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Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements

This work shows the feasibility of collecting linear accelerator beam data using just a 1‐D water tank and automated couch movements with the goal to maximize the cost effectiveness in resource‐limited clinical settings. Two commissioning datasets were acquired: (a) using a standard of practice 3D w...

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Autores principales: Knutson, Nels C., Schmidt, Matthew C., Belley, Matthew D., Nguyen, Ngoc, Price, Michael, Mutic, Sasa, Sajo, Erno, Li, H. Harold
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236829/
https://www.ncbi.nlm.nih.gov/pubmed/30188009
http://dx.doi.org/10.1002/acm2.12444
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author Knutson, Nels C.
Schmidt, Matthew C.
Belley, Matthew D.
Nguyen, Ngoc
Price, Michael
Mutic, Sasa
Sajo, Erno
Li, H. Harold
author_facet Knutson, Nels C.
Schmidt, Matthew C.
Belley, Matthew D.
Nguyen, Ngoc
Price, Michael
Mutic, Sasa
Sajo, Erno
Li, H. Harold
author_sort Knutson, Nels C.
collection PubMed
description This work shows the feasibility of collecting linear accelerator beam data using just a 1‐D water tank and automated couch movements with the goal to maximize the cost effectiveness in resource‐limited clinical settings. Two commissioning datasets were acquired: (a) using a standard of practice 3D water tank scanning system (3DS) and (b) using a novel technique to translate a commercial TG‐51 complaint 1D water tank via automated couch movements (1DS). The Extensible Markup Language (XML) was used to dynamically move the linear accelerator couch position (and thus the 1D tank) during radiation delivery for the acquisition of inline, crossline, and diagonal profiles. Both the 1DS and 3DS datasets were used to generate beam models (BM (1) (DS) and BM (3) (DS)) in a commercial treatment planning system (TPS). 98.7% of 1DS measured points had a gamma value (2%/2 mm) < 1 when compared with the 3DS. Static jaw defined field and dynamic MLC field dose distribution comparisons for the TPS beam models BM (1) (DS) and BM (3) (DS) had 3D gamma values (2%/2 mm) < 1 for all 24,900,000 data points tested and >99.5% pass rate with gamma value (1%/1 mm) < 1. In conclusion, automated couch motions and a 1D scanning tank were used to collect commissioning beam data with accuracy comparable to traditionally acquired data using a 3D scanning system. TPS beam models generated directly from 1DS measured data were clinically equivalent to a model derived from 3DS data.
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spelling pubmed-62368292018-11-20 Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements Knutson, Nels C. Schmidt, Matthew C. Belley, Matthew D. Nguyen, Ngoc Price, Michael Mutic, Sasa Sajo, Erno Li, H. Harold J Appl Clin Med Phys Radiation Oncology Physics This work shows the feasibility of collecting linear accelerator beam data using just a 1‐D water tank and automated couch movements with the goal to maximize the cost effectiveness in resource‐limited clinical settings. Two commissioning datasets were acquired: (a) using a standard of practice 3D water tank scanning system (3DS) and (b) using a novel technique to translate a commercial TG‐51 complaint 1D water tank via automated couch movements (1DS). The Extensible Markup Language (XML) was used to dynamically move the linear accelerator couch position (and thus the 1D tank) during radiation delivery for the acquisition of inline, crossline, and diagonal profiles. Both the 1DS and 3DS datasets were used to generate beam models (BM (1) (DS) and BM (3) (DS)) in a commercial treatment planning system (TPS). 98.7% of 1DS measured points had a gamma value (2%/2 mm) < 1 when compared with the 3DS. Static jaw defined field and dynamic MLC field dose distribution comparisons for the TPS beam models BM (1) (DS) and BM (3) (DS) had 3D gamma values (2%/2 mm) < 1 for all 24,900,000 data points tested and >99.5% pass rate with gamma value (1%/1 mm) < 1. In conclusion, automated couch motions and a 1D scanning tank were used to collect commissioning beam data with accuracy comparable to traditionally acquired data using a 3D scanning system. TPS beam models generated directly from 1DS measured data were clinically equivalent to a model derived from 3DS data. John Wiley and Sons Inc. 2018-09-06 /pmc/articles/PMC6236829/ /pubmed/30188009 http://dx.doi.org/10.1002/acm2.12444 Text en © 2018 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
Knutson, Nels C.
Schmidt, Matthew C.
Belley, Matthew D.
Nguyen, Ngoc
Price, Michael
Mutic, Sasa
Sajo, Erno
Li, H. Harold
Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements
title Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements
title_full Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements
title_fullStr Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements
title_full_unstemmed Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements
title_short Equivalency of beam scan data collection using a 1D tank and automated couch movements to traditional 3D tank measurements
title_sort equivalency of beam scan data collection using a 1d tank and automated couch movements to traditional 3d tank measurements
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236829/
https://www.ncbi.nlm.nih.gov/pubmed/30188009
http://dx.doi.org/10.1002/acm2.12444
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