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Title: SU-F-T-370: A Fast Monte Carlo Dose Engine for Gamma Knife

Abstract

Purpose: To develop a fast Monte Carlo dose calculation algorithm for Gamma Knife. Methods: To make the simulation more efficient, we implemented the track repeating technique on GPU. We first use EGSnrc to pre-calculate the photon and secondary electron tracks in water from two mono-energy photons of 60Co. The total photon mean free paths for different materials and energies are obtained from NIST. During simulation, each entire photon track was first loaded to shared memory for each block, the incident original photon was then splitted to Nthread sub-photons, each thread transport one sub-photon, the Russian roulette technique was applied for scattered and bremsstrahlung photons. The resultant electrons from photon interactions are simulated by repeating the recorded electron tracks. The electron step length is stretched/shrunk proportionally based on the local density and stopping power ratios of the local material. Energy deposition in a voxel is proportional to the fraction of the equivalent step length in that voxel. To evaluate its accuracy, dose deposition in a 300mm*300mm*300mm water phantom is calculated, and compared to EGSnrc results. Results: Both PDD and OAR showed great agreements (within 0.5%) between our dose engine result and the EGSnrc result. It only takes less than 1 minmore » for every simulation, being reduced up to ∼40 times compared to EGSnrc simulations. Conclusion: We have successfully developed a fast Monte Carlo dose engine for Gamma Knife.« less

Authors:
;  [1];  [2]
  1. Southern Medical University, Guangzhou, Guangdong (China)
  2. Beihang University, Beijing, Beijing (China)
Publication Date:
OSTI Identifier:
22648968
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; COBALT 60; MONTE CARLO METHOD; PARTICLE TRACKS; PHOTONS; RADIATION DOSES; RADIOTHERAPY; SIMULATION

Citation Formats

Song, T, Zhou, L, and Li, Y. SU-F-T-370: A Fast Monte Carlo Dose Engine for Gamma Knife. United States: N. p., 2016. Web. doi:10.1118/1.4956555.
Song, T, Zhou, L, & Li, Y. SU-F-T-370: A Fast Monte Carlo Dose Engine for Gamma Knife. United States. doi:10.1118/1.4956555.
Song, T, Zhou, L, and Li, Y. Wed . "SU-F-T-370: A Fast Monte Carlo Dose Engine for Gamma Knife". United States. doi:10.1118/1.4956555.
@article{osti_22648968,
title = {SU-F-T-370: A Fast Monte Carlo Dose Engine for Gamma Knife},
author = {Song, T and Zhou, L and Li, Y},
abstractNote = {Purpose: To develop a fast Monte Carlo dose calculation algorithm for Gamma Knife. Methods: To make the simulation more efficient, we implemented the track repeating technique on GPU. We first use EGSnrc to pre-calculate the photon and secondary electron tracks in water from two mono-energy photons of 60Co. The total photon mean free paths for different materials and energies are obtained from NIST. During simulation, each entire photon track was first loaded to shared memory for each block, the incident original photon was then splitted to Nthread sub-photons, each thread transport one sub-photon, the Russian roulette technique was applied for scattered and bremsstrahlung photons. The resultant electrons from photon interactions are simulated by repeating the recorded electron tracks. The electron step length is stretched/shrunk proportionally based on the local density and stopping power ratios of the local material. Energy deposition in a voxel is proportional to the fraction of the equivalent step length in that voxel. To evaluate its accuracy, dose deposition in a 300mm*300mm*300mm water phantom is calculated, and compared to EGSnrc results. Results: Both PDD and OAR showed great agreements (within 0.5%) between our dose engine result and the EGSnrc result. It only takes less than 1 min for every simulation, being reduced up to ∼40 times compared to EGSnrc simulations. Conclusion: We have successfully developed a fast Monte Carlo dose engine for Gamma Knife.},
doi = {10.1118/1.4956555},
journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 43,
place = {United States},
year = {2016},
month = {6}
}