Cargando…

Evaluation of fluence‐smoothing feature for three IMRT planning systems

Commercially available intensity‐modulated radiation therapy (IMRT) inverse treatment planning systems (ITPS) typically include a smoothing function which allows the user to vary the complexity of delivered beam fluence patterns. This study evaluated the behavior of three ITPSs when varying smoothin...

Descripción completa

Detalles Bibliográficos
Autores principales: Anker, Christopher J., Wang, Brian, Tobler, Matt, Chapek, Julie, Shrieve, Dennis C., Hitchcock, Ying J., Salter, Bill J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5719958/
https://www.ncbi.nlm.nih.gov/pubmed/20592692
http://dx.doi.org/10.1120/jacmp.v11i2.3035
_version_ 1783284588248825856
author Anker, Christopher J.
Wang, Brian
Tobler, Matt
Chapek, Julie
Shrieve, Dennis C.
Hitchcock, Ying J.
Salter, Bill J.
author_facet Anker, Christopher J.
Wang, Brian
Tobler, Matt
Chapek, Julie
Shrieve, Dennis C.
Hitchcock, Ying J.
Salter, Bill J.
author_sort Anker, Christopher J.
collection PubMed
description Commercially available intensity‐modulated radiation therapy (IMRT) inverse treatment planning systems (ITPS) typically include a smoothing function which allows the user to vary the complexity of delivered beam fluence patterns. This study evaluated the behavior of three ITPSs when varying smoothing parameters. We evaluated four cases treated with IMRT in our clinic: sinonasal carcinoma (SNC), glioblastoma multiforme (GBM), base of tongue carcinoma (BOT), and prostate carcinoma (PST). Varian Eclipse v6.5, BrainLAB BrainScan v5.31, and Nomos Corvus v6.2 ITPSs were studied for the SNC, GBM, and PST sites. Only Eclipse and Corvus were studied for BOT due to field size constraints of the BrainLAB MM3 collimator. For each ITPS, plans were first optimized using vendor‐recommended default “smoothing” values. Treatment plans were then reoptimized, exploring various smoothing values. Key metrics recorded included a delivery complexity (DC) metric and the Ian Paddick Conformality Index (IPCI). Results varied widely by vendor with regard to the impact of smoothing on complexity and conformality. Plans run on the Corvus ITPS showed the logically anticipated increase in DC as smoothing was decreased, along with associated improved organ‐at‐risk (OAR) sparing. Both Eclipse and BrainScan experienced an expected trend for increased DC as smoothing was decreased. However, this increase did not typically result in appreciably improved OAR sparing. For Eclipse and Corvus, and to a much lesser extent BrainScan, increases in smoothing decreased DC but eventually caused unacceptable losses in plan conformality. Depending on the ITPS, potential benefits from optimizing fluence smoothing levels can be significant, allowing for increases in either efficiency or conformality. Because of variability in smoothing function behavior by ITPS, it is important that users familiarize themselves with the effects of varying smoothing parameters for their respective ITPS. Based on the experience gained here, we provide recommended workflows for each ITPS to best exploit the fluence‐smoothing features of the system. PACS numbers: 87.56.bd, 87.56.N‐
format Online
Article
Text
id pubmed-5719958
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-57199582018-04-02 Evaluation of fluence‐smoothing feature for three IMRT planning systems Anker, Christopher J. Wang, Brian Tobler, Matt Chapek, Julie Shrieve, Dennis C. Hitchcock, Ying J. Salter, Bill J. J Appl Clin Med Phys Radiation Oncology Physics Commercially available intensity‐modulated radiation therapy (IMRT) inverse treatment planning systems (ITPS) typically include a smoothing function which allows the user to vary the complexity of delivered beam fluence patterns. This study evaluated the behavior of three ITPSs when varying smoothing parameters. We evaluated four cases treated with IMRT in our clinic: sinonasal carcinoma (SNC), glioblastoma multiforme (GBM), base of tongue carcinoma (BOT), and prostate carcinoma (PST). Varian Eclipse v6.5, BrainLAB BrainScan v5.31, and Nomos Corvus v6.2 ITPSs were studied for the SNC, GBM, and PST sites. Only Eclipse and Corvus were studied for BOT due to field size constraints of the BrainLAB MM3 collimator. For each ITPS, plans were first optimized using vendor‐recommended default “smoothing” values. Treatment plans were then reoptimized, exploring various smoothing values. Key metrics recorded included a delivery complexity (DC) metric and the Ian Paddick Conformality Index (IPCI). Results varied widely by vendor with regard to the impact of smoothing on complexity and conformality. Plans run on the Corvus ITPS showed the logically anticipated increase in DC as smoothing was decreased, along with associated improved organ‐at‐risk (OAR) sparing. Both Eclipse and BrainScan experienced an expected trend for increased DC as smoothing was decreased. However, this increase did not typically result in appreciably improved OAR sparing. For Eclipse and Corvus, and to a much lesser extent BrainScan, increases in smoothing decreased DC but eventually caused unacceptable losses in plan conformality. Depending on the ITPS, potential benefits from optimizing fluence smoothing levels can be significant, allowing for increases in either efficiency or conformality. Because of variability in smoothing function behavior by ITPS, it is important that users familiarize themselves with the effects of varying smoothing parameters for their respective ITPS. Based on the experience gained here, we provide recommended workflows for each ITPS to best exploit the fluence‐smoothing features of the system. PACS numbers: 87.56.bd, 87.56.N‐ John Wiley and Sons Inc. 2010-04-16 /pmc/articles/PMC5719958/ /pubmed/20592692 http://dx.doi.org/10.1120/jacmp.v11i2.3035 Text en © 2010 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
Anker, Christopher J.
Wang, Brian
Tobler, Matt
Chapek, Julie
Shrieve, Dennis C.
Hitchcock, Ying J.
Salter, Bill J.
Evaluation of fluence‐smoothing feature for three IMRT planning systems
title Evaluation of fluence‐smoothing feature for three IMRT planning systems
title_full Evaluation of fluence‐smoothing feature for three IMRT planning systems
title_fullStr Evaluation of fluence‐smoothing feature for three IMRT planning systems
title_full_unstemmed Evaluation of fluence‐smoothing feature for three IMRT planning systems
title_short Evaluation of fluence‐smoothing feature for three IMRT planning systems
title_sort evaluation of fluence‐smoothing feature for three imrt planning systems
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5719958/
https://www.ncbi.nlm.nih.gov/pubmed/20592692
http://dx.doi.org/10.1120/jacmp.v11i2.3035
work_keys_str_mv AT ankerchristopherj evaluationoffluencesmoothingfeatureforthreeimrtplanningsystems
AT wangbrian evaluationoffluencesmoothingfeatureforthreeimrtplanningsystems
AT toblermatt evaluationoffluencesmoothingfeatureforthreeimrtplanningsystems
AT chapekjulie evaluationoffluencesmoothingfeatureforthreeimrtplanningsystems
AT shrievedennisc evaluationoffluencesmoothingfeatureforthreeimrtplanningsystems
AT hitchcockyingj evaluationoffluencesmoothingfeatureforthreeimrtplanningsystems
AT salterbillj evaluationoffluencesmoothingfeatureforthreeimrtplanningsystems