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Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer

BACKGROUND: Automated treatment planning and/or optimization systems (ATPS) are in the process of broad clinical implementation aiming at reducing inter-planner variability, reducing the planning time allocated for the optimization process and improving plan quality. Five different ATPS used clinica...

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Autores principales: Krayenbuehl, J., Zamburlini, M., Ghandour, S., Pachoud, M., Lang-Tanadini, S., Tol, J., Guckenberger, M., Verbakel, W. F. A. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131745/
https://www.ncbi.nlm.nih.gov/pubmed/30201017
http://dx.doi.org/10.1186/s13014-018-1113-z
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author Krayenbuehl, J.
Zamburlini, M.
Ghandour, S.
Pachoud, M.
Lang-Tanadini, S.
Tol, J.
Guckenberger, M.
Verbakel, W. F. A. R.
author_facet Krayenbuehl, J.
Zamburlini, M.
Ghandour, S.
Pachoud, M.
Lang-Tanadini, S.
Tol, J.
Guckenberger, M.
Verbakel, W. F. A. R.
author_sort Krayenbuehl, J.
collection PubMed
description BACKGROUND: Automated treatment planning and/or optimization systems (ATPS) are in the process of broad clinical implementation aiming at reducing inter-planner variability, reducing the planning time allocated for the optimization process and improving plan quality. Five different ATPS used clinically were evaluated for advanced head and neck cancer (HNC). METHODS: Three radiation oncology departments compared 5 different ATPS: 1) Automatic Interactive Optimizer (AIO) in combination with RapidArc (in-house developed and Varian Medical Systems); 2) Auto-Planning (AP) (Philips Radiation Oncology Systems); 3) RapidPlan version 13.6 (RP1) with HNC model from University Hospital A (Varian Medical Systems, Palo Alto, USA); 4) RapidPlan version 13.7 (RP2) combined with scripting for automated setup of fields with HNC model from University Hospital B; 5) Raystation multicriteria optimization algorithm version 5 (RS) (Laboratories AB, Stockholm, Sweden). Eight randomly selected HNC cases from institution A and 8 from institution B were used. PTV coverage, mean and maximum dose to the organs at risk and effective planning time were compared. Ranking was done based on 3 Gy increments for the parallel organs. RESULTS: All planning systems achieved the hard dose constraints for the PTVs and serial organs for all patients. Overall, AP achieved the best ranking for the parallel organs followed by RS, AIO, RP2 and RP1. The oral cavity mean dose was the lowest for RS (31.3 ± 17.6 Gy), followed by AP (33.8 ± 17.8 Gy), RP1 (34.1 ± 16.7 Gy), AIO (36.1 ± 16.8 Gy) and RP2 (36.3 ± 16.2 Gy). The submandibular glands mean dose was 33.6 ± 10.8 Gy (AP), 35.2 ± 8.4 Gy (AIO), 35.5 ± 9.3 Gy (RP2), 36.9 ± 7.6 Gy (RS) and 38.2 ± 7.0 Gy (RP1). The average effective planning working time was substantially different between the five ATPS (in minutes): < 2 ± 1 for AIO and RP2, 5 ± 1 for AP, 15 ± 2 for RP1 and 340 ± 48 for RS, respectively. CONCLUSIONS: All ATPS were able to achieve all planning DVH constraints and the effective working time was kept bellow 20 min for each ATPS except for RS. For the parallel organs, AP performed the best, although the differences were small.
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spelling pubmed-61317452018-09-13 Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer Krayenbuehl, J. Zamburlini, M. Ghandour, S. Pachoud, M. Lang-Tanadini, S. Tol, J. Guckenberger, M. Verbakel, W. F. A. R. Radiat Oncol Research BACKGROUND: Automated treatment planning and/or optimization systems (ATPS) are in the process of broad clinical implementation aiming at reducing inter-planner variability, reducing the planning time allocated for the optimization process and improving plan quality. Five different ATPS used clinically were evaluated for advanced head and neck cancer (HNC). METHODS: Three radiation oncology departments compared 5 different ATPS: 1) Automatic Interactive Optimizer (AIO) in combination with RapidArc (in-house developed and Varian Medical Systems); 2) Auto-Planning (AP) (Philips Radiation Oncology Systems); 3) RapidPlan version 13.6 (RP1) with HNC model from University Hospital A (Varian Medical Systems, Palo Alto, USA); 4) RapidPlan version 13.7 (RP2) combined with scripting for automated setup of fields with HNC model from University Hospital B; 5) Raystation multicriteria optimization algorithm version 5 (RS) (Laboratories AB, Stockholm, Sweden). Eight randomly selected HNC cases from institution A and 8 from institution B were used. PTV coverage, mean and maximum dose to the organs at risk and effective planning time were compared. Ranking was done based on 3 Gy increments for the parallel organs. RESULTS: All planning systems achieved the hard dose constraints for the PTVs and serial organs for all patients. Overall, AP achieved the best ranking for the parallel organs followed by RS, AIO, RP2 and RP1. The oral cavity mean dose was the lowest for RS (31.3 ± 17.6 Gy), followed by AP (33.8 ± 17.8 Gy), RP1 (34.1 ± 16.7 Gy), AIO (36.1 ± 16.8 Gy) and RP2 (36.3 ± 16.2 Gy). The submandibular glands mean dose was 33.6 ± 10.8 Gy (AP), 35.2 ± 8.4 Gy (AIO), 35.5 ± 9.3 Gy (RP2), 36.9 ± 7.6 Gy (RS) and 38.2 ± 7.0 Gy (RP1). The average effective planning working time was substantially different between the five ATPS (in minutes): < 2 ± 1 for AIO and RP2, 5 ± 1 for AP, 15 ± 2 for RP1 and 340 ± 48 for RS, respectively. CONCLUSIONS: All ATPS were able to achieve all planning DVH constraints and the effective working time was kept bellow 20 min for each ATPS except for RS. For the parallel organs, AP performed the best, although the differences were small. BioMed Central 2018-09-10 /pmc/articles/PMC6131745/ /pubmed/30201017 http://dx.doi.org/10.1186/s13014-018-1113-z Text en © The Author(s). 2018 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
Krayenbuehl, J.
Zamburlini, M.
Ghandour, S.
Pachoud, M.
Lang-Tanadini, S.
Tol, J.
Guckenberger, M.
Verbakel, W. F. A. R.
Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer
title Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer
title_full Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer
title_fullStr Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer
title_full_unstemmed Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer
title_short Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer
title_sort planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131745/
https://www.ncbi.nlm.nih.gov/pubmed/30201017
http://dx.doi.org/10.1186/s13014-018-1113-z
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