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PubMed · 11674815

Beam-commissioning methodology for a three-dimensional convolution/superposition photon dose algorithm.

Abstract

Commissioning beam data for the convolution/superposition dose-calculation algorithm used in a commercial three-dimensional radiation treatment planning (3D RTP) system (PINNACLE(3), ADAC Laboratories, Milpitas, CA) can be difficult and time consuming. Sixteen adjustable parameters, as well as spectral weights representing a discrete energy spectrum, must be fit to sets of central-axis depth doses and off-axis profiles for a large number of field sizes. This paper presents the beam-commissioning methodology that we used to generate accurate beam models. The methodology is relatively rapid and provides physically reasonable values for beam parameters. The methodology was initiated by using vendor-provided automodeling software to generate a single set of beam parameters that gives an approximate fit to relative dose distributions for all beams, open and wedged, in a data set. A limited number of beam parameters were adjusted by small amounts to give accurate beam models for four open-beam field sizes and three wedged-beam field sizes. Beam parameters for other field sizes were interpolated and validated against measured beam data. Using this methodology, a complete set of beam parameters for a single energy can be generated and validated in approximately 40 h. The resulting parameter values yielded calculated relative doses that matched measured relative doses in a water phantom to within 0.5-1.0% along the central axis and 2% along off-axis beam profiles for field sizes from 4 cmx4 cm to the largest field size available. While the methodology presented is specific to the ADAC PINNACLE(3) treatment planning system, the approach should apply to other implementations of the dose model in other treatment planning system.

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BibTeXRIS

G Starkschall, R E Steadham, R A Popple, S Ahmad, I I Rosen. 2000. Beam-commissioning methodology for a three-dimensional convolution/superposition photon dose algorithm.. https://doi.org/10.1120/jacmp.v1i1.2651

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