title: An efficient method to determine double Gaussian fluence parameters in the eclipse™ proton pencil beam model.
abstract: OBJECTIVE
  To find an efficient method to configure the proton fluence for a commercial proton pencil beam scanning (PBS) treatment planning system (TPS).
  
  
  METHODS
  An in-water dose kernel was developed to mimic the dose kernel of the pencil beam convolution superposition algorithm, which is part of the commercial proton beam therapy planning software, eclipse™ (Varian Medical Systems, Palo Alto, CA). The field size factor (FSF) was calculated based on the spot profile reconstructed by the in-house dose kernel. The workflow of using FSFs to find the desirable proton fluence is presented. The in-house derived spot profile and FSF were validated by a direct comparison with those calculated by the eclipse TPS. The validation included 420 comparisons of the FSFs from 14 proton energies, various field sizes from 2 to 20 cm and various depths from 20% to 80% of proton range.
  
  
  RESULTS
  The relative in-water lateral profiles between the in-house calculation and the eclipse TPS agree very well even at the level of 10-4. The FSFs between the in-house calculation and the eclipse TPS also agree well. The maximum deviation is within 0.5%, and the standard deviation is less than 0.1%.
  
  
  CONCLUSIONS
  The authors' method significantly reduced the time to find the desirable proton fluences of the clinical energies. The method is extensively validated and can be applied to any proton centers using PBS and the eclipse TPS.
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona 85054.
authors.forename: Jiajian
authors.initials: J
authors.lastname: Shen
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona 85054.
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona 85054.
authors.forename: Joshua
authors.initials: J
authors.lastname: Stoker
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona 85054.
authors.forename: Xiaoning
authors.initials: X
authors.lastname: Ding
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona 85054.
authors.forename: Aman
authors.initials: A
authors.lastname: Anand
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona 85054.
authors.forename: Yanle
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Rochester, Rochester, Minnesota 55905.
authors.forename: Michael G
authors.initials: MG
authors.lastname: Herman
authors.affiliation: Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona 85054.
authors.forename: Martin
authors.initials: M
authors.lastname: Bues
mesh_terms: D008954:Models, Biological; D016011:Normal Distribution; D061766:Proton Therapy; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D014867:Water
chemical_list: D014867:Water