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Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant

PURPOSE: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) t...

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Autores principales: Court, Laurence, Aggarwal, Ajay, Burger, Hester, Cardenas, Carlos, Chung, Christine, Douglas, Raphael, du Toit, Monique, Jaffray, David, Jhingran, Anuja, Mejia, Michael, Mumme, Raymond, Muya, Sikudhani, Naidoo, Komeela, Ndumbalo, Jerry, Nealon, Kelly, Netherton, Tucker, Nguyen, Callistus, Olanrewaju, Niki, Parkes, Jeannette, Shaw, Willie, Trauernicht, Christoph, Xu, Melody, Yang, Jinzhong, Zhang, Lifei, Simonds, Hannah, Beadle, Beth M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581646/
https://www.ncbi.nlm.nih.gov/pubmed/37471671
http://dx.doi.org/10.1200/GO.22.00431
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author Court, Laurence
Aggarwal, Ajay
Burger, Hester
Cardenas, Carlos
Chung, Christine
Douglas, Raphael
du Toit, Monique
Jaffray, David
Jhingran, Anuja
Mejia, Michael
Mumme, Raymond
Muya, Sikudhani
Naidoo, Komeela
Ndumbalo, Jerry
Nealon, Kelly
Netherton, Tucker
Nguyen, Callistus
Olanrewaju, Niki
Parkes, Jeannette
Shaw, Willie
Trauernicht, Christoph
Xu, Melody
Yang, Jinzhong
Zhang, Lifei
Simonds, Hannah
Beadle, Beth M.
author_facet Court, Laurence
Aggarwal, Ajay
Burger, Hester
Cardenas, Carlos
Chung, Christine
Douglas, Raphael
du Toit, Monique
Jaffray, David
Jhingran, Anuja
Mejia, Michael
Mumme, Raymond
Muya, Sikudhani
Naidoo, Komeela
Ndumbalo, Jerry
Nealon, Kelly
Netherton, Tucker
Nguyen, Callistus
Olanrewaju, Niki
Parkes, Jeannette
Shaw, Willie
Trauernicht, Christoph
Xu, Melody
Yang, Jinzhong
Zhang, Lifei
Simonds, Hannah
Beadle, Beth M.
author_sort Court, Laurence
collection PubMed
description PURPOSE: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access). DESIGN: In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology. RESULTS: RPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain. CONCLUSION: The RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of cancer treatment.
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spelling pubmed-105816462023-10-18 Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant Court, Laurence Aggarwal, Ajay Burger, Hester Cardenas, Carlos Chung, Christine Douglas, Raphael du Toit, Monique Jaffray, David Jhingran, Anuja Mejia, Michael Mumme, Raymond Muya, Sikudhani Naidoo, Komeela Ndumbalo, Jerry Nealon, Kelly Netherton, Tucker Nguyen, Callistus Olanrewaju, Niki Parkes, Jeannette Shaw, Willie Trauernicht, Christoph Xu, Melody Yang, Jinzhong Zhang, Lifei Simonds, Hannah Beadle, Beth M. JCO Glob Oncol REVIEW ARTICLES PURPOSE: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access). DESIGN: In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology. RESULTS: RPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain. CONCLUSION: The RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of cancer treatment. Wolters Kluwer Health 2023-07-20 /pmc/articles/PMC10581646/ /pubmed/37471671 http://dx.doi.org/10.1200/GO.22.00431 Text en © 2023 by American Society of Clinical Oncology https://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/)
spellingShingle REVIEW ARTICLES
Court, Laurence
Aggarwal, Ajay
Burger, Hester
Cardenas, Carlos
Chung, Christine
Douglas, Raphael
du Toit, Monique
Jaffray, David
Jhingran, Anuja
Mejia, Michael
Mumme, Raymond
Muya, Sikudhani
Naidoo, Komeela
Ndumbalo, Jerry
Nealon, Kelly
Netherton, Tucker
Nguyen, Callistus
Olanrewaju, Niki
Parkes, Jeannette
Shaw, Willie
Trauernicht, Christoph
Xu, Melody
Yang, Jinzhong
Zhang, Lifei
Simonds, Hannah
Beadle, Beth M.
Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant
title Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant
title_full Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant
title_fullStr Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant
title_full_unstemmed Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant
title_short Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant
title_sort addressing the global expertise gap in radiation oncology: the radiation planning assistant
topic REVIEW ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581646/
https://www.ncbi.nlm.nih.gov/pubmed/37471671
http://dx.doi.org/10.1200/GO.22.00431
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