Fuzzy logic guided inverse treatment planning.
A fuzzy logic technique was applied to optimize the weighting factors in the objective function of an inverse treatment planning system for intensity-modulated radiation therapy (IMRT). Based on this technique, the optimization of weighting factors is guided by the fuzzy rules while the intensity spectrum is optimized by a fast-monotonic-descent method. The resultant fuzzy logic guided inverse planning system is capable of finding the optimal combination of weighting factors for different anatomical structures involved in treatment planning. This system was tested using one simulated (but clinically relevant) case and one clinical case. The results indicate that the optimal balance between the target dose and the critical organ dose is achieved by a refined combination of weighting factors. With the help of fuzzy inference, the efficiency and effectiveness of inverse planning for IMRT are substantially improved.
Yan
Hui
H
Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan 48202, USA. hyan1@hfhs.org
Yin
Fang-Fang
FF
Guan
Huaiqun
H
Kim
Jae Ho
JH
D000465:Algorithms; D017143:Fuzzy Logic; D006801:Humans; D015233:Models, Statistical; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D011874:Radiometry; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*