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Initial evaluation of automated treatment planning software
Even with advanced inverse‐planning techniques, radiation treatment plan optimization remains a very time‐consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690942/ https://www.ncbi.nlm.nih.gov/pubmed/27167292 http://dx.doi.org/10.1120/jacmp.v17i3.6167 |
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author | Gintz, Dawn Latifi, Kujtim Caudell, Jimmy Nelms, Benjamin Zhang, Geoffrey Moros, Eduardo Feygelman, Vladimir |
author_facet | Gintz, Dawn Latifi, Kujtim Caudell, Jimmy Nelms, Benjamin Zhang, Geoffrey Moros, Eduardo Feygelman, Vladimir |
author_sort | Gintz, Dawn |
collection | PubMed |
description | Even with advanced inverse‐planning techniques, radiation treatment plan optimization remains a very time‐consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators to progressively guide the traditional optimization process with automatically created regions of interest and associated dose‐volume objectives. We report on the initial evaluation of this algorithm on 10 challenging cases of locoreginally advanced head and neck cancer. All patients were treated with VMAT to 70 Gy to the gross disease and 56 Gy to the elective bilateral nodes. The results of post‐treatment autoplanning (AP) were compared to the original human‐driven plans (HDP). We used an objective scoring system based on defining a collection of specific dosimetric metrics and corresponding numeric score functions for each. Five AP techniques with different input dose goals were applied to all patients. The best of them averaged the composite score 8% lower than the HDP, across the patient population. The difference in median values was statistically significant at the 95% confidence level (Wilcoxon paired signed‐rank test [Formula: see text]). This result reflects the premium the institution places on dose homogeneity, which was consistently higher with the HDPs. The OAR sparing was consistently better with the APs, the differences reaching statistical significance for the mean doses to the parotid glands ([Formula: see text]) and the inferior pharyngeal constrictor ([Formula: see text]), as well as for the maximum doses to the spinal cord ([Formula: see text]) and brainstem ([Formula: see text]). If one is prepared to accept less stringent dose homogeneity criteria from the RTOG 1016 protocol, nine APs would comply with the protocol, while providing lower OAR doses than the HDPs. Overall, AP is a promising clinical tool, but it could benefit from a better process for shifting the balance between the target dose coverage/homogeneity and OAR sparing. PACS number(s): 87.55.D |
format | Online Article Text |
id | pubmed-5690942 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-56909422018-04-02 Initial evaluation of automated treatment planning software Gintz, Dawn Latifi, Kujtim Caudell, Jimmy Nelms, Benjamin Zhang, Geoffrey Moros, Eduardo Feygelman, Vladimir J Appl Clin Med Phys Radiation Oncology Physics Even with advanced inverse‐planning techniques, radiation treatment plan optimization remains a very time‐consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators to progressively guide the traditional optimization process with automatically created regions of interest and associated dose‐volume objectives. We report on the initial evaluation of this algorithm on 10 challenging cases of locoreginally advanced head and neck cancer. All patients were treated with VMAT to 70 Gy to the gross disease and 56 Gy to the elective bilateral nodes. The results of post‐treatment autoplanning (AP) were compared to the original human‐driven plans (HDP). We used an objective scoring system based on defining a collection of specific dosimetric metrics and corresponding numeric score functions for each. Five AP techniques with different input dose goals were applied to all patients. The best of them averaged the composite score 8% lower than the HDP, across the patient population. The difference in median values was statistically significant at the 95% confidence level (Wilcoxon paired signed‐rank test [Formula: see text]). This result reflects the premium the institution places on dose homogeneity, which was consistently higher with the HDPs. The OAR sparing was consistently better with the APs, the differences reaching statistical significance for the mean doses to the parotid glands ([Formula: see text]) and the inferior pharyngeal constrictor ([Formula: see text]), as well as for the maximum doses to the spinal cord ([Formula: see text]) and brainstem ([Formula: see text]). If one is prepared to accept less stringent dose homogeneity criteria from the RTOG 1016 protocol, nine APs would comply with the protocol, while providing lower OAR doses than the HDPs. Overall, AP is a promising clinical tool, but it could benefit from a better process for shifting the balance between the target dose coverage/homogeneity and OAR sparing. PACS number(s): 87.55.D John Wiley and Sons Inc. 2016-05-08 /pmc/articles/PMC5690942/ /pubmed/27167292 http://dx.doi.org/10.1120/jacmp.v17i3.6167 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 Gintz, Dawn Latifi, Kujtim Caudell, Jimmy Nelms, Benjamin Zhang, Geoffrey Moros, Eduardo Feygelman, Vladimir Initial evaluation of automated treatment planning software |
title | Initial evaluation of automated treatment planning software |
title_full | Initial evaluation of automated treatment planning software |
title_fullStr | Initial evaluation of automated treatment planning software |
title_full_unstemmed | Initial evaluation of automated treatment planning software |
title_short | Initial evaluation of automated treatment planning software |
title_sort | initial evaluation of automated treatment planning software |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690942/ https://www.ncbi.nlm.nih.gov/pubmed/27167292 http://dx.doi.org/10.1120/jacmp.v17i3.6167 |
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