Recent Advances in Intensity Modulated Proton Therapy Treatment Planning Optimization

Radiation therapy is a non-invasive treatment modality for cancer patients. Radiation therapy treatment planning for cancer patients provides many challenging optimization problems. Various variables of a treatment plan need to be optimized so that the resulting plan can kill all cancerous cells while minimizing damage on the patient’s normal tissues. Intensity modulated proton therapy (IMPT) has recently emerged as one of the most advanced radiation therapy modalities, and is being adopted by more and more cancer hospitals in the U.S. and the World. However, optimization methods that are specifically designed for IMPT treatment planning have not been well studied. Unlike conventional photon-based radiation therapies such as 3D conformal radiation therapy (3DCRT) and intensity modulated radiation therapy (IMRT), IMPT is highly sensitive to uncertainties and its optimization involves very large data sets. In addition, the biological effects of protons are greater in tissues. In this paper, we introduce recent advances in IMPT optimization methods and demonstrate how uncertainty incorporated models and efficient solution algorithms help selecting treatment variables including beam angles, proton energy levels, and intensity profiles. Furthermore, optimization models considering proton biological effects are discussed.