Treatment planning using a dose-volume feasibility search algorithm

Purpose: An approach to treatment plan optimization is presented that inputs dose-volume constraints and utilizes a feasibility search algorithm that seeks st set of beam weights so that the calculated dose distributions satisfy the dose-volume constraints. In contrast to a search for the "best" plan, this approach can quickly determine feasibility and point out the mast restrictive of the predetermined constraints. Methods and Materials: The cyclic subgradient projection (CSP) algorithm was modified to incorporate dose-volume constraints in a treatment plan optimization schema, The algorithm was applied to determine beam weights for several representative three-dimensional treatment plans, Results: Using the modified CSP algorithm, we found that either a feasible solution to the dose-volume constraint problem was found or the program determined, after a predetermined set of iterations was performed, that no feasible solution existed for the particular set of dose-volume constraints, If no feasible solution existed, we relaxed several of the dose-volume constraints and were able to achieve a feasible solution. Conclusion: Feasibility search algorithms can be used in radiation treatment planning to generate a treatment plan that meets the dose-volume constraints established by the radiation oncologist. In the absence of a feasible solution, these algorithms can provide information to the radiation oncologist as to how the dose-volume constraints may be modified to achieve a feasible solution. (C) 2001 Elsevier Science Inc.