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Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics
PURPOSE: The purpose of this study was to validate a fully automatic treatment planning system for conventional radiotherapy of cervical cancer. This system was developed to mitigate staff shortages in low-resource clinics. METHODS: In collaboration with hospitals in South Africa and the United Stat...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Clinical Oncology
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426517/ https://www.ncbi.nlm.nih.gov/pubmed/30629457 http://dx.doi.org/10.1200/JGO.18.00107 |
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author | Kisling, Kelly Zhang, Lifei Simonds, Hannah Fakie, Nazia Yang, Jinzhong McCarroll, Rachel Balter, Peter Burger, Hester Bogler, Oliver Howell, Rebecca Schmeler, Kathleen Mejia, Mike Beadle, Beth M. Jhingran, Anuja Court, Laurence |
author_facet | Kisling, Kelly Zhang, Lifei Simonds, Hannah Fakie, Nazia Yang, Jinzhong McCarroll, Rachel Balter, Peter Burger, Hester Bogler, Oliver Howell, Rebecca Schmeler, Kathleen Mejia, Mike Beadle, Beth M. Jhingran, Anuja Court, Laurence |
author_sort | Kisling, Kelly |
collection | PubMed |
description | PURPOSE: The purpose of this study was to validate a fully automatic treatment planning system for conventional radiotherapy of cervical cancer. This system was developed to mitigate staff shortages in low-resource clinics. METHODS: In collaboration with hospitals in South Africa and the United States, we have developed the Radiation Planning Assistant (RPA), which includes algorithms for automating every step of planning: delineating the body contour, detecting the marked isocenter, designing the treatment-beam apertures, and optimizing the beam weights to minimize dose heterogeneity. First, we validated the RPA retrospectively on 150 planning computed tomography (CT) scans. We then tested it remotely on 14 planning CT scans at two South African hospitals. Finally, automatically planned treatment beams were clinically deployed at our institution. RESULTS: The automatically and manually delineated body contours agreed well (median mean surface distance, 0.6 mm; range, 0.4 to 1.9 mm). The automatically and manually detected marked isocenters agreed well (mean difference, 1.1 mm; range, 0.1 to 2.9 mm). In validating the automatically designed beam apertures, two physicians, one from our institution and one from a South African partner institution, rated 91% and 88% of plans acceptable for treatment, respectively. The use of automatically optimized beam weights reduced the maximum dose significantly (median, −1.9%; P < .001). Of the 14 plans from South Africa, 100% were rated clinically acceptable. Automatically planned treatment beams have been used for 24 patients with cervical cancer by physicians at our institution, with edits as needed, and its use is ongoing. CONCLUSION: We found that fully automatic treatment planning is effective for cervical cancer radiotherapy and may provide a reliable option for low-resource clinics. Prospective studies are ongoing in the United States and are planned with partner clinics. |
format | Online Article Text |
id | pubmed-6426517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Society of Clinical Oncology |
record_format | MEDLINE/PubMed |
spelling | pubmed-64265172019-04-09 Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics Kisling, Kelly Zhang, Lifei Simonds, Hannah Fakie, Nazia Yang, Jinzhong McCarroll, Rachel Balter, Peter Burger, Hester Bogler, Oliver Howell, Rebecca Schmeler, Kathleen Mejia, Mike Beadle, Beth M. Jhingran, Anuja Court, Laurence J Glob Oncol Original Reports PURPOSE: The purpose of this study was to validate a fully automatic treatment planning system for conventional radiotherapy of cervical cancer. This system was developed to mitigate staff shortages in low-resource clinics. METHODS: In collaboration with hospitals in South Africa and the United States, we have developed the Radiation Planning Assistant (RPA), which includes algorithms for automating every step of planning: delineating the body contour, detecting the marked isocenter, designing the treatment-beam apertures, and optimizing the beam weights to minimize dose heterogeneity. First, we validated the RPA retrospectively on 150 planning computed tomography (CT) scans. We then tested it remotely on 14 planning CT scans at two South African hospitals. Finally, automatically planned treatment beams were clinically deployed at our institution. RESULTS: The automatically and manually delineated body contours agreed well (median mean surface distance, 0.6 mm; range, 0.4 to 1.9 mm). The automatically and manually detected marked isocenters agreed well (mean difference, 1.1 mm; range, 0.1 to 2.9 mm). In validating the automatically designed beam apertures, two physicians, one from our institution and one from a South African partner institution, rated 91% and 88% of plans acceptable for treatment, respectively. The use of automatically optimized beam weights reduced the maximum dose significantly (median, −1.9%; P < .001). Of the 14 plans from South Africa, 100% were rated clinically acceptable. Automatically planned treatment beams have been used for 24 patients with cervical cancer by physicians at our institution, with edits as needed, and its use is ongoing. CONCLUSION: We found that fully automatic treatment planning is effective for cervical cancer radiotherapy and may provide a reliable option for low-resource clinics. Prospective studies are ongoing in the United States and are planned with partner clinics. American Society of Clinical Oncology 2019-01-10 /pmc/articles/PMC6426517/ /pubmed/30629457 http://dx.doi.org/10.1200/JGO.18.00107 Text en © 2018 by American Society of Clinical Oncology https://creativecommons.org/licenses/by/4.0/ Licensed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Original Reports Kisling, Kelly Zhang, Lifei Simonds, Hannah Fakie, Nazia Yang, Jinzhong McCarroll, Rachel Balter, Peter Burger, Hester Bogler, Oliver Howell, Rebecca Schmeler, Kathleen Mejia, Mike Beadle, Beth M. Jhingran, Anuja Court, Laurence Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics |
title | Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics |
title_full | Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics |
title_fullStr | Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics |
title_full_unstemmed | Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics |
title_short | Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics |
title_sort | fully automatic treatment planning for external-beam radiation therapy of locally advanced cervical cancer: a tool for low-resource clinics |
topic | Original Reports |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426517/ https://www.ncbi.nlm.nih.gov/pubmed/30629457 http://dx.doi.org/10.1200/JGO.18.00107 |
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