A Two-Stage Programming Approach to Fluence Map Optimization for Intensity-Modulated Radiation Therapy Treatment Planning

Abstract

The fluence map optimization (FMO) problem is one of the most studied problems in intensity-modulated radiation therapy treatment planning. Although many approaches have shown to yield good solutions to the FMO problem, the optimal solutions obtained ensure that the resulting treatment is the best possible with respect to the weighting parameters of the formulation used. Since the ‘optimal’ weighting scheme is unknown, the choice of the weight parameters is typically a long trial-and-error process until a satisfactory solution is achieved. Moreover, for selecting the best irradiating directions, it is not clear how traditional trial-and-error parameter tuning should be incorporated or managed. A two-stage programming approach is proposed to reduce the dependency of the optimal solutions on the weight parameters and simultaneously improve the overall plan quality. This approach is yet another step towards automated generation of treatment plans which will result in breakthrough developments in radiation therapy care.