title: A comparison of inverse optimization algorithms for HDR/PDR prostate brachytherapy treatment planning.
abstract: OBJECTIVE
  Graphical optimization (GrO) is a common method for high-dose-rate/pulsed-dose-rate (PDR) prostate brachytherapy treatment planning. New methods performing inverse optimization of the dose distribution have been developed over the past years. The purpose is to compare GrO and two established inverse methods, inverse planning simulated annealing (IPSA) and hybrid inverse treatment planning and optimization (HIPO), and one new method, enhanced geometric optimization-interactive inverse planning (EGO-IIP), in terms of speed and dose-volume histogram (DVH) parameters.
  
  
  METHODS
  For 26 prostate cancer patients treated with a PDR brachytherapy boost, an experienced treatment planner optimized the dose distributions using four different methods: GrO, IPSA, HIPO, and EGO-IIP. Relevant DVH parameters (prostate-V100%, D90%, V150%; urethra-D(0.1cm3) and D(1.0cm3); rectum-D(0.1cm3) and D(2.0cm3); bladder-D(2.0cm3)) were evaluated and their compliance to the constraints. Treatment planning time was also recorded.
  
  
  RESULTS
  All inverse methods resulted in shorter planning time (mean, 4-6.7 min), as compared with GrO (mean, 7.6 min). In terms of DVH parameters, none of the inverse methods outperformed the others. However, all inverse methods improved on compliance to the planning constraints as compared with GrO. On average, EGO-IIP and GrO resulted in highest D90%, and the IPSA plans resulted in lowest bladder D2.0cm3 and urethra D(1.0cm3).
  
  
  CONCLUSIONS
  Inverse planning methods decrease planning time as compared with GrO for PDR/high-dose-rate prostate brachytherapy. DVH parameters are comparable for all methods.
authors.affiliation: Department of Radiation Oncology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands. Electronic address: a.m.dinkla@amc.uva.nl.
authors.forename: Anna M
authors.initials: AM
authors.lastname: Dinkla
authors.affiliation: Department of Radiation Oncology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Rob
authors.initials: R
authors.lastname: van der Laarse
authors.affiliation: Department of Radiation Oncology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Emmie
authors.initials: E
authors.lastname: Kaljouw
authors.affiliation: Department of Radiation Oncology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Bradley R
authors.initials: BR
authors.lastname: Pieters
authors.affiliation: Department of Radiation Oncology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Kees
authors.initials: K
authors.lastname: Koedooder
authors.affiliation: Department of Radiation Oncology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Niek
authors.initials: N
authors.lastname: van Wieringen
authors.affiliation: Department of Radiation Oncology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Arjan
authors.initials: A
authors.lastname: Bel
mesh_terms: D000465:Algorithms; D001918:Brachytherapy / Q000379:methods*; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies
keywords: Brachytherapy; EGO–IIP; HIPO; IPSA; Inverse planning; Prostate neoplasms