Anatomy-based three-dimensional dose optimization in brachytherapy using multiobjective genetic algorithms.
In conventional dose optimization algorithms, in brachytherapy, multiple objectives are expressed in terms of an aggregating function which combines individual objective values into a single utility value, making the problem single objective, prior to optimization. A multiobjective genetic algorithm (MOGA) was developed for dose optimization based on an a posteriori approach, leaving the decision-making process to a planner and offering a representative trade-off surface of the various objectives. The MOGA provides a flexible search engine which provides the maximum of information for a decision maker. Tests performed with various treatment plans in brachytherapy have shown that MOGA gives solutions which are superior to those of traditional dose optimization algorithms. Objectives were proposed in terms of the COIN distribution and differential volume histograms, taking into account patient anatomy in the optimization process.
Lahanas
M
M
Department of Medical Physics & Engineering, Strahlenklinik, Städtische Kliniken Offenbach, Germany.
Baltas
D
D
Zamboglou
N
N
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D001859:Bone Neoplasms / Q000532:radiotherapy; D001918:Brachytherapy / Q000379:methods*; D001943:Breast Neoplasms / Q000532:radiotherapy; D005260:Female; D006801:Humans; D008297:Male; D008957:Models, Genetic; D008962:Models, Theoretical; D011471:Prostatic Neoplasms / Q000532:radiotherapy; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data; D012272:Ribs; D012985:Software Design