Inverse planning for intensity-modulated arc therapy using direct aperture optimization

Abstract

Intensity-modulated arc therapy (IMAT) is a radiation therapy delivery technique that combines gantry rotation with dynamic multi-leaf collimation (MLC). With IMAT, the benefits of rotational IMRT can be realized using a conventional linear accelerator and a conventional MLC. Thus far, the advantages of IMAT have gone largely unrealized due to the lack of robust automated planning tools capable of producing efficient IMAT treatment plans. This work describes an inverse treatment planning algorithm, called 'direct aperture optimization' (DAO) that can be used to generate inverse treatment plans for IMAT. In contrast to traditional inverse planning techniques where the relative weights of a series of pencil beams are optimized, DAO optimizes the leaf positions and weights of the apertures in the plan. This technique allows any delivery constraints to be enforced during the optimization, eliminating the need for a leaf-sequencing step. It is this feature that enables DAO to easily create inverse plans for IMAT. To illustrate the feasibility of DAO applied to IMAT, several cases are presented, including a cylindrical phantom, a head and neck patient and a prostate patient.