Ant colony system for the beam angle optimization problem in radiotherapy planning: a preliminary study
ABSTRACT Intensity-modulated radiotherapy (IMRT) is being increasingly used for treatment of malignant cancer. Beam angle optimization (BAO) is an important problem in IMRT. In this paper, an emerging population-based meta-heuristic algorithm named ant colony optimization (ACO) is introduced to solve the BAO problem. In the proposed algorithm, a multi-layered graph is designed to map the BAO problem to ACO, and a heuristic function based on the beam's-eye-view dosimetrics (BEVD) score is introduced. In order to verify the feasibility of the presented algorithm, a clinical prostate tumor case is employed, and the preliminary results demonstrate that ACO appears more effcient than genetic algorithm (GA) and can find the optimal beam angles within a clinically acceptable computation time.
- International Journal of Radiation OncologyBiologyPhysics 08/1996; 35(4):845-6. · 4.52 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: The problem of optimizing beam orientations for irradiations with multiple fixed beams is investigated. It is shown that this is a complex, in mathematical terms 'non-convex', optimization problem, whose solution requires sophisticated techniques. In this work, the optimization is performed with the method of simulated annealing. In order to keep the calculation time within reasonable limits, the problem is expressed in the spatial frequency domain using Parseval's theorem. All calculations are then performed in the frequency domain. The algorithm is described in detail. Various treatment techniques, including intensity modulation, are considered. The results for various exemplary cases are presented. They are based on a simplified dose calculation model. A general conclusion is that the optimum beam configuration for multiple-beam irradiations (with more than three beams) tends to be an even distribution over an angular range of 0 to 2 pi.Physics in Medicine and Biology 03/1993; 38(2):291-304. · 2.70 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Selection of beam configuration in currently available intensity-modulated radiotherapy (IMRT) treatment planning systems is still based on trial-and-error search. Computer beam orientation optimization has the potential to improve the situation, but its practical implementation is hindered by the excessive computing time associated with the calculation. The purpose of this work is to provide an effective means to speed up the beam orientation optimization by incorporating a priori geometric and dosimetric knowledge of the system and to demonstrate the utility of the new algorithm for beam placement in IMRT. Beam orientation optimization was performed in two steps. First, the quality of each possible beam orientation was evaluated using beam's-eye-view dosimetrics (BEVD) developed in our previous study. A simulated annealing algorithm was then employed to search for the optimal set of beam orientations, taking into account the BEVD scores of different incident beam directions. During the calculation, sampling of gantry angles was weighted according to the BEVD score computed before the optimization. A beam direction with a higher BEVD score had a higher probability of being included in the trial configuration, and vice versa. The inclusion of the BEVD weighting in the stochastic beam angle sampling process made it possible to avoid spending valuable computing time unnecessarily at "bad" beam angles. An iterative inverse treatment planning algorithm was used for beam intensity profile optimization during the optimization process. The BEVD-guided beam orientation optimization was applied to an IMRT treatment of paraspinal tumor. The advantage of the new optimization algorithm was demonstrated by comparing the calculation with the conventional scheme without the BEVD weighting in the beam sampling. The BEVD tool provided useful guidance for the selection of the potentially good directions for the beams to incident and was used to guide the search for the optimal beam configuration. The BEVD-guided sampling improved both optimization speed and convergence of the calculation. A comparison of several five-field IMRT treatment plans obtained with and without BEVD guidance indicated that the computational efficiency was increased by a factor of approximately 10. Incorporation of BEVD information allows for development of a more robust tool for beam orientation optimization in IMRT planning. It enables us to more effectively use the angular degree of freedom in IMRT without paying the excessive computing overhead and brings us one step closer to the goal of automated selection of beam orientations in a clinical environment.International Journal of Radiation OncologyBiologyPhysics 01/2003; 54(5):1565-74. · 4.52 Impact Factor