title: Monte Carlo based, patient-specific RapidArc QA using Linac log files.
abstract: OBJECTIVE
  A Monte Carlo (MC) based QA process to validate the dynamic beam delivery accuracy for Varian RapidArc (Varian Medical Systems, Palo Alto, CA) using Linac delivery log files (DynaLog) is presented. Using DynaLog file analysis and MC simulations, the goal of this article is to (a) confirm that adequate sampling is used in the RapidArc optimization algorithm (177 static gantry angles) and (b) to assess the physical machine performance [gantry angle and monitor unit (MU) delivery accuracy].
  
  
  METHODS
  Ten clinically acceptable RapidArc treatment plans were generated for various tumor sites and delivered to a water-equivalent cylindrical phantom on the treatment unit. Three Monte Carlo simulations were performed to calculate dose to the CT phantom image set: (a) One using a series of static gantry angles defined by 177 control points with treatment planning system (TPS) MLC control files (planning files), (b) one using continuous gantry rotation with TPS generated MLC control files, and (c) one using continuous gantry rotation with actual Linac delivery log files. Monte Carlo simulated dose distributions are compared to both ionization chamber point measurements and with RapidArc TPS calculated doses. The 3D dose distributions were compared using a 3D gamma-factor analysis, employing a 3%/3 mm distance-to-agreement criterion.
  
  
  RESULTS
  The dose difference between MC simulations, TPS, and ionization chamber point measurements was less than 2.1%. For all plans, the MC calculated 3D dose distributions agreed well with the TPS calculated doses (gamma-factor values were less than 1 for more than 95% of the points considered). Machine performance QA was supplemented with an extensive DynaLog file analysis. A DynaLog file analysis showed that leaf position errors were less than 1 mm for 94% of the time and there were no leaf errors greater than 2.5 mm. The mean standard deviation in MU and gantry angle were 0.052 MU and 0.355 degrees, respectively, for the ten cases analyzed.
  
  
  CONCLUSIONS
  The accuracy and flexibility of the Monte Carlo based RapidArc QA system were demonstrated. Good machine performance and accurate dose distribution delivery of RapidArc plans were observed. The sampling used in the TPS optimization algorithm was found to be adequate.
authors.affiliation: Physics and Astronomy, University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada. tteke2@bccancer.bc.ca
authors.forename: Tony
authors.initials: T
authors.lastname: Teke
authors.forename: Alanah M
authors.initials: AM
authors.lastname: Bergman
authors.forename: William
authors.initials: W
authors.lastname: Kwa
authors.forename: Bradford
authors.initials: B
authors.lastname: Gill
authors.forename: Cheryl
authors.initials: C
authors.lastname: Duzenli
authors.forename: I Antoniu
authors.initials: IA
authors.lastname: Popescu
mesh_terms: D016208:Databases, Factual; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D009010:Monte Carlo Method; D009369:Neoplasms / Q000532:radiotherapy*; D010315:Particle Accelerators; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D012986:Software Validation