title: Very fast simulated reannealing in radiation therapy treatment plan optimization.
abstract: OBJECTIVE
  Very Fast Simulated Reannealing is a relatively new (1989) and sophisticated algorithm for simulated annealing applications. It offers the advantages of annealing methods while requiring shorter execution times. The purpose of this investigation was to adapt Very Fast Simulated Reannealing to conformal treatment planning optimization.
  
  
  METHODS
  We used Very Fast Simulated Reannealing to optimize treatments for three clinical cases with two different cost functions. The first cost function was linear (minimum target dose) with nonlinear dose-volume normal tissue constraints. The second cost function (probability of uncomplicated local control) was a weighted product of normal tissue complication probabilities and the tumor control probability.
  
  
  RESULTS
  For the cost functions used in this study, the Very Fast Simulated Reannealing algorithm achieved results within 5-10% of the final solution (100,000 iterations) after 1000 iterations and within 3-5% of the final solution after 5000-10000 iterations. These solutions were superior to those produced by a conventional treatment plan based on an analysis of the resulting dose-volume histograms. However, this technique is a stochastic method and results vary in a statistical manner. Successive solutions may differ by up to 10%.
  
  
  CONCLUSIONS
  Very Fast Simulated Reannealing, with modifications, is suitable for radiation therapy treatment planning optimization. It produced results within 3-10% of the optimal solution, produced using another optimization algorithm (Mixed Integer Programming), in clinically useful execution times.
authors.affiliation: University of Texas Medical Branch, Department of Radiation Therapy, Galveston 77550.
authors.forename: S M
authors.initials: SM
authors.lastname: Morrill
authors.forename: K S
authors.initials: KS
authors.lastname: Lam
authors.forename: R G
authors.initials: RG
authors.lastname: Lane
authors.forename: M
authors.initials: M
authors.lastname: Langer
authors.forename: I I
authors.initials: II
authors.lastname: Rosen
mesh_terms: D000465:Algorithms; D006801:Humans; D011879:Radiotherapy Dosage; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D013269:Stochastic Processes