SUFT371: Development of a Linac Monte Carlo Model to Calculate Surface Dose
Abstract
Purpose: To generate and validate a linac Monte Carlo (MC) model for surface dose prediction. Methods: BEAMnrc V42.4.0 was used to model 6 and 18 MV photon beams for a commercially available linac. DOSXYZnrc V42.4.0 calculated 3D dose distributions in water. Percent depth dose (PDD) and beam profiles were extracted for comparison to measured data. Surface dose and at depths in the buildup region was measured with radiochromic film at 100 cm SSD for 4 × 4 cm{sup 2} and 10 × 10 cm{sup 2} collimator settings for open and MLC collimated fields. For the 6 MV beam, films were placed at depths ranging from 0.015 cm to 2 cm and for 18 MV, 0.015 cm to 3.5 cm in Solid Water™. Films were calibrated for both photon energies at their respective dmax. PDDs and profiles were extracted from the film and compared to the MC data. The MC model was adjusted to match measured PDD and profiles. Results: For the 6 MV beam, the mean error(ME) in PDD between film and MC for open fields was 1.9%, whereas it was 2.4% for MLC. For the 18 MV beam, the ME in PDD for open fields was 2% and wasmore »
 Authors:
 UT MD Anderson Cancer Center, Houston, TX (United States)
 Publication Date:
 OSTI Identifier:
 22648969
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 61 RADIATION PROTECTION AND DOSIMETRY; BEAM PROFILES; DEPTH DOSE DISTRIBUTIONS; LINEAR ACCELERATORS; MONTE CARLO METHOD; PHOTON BEAMS
Citation Formats
Prajapati, S, Yan, Y, and Gifford, K. SUFT371: Development of a Linac Monte Carlo Model to Calculate Surface Dose. United States: N. p., 2016.
Web. doi:10.1118/1.4956556.
Prajapati, S, Yan, Y, & Gifford, K. SUFT371: Development of a Linac Monte Carlo Model to Calculate Surface Dose. United States. doi:10.1118/1.4956556.
Prajapati, S, Yan, Y, and Gifford, K. 2016.
"SUFT371: Development of a Linac Monte Carlo Model to Calculate Surface Dose". United States.
doi:10.1118/1.4956556.
@article{osti_22648969,
title = {SUFT371: Development of a Linac Monte Carlo Model to Calculate Surface Dose},
author = {Prajapati, S and Yan, Y and Gifford, K},
abstractNote = {Purpose: To generate and validate a linac Monte Carlo (MC) model for surface dose prediction. Methods: BEAMnrc V42.4.0 was used to model 6 and 18 MV photon beams for a commercially available linac. DOSXYZnrc V42.4.0 calculated 3D dose distributions in water. Percent depth dose (PDD) and beam profiles were extracted for comparison to measured data. Surface dose and at depths in the buildup region was measured with radiochromic film at 100 cm SSD for 4 × 4 cm{sup 2} and 10 × 10 cm{sup 2} collimator settings for open and MLC collimated fields. For the 6 MV beam, films were placed at depths ranging from 0.015 cm to 2 cm and for 18 MV, 0.015 cm to 3.5 cm in Solid Water™. Films were calibrated for both photon energies at their respective dmax. PDDs and profiles were extracted from the film and compared to the MC data. The MC model was adjusted to match measured PDD and profiles. Results: For the 6 MV beam, the mean error(ME) in PDD between film and MC for open fields was 1.9%, whereas it was 2.4% for MLC. For the 18 MV beam, the ME in PDD for open fields was 2% and was 3.5% for MLC. For the 6 MV beam, the average root mean square(RMS) deviation for the central 80% of the beam profile for open fields was 1.5%, whereas it was 1.6% for MLC. For the 18 MV beam, the maximum RMS for open fields was 3%, and was 3.1% for MLC. Conclusion: The MC model of a linac agreed to within 4% of film measurements for depths ranging from the surface to dmax. Therefore, the MC linac model can predict surface dose for clinical applications. Future work will focus on adjusting the linac MC model to reduce RMS error and improve accuracy.},
doi = {10.1118/1.4956556},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}

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