TY - JOUR
T1 - Is full-automation in radiotherapy treatment planning ready for take off?
AU - Callens, Dylan
AU - Malone, Ciaran
AU - Carver, Antony
AU - Fiandra, Christian
AU - Gooding, Mark J.
AU - Korreman, Stine S.
AU - Matos Dias, Joana
AU - Popple, Richard A.
AU - Rocha, Humberto
AU - Crijns, Wouter
AU - Cardenas, Carlos E.
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/12
Y1 - 2024/12
N2 - Radiotherapy treatment planning is undergoing a transformation with the increasing integration of automation. This transition draws parallels with the aviation industry, which has a long-standing history of addressing challenges and opportunities introduced by automated systems. Both fields witness a shift from manual operations to systems capable of operating independently, raising questions about the risks and evolving role of humans within automated workflows. In response to this shift, a working group assembled during the ESTRO Physics Workshop 2023, reflected on parallels to draw lessons for radiotherapy. A taxonomy is proposed, leveraging insights from aviation, that outlines the observed levels of automation within the context of radiotherapy and their corresponding implications for human involvement. Among the common identified risks associated with automation integration are complacency, overreliance, attention tunneling, data overload, a lack of transparency and training. These risks require mitigation strategies. Such strategies include ensuring role complementarity, introducing checklists and safety requirements for human-automation interaction and using automation for cognitive unload and workflow management. Focusing on already automated processes, such as dose calculation and auto-contouring as examples, we have translated lessons learned from aviation. It remains crucial to strike a balance between automation and human involvement. While automation offers the potential for increased efficiency and accuracy, it must be complemented by human oversight, expertise, and critical decision-making. The irreplaceable value of human judgment remains, particularly in complex clinical situations. Learning from aviation, we identify a need for human factors engineering research in radiation oncology and a continued requirement for proactive incident learning.
AB - Radiotherapy treatment planning is undergoing a transformation with the increasing integration of automation. This transition draws parallels with the aviation industry, which has a long-standing history of addressing challenges and opportunities introduced by automated systems. Both fields witness a shift from manual operations to systems capable of operating independently, raising questions about the risks and evolving role of humans within automated workflows. In response to this shift, a working group assembled during the ESTRO Physics Workshop 2023, reflected on parallels to draw lessons for radiotherapy. A taxonomy is proposed, leveraging insights from aviation, that outlines the observed levels of automation within the context of radiotherapy and their corresponding implications for human involvement. Among the common identified risks associated with automation integration are complacency, overreliance, attention tunneling, data overload, a lack of transparency and training. These risks require mitigation strategies. Such strategies include ensuring role complementarity, introducing checklists and safety requirements for human-automation interaction and using automation for cognitive unload and workflow management. Focusing on already automated processes, such as dose calculation and auto-contouring as examples, we have translated lessons learned from aviation. It remains crucial to strike a balance between automation and human involvement. While automation offers the potential for increased efficiency and accuracy, it must be complemented by human oversight, expertise, and critical decision-making. The irreplaceable value of human judgment remains, particularly in complex clinical situations. Learning from aviation, we identify a need for human factors engineering research in radiation oncology and a continued requirement for proactive incident learning.
KW - Automation
KW - Human oversight
KW - Treatment planning
UR - http://www.scopus.com/inward/record.url?scp=85205226352&partnerID=8YFLogxK
U2 - 10.1016/j.radonc.2024.110546
DO - 10.1016/j.radonc.2024.110546
M3 - Review
C2 - 39326522
AN - SCOPUS:85205226352
SN - 0167-8140
VL - 201
JO - Radiotherapy and Oncology
JF - Radiotherapy and Oncology
M1 - 110546
ER -