SU‐E‐T‐853: Robust Multicriteria Optimization for IMPT

Abstract

Purpose: A time and memory efficient projection algorithm for solving large scale IMPT treatment plans in a multicriteria setting has been published. However, the more conformal dose distribution of IMPT compared with that of IMRT comes with its sensitivity to uncertainties such as proton range uncertainty and set‐up error. To design a practically efficacious IMPT treatment system, robustness has to be accounted for to reduce the uncertainties. Methods: A nominal scenario and eight worst‐case scenarios (six extreme patient positions,proton beam undershoot and overshoot) are used to sample the uncertainty space. A solution can be constrained using a subset or all of the nine scenarios to be robust given any realization of the random errors. Moreover, the best quality plan can be pursued by navigating the Pareto space constituted by a number of optimal plans according to their own criteria of optimality. The method deals with very fine dose grid and tens of thousands modulated proton beamlets, therefore fully utilizes the potential of IMPT. Results: A base of skull case with 1mm dose‐grid resolution is applied to demonstrate the robustness of the solution. Compared to the plan obtained by the same problem formulation but considering only the nominal scenario, the DVH band of the robust plan is more stable, meaning the dose distribution varies little under even the worst scenario. The optimization for each task takes only seconds on a standard computer, making a computationally friendly interface possible to the planner. Conclusions: The uncertainty pertinent to the IMPT procedure can be reduced during treatment planning by optimizing some best plans that emphasize different treatment objectives and then interactively seeking for a compromised one from the Pareto solution space. The method works very fast for rather fine dose grid and sufficiently large beamlet numbers, thus streamlines the IMPT treatment process.