Multiobjective evolutionary optimization of the number of beams, their orientations and weights for intensity-modulated radiation therapy.
We propose a hybrid multiobjective (MO) evolutionary optimization algorithm (MOEA) for intensity-modulated radiotherapy inverse planning and apply it to optimize the number of incident beams, their orientations and intensity profiles. The algorithm produces a set of efficient solutions, which represent different clinical trade-offs and contains information such as variety of dose distributions and dose-volume histograms. No importance factors are required and solutions can be obtained in regions not accessible by conventional weighted sum approaches. The application of the algorithm using a test case, a prostate and a head and neck tumour case is shown. The results are compared with MO inverse planning using a gradient-based optimization algorithm.
Schreibmann
Eduard
E
Department of Medical Physics and Engineering, Strahlenklinik, Klinikum Offenbach, 63069 Offenbach, Germany. eschreibmann@yahoo.com
Lahanas
Michael
M
Xing
Lei
L
Baltas
Dimos
D
D000465:Algorithms; D006258:Head and Neck Neoplasms / Q000532:radiotherapy; D006801:Humans; D008297:Male; D015233:Models, Statistical; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D011471:Prostatic Neoplasms / Q000532:radiotherapy; D011874:Radiometry; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal; D013997:Time Factors