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Couch modeling optimization for tomotherapy planning and delivery

We sought to validate new couch modeling optimization for tomotherapy planning and delivery. We constructed simplified virtual structures just above a default setting couch through a planning support system (MIM Maestro, version 8.2, MIM Software Inc, Cleveland, OH, USA). Based on ionization chamber...

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Autores principales: Okada, Wataru, Tanooka, Masao, Sano, Keisuke, Shibata, Mayuri, Doi, Hiroshi, Miyazaki, Masayoshi, Nakahara, Ryuta, Sueoka, Masaki, Suzuki, Hitomi, Fujiwara, Masayuki, Inomata, Taisuke, Yamakado, Koichiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6698767/
https://www.ncbi.nlm.nih.gov/pubmed/31343831
http://dx.doi.org/10.1002/acm2.12686
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author Okada, Wataru
Tanooka, Masao
Sano, Keisuke
Shibata, Mayuri
Doi, Hiroshi
Miyazaki, Masayoshi
Nakahara, Ryuta
Sueoka, Masaki
Suzuki, Hitomi
Fujiwara, Masayuki
Inomata, Taisuke
Yamakado, Koichiro
author_facet Okada, Wataru
Tanooka, Masao
Sano, Keisuke
Shibata, Mayuri
Doi, Hiroshi
Miyazaki, Masayoshi
Nakahara, Ryuta
Sueoka, Masaki
Suzuki, Hitomi
Fujiwara, Masayuki
Inomata, Taisuke
Yamakado, Koichiro
author_sort Okada, Wataru
collection PubMed
description We sought to validate new couch modeling optimization for tomotherapy planning and delivery. We constructed simplified virtual structures just above a default setting couch through a planning support system (MIM Maestro, version 8.2, MIM Software Inc, Cleveland, OH, USA). Based on ionization chamber measurements, we performed interactive optimization and determined the most appropriate physical density of these virtual structures in a treatment planning system (TPS). To validate this couch optimization, Gamma analysis and these statistical analyses between a three‐dimensional diode array QA system (ArcCHECK, Sun Nuclear, Melbourne, FL, USA) results and calculations from ionization chamber measurements were performed at 3%/2 mm criteria with a threshold of 10% in clinical QA plans. Using a virtual model consisting of a center slab density of 4.2 g/cm(3) and both side slabs density of 1.9 g/cm(3), we demonstrated close agreement between measured dose and the TPS calculated dose. Agreement was within 1% for all gantry angles at the isocenter and within 2% in off‐axis plans. In validation of the couch modeling in a clinical QA plan, the average gamma passing rate improved approximately 0.6%–5.1%. It was statistically significant (P < 0.05) for all treatment sites. We successfully generated an accurate couch model for a TomoTherapy TPS by interactively optimizing the physical density of the couch using a planning support system. This modeling proved to be an efficient way of correcting the dosimetric effects of the treatment couch in tomotherapy planning and delivery.
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spelling pubmed-66987672019-08-22 Couch modeling optimization for tomotherapy planning and delivery Okada, Wataru Tanooka, Masao Sano, Keisuke Shibata, Mayuri Doi, Hiroshi Miyazaki, Masayoshi Nakahara, Ryuta Sueoka, Masaki Suzuki, Hitomi Fujiwara, Masayuki Inomata, Taisuke Yamakado, Koichiro J Appl Clin Med Phys Radiation Oncology Physics We sought to validate new couch modeling optimization for tomotherapy planning and delivery. We constructed simplified virtual structures just above a default setting couch through a planning support system (MIM Maestro, version 8.2, MIM Software Inc, Cleveland, OH, USA). Based on ionization chamber measurements, we performed interactive optimization and determined the most appropriate physical density of these virtual structures in a treatment planning system (TPS). To validate this couch optimization, Gamma analysis and these statistical analyses between a three‐dimensional diode array QA system (ArcCHECK, Sun Nuclear, Melbourne, FL, USA) results and calculations from ionization chamber measurements were performed at 3%/2 mm criteria with a threshold of 10% in clinical QA plans. Using a virtual model consisting of a center slab density of 4.2 g/cm(3) and both side slabs density of 1.9 g/cm(3), we demonstrated close agreement between measured dose and the TPS calculated dose. Agreement was within 1% for all gantry angles at the isocenter and within 2% in off‐axis plans. In validation of the couch modeling in a clinical QA plan, the average gamma passing rate improved approximately 0.6%–5.1%. It was statistically significant (P < 0.05) for all treatment sites. We successfully generated an accurate couch model for a TomoTherapy TPS by interactively optimizing the physical density of the couch using a planning support system. This modeling proved to be an efficient way of correcting the dosimetric effects of the treatment couch in tomotherapy planning and delivery. John Wiley and Sons Inc. 2019-07-25 /pmc/articles/PMC6698767/ /pubmed/31343831 http://dx.doi.org/10.1002/acm2.12686 Text en © 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Radiation Oncology Physics
Okada, Wataru
Tanooka, Masao
Sano, Keisuke
Shibata, Mayuri
Doi, Hiroshi
Miyazaki, Masayoshi
Nakahara, Ryuta
Sueoka, Masaki
Suzuki, Hitomi
Fujiwara, Masayuki
Inomata, Taisuke
Yamakado, Koichiro
Couch modeling optimization for tomotherapy planning and delivery
title Couch modeling optimization for tomotherapy planning and delivery
title_full Couch modeling optimization for tomotherapy planning and delivery
title_fullStr Couch modeling optimization for tomotherapy planning and delivery
title_full_unstemmed Couch modeling optimization for tomotherapy planning and delivery
title_short Couch modeling optimization for tomotherapy planning and delivery
title_sort couch modeling optimization for tomotherapy planning and delivery
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6698767/
https://www.ncbi.nlm.nih.gov/pubmed/31343831
http://dx.doi.org/10.1002/acm2.12686
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