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Automation in Radiation Therapy: Past, Present, and Future

J Bourland1*, S Parker2*, B Sintay3*, (1) Wake Forest University, Winston-salem, NC, (2) University North Carolina, High Point, NC, (3) Cone Health, Summerfield, NC


(Monday, 7/30/2018) 7:30 AM - 8:25 AM

Room: Karl Dean Ballroom A2

Automation is the future and its applications continue to make radiation oncology and medical physics both safer and more efficient. This session will (1) provide a history of automation in radiation oncology, (2) introduce the concept of the paradox of automation to the medical physics community, and (3) discuss current trends and the future direction of automation in radiation oncology.

Radiation oncology has a rich history of automation corresponding with the development of computing and digital electronic capabilities. Early examples of increased automation in radiation oncology include computerized radiation treatment devices, advances in field shaping, computerized treatment planning, and implementation of patient information and treatment verification systems. These components have evolved to provide integrated, fully automated systems for all aspects and processes used to accomplish radiation treatment.

However, automation of radiation treatment processes is not without risk. The paradox of automation is the concept that when automated systems are used, human interaction is both more crucial and less likely to be successful. Examples of this paradox range from simple documentation errors in medical care to plane crashes resulting in loss of life. While automation greatly contributes to radiation oncology processes, human oversight and interactions remain critical for safe and effective clinical care.

Efforts to improve the safety and simplicity of key tasks in radiation oncology have led to a new paradigm of automation. Electronic medical records are a prevalent form of documentation. Integrated patient databases have eliminated the need for therapists to manually set critical treatment parameters, such as monitor units and field size, and immediately provide data for research and business. Scripting is now possible and is being used with fully computerized treatment planning. Our future is even more exciting - machine learning will transform the way we remember our past and design our future. Highly evolved workflows may drastically change the performance of routine tasks such as image segmentation, contouring and treatment planning. The future of automation is pointed at efficiency, value, and quality and remains as wide open as our imagination.

Learning Objectives:
1. Discuss the history of automation in radiation oncology
2. Explain the paradox of automation
3. Describe the future directions of automation in radiation oncology

Funding Support, Disclosures, and Conflict of Interest: JD Bourland discloses the following research funding: 1. DOD, PR141508, GRANT 11779583 2. Asell LLC/BARDA, HHSO100201700022C Subcontract 3. NIH/NIAID, U19 AI67798 (subcontract 131714) Benjamin J. Sintay receives honoraria and travel support from Varian Medical Systems for speaking and serving on advisory boards.



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