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Single click automated breast planning with iterative optimization

PURPOSE: To present the development of an in‐house coded solution for treatment planning of tangential breast radiotherapy that creates single click plans by emulating the iterative optimization process of human dosimetrists. METHOD: One hundred clinical breast cancer patients were retrospectively p...

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Autores principales: Archibald‐Heeren, Ben, Byrne, Mikel, Hu, Yunfei, Liu, Guilin, Collett, Nick, Cai, Meng, Wang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700918/
https://www.ncbi.nlm.nih.gov/pubmed/33016622
http://dx.doi.org/10.1002/acm2.13033
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author Archibald‐Heeren, Ben
Byrne, Mikel
Hu, Yunfei
Liu, Guilin
Collett, Nick
Cai, Meng
Wang, Yang
author_facet Archibald‐Heeren, Ben
Byrne, Mikel
Hu, Yunfei
Liu, Guilin
Collett, Nick
Cai, Meng
Wang, Yang
author_sort Archibald‐Heeren, Ben
collection PubMed
description PURPOSE: To present the development of an in‐house coded solution for treatment planning of tangential breast radiotherapy that creates single click plans by emulating the iterative optimization process of human dosimetrists. METHOD: One hundred clinical breast cancer patients were retrospectively planned with an automated planning (AP) code incorporating the hybrid intensity‐modulated radiotherapy (IMRT) approach. The code automates all planning processes including plan generation, beam generation, gantry and collimator angle determination, open segments and dynamic IMRT fluence and calculations. Thirty‐nine dose volume histogram (DVH) metrics taken from three international recommendations were compared between the automated and clinical plans (CP), along with median interquartile analysis of the DVH distributions. Total planning time and delivery QA were also compared between the plan sets. RESULTS: Of the 39 planning metrics analyzed 23 showed no significant difference between clinical and automated planning techniques. Of the 16 metrics with statistically significant variations, 2 were improved in the clinical plans in comparison to 14 improved in the AP plans. Automated plans produced a greater number of ideal plans against international guidelines as per EviQ (AP:77%, CP:68%), RTOG 1005 (AP:80%, CP:71%), and London Cancer references (AP:80%, CP:75%). Delivery QA results for both techniques were equivalent. Automated planning techniques resulted in an average reduction in planning time from 23 to 5 minutes. CONCLUSION: We have introduced an automated planning code with iterative optimization that produces equivalent quality plans to manual clinical planning. The resultant change in workflow results in a reduction in treatment planning times.
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spelling pubmed-77009182020-12-03 Single click automated breast planning with iterative optimization Archibald‐Heeren, Ben Byrne, Mikel Hu, Yunfei Liu, Guilin Collett, Nick Cai, Meng Wang, Yang J Appl Clin Med Phys Radiation Oncology Physics PURPOSE: To present the development of an in‐house coded solution for treatment planning of tangential breast radiotherapy that creates single click plans by emulating the iterative optimization process of human dosimetrists. METHOD: One hundred clinical breast cancer patients were retrospectively planned with an automated planning (AP) code incorporating the hybrid intensity‐modulated radiotherapy (IMRT) approach. The code automates all planning processes including plan generation, beam generation, gantry and collimator angle determination, open segments and dynamic IMRT fluence and calculations. Thirty‐nine dose volume histogram (DVH) metrics taken from three international recommendations were compared between the automated and clinical plans (CP), along with median interquartile analysis of the DVH distributions. Total planning time and delivery QA were also compared between the plan sets. RESULTS: Of the 39 planning metrics analyzed 23 showed no significant difference between clinical and automated planning techniques. Of the 16 metrics with statistically significant variations, 2 were improved in the clinical plans in comparison to 14 improved in the AP plans. Automated plans produced a greater number of ideal plans against international guidelines as per EviQ (AP:77%, CP:68%), RTOG 1005 (AP:80%, CP:71%), and London Cancer references (AP:80%, CP:75%). Delivery QA results for both techniques were equivalent. Automated planning techniques resulted in an average reduction in planning time from 23 to 5 minutes. CONCLUSION: We have introduced an automated planning code with iterative optimization that produces equivalent quality plans to manual clinical planning. The resultant change in workflow results in a reduction in treatment planning times. John Wiley and Sons Inc. 2020-10-05 /pmc/articles/PMC7700918/ /pubmed/33016622 http://dx.doi.org/10.1002/acm2.13033 Text en © 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Radiation Oncology Physics
Archibald‐Heeren, Ben
Byrne, Mikel
Hu, Yunfei
Liu, Guilin
Collett, Nick
Cai, Meng
Wang, Yang
Single click automated breast planning with iterative optimization
title Single click automated breast planning with iterative optimization
title_full Single click automated breast planning with iterative optimization
title_fullStr Single click automated breast planning with iterative optimization
title_full_unstemmed Single click automated breast planning with iterative optimization
title_short Single click automated breast planning with iterative optimization
title_sort single click automated breast planning with iterative optimization
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700918/
https://www.ncbi.nlm.nih.gov/pubmed/33016622
http://dx.doi.org/10.1002/acm2.13033
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