A Research On The Optimization Methods For Radiation Treatment Planning

Optimization plays an important role in the radiation treatment planning. In this thesis, a collection of optimization solutions is presented for the radiation treatment planning problems.Firstly, modern optimization theory and methods are reviewed, and a hybrid multiobjective optimization algorithm, which combines state-of-the-art multiobjective optimization algorithm-NSGA-II with local search methods and external elitist pool, is developed. The experimental results show that hybridization with local search can efficiently improve the search ability of the multiobjective optimization algorithms, and well distributed Pareto set could be got.Secondly, a two-step automated treatment planning algorithm is developed for the Leksell Gamma Knife, a specialized unit for radiation treatment of brain tumour. In the first step, an improved distance transform based method is used to find the best number of shots, shot locations and collimator sizes for treatment planning. In the second step, in order to avoid trapping into local minimum, a hybrid genetic algorithm combined with BFGS algorithm is employed to find the optimal radiation exposure time by fixing the values of the discrete variables generated in the first step.Thirdly, a novel shot design and optimization method is proposed for the whole body Gamma Knife treatment planning system which is used to treat large tumor, a boundary box based optimization model is proposed and solved by genetic algorithm. The method makes the treatment procedure more convenient and fast, and reduces the shot location error during the treatment procedure.Fourthly, on the basis of shots optimization arrangement for the whole body Gamma Knife treatment planning system, genetic algorithm is applied to find the best treatment path to make the treatment procedure more convenient and reduce the doctor's work intensity. In case of a large amount of shots are needed, a layer by layer treatment path optimization scheme is proposed to reduce computation time and meet the clinical need, but with a little performance decrease. Fifthly, NSGA-â…¡hybrid multiobjective optimization algorithm,using L-BFGS algorithm as local search method, is applied to the optimization of inverse planning in intensity modulated radiation therapy(IMRT). The non-dominated solutions obtained by hybrid multiobjective optimization algorithm are distributed uniformly and this algorithm is more robust than those of the weighted method. The last non-dominated solutions allow the doctors to select the solution which best fits the clinical needs according to the corresponding decision tools such as dose-volume histograms, isodose lines, and the distribution of the solutions.Finally, a method combined the active navigation with optimization algorithm for the planning of peripheral intravascular brachytherapy is proposed. A virtual reality system based on active navigation is developed on Windows platform for the peripheral intravascular brachytherapy, and an optimization model is proposed for the peripheral intravascular brachytherapy. According to the characteristics of the vessel obtained by active navigation, a method combined GA-BFGS hybrid genetic algorithm with simulated annealing algorithm is applied to optimize the related parameters,GA-BFGS hybrid genetic algorithm is used to optimize the continuous parameters, i.e., the dwell time; simulated annealing is used to optimize discrete parameter, i.e., the dwell positions located at the centreline of the vascular. This strategy takes into consideration the formula of the objective function, the fast convergence of BFGS algorithm and the global convergence of both genetic algorithm and simulated annealing algorithm.