Abstract
Currently, radiation therapy is a common treatment for some specific tumors in the treatments of cancer. Intensity modulated radiation therapy (IMRT) is a widely adopted new radiation therapy tool in recently years, which can deliver high radiation doses to the tumor while reducing sparing of surrounding normal tissues by modulate radiation intensity across beams. The optimal IMRT treatment planning depends on the collection of directions and corresponding intensities. However, in current practice of IMRT, beam angle selection is accomplished by a trial-and-error approach based on the treatment planner’s experience or intuition. In this thesis, in order to assist the planner to optimize IMRT treatment planning efficiently, reduce the computational time and improve the quality of the treatment, we code a program to pre-calculate the radiation dose in each voxel by the form of discretization. We then present a mathematical model to optimize beam angle and fluence map simultaneously by mixed integer programming approach. In addition, we consider the practical experience of the planner and dose-volume constraints in the proposed model to improve the quality of the treatment. According to the results of the experiment, we show that the performance of our method to solve IMRT treatment planning is better than previous works in decreasing radiation dose of organs at risk and computational time.