Prediction of stopping-power ratios in flattening-filter free beams.

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Abstract

PURPOSE: In recent years, there has been an increasing interest in flattening-filter free (FFF) beams. However, since the removal of the flattening filter will affect both the mean and the variance of the energy spectrum, current beam-quality specifiers may not be adequate for reference dosimetry in such beams. The purpose of this work was to investigate an alternative, more general beam-quality specifier. METHODS: The beam-quality specifier used in this work was a combination of the kerma-weighted mean and the coefficient of variation of the linear attenuation coefficient in water. These parameters can in theory be determined from narrow-beam transmission measurements using a miniphantom "in-air," which is a measurement condition well suited also to small and nonstandard fields. The relation between the Spencer-Attix stopping-power ratios and this novel beam-quality specifier was described by a simple polynomial. For reference, the authors used Monte Carlo calculated spectra and stopping-power data for nine different beams, with and without flattening filter. RESULTS: The polynomial coefficients were obtained by least-squares optimization. For all beams included in this investigation, the average of the differences between the predicted and the Monte Carlo calculated stopping-power ratios was 0.02 +/- 0.17% (1 SD) (including TomoTherapy and CyberKnife example beams). CONCLUSIONS: An alternative dual-parameter beam-quality specifier was investigated. The evaluation suggests that it can be used successfully to predict stopping-power ratios in FFF as well as conventional beams, regardless of filtration.

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Biophysics

Keywords

  • dosimetry, phantoms, Monte Carlo methods, radiation therapy
Original languageEnglish
Pages (from-to)1164-1168
JournalMedical Physics
Volume37
Issue number3
Publication statusPublished - 2010
Publication categoryResearch
Peer-reviewedYes

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