Cargando…

Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach

PURPOSE: To assess the worst-case robust optimization IMPT plans with setup and range uncertainties and to test the hypothesis that the worst-case robust optimization strategies could cover most possible setup and range uncertainties in the real scenarios. METHODS: We analyzed the nominal and worst-...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Zhiyong, Li, Heng, Li, Yupeng, Li, Yuting, Chang, Yu, Li, Qin, Yang, Kunyu, Wu, Gang, Sahoo, Narayan, Poenisch, Falk, Gillin, Michael, Zhu, X. Ronald, Zhang, Xiaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642585/
https://www.ncbi.nlm.nih.gov/pubmed/31324257
http://dx.doi.org/10.1186/s13014-019-1335-8
_version_ 1783437006558199808
author Yang, Zhiyong
Li, Heng
Li, Yupeng
Li, Yuting
Chang, Yu
Li, Qin
Yang, Kunyu
Wu, Gang
Sahoo, Narayan
Poenisch, Falk
Gillin, Michael
Zhu, X. Ronald
Zhang, Xiaodong
author_facet Yang, Zhiyong
Li, Heng
Li, Yupeng
Li, Yuting
Chang, Yu
Li, Qin
Yang, Kunyu
Wu, Gang
Sahoo, Narayan
Poenisch, Falk
Gillin, Michael
Zhu, X. Ronald
Zhang, Xiaodong
author_sort Yang, Zhiyong
collection PubMed
description PURPOSE: To assess the worst-case robust optimization IMPT plans with setup and range uncertainties and to test the hypothesis that the worst-case robust optimization strategies could cover most possible setup and range uncertainties in the real scenarios. METHODS: We analyzed the nominal and worst-case robust optimization IMPT plans of seven patients with head and neck cancer patients. To take uncertainties into account for the dose calculation, we performed a comprehensive simulation in which the dose was recalculated 625 times per given plan using Gaussian systematic setup and proton range uncertainties. Subsequently, based on the simulation results, we calculated the target coverage in all perturbation scenarios, as well as the ratios of target coverage located within the threshold of eight worst-case scenarios. We set the criteria for the optimized plan to be the ratios of 1) the dose delivered to 95% (D95%) of clinical target volumes 1 and 2 (CTV1 and CTV2) above 95% of the prescribed dose, and 2) the D95% of clinical target volume 3 (CTV3) above 90% of the prescribed dose in worst-case situations. RESULTS: The probability that the perturbed-dose indices of the CTVs in each scenario were within the worst-case scenario limits ranged from 89.51 to 91.22% for both the nominal and worst-case robust optimization IMPT plans. A quartile analysis showed that the selective robust optimization IMPT plans all had higher D95% values for CTV1, CTV2, and CTV3 than did the nominal IMPT plans. CONCLUSIONS: The worst-case strategy for robust optimization is adequately models and covers most of the setup and range uncertainties for the IMPT treatment of head and neck patients in our center. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13014-019-1335-8) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6642585
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-66425852019-07-29 Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach Yang, Zhiyong Li, Heng Li, Yupeng Li, Yuting Chang, Yu Li, Qin Yang, Kunyu Wu, Gang Sahoo, Narayan Poenisch, Falk Gillin, Michael Zhu, X. Ronald Zhang, Xiaodong Radiat Oncol Research PURPOSE: To assess the worst-case robust optimization IMPT plans with setup and range uncertainties and to test the hypothesis that the worst-case robust optimization strategies could cover most possible setup and range uncertainties in the real scenarios. METHODS: We analyzed the nominal and worst-case robust optimization IMPT plans of seven patients with head and neck cancer patients. To take uncertainties into account for the dose calculation, we performed a comprehensive simulation in which the dose was recalculated 625 times per given plan using Gaussian systematic setup and proton range uncertainties. Subsequently, based on the simulation results, we calculated the target coverage in all perturbation scenarios, as well as the ratios of target coverage located within the threshold of eight worst-case scenarios. We set the criteria for the optimized plan to be the ratios of 1) the dose delivered to 95% (D95%) of clinical target volumes 1 and 2 (CTV1 and CTV2) above 95% of the prescribed dose, and 2) the D95% of clinical target volume 3 (CTV3) above 90% of the prescribed dose in worst-case situations. RESULTS: The probability that the perturbed-dose indices of the CTVs in each scenario were within the worst-case scenario limits ranged from 89.51 to 91.22% for both the nominal and worst-case robust optimization IMPT plans. A quartile analysis showed that the selective robust optimization IMPT plans all had higher D95% values for CTV1, CTV2, and CTV3 than did the nominal IMPT plans. CONCLUSIONS: The worst-case strategy for robust optimization is adequately models and covers most of the setup and range uncertainties for the IMPT treatment of head and neck patients in our center. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13014-019-1335-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-19 /pmc/articles/PMC6642585/ /pubmed/31324257 http://dx.doi.org/10.1186/s13014-019-1335-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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
Yang, Zhiyong
Li, Heng
Li, Yupeng
Li, Yuting
Chang, Yu
Li, Qin
Yang, Kunyu
Wu, Gang
Sahoo, Narayan
Poenisch, Falk
Gillin, Michael
Zhu, X. Ronald
Zhang, Xiaodong
Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach
title Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach
title_full Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach
title_fullStr Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach
title_full_unstemmed Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach
title_short Statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach
title_sort statistical evaluation of worst-case robust optimization intensity-modulated proton therapy plans using an exhaustive sampling approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642585/
https://www.ncbi.nlm.nih.gov/pubmed/31324257
http://dx.doi.org/10.1186/s13014-019-1335-8
work_keys_str_mv AT yangzhiyong statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT liheng statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT liyupeng statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT liyuting statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT changyu statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT liqin statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT yangkunyu statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT wugang statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT sahoonarayan statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT poenischfalk statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT gillinmichael statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT zhuxronald statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach
AT zhangxiaodong statisticalevaluationofworstcaserobustoptimizationintensitymodulatedprotontherapyplansusinganexhaustivesamplingapproach