title: The influence of field size on stopping-power ratios in- and out-of-field: quantitative data for the BrainLAB m3 micro-multileaf collimator.
abstract: The objective of this work is to quantify the systematic errors introduced by the common assumption of invariant secondary electron spectra with changing field sizes, as relevant to stereotactic radiotherapy and other treatment modes incorporating small beam segments delivered with a linac-based stereotactic unit. The EGSnrc/BEAMnrc Monte Carlo radiation transport code was used to construct a dosimetrically-matched model of a Varian 600C linear accelerator with mounted BrainLAB micro-multileaf collimator. Stopping-power ratios were calculated for field sizes ranging from 6 × 6 mm2 up to the maximum (98 × 98 mm2), and differences between these and the reference field were computed. Quantitative stopping power data for the BrainLAB micro-multileaf collimator has been compiled. Field size dependent differences to reference conditions increase with decreasing field size and increasing depth, but remain a fraction of a percent for all field sizes studied. However, for dosimetry outside the primary field, errors induced by the assumption of invariant electron spectra can be greater than 1%, increasing with field size. It is also shown that simplification of the Spencer-Attix formulation by ignoring secondary electrons below the cutoff kinetic energy applied to the integration results in underestimation of stopping-power ratios of about 0.3% (and is independent of field size and depth). This work is the first to quantify stopping powers from a BrainLAB micro-multileaf collimator. Many earlier studies model simplified beams, ignoring collimator scatter, which is shown to significantly influence the spectrum. Importantly, we have confirmed that the assumption of unchanging electron spectra with varying field sizes is justifiable when performing (typical) in-field dosimetry of stereotactic fields. Clinicians and physicists undertaking precise out-of-field measurements for the purposes of risk estimation, ought to be aware that the more pronounced spectral variation results in stopping powers (and hence doses) that differ more than for in-field dosimetry.
authors.affiliation: School of Applied Sciences and Health Innovations Research Institute, RMIT University, Melbourne, Australia. michael.taylor@rmit.edu.au
authors.forename: Michael
authors.initials: M
authors.lastname: Taylor
authors.forename: Tanya
authors.initials: T
authors.lastname: Kairn
authors.forename: Tomas
authors.initials: T
authors.lastname: Kron
authors.forename: Leon
authors.initials: L
authors.lastname: Dunn
authors.forename: Peter N
authors.initials: PN
authors.lastname: Johnston
authors.forename: Rick D
authors.initials: RD
authors.lastname: Franich
mesh_terms: D003198:Computer Simulation; D004583:Electrons; D006801:Humans; D008962:Models, Theoretical; D009010:Monte Carlo Method; D010315:Particle Accelerators / Q000295:instrumentation; D019047:Phantoms, Imaging; D011874:Radiometry; D016634:Radiosurgery; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted; D012984:Software