A computational study on different penalty approaches for constrained optimization in radiation therapy treatment planning with a simulated annealing algorithm

In intensity modulated radiation therapy (IMRT) a treatment plan is a high dimensionality optimization problem with the goal to give the prescribed radiation dose to the Planning Target Volume (PTV) while sparing critical organs. A clinically acceptable plan is usually generated by a numerical optimization process in pursuit of attaining the above mentioned goal. Incorporation of dose volume constraints (DVCs) for the OARs introduce an additional degree of impediment to the optimization task. Heuristic algorithms have been ascertained in the past as a powerful tool for various problems in radiation therapy, such as beam angle optimization (BAO) and IMRT treatment planning. Simulated Annealing (SA) algorithm has the capability to find global minima for bound-constrained optimization problems. However, its performance depends on the penalty method which is utilized for the constraints. In the current study we investigate the performance of three penalty methods for IMRT treatment planning for five prostate cases with dose volume constraints. In addition, sensitivity analysis was performed in order to study the effect of the penalty variables on the treatment plan. Finally the merits and demerits of each method have been discussed.