Optimization of inverse treatment planning using a fuzzy weight function

A fuzzy approach has been applied to inverse treatment planning optimizatio n in radiation therapy. The proposed inverse-planning algorithm optimizes b oth the intensity-modulated beam (LMB) and the normal tissue prescription. In the LMB optimization, we developed a fast-monotonic-descent (FMD) method that has the property of fast and monotonic convergence to the minimum for a constrained quadratic objective function. In addition, a fuzzy weight fu nction is employed to express the vague knowledge about the importance of m atching the calculated dose to the prescribed dose in the normal tissue. Th en, a validity function is established to optimize the normal tissue prescr iption. The performance of this new fuzzy prescription algorithm has been c ompared to that based on hard prescription methods for two treatment geomet ries. The FMD method presented here both provides a full-analytical solutio n to the optimization of intensity-modulated beams, and guarantees fast and monotonic convergence to the minimum. It has been shown that the fuzzy inv erse planning technique is capable of achieving an optimal balance between the objective of matching the calculated dose to the prescribed dose for th e target volume and the objective of minimizing the normal tissue dose. (C) 2000 American Association of Physicists in Medicine.