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Carpentier, Emilie E.
Mcdermott, Ronan L.
Su, Shiqin
Rostamzadeh, Maryam
Popescu, I. Antoniu
Bergman, Alanah M.
Mestrovic, Ante
Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator
title Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator
title_full Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator
title_fullStr Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator
title_full_unstemmed Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator
title_short Monte Carlo Modeling of Dynamic Tumor Tracking on a Gimbaled Linear Accelerator
title_sort monte carlo modeling of dynamic tumor tracking on a gimbaled linear accelerator
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10277301/
https://www.ncbi.nlm.nih.gov/pubmed/37342609
http://dx.doi.org/10.4103/jmp.jmp_108_22
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