Cargando…

Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction

A recent publication indicated that the patient anatomical feature (PAF) model was capable of predicting optimal objectives based on past experience. In this study, the benefits of IMRT optimization using PAF‐predicted objectives as guidance for prostate were evaluated. Three different optimization...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Yun, Li, Taoran, Yuan, Lulin, Ge, Yaorong, Yin, Fang‐Fang, Lee, W. Robert, Wu, Q. Jackie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690098/
https://www.ncbi.nlm.nih.gov/pubmed/26103191
http://dx.doi.org/10.1120/jacmp.v16i2.5204
_version_ 1783279529144352768
author Yang, Yun
Li, Taoran
Yuan, Lulin
Ge, Yaorong
Yin, Fang‐Fang
Lee, W. Robert
Wu, Q. Jackie
author_facet Yang, Yun
Li, Taoran
Yuan, Lulin
Ge, Yaorong
Yin, Fang‐Fang
Lee, W. Robert
Wu, Q. Jackie
author_sort Yang, Yun
collection PubMed
description A recent publication indicated that the patient anatomical feature (PAF) model was capable of predicting optimal objectives based on past experience. In this study, the benefits of IMRT optimization using PAF‐predicted objectives as guidance for prostate were evaluated. Three different optimization methods were compared. 1) Expert Plan: Ten prostate cases (16 plans) were planned by an expert planner using conventional trial‐and‐error approach started with institutional modified OAR and PTV constraints. Optimization was stopped at 150 iterations and that plan was saved as Expert Plan. 2) Clinical Plan: The planner would keep working on the Expert Plan till he was satisfied with the dosimetric quality and the final plan was referred to as Clinical Plan. 3) PAF Plan: A third sets of plans for the same ten patients were generated fully automatically using predicted DVHs as guidance. The optimization was based on PAF‐based predicted objectives, and was continued to 150 iterations without human interaction. [Formula: see text] and [Formula: see text] for PTV, [Formula: see text] for femoral heads, [Formula: see text] , D(10cc), [Formula: see text] , and [Formula: see text] for bladder/rectum were compared. Clinical Plans are further optimized with more iterations and adjustments, but in general provided limited dosimetric benefits over Expert Plans. PTV [Formula: see text] agreed within 2.31% among Expert, Clinical, and PAF plans. Between Clinical and PAF Plans, differences for [Formula: see text] of PTV, bladder, and rectum were within 2.65%, 2.46%, and 2.20%, respectively. Bladder D(10cc) was higher for PAF but [Formula: see text] in general. Bladder [Formula: see text] and [Formula: see text] were lower for PAF, by up to 7.71% and 6.81%, respectively. Rectum D(10cc), [Formula: see text] , and [Formula: see text] were 2.11%, 2.72%, and 0.27% lower for PAF, respectively. [Formula: see text] for femoral heads were comparable ([Formula: see text] on average). Compared to Clinical Plan ([Formula: see text]), the average optimization time for PAF plan was reduced by 5.2 min on average, with a maximum reduction of 7.1 min. Total numbers of MUs per plan for PAF Plans were lower than Clinical Plans, indicating better delivery efficiency. The PAF‐guided planning process is capable of generating clinical‐quality prostate IMRT plans with no human intervention. Compared to manual optimization, this automatic optimization increases planning and delivery efficiency, while maintaining plan quality. PACS numbers: 87.55.D‐, 87.55.de, 87.53.Jw
format Online
Article
Text
id pubmed-5690098
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-56900982018-04-02 Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction Yang, Yun Li, Taoran Yuan, Lulin Ge, Yaorong Yin, Fang‐Fang Lee, W. Robert Wu, Q. Jackie J Appl Clin Med Phys Radiation Oncology Physics A recent publication indicated that the patient anatomical feature (PAF) model was capable of predicting optimal objectives based on past experience. In this study, the benefits of IMRT optimization using PAF‐predicted objectives as guidance for prostate were evaluated. Three different optimization methods were compared. 1) Expert Plan: Ten prostate cases (16 plans) were planned by an expert planner using conventional trial‐and‐error approach started with institutional modified OAR and PTV constraints. Optimization was stopped at 150 iterations and that plan was saved as Expert Plan. 2) Clinical Plan: The planner would keep working on the Expert Plan till he was satisfied with the dosimetric quality and the final plan was referred to as Clinical Plan. 3) PAF Plan: A third sets of plans for the same ten patients were generated fully automatically using predicted DVHs as guidance. The optimization was based on PAF‐based predicted objectives, and was continued to 150 iterations without human interaction. [Formula: see text] and [Formula: see text] for PTV, [Formula: see text] for femoral heads, [Formula: see text] , D(10cc), [Formula: see text] , and [Formula: see text] for bladder/rectum were compared. Clinical Plans are further optimized with more iterations and adjustments, but in general provided limited dosimetric benefits over Expert Plans. PTV [Formula: see text] agreed within 2.31% among Expert, Clinical, and PAF plans. Between Clinical and PAF Plans, differences for [Formula: see text] of PTV, bladder, and rectum were within 2.65%, 2.46%, and 2.20%, respectively. Bladder D(10cc) was higher for PAF but [Formula: see text] in general. Bladder [Formula: see text] and [Formula: see text] were lower for PAF, by up to 7.71% and 6.81%, respectively. Rectum D(10cc), [Formula: see text] , and [Formula: see text] were 2.11%, 2.72%, and 0.27% lower for PAF, respectively. [Formula: see text] for femoral heads were comparable ([Formula: see text] on average). Compared to Clinical Plan ([Formula: see text]), the average optimization time for PAF plan was reduced by 5.2 min on average, with a maximum reduction of 7.1 min. Total numbers of MUs per plan for PAF Plans were lower than Clinical Plans, indicating better delivery efficiency. The PAF‐guided planning process is capable of generating clinical‐quality prostate IMRT plans with no human intervention. Compared to manual optimization, this automatic optimization increases planning and delivery efficiency, while maintaining plan quality. PACS numbers: 87.55.D‐, 87.55.de, 87.53.Jw John Wiley and Sons Inc. 2015-03-08 /pmc/articles/PMC5690098/ /pubmed/26103191 http://dx.doi.org/10.1120/jacmp.v16i2.5204 Text en © 2015 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
Yang, Yun
Li, Taoran
Yuan, Lulin
Ge, Yaorong
Yin, Fang‐Fang
Lee, W. Robert
Wu, Q. Jackie
Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction
title Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction
title_full Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction
title_fullStr Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction
title_full_unstemmed Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction
title_short Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction
title_sort quantitative comparison of automatic and manual imrt optimization for prostate cancer: the benefits of dvh prediction
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690098/
https://www.ncbi.nlm.nih.gov/pubmed/26103191
http://dx.doi.org/10.1120/jacmp.v16i2.5204
work_keys_str_mv AT yangyun quantitativecomparisonofautomaticandmanualimrtoptimizationforprostatecancerthebenefitsofdvhprediction
AT litaoran quantitativecomparisonofautomaticandmanualimrtoptimizationforprostatecancerthebenefitsofdvhprediction
AT yuanlulin quantitativecomparisonofautomaticandmanualimrtoptimizationforprostatecancerthebenefitsofdvhprediction
AT geyaorong quantitativecomparisonofautomaticandmanualimrtoptimizationforprostatecancerthebenefitsofdvhprediction
AT yinfangfang quantitativecomparisonofautomaticandmanualimrtoptimizationforprostatecancerthebenefitsofdvhprediction
AT leewrobert quantitativecomparisonofautomaticandmanualimrtoptimizationforprostatecancerthebenefitsofdvhprediction
AT wuqjackie quantitativecomparisonofautomaticandmanualimrtoptimizationforprostatecancerthebenefitsofdvhprediction