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Adaptive Radiotherapy

G Hugo1*, M Matuszak2*, M Cao3*, (1) Washington University School of Medicine, St. Louis, MO, (2) University of Michigan, Ann Arbor, MI, (3) UCLA School of Medicine, Los Angeles, CA


(Sunday, 7/12/2020) 2:00 PM - 3:00 PM [Eastern Time (GMT-4)]

Room: Track 5

Adaptive radiotherapy (ART) has been a topic of research interest for several decades, however, it has not been widely implemented in the clinic due to lack of practical tools and strategies to make it feasible in a clinical setting. In the past few years, we have seen significant technological advancements that have improved the quality and efficiency of every step of the radiotherapy process. High quality in-room imaging available on standard treatment machines, as well as more recent introduction of new technologies such as the MR-linac, can provide simulation quality images for plan adaptation, without the need to re-simulate the patient. Additionally, the use of artificial intelligence and knowledge based planning, have the potential to enable automation of both contouring and planning, allowing for plan adaptation without significant changes in the required resources or time. These changes, combined with more efficient workflows, would allow ART to become a routine part of any clinical practice in both online and offline applications soon.

The goal of this session is to provide an overview of clinical indications for both anatomical, and functional adaptation, discuss the strategies for online and offline adaptation, and to provide an overview of the current technologies and strategies utilized in the clinic.

Learning Objectives:
1. Understand sources of geometric and anatomical change, and indications for online and offline plan adaptation.
2. Understand sources of functional and biological changes during treatment, strategies to identify these changes, and current approaches to adaptation.
3. Understand current technology, tools, and workflows for online and offline adaptation, and considerations for quality assurance.



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