High-dose-rate (HDR) brachytherapy is a standard treatment modality to treat cancer (e.g., prostate and cervical cancer) using the ionizing radiation of a small encapsulated radioactive source. The curative aim in the clinic is to create treatment plans that maximize the dose to the tumor while minimizing the dose to normal tissues. When it comes to the treatment plan generation, manual fine tuning of an objective function is necessary to achieve optimal trade-offs between these two conflicting objectives. Therefore, the plan generation is a time-consuming iterative task for practitioners; the plan quality can be dependent on the user skills.

The purpose of the project is to implement efficient optimization algorithms on GPU that can generate thousands of alternative plans with optimal trade-offs (Pareto-optimal plans) within seconds. Using real-time plan navigation tools, the user can quickly explore the trade-offs through the set of Pareto-optimal plans and select the best plan for the patient at hand. The impact of these novel optimization approaches is quantified and compared to the standard clinical approach.