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Program Information

Online Adaptive Radiotherapy - Considerations for Practical Clinical Implementation


R Kashani

J Lamb

X Li




R Kashani1*, J Lamb2*, X Li3*, (1) Washington University School of Medicine, St. Louis, MO, (2) University of California, Los Angeles, Los Angeles, CA, (3) Medical College of Wisconsin, Milwaukee, WI

Presentations

2:45 PM : Online Adaptive MR-Guided RT: Workflow and Clinical Implementation - R Kashani, Presenting Author
3:05 PM : MRI-Guided Online Adaptive Radiotherapy: The UCLA Approach to Quality Management - J Lamb, Presenting Author
3:25 PM : Fast Online Replanning Techniques - X Li, Presenting Author

MO-E-BRC-0 (Monday, August 1, 2016) 2:45 PM - 3:45 PM Room: Ballroom C



Online adaptive radiation therapy has the potential to ensure delivery of optimal treatment to the patient by accounting for anatomical and potentially functional changes that occur from one fraction to the next and over the course of treatment. While on-line adaptive RT (ART) has been a topic of many publications, discussions, and research, it has until very recently remained largely a concept and not a practical implementation. However, recent advances in on-table imaging, use of deformable image registration for contour generation and dose tracking, faster and more efficient plan optimization, as well as fast quality assurance method has enabled the implementation of ART in the clinic in the past couple of years. The introduction of these tools into routine clinical use requires many considerations and progressive knowledge to understand how processes that have historically taken hours/days to complete can now be done in less than 30 minutes.

This session will discuss considerations to perform real time contouring, planning and patient specific QA, as well as a practical workflow and the required resources.

Learning Objectives:

1.To understand the difficulties, challenges and available technologies for online adaptive RT.
2.To understand how to implement online adaptive therapy in a clinical environment and to understand the workflow and resources required.
3.To understand the limitations and sources of uncertainty in the online adaptive process


Funding Support, Disclosures, and Conflict of Interest: I have research funding from ViewRay Inc. and Philips Medical Systems.; R. Kashani, I have research funding from ViewRay Inc. and Philips Medical Systems.; X. Li, Research supported by Elekta Inc.

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