SU-E-T-752: Energy Spectrum and Fluence Reconstruction of High Energy Photon Beams Based on Analytical Double-Source Model

Abstract

Purpose: To improve the accuracy on unfolding photon energy spectra and fluence for dose calculation, by use of measured percentage depth dose and off-axis ratio, an analytical double-source model considered both photon beam and electron contamination was constructed, an improvement of Schiff formula and finite-size pencil beam (FSPB) model. Methods: For energy spectrum reconstruction, several regression algorithms were used to obtain the optimum solution. It was also compared with the mono-source model that ignored the electron contamination. For energy fluence reconstruction, the double-source FSPB was developed by considering the energy spectra of photon beam and electron contamination, and was also reconstructed by above algorithms. Results: A representative testing sample, the AAPM 55# report as an 18MVˈs AECL Therac-20 medical linac, was used. The comparison between the double-source model and mono-source model in energy spectrum reconstruction found that there was a great improvement in accuracy; the mean error of double-source model was about 0.015% while the mono-source modelˈs was about 0.1%. We found that there are two peaks at 2 and 3 MeV in the photon energy spectra and the peak of the electron energy was in the low energy. We also found that if ignoring the electron contamination, the peak of the photon energy spectra could drift to the lower energy, and the mean error became great. We also obtained the accurate energy fluence, only about 0.01% mean error in the field. Conclusions: This study has revealed the great improvement of Schiff formula and FSPB model on energy spectrum and fluence of photon beam and electron contamination by reconstruction method, an analytical double-source model. Our finding will help know more about detail of medical linac, and improve the dose accuracy in dose calculation of radiotherapy by use of this reconstructed information. Supported by the National Natural Science Foundation under grant No.30900386 and the Anhui Provincial Natural Science Foundation under grantNo. 090413095 and 11040606Q55.