Robust optimization with accumulated dose over full treatment course reduces dose to organs at risk
PO-1444
Abstract
Robust optimization with accumulated dose over full treatment course reduces dose to organs at risk
Authors: Engwall|, Erik(1)*[erik.engwall@raysearchlabs.com];Fredriksson|, Albin(1);Andersson|, Björn(1);
(1)RaySearch Laboratories, Research and Development, Stockholm, Sweden;
Show Affiliations
Hide Affiliations
Purpose or Objective
Current methods for robust optimization available in commercial treatment planning systems are limited to account for errors that are the same through all fractions of the treatment. In this study we propose a new robust optimization approach, where each scenario corresponds to the full treatment course with different errors in each fraction.
Material and Methods
The novel method is implemented in a research version of the treatment planning system RayStation. It utilizes a large number of CTs created from the planning CT through simulated organ motion. The organ motion is simulated with normally distributed motion amplitudes with a standard deviation (σ) of 5 mm (and limited to 3σ). Fraction doses are sampled into a treatment course scenario and accumulated onto the planning CT using deformable image registrations between the simulated CTs and the planning CT. Worst-case robust optimization is subsequently performed over 1000 treatment course scenarios.
To assess the performance of plans created with the new robust optimization method, they are compared to traditional PTV plans with increasing margins in steps of 1 mm between 5 and 15 mm. The plans are evaluated for three prostate patients treated with seven-beam SMLC plans. The plans were optimized with a constraint on the prescription dose (77 Gy in 35 fractions) to 100% of the target (CTV for robustly optimized plans; PTV for PTV plans).
Evaluation is performed in an adapted version of the Robust evaluation module of RayStation. The evaluation is fully independent from the robust optimization taking 125 simulated CT images (randomly sampled organ motion amplitudes from a Gaussian distribution with σ = 5 mm), and creating 200 evaluation scenarios by accumulating deformed doses on the planning CT.
Results
For each patient case, the PTV plan that achieves equivalent target coverage as the robustly optimized plan, is used for comparison with respect to clinical goals. This results in a margin of 9 mm in two cases and 7 mm in one case. For all patients, the doses to organs at risks are highly reduced for the robustly optimized plan as compared to the PTV plans, as is exemplified for one of the patients in Figure 1. The reduction of dose to healthy tissue comes at the expense of a higher maximum dose in the target.
The margins in the compared PTV plans are higher than normally used in clinical practice and the dose to surrounding tissue could be reduced with smaller margins. However, with reduced margins, the target coverage would be compromised during the course of treatment, and it is likely that adaptive replanning would be needed, which would not be the case for the robustly optimized plans.
Comparison of a robustly optimized plan (a) and a PTV plan with 9 mm margin (b).
Conclusion
Robust optimization based on accumulated dose over the full treatment course provides excellent target coverage for the investigated prostate patients, while lowering the dose to organs at risk by a substantial amount and limiting the need for adaptive replanning.