M. A. Earl

We have designed a toolbox that provides an environment for testing radiotherapy optimization techniques, objective functions, and constraints. A set of three-dimensional (3D) pencil beam dose distributions have been computed for a cylindrical phantom. The 6 MV pencil beams were computed using a superposition-based dose engine commissioned for an Elekta SL20 linear accelerator. Due to the cylindrical symmetry of the phantom, the pencil beam dose distributions for any arbitrary beam angle can be determined by simply rotating the pencil beam data sets. Thus, the full accuracy is maintained without the need for additional dose calculations or large data storage requirements. In addition to the pencil beam data sets, tools are included for (1) rotating the pencil beams, (2) calculating the beam's eye view, (3) drawing structures, (4) writing the pencil beam dose data out to the optimizer, and (5) visualizing the optimized results. The pencil beam data sets and the corresponding tools are available for download at http://medschool.umaryland.edu/departments/radiationoncology/pencilbeam/. With this toolbox, researchers will have the ability to rapidly test new optimization techniques and formulations for intensity modulated radiation therapy and 3D conformal radiotherapy.

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.

We studied the dose distributions from electron beams subjected to a longitudinal magnetic field applied to them before they reach the phantom. We found that specific combinations of the length and intensity of the magnetic field produced enhancement of the peaks of the central‐axis depth‐dose distributions. TheEGS4Monte Carlo system was used in this study. In the simulations, a uniform axial magnetic field parallel to the electron beam direction was applied to the air gap between the collimation and the phantom. We extensively studied the simplified case of an 18 MeV electron beam point source. Dose deposition was calculated for various magnetic field strengths, distances through which the magnetic field was applied, collimation sizes, and source to collimation distances. The magnetic field strengths varied from 0 to 3 T, the source‐to‐collimation distances studied were 50 and 95 cm, the collimation sizes studied were 10×10 and 20×20 cm², and the distance through which the field was applied ranged from 10 to 20 cm. Specific combinations of these variables resulted in as much as a 70% enhancement of the peak dose relative to the surface dose. Finally, to determine how the geometry of a real accelerator affects the resulting dose distribution, we performed a full simulation of an Elekta SL20 linear accelerator and compared the results with the ideal case.