Selection and determination of beam weights based on genetic algorithms for conformal radiotherapy treatment planning.

Academic Article

Abstract

  • A genetic algorithm has been used to optimize the selection of beam weights for external beam three-dimensional conformal radiotherapy treatment planning. A fitness function is defined, which includes a difference function to achieve a least-square fit to doses at preselected points in a planning target volume, and a penalty item to constrain the maximum allowable doses delivered to critical organs. Adjustment between the dose uniformity within the target volume and the dose constraint to the critical structures can be achieved by varying the beam weight variables in the fitness function. A floating-point encoding schema and several operators, like uniform crossover, arithmetical crossover, geometrical crossover, Gaussian mutation and uniform mutation, have been used to evolve the population. Three different cases were used to verify the correctness of the algorithm and quality assessment based on dose-volume histograms and three-dimensional dose distributions were given. The results indicate that the genetic algorithm presented here has considerable potential.
  • Authors

    Published In

    Keywords

  • Adolescent, Algorithms, Central Nervous System Neoplasms, Child, Ependymoma, Humans, Image Processing, Computer-Assisted, Lymphoma, Non-Hodgkin, Models, Genetic, Phantoms, Imaging, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted, Radiotherapy, Conformal, Retroperitoneal Neoplasms, Rhabdomyosarcoma, Sensitivity and Specificity
  • Pubmed Id

  • 26186260
  • Authorlist

  • Wu X; Zhu Y; Dai J; Wang Z
  • Start Page

  • 2547
  • End Page

  • 2558
  • Volume

  • 45
  • Issue

  • 9