Radiotherapy is one of the major modalities of cancer treatment that can be prescribed as the main treatment or can be given in combination with surgery and/or chemotherapy. Radiotherapy is the use of radiation beams, precisely directed to diseased cells, to fight cancer. The main objective of radiotherapy is to deliver radiation to the tumor to kill cancerous cells without harming the surrounding healthy tissue. Each cancer patient’s tumor is unique in terms of its shape, location, and the surrounding healthy tissue. The machine settings, including the beam angles and beam shapes, must be customized based on the patient’s image data and the physician’s dose prescription for both the tumor and nearby healthy tissues. This gives rise to large-scale, multi-criteria, and often non-convex optimization problems. In this workshop, we would review and discuss these challenging optimization problems and share our experience in using these models to treat real patients in our hospital (Memorial Sloan Kettering Cancer Center, New York).
