Abstract: A method to assist in the selection of optimum beam orientations for radiation therapy when a planning treatment volume (PTV) is adjacent to one or more organs-at-risk (OARs). A mathematical analysis of the boundaries between the PTV and OARs allows the definition of a continuum of pairs of gantry and table angles whose beam orientations have planes that are essentially parallel to those boundaries, and can, therefore, separate the PTV from the OARs when a multi-leaf collimator is used in the therapy. The Radiation Oncologist can then select one or more pairs of gantry and table angles from the continuum as input to a beam optimization step. The selected angles can deliver highly uniform dose to the PTV, while minimizing the radiation dose to the OARs.

Abstract: A method to assist in the selection of optimum beam orientations for radiation therapy when a planning treatment volume (PTV) is adjacent to one or more organs-at-risk (OARs). A mathematical analysis of the boundaries between the PTV and OARs allows the definition of a continuum of pairs of gantry and table angles whose beam orientations have planes that are essentially parallel to those boundaries, and can, therefore, separate the PTV from the OARs when a multi-leaf collimator is used in the therapy. The Radiation Oncologist can then select one or more pairs of gantry and table angles from the continuum as input to a beam optimization step. The selected angles can deliver highly uniform dose to the PTV, while minimizing the radiation dose to the OARs.

Abstract: A method of optimization for fluence modulated radiation therapy or fluence modulated radiation surgery based on a new Adaptive Simulated Annealing (ASA) method. The cost function of the ASA method is analytic and, therefore, has first partial derivatives with respect to the fluences to be estimated that can be calculated rapidly. That cost function has terms for the organs at risk that change dynamically as the iterative calculations proceed towards an optimization. The resulting dose volume distributions for the organs at risk are near the distributions specified by the user, while the doses to the planning treatment volume voxels are as close to the desired dose as physically possible, consistent with the conditions established for the organs at risk.

Abstract: A method for optimization of radiation therapy planning based on a new Dynamically Penalized Likelihood (DLP) algorithm. The target function of the DLP algorithm contains likelihood terms and penalty terms connected to the likelihood terms by a number of dynamically updated penalty coefficients. The method results in a highly uniform dose to the tumor or radiosurgery volume, at the expense of some non-uniformity in the dose delivered to defined sensitive tissues.