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Determination, Minimization and Communication of Uncertainties in Radiation Therapy

J Van Dyk

J Palta

T Bortfeld

B Mijnheer

J Van Dyk1*, J Palta2*, T Bortfeld3*, B Mijnheer4*, (1) Western University, London, ON, (2) Virginia Commonwealth University, Richmond, VA, (3) Massachusetts General Hospital, Boston, MA, (4) Netherlands Cancer Institute, Amsterdam, North Holland


MO-E-BRE-1 Monday 1:45PM - 3:45PM Room: Ballroom E

Medical Physicists have a general understanding of uncertainties in the radiation treatment process, both with respect to dosimetry and geometry. However, there is a desire to be more quantitative about uncertainty estimation. A recent International Atomic Energy Agency (IAEA) report (about to be published) recommends that we should be as “accurate as reasonably achievable, technical and biological factors being taken into account”. Thus, a single recommendation as a goal for accuracy in radiation therapy is an oversimplification. That report also suggests that individual clinics should determine their own level of uncertainties for their specific treatment protocols. The question is “how do we implement this in clinical practice”? AAPM Monograph 35 (2011 AAPM Summer School) addressed many specific aspects of uncertainties in each of the steps of a course of radiation treatment. The intent of this symposium is: (1) to review uncertainty considerations in the entire radiation treatment process including uncertainty determination for each step and uncertainty propagation for the total process, (2) to consider aspects of robust optimization which optimizes treatment plans while protecting them against uncertainties, and (3) to describe various methods of displaying uncertainties and communicating uncertainties to the relevant professionals. While the theoretical and research aspects will also be described, the emphasis will be on the practical considerations for the medical physicist in clinical practice.

Learning Objectives:
1. To review uncertainty determination in the overall radiation treatment process.
2. To consider uncertainty modeling and uncertainty propagation.
3. To highlight the basic ideas and clinical potential of robust optimization procedures to generate optimal treatment plans that are not severely affected by uncertainties.
4. To describe methods of uncertainty communication and display.


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