Poster — Thur Eve — 61: A new framework for MPERT plan optimization using MC-DAO
- University of Victoria, Victoria, British Columbia (Canada)
- Department of Physics, Stanford University, Palo Alto, CA (United States)
- Department of Medical Physics, British Columbia Cancer Agency—Vancouver Island Center, Victoria, British Columbia (Canada)
This work combines the inverse planning technique known as Direct Aperture Optimization (DAO) with Intensity Modulated Radiation Therapy (IMRT) and combined electron and photon therapy plans. In particular, determining conditions under which Modulated Photon/Electron Radiation Therapy (MPERT) produces better dose conformality and sparing of organs at risk than traditional IMRT plans is central to the project. Presented here are the materials and methods used to generate and manipulate the DAO procedure. Included is the introduction of a powerful Java-based toolkit, the Aperture-based Monte Carlo (MC) MPERT Optimizer (AMMO), that serves as a framework for optimization and provides streamlined access to underlying particle transport packages. Comparison of the toolkit's dose calculations to those produced by the Eclipse TPS and the demonstration of a preliminary optimization are presented as first benchmarks. Excellent agreement is illustrated between the Eclipse TPS and AMMO for a 6MV photon field. The results of a simple optimization shows the functioning of the optimization framework, while significant research remains to characterize appropriate constraints.
- OSTI ID:
- 22407681
- Journal Information:
- Medical Physics, Vol. 41, Issue 8; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-2405
- Country of Publication:
- United States
- Language:
- English
Similar Records
Beamlet based direct aperture optimization for MERT using a photon MLC
SU-E-T-196: Comparative Analysis of Surface Dose Measurements Using MOSFET Detector and Dose Predicted by Eclipse - AAA with Varying Dose Calculation Grid Size