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Quantification and Visualization of Treatment Plan Robustness in Radiotherapy


M Fix

MK Fix*, W Volken , D Frei , D Terribilini , DM Aebersold , P Manser , Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Switzerland

Presentations

TH-AB-BRB-5 (Thursday, July 16, 2015) 7:30 AM - 9:30 AM Room: Ballroom B


Purpose:
Currently, the robustness is not taken into account in the evaluation process of treatment plans in radiotherapy. One reason is the lack of algorithms to determine and to visualize the robustness. Thus, the aim of this work is to develop tools and methods to quantify and visualize the robustness for treatment plans including random and systematic setup uncertainties.

Methods:
A setup error phase-space including systematic and random setup errors for translation and rotation is explored to determine the plan robustness by applying different approaches. One approach shifts the optimized dose distributions relatively to the patient geometry and, thus, dosimetric parameters or DVHs can be quickly estimated. A ‘robustness-map’ for this plan is created based on user-defined criteria defining the robustness for the case considered. These criteria subdivide the robustness-map for the setup error phase-space into a region that is compatible with these criteria and another that is not. However, approaches using further dose calculations for the setup error phase space are needed to achieve reliable conclusions of the robustness. Thus, additional dose calculations using different resolutions of the setup error phase-space are performed guided by the robustness-map achieved using the dose-shifting approach. The intermediate dose distributions are determined by nearest neighbor interpolation.

Results:
A graphical user interface based on QT version 5.3.1 was developed to visualize robustness-maps, dose-differences and DVHs. Additionally, correlations of all quantities can be displayed. The creation of robustness-maps is useful to assess and compare the robustness of different treatment plans and was successfully applied to plans covering different tumor-sites. Differences in DVH parameters using the different approaches are within 5%.

Conclusion:
The developed tool for visualization and analysis of robustness-maps is an easy and efficient way to compare the robustness of treatment plans. This work was supported by Varian Medical Systems.

Funding Support, Disclosures, and Conflict of Interest: This work was supported by Varian Medical Physics.


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