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Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning
BACKGROUND: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the judgment of the experienced planner. METHODS: Thirty...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433067/ https://www.ncbi.nlm.nih.gov/pubmed/25957871 http://dx.doi.org/10.1186/s13014-015-0416-6 |
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author | Nwankwo, Obioma Mekdash, Hana Sihono, Dwi Seno Kuncoro Wenz, Frederik Glatting, Gerhard |
author_facet | Nwankwo, Obioma Mekdash, Hana Sihono, Dwi Seno Kuncoro Wenz, Frederik Glatting, Gerhard |
author_sort | Nwankwo, Obioma |
collection | PubMed |
description | BACKGROUND: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the judgment of the experienced planner. METHODS: Thirty volumetric modulated arc therapy plans were randomly selected from a database of prostate plans that were generated by experienced planners (expert plans). The anatomical data (CT scan and delineation of organs) of these patients and the KBRT algorithm were given to a novice with no prior treatment planning experience. The inexperienced planner used the knowledge-based algorithm to predict the dose that the OARs receive based on their proximity to the treated volume. The population-based OAR constraints were changed to the predicted doses. A KBRT plan was subsequently generated. The KBRT and expert plans were compared for the achieved target coverage and OAR sparing. The target coverages were compared using the Uniformity Index (UI), while 5 dose-volume points (D(10), D(30,) D(50), D(70) and D(90)) were used to compare the OARs (bladder and rectum) doses. Wilcoxon matched-pairs signed rank test was used to check for significant differences (p < 0.05) between both datasets. RESULTS: The KBRT and expert plans achieved mean UI values of 1.10 ± 0.03 and 1.10 ± 0.04, respectively. The Wilcoxon test showed no statistically significant difference between both results. The D(90), D(70,) D(50), D(30) and D(10) values of the two planning strategies, and the Wilcoxon test results suggests that the KBRT plans achieved a statistically significant lower bladder dose (at D(30)), while the expert plans achieved a statistically significant lower rectal dose (at D(10) and D(30)). CONCLUSIONS: The results of this study show that the KBRT treatment planning approach is a promising method to objectively incorporate patient anatomical variations in radiotherapy treatment planning. |
format | Online Article Text |
id | pubmed-4433067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44330672015-05-16 Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning Nwankwo, Obioma Mekdash, Hana Sihono, Dwi Seno Kuncoro Wenz, Frederik Glatting, Gerhard Radiat Oncol Research BACKGROUND: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the judgment of the experienced planner. METHODS: Thirty volumetric modulated arc therapy plans were randomly selected from a database of prostate plans that were generated by experienced planners (expert plans). The anatomical data (CT scan and delineation of organs) of these patients and the KBRT algorithm were given to a novice with no prior treatment planning experience. The inexperienced planner used the knowledge-based algorithm to predict the dose that the OARs receive based on their proximity to the treated volume. The population-based OAR constraints were changed to the predicted doses. A KBRT plan was subsequently generated. The KBRT and expert plans were compared for the achieved target coverage and OAR sparing. The target coverages were compared using the Uniformity Index (UI), while 5 dose-volume points (D(10), D(30,) D(50), D(70) and D(90)) were used to compare the OARs (bladder and rectum) doses. Wilcoxon matched-pairs signed rank test was used to check for significant differences (p < 0.05) between both datasets. RESULTS: The KBRT and expert plans achieved mean UI values of 1.10 ± 0.03 and 1.10 ± 0.04, respectively. The Wilcoxon test showed no statistically significant difference between both results. The D(90), D(70,) D(50), D(30) and D(10) values of the two planning strategies, and the Wilcoxon test results suggests that the KBRT plans achieved a statistically significant lower bladder dose (at D(30)), while the expert plans achieved a statistically significant lower rectal dose (at D(10) and D(30)). CONCLUSIONS: The results of this study show that the KBRT treatment planning approach is a promising method to objectively incorporate patient anatomical variations in radiotherapy treatment planning. BioMed Central 2015-05-10 /pmc/articles/PMC4433067/ /pubmed/25957871 http://dx.doi.org/10.1186/s13014-015-0416-6 Text en © Nwankwo et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Nwankwo, Obioma Mekdash, Hana Sihono, Dwi Seno Kuncoro Wenz, Frederik Glatting, Gerhard Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning |
title | Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning |
title_full | Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning |
title_fullStr | Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning |
title_full_unstemmed | Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning |
title_short | Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning |
title_sort | knowledge-based radiation therapy (kbrt) treatment planning versus planning by experts: validation of a kbrt algorithm for prostate cancer treatment planning |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433067/ https://www.ncbi.nlm.nih.gov/pubmed/25957871 http://dx.doi.org/10.1186/s13014-015-0416-6 |
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