ESTRO 2022 - Abstract Book

S619

Abstract book

ESTRO 2022

Methods

Motion management for intrafraction drift effectively introduces a cut-off in the error distribution, changing it to a truncated Gaussian. Assuming a cut-off at c we study the dependency of the margin on the cut-off parameter for motion modelled as a discrete ‘jump’ and a continuous drift. We study the relative change in the margin for different number of fractions and underlying error distributions. In online adaptive radiotherapy a new plan is generated every fraction based on the delineations of that fraction. In such a workflow, the margin does not need to be constant over the whole course of treatment. Using adaptive margins, the dose already delivered to the target can be taken into account allowing for margin reductions when treatment progresses smoothly and increased margins when unexpected motion during delivery has occurred. We introduce a methodology to calculate adaptive margins based on the accumulated dose to the CTV and study its benefit.

Results

We found that the relative change due to motion management in the margin m_c/m is equal to 0.3c, independently of the standard deviation, number of fractions and for both motion patterns (see figure 1A). Online adaptation of the margins allows for the margins to be on average over the treatment down to 65% of the corresponding constant margins. Most of the benefit can be ascribed to the elimination of the effective systematic error over the course of treatment and therefore the benefit is larger when the number of fractions increases (see figure 1B)

Conclusion

Based on the results presented, the required treatment margins can be determined when motion management strategies or online adaptation are applied. Our analysis can be used to study the potential benefit of different strategies for different treatment sites. This allows clinicians to choose the most appropriate strategy for margin reduction for modern radiotherapy.

Symposium: Online adaptive radiotherapy: The future is near!

SP-0703 Lessons learned in two years treating patients with CBCT guided online adaptive radiotherapy

L. ten Asbroek Medisch Spectrum Twente, Enschede, The Netherlands

Abstract Text Two and a half years ago, we were the second hospital in the world to start with treating patients using Varian's Ethos™. Ethos is a machine with which you can perform both IGRT and online adaptive treatments. It is a conebeam CT based machine, enhanced with artificial intelligence. Due to this artificial intelligence it is possible to treat patients online adaptively within 15 minutes. At the time, we chose to start treating prostate cancer patients adaptively. This enabled us to gain a lot of experience in a short period of time. We have currently treated more than 200 patients online adaptively. Today we offer online adaptive treatments for all common tumours in the pelvis and we are working to expand to other indications. Because our radiotherapy department is relatively small (2500 patients a year), it was important for us that the online adaptive workflow is simple and fast. So the goal was that we wouldn't lose any capacity and we’re still able to treat all our patients. In addition, we have worked on a training program to train the RTTs to advanced adapters. As a result, all adaptive treatments can now be performed by two RTTs only. A doctor and physicist are only present during the first online adaptive treatment fraction of a patient. In this presentation I will elaborate on the Ethos workflow, our training program for RTTs and the treatment results

SP-0704 MR guided online adaptive RT (MRlinac)

M. Chamberlain