RESUMO
Objective:To propose a new robust optimization method, known as modified worst case method, was proposed, which can enable users to control the trade-off between nominal plan quality and plan robustness.Methods:In each iteration of the plan optimization process, the dose value of each voxel in nine scenarios, which corresponded to a nominal scenario and eight perturbed scenarios with range or set-up uncertainties, were calculated and the maximum of deviations of each scenario voxel dose from that of the nominal scenario was included as an additive robust optimization term in the objective function. A weighting factor p robust was used to this robust optimization term to balance the nominal plan quality and plan robustness. Results:The robust optimization methods were implemented and compared in an in-house developed robust optimization module. When p robust=0.8, compared with conventional optimization, the ΔD 95% of CTV was reduced from 9.8 Gy to 7.6 Gy. When p robust was reduced from 1 to 0, ΔD 95% was increased from 7.0 Gy to 9.8 Gy, whereas the D 95% and D max of CTV, and the D 5% and D max of organs at risk (OAR) in the nominal scenario were reduced. Conclusions:The proposed modified worst case method can effectively improve the robustness of the plan to the range and set-up uncertainties. Besides, the weighting factor p robust in this method can be adopted to control the trade-off between nominal plan quality and plan robustness.