Treatment of cancer with radiation is a proven technique used worldwide. One of the ways to treat prostate cancer is by using brachytherapy either alone or as a boost. At the moment, the techniques used depend on the experience of the treatment team and researchers are trying to overcome this problem.
In our case, the technology considered to address this problem is deep learning. Therefore, the aim of this project is to use deep learning to develop tools for planning in high dose rate brachytherapy for the treatment of prostate cancer.
Four different phases are initially targeted. The first consists of a classification of treatment plans. The second is a “reinforce learning” approach to help optimize treatment plans, by modifying the optimization objectives in order to consider each patient in a unique way. The third is dose map prediction based on patient anatomy. The fourth is the generation of treatment plans; from the patient's anatomy or from a dose map to find an adequate treatment plan.
The proposed work is a new approach that will ultimately help with the planning of high dose rate brachytherapy treatments for prostate cancer.