Automation and artificial intelligence in radiation therapy treatment planning

Author:

Jones Scott1ORCID,Thompson Kenton2,Porter Brian3,Shepherd Meegan34ORCID,Sapkaroski Daniel25ORCID,Grimshaw Alexandra6,Hargrave Catriona17ORCID

Affiliation:

1. Radiation Oncology Princess Alexandra Hospital Raymond Terrace Brisbane Queensland Australia

2. Department of Radiation Therapy Services Peter MacCullum Cancer Care Centre Melbourne Victoria Australia

3. Northern Sydney Cancer Centre Royal North Shore Hospital Sydney New South Wales Australia

4. Monash University Clayton Victoria Australia

5. RMIT University Melbourne Victoria Australia

6. W.P Holman Clinic Royal Hobart Hospital Hobart Tasmania Australia

7. Queensland University of Technology, Faculty of Health, School of Clinical Sciences Brisbane Queensland Australia

Abstract

AbstractAutomation 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.

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference47 articles.

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