Automation and artificial intelligence in radiation therapy treatment planning.

Autor: Jones S; Radiation Oncology Princess Alexandra Hospital Raymond Terrace, Brisbane, Queensland, Australia., Thompson K; Department of Radiation Therapy Services, Peter MacCullum Cancer Care Centre, Melbourne, Victoria, Australia., Porter B; Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia., Shepherd M; Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, New South Wales, Australia.; Monash University, Clayton, Victoria, Australia., Sapkaroski D; Department of Radiation Therapy Services, Peter MacCullum Cancer Care Centre, Melbourne, Victoria, Australia.; RMIT University, Melbourne, Victoria, Australia., Grimshaw A; W.P Holman Clinic, Royal Hobart Hospital, Hobart, Tasmania, Australia., Hargrave C; Radiation Oncology Princess Alexandra Hospital Raymond Terrace, Brisbane, Queensland, Australia.; Queensland University of Technology, Faculty of Health, School of Clinical Sciences, Brisbane, Queensland, Australia.
Jazyk: angličtina
Zdroj: Journal of medical radiation sciences [J Med Radiat Sci] 2024 Jun; Vol. 71 (2), pp. 290-298. Date of Electronic Publication: 2023 Oct 04.
DOI: 10.1002/jmrs.729
Abstrakt: Automation and artificial intelligence (AI) is already possible for many radiation therapy planning and treatment processes with the aim of improving workflows and increasing efficiency in radiation oncology departments. Currently, AI technology is advancing at an exponential rate, as are its applications in radiation oncology. This commentary highlights the way AI has begun to impact radiation therapy treatment planning and looks ahead to potential future developments in this space. Historically, radiation therapist's (RT's) role has evolved alongside the adoption of new technology. In Australia, RTs have key clinical roles in both planning and treatment delivery and have been integral in the implementation of automated solutions for both areas. They will need to continue to be informed, to adapt and to transform with AI technologies implemented into clinical practice in radiation oncology departments. RTs will play an important role in how AI-based automation is implemented into practice in Australia, ensuring its application can truly enable personalised and higher-quality treatment for patients. To inform and optimise utilisation of AI, research should not only focus on clinical outcomes but also AI's impact on professional roles, responsibilities and service delivery. Increased efficiencies in the radiation therapy workflow and workforce need to maintain safe improvements in practice and should not come at the cost of creativity, innovation, oversight and safety.
(© 2023 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.)
Databáze: MEDLINE
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