Controlling the dose distribution with gEUD-type constraints within the convex IMRT optimization framework

Radiation therapy is an important modality in treating various cancers. Various treatment planning and delivery technologies have emerged to support Intensity Modulated Radiation Therapy (IMRT), creating significant opportunities to advance this type of treatment. We investigate the possibility of including the dose prescription, specified by the Dose Volume Histogram (DVH), within the convex optimization framework for inverse IMRT treatment planning. Specifically, we study the quality of approximating a given DVH with a superset of generalized Equivalent Uniform Dose (gEUD)-based constraints, the so-called Generalized Moment Constraints (GMCs). The newly proposed approach is promising as demonstrated by the computational study where the rectum DVH is considered. Unlike the precise dose-volume constraint formulation that necessitates the use of expensive computing resources, our convex optimization approach is feasible for implementation on a single-processor treatment planning station.