Radiotherapy is a common treatment for many types of cancers. It uses ionising radiation to control or kill cancerous cells. Although there has been rapid development in radiotherapy equipment in the past decade, it has come at the cost of increased complexity in radiotherapy treatment plan design.
Treatment planning involves multiple interlinked optimisation problems to determine the optimal beam direction, radiation intensities, machine settings and many other parameters. The process is complicated further by conflicting objectives; an ideal plan would maximise the radiation to the tumour whilst minimising the radiation to the surrounding healthy cells.
This talk describes research into reducing the trial and error process from the treatment planning. Data Envelopment Analysis (DEA) and robust optimisation will be introduced as a method to assess the quality of individual treatment plans.