title: Computer optimization of noncoplanar beam setups improves stereotactic treatment of liver tumors.
abstract: OBJECTIVE
  To investigate whether computer-optimized fully noncoplanar beam setups may improve treatment plans for the stereotactic treatment of liver tumors.
  
  
  METHODS
  An algorithm for automated beam orientation and weight selection (Cycle) was extended for noncoplanar stereotactic treatments. For 8 liver patients previously treated in our clinic using a prescription isodose of 65%, Cycle was used to generate noncoplanar and coplanar plans with the highest achievable minimum planning target volume (PTV) dose for the clinically delivered isocenter and mean liver doses, while not violating the clinically applied hard planning constraints. The clinical and the optimized coplanar and noncoplanar plans were compared, with respect to D(PTV,99%), the dose received by 99% of the PTV, the PTV generalized equivalent uniform dose (gEUD), and the compliance with the clinical constraints.
  
  
  RESULTS
  For each patient, the ratio between D(PTV,99%) and D(isoc), and the gEUD(-5) and gEUD(-20) values of the optimized noncoplanar plan were higher than for the clinical plan with an average increase of respectively 18.8% (range, 7.8-24.0%), 6.4 Gy (range, 3.4-11.8 Gy), and 10.3 Gy (range, 6.7-12.5). D(PTV,99%)/D(isoc), gEUD(-5), and gEUD(-20) of the optimized noncoplanar plan was always higher than for the optimized coplanar plan with an average increase of, respectively, 4.5% (range, 0.2-9.7%), 2.7 Gy (range, 0.6-9.7 Gy), and 3.4 Gy (range, 0.6-9.9 Gy). All plans were within the imposed hard constraints. On average, the organs at risk were better spared with the optimized noncoplanar plan than with the optimized coplanar plan and the clinical plan.
  
  
  CONCLUSIONS
  The use of automatically generated, fully noncoplanar beam setups results in plans that are favorable compared with coplanar techniques. Because of the automation, we found that the planning workload can be decreased from 1 to 2 days to 1 to 2 h.
authors.affiliation: Department of Radiation Oncology, Erasmus MC-Daniel den Hoed Cancer Center, Rotterdam, The Netherlands. j.depooter@erasmusmc.nl
authors.forename: Jacco A
authors.initials: JA
authors.lastname: de Pooter
authors.forename: Alejandra
authors.initials: A
authors.lastname: Méndez Romero
authors.forename: Wim P A
authors.initials: WP
authors.lastname: Jansen
authors.forename: Pascal R M
authors.initials: PR
authors.lastname: Storchi
authors.forename: Evert
authors.initials: E
authors.lastname: Woudstra
authors.forename: Peter C
authors.initials: PC
authors.lastname: Levendag
authors.forename: Ben J M
authors.initials: BJ
authors.lastname: Heijmen
mesh_terms: D000465:Algorithms; D006801:Humans; D008113:Liver Neoplasms / Q000532:radiotherapy*; D011832:Radiation Injuries / Q000517:prevention & control; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D013238:Stereotaxic Techniques