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A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy

PURPOSE: To optimize collimator setting to improve dosimetric quality of pancreas volumetric modulated arc therapy plan for stereotactic body radiation therapy. MATERIALS AND METHODS: Fifty-five volumetric modulated arc therapy cases in stereotactic body radiation therapy of pancreas were retrospect...

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Autores principales: Li, Xinyi, Wu, Jackie, Palta, Manisha, Zhang, You, Sheng, Yang, Zhang, Jiahan, Wang, Chunhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702773/
https://www.ncbi.nlm.nih.gov/pubmed/31426721
http://dx.doi.org/10.1177/1533033819870767
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author Li, Xinyi
Wu, Jackie
Palta, Manisha
Zhang, You
Sheng, Yang
Zhang, Jiahan
Wang, Chunhao
author_facet Li, Xinyi
Wu, Jackie
Palta, Manisha
Zhang, You
Sheng, Yang
Zhang, Jiahan
Wang, Chunhao
author_sort Li, Xinyi
collection PubMed
description PURPOSE: To optimize collimator setting to improve dosimetric quality of pancreas volumetric modulated arc therapy plan for stereotactic body radiation therapy. MATERIALS AND METHODS: Fifty-five volumetric modulated arc therapy cases in stereotactic body radiation therapy of pancreas were retrospectively included in this study with internal review board approval. Different from the routine practice of initializing collimator settings with a template, the proposed algorithm simultaneously optimizes the collimator angles and jaw positions that are customized to the patient geometry. Specifically, this algorithm includes 2 key steps: (1) an iterative optimization algorithm via simulated annealing that generates a set of potential collimator settings from 39 cases with pancreas stereotactic body radiation therapy, and (2) a multi-leaf collimator modulation scoring system that makes the final decision of the optimal collimator settings (collimator angles and jaw positions) based on organs at risk sparing criteria. For validation, the other 16 cases with pancreas stereotactic body radiation therapy were analyzed. Two plans were generated for each validation case, with one plan optimized using the proposed algorithm (Plan(opt)) and the other plan with the template setting (Plan(conv)). Each plan was optimized with 2 full arcs and the same set of constraints for the same case. Dosimetric results were analyzed and compared, including target dose coverage, conformity, organs at risk maximum dose, and modulation complexity score. All results were tested by Wilcoxon signed rank tests, and the statistical significance level was set to .05. RESULTS: Both plan groups had comparable target dose coverage and mean doses of all organs at risk. However, organs at risk (stomach, duodenum, large/small bowel) maximum dose sparing (D(0.1 cc) and D(0.03 cc)) was improved in Plan(opt) compared to Plan(conv). Plan(opt) also showed lower modulation complexity score, which suggests better capability of handling complex shape and sparing organs at risk . CONCLUSIONS: The proposed collimator settings optimization algorithm successfully improved dosimetric performance for dual-arc pancreas volumetric modulated arc therapy plans in stereotactic body radiation therapy of pancreas. This algorithm has the capability of immediate clinical application.
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spelling pubmed-67027732019-08-27 A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy Li, Xinyi Wu, Jackie Palta, Manisha Zhang, You Sheng, Yang Zhang, Jiahan Wang, Chunhao Technol Cancer Res Treat Special Collection on Artificial Intelligence Based Treatment Planning for Radiotherapy PURPOSE: To optimize collimator setting to improve dosimetric quality of pancreas volumetric modulated arc therapy plan for stereotactic body radiation therapy. MATERIALS AND METHODS: Fifty-five volumetric modulated arc therapy cases in stereotactic body radiation therapy of pancreas were retrospectively included in this study with internal review board approval. Different from the routine practice of initializing collimator settings with a template, the proposed algorithm simultaneously optimizes the collimator angles and jaw positions that are customized to the patient geometry. Specifically, this algorithm includes 2 key steps: (1) an iterative optimization algorithm via simulated annealing that generates a set of potential collimator settings from 39 cases with pancreas stereotactic body radiation therapy, and (2) a multi-leaf collimator modulation scoring system that makes the final decision of the optimal collimator settings (collimator angles and jaw positions) based on organs at risk sparing criteria. For validation, the other 16 cases with pancreas stereotactic body radiation therapy were analyzed. Two plans were generated for each validation case, with one plan optimized using the proposed algorithm (Plan(opt)) and the other plan with the template setting (Plan(conv)). Each plan was optimized with 2 full arcs and the same set of constraints for the same case. Dosimetric results were analyzed and compared, including target dose coverage, conformity, organs at risk maximum dose, and modulation complexity score. All results were tested by Wilcoxon signed rank tests, and the statistical significance level was set to .05. RESULTS: Both plan groups had comparable target dose coverage and mean doses of all organs at risk. However, organs at risk (stomach, duodenum, large/small bowel) maximum dose sparing (D(0.1 cc) and D(0.03 cc)) was improved in Plan(opt) compared to Plan(conv). Plan(opt) also showed lower modulation complexity score, which suggests better capability of handling complex shape and sparing organs at risk . CONCLUSIONS: The proposed collimator settings optimization algorithm successfully improved dosimetric performance for dual-arc pancreas volumetric modulated arc therapy plans in stereotactic body radiation therapy of pancreas. This algorithm has the capability of immediate clinical application. SAGE Publications 2019-08-19 /pmc/articles/PMC6702773/ /pubmed/31426721 http://dx.doi.org/10.1177/1533033819870767 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Special Collection on Artificial Intelligence Based Treatment Planning for Radiotherapy
Li, Xinyi
Wu, Jackie
Palta, Manisha
Zhang, You
Sheng, Yang
Zhang, Jiahan
Wang, Chunhao
A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy
title A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy
title_full A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy
title_fullStr A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy
title_full_unstemmed A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy
title_short A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy
title_sort collimator setting optimization algorithm for dual-arc volumetric modulated arc therapy in pancreas stereotactic body radiation therapy
topic Special Collection on Artificial Intelligence Based Treatment Planning for Radiotherapy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702773/
https://www.ncbi.nlm.nih.gov/pubmed/31426721
http://dx.doi.org/10.1177/1533033819870767
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