Cargando…

Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system

A new GPU‐based Monte Carlo dose calculation algorithm (GPUMCD), developed by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for...

Descripción completa

Detalles Bibliográficos
Autores principales: Paudel, Moti R., Kim, Anthony, Sarfehnia, Arman, Ahmad, Sayed B., Beachey, David J., Sahgal, Arjun, Keller, Brian M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690498/
https://www.ncbi.nlm.nih.gov/pubmed/27929496
http://dx.doi.org/10.1120/jacmp.v17i6.6455
_version_ 1783279620267704320
author Paudel, Moti R.
Kim, Anthony
Sarfehnia, Arman
Ahmad, Sayed B.
Beachey, David J.
Sahgal, Arjun
Keller, Brian M.
author_facet Paudel, Moti R.
Kim, Anthony
Sarfehnia, Arman
Ahmad, Sayed B.
Beachey, David J.
Sahgal, Arjun
Keller, Brian M.
author_sort Paudel, Moti R.
collection PubMed
description A new GPU‐based Monte Carlo dose calculation algorithm (GPUMCD), developed by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios — tumor‐in‐lung, lung, and bone‐in‐tissue — was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correction. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for [Formula: see text] , and [Formula: see text] field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within [Formula: see text] of film measurements and within 1% of ion chamber measurements. For the tumor‐in‐lung phantom, the calculated doses were within [Formula: see text] of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within [Formula: see text] of film measurements, except for the [Formula: see text] field size where the CCC algorithm underestimated the depth dose by [Formula: see text] in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within [Formula: see text] of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly. PACS number(s): 87.53.Bn, 87.55.dh, 87.55.km
format Online
Article
Text
id pubmed-5690498
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-56904982018-04-02 Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system Paudel, Moti R. Kim, Anthony Sarfehnia, Arman Ahmad, Sayed B. Beachey, David J. Sahgal, Arjun Keller, Brian M. J Appl Clin Med Phys Radiation Oncology Physics A new GPU‐based Monte Carlo dose calculation algorithm (GPUMCD), developed by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios — tumor‐in‐lung, lung, and bone‐in‐tissue — was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correction. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for [Formula: see text] , and [Formula: see text] field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within [Formula: see text] of film measurements and within 1% of ion chamber measurements. For the tumor‐in‐lung phantom, the calculated doses were within [Formula: see text] of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within [Formula: see text] of film measurements, except for the [Formula: see text] field size where the CCC algorithm underestimated the depth dose by [Formula: see text] in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within [Formula: see text] of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly. PACS number(s): 87.53.Bn, 87.55.dh, 87.55.km John Wiley and Sons Inc. 2016-11-08 /pmc/articles/PMC5690498/ /pubmed/27929496 http://dx.doi.org/10.1120/jacmp.v17i6.6455 Text en © 2016 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
Paudel, Moti R.
Kim, Anthony
Sarfehnia, Arman
Ahmad, Sayed B.
Beachey, David J.
Sahgal, Arjun
Keller, Brian M.
Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system
title Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system
title_full Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system
title_fullStr Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system
title_full_unstemmed Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system
title_short Experimental evaluation of a GPU‐based Monte Carlo dose calculation algorithm in the Monaco treatment planning system
title_sort experimental evaluation of a gpu‐based monte carlo dose calculation algorithm in the monaco treatment planning system
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690498/
https://www.ncbi.nlm.nih.gov/pubmed/27929496
http://dx.doi.org/10.1120/jacmp.v17i6.6455
work_keys_str_mv AT paudelmotir experimentalevaluationofagpubasedmontecarlodosecalculationalgorithminthemonacotreatmentplanningsystem
AT kimanthony experimentalevaluationofagpubasedmontecarlodosecalculationalgorithminthemonacotreatmentplanningsystem
AT sarfehniaarman experimentalevaluationofagpubasedmontecarlodosecalculationalgorithminthemonacotreatmentplanningsystem
AT ahmadsayedb experimentalevaluationofagpubasedmontecarlodosecalculationalgorithminthemonacotreatmentplanningsystem
AT beacheydavidj experimentalevaluationofagpubasedmontecarlodosecalculationalgorithminthemonacotreatmentplanningsystem
AT sahgalarjun experimentalevaluationofagpubasedmontecarlodosecalculationalgorithminthemonacotreatmentplanningsystem
AT kellerbrianm experimentalevaluationofagpubasedmontecarlodosecalculationalgorithminthemonacotreatmentplanningsystem