Mathematical optimization of dose planning in high dose-rate brachytherapy
Abstract
The project is about brachytherapy, which is a modality of radiation therapy, used for cancer treatment. In brachytherapy the radiation is delivered from within the tumor. The aim with the treatment is to deliver a high enough dose to the tumor while sparing organs at risk.
There are primarily two research directions for which additional computational resources and the use of NSC would be very helpful.
1. Taking uncertainties into account. There are inherent uncertainties both from image modalities such as CT or ultrasound and from mechanical equipment. The aim with the research is to find a treatment plan which are robust with respect to the uncertainties, that is, considering worst-case realizations of the different uncertainties, we want to find a plan which mitigates the uncertainties. It is not possible to explicitly investigate all possible worst-case scenarios, as the number of such scenarios is in the order of 10^100, efficient algorithms are needed to model and the solve the problem of finding the worst scenario. Computational resources are needed to show the efficiency of the proposed algorithm.
2. Patient-specific 3D printed applicators for head-and-neck cancers is an emerging technique in clinical practice. Advantages with these customized applicators is better treatment quality and the possibility to treat tumors with a larger variation in sizes and shapes. With this project we propose a mathematical optimization-based algorithm to find how applicators can be designed. The use of NSC is needed for running the algorithm. We collaborate with Karolinska Institute on this research topic.
