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Title: SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement

Abstract

Purpose: Adding kernels (small perturbations in leaf positions) to the existing apertures of VMAT control points may improve plan quality. We investigate the calculation of kernel doses using a parallelized Monte Carlo (MC) method. Methods: A clinical prostate VMAT DICOM plan was exported from Eclipse. An arbitrary control point and leaf were chosen, and a modified MLC file was created, corresponding to the leaf position offset by 0.5cm. The additional dose produced by this 0.5 cm × 0.5 cm kernel was calculated using the DOSXYZnrc component module of BEAMnrc. A range of particle history counts were run (varying from 3 × 10{sup 6} to 3 × 10{sup 7}); each job was split among 1, 10, or 100 parallel processes. A particle count of 3 × 10{sup 6} was established as the lower range because it provided the minimal accuracy level. Results: As expected, an increase in particle counts linearly increases run time. For the lowest particle count, the time varied from 30 hours for the single-processor run, to 0.30 hours for the 100-processor run. Conclusion: Parallel processing of MC calculations in the EGS framework significantly decreases time necessary for each kernel dose calculation. Particle counts lower than 1 × 10{supmore » 6} have too large of an error to output accurate dose for a Monte Carlo kernel calculation. Future work will investigate increasing the number of parallel processes and optimizing run times for multiple kernel calculations.« less

Authors:
 [1];  [2]; ;  [3]
  1. State University of New York at Fredonia, Fredonia, NY (United States)
  2. (United States)
  3. Roswell Park Cancer Institute, Buffalo, NY (United States)
Publication Date:
OSTI Identifier:
22624425
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:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; ERRORS; KERNELS; MONTE CARLO METHOD; OPTIMIZATION; PARALLEL PROCESSING; PROSTATE; RADIATION DOSES; RADIOTHERAPY

Citation Formats

Chamberlain, S, Roswell Park Cancer Institute, Buffalo, NY, French, S, and Nazareth, D. SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement. United States: N. p., 2016. Web. doi:10.1118/1.4955684.
Chamberlain, S, Roswell Park Cancer Institute, Buffalo, NY, French, S, & Nazareth, D. SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement. United States. doi:10.1118/1.4955684.
Chamberlain, S, Roswell Park Cancer Institute, Buffalo, NY, French, S, and Nazareth, D. Wed . "SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement". United States. doi:10.1118/1.4955684.
@article{osti_22624425,
title = {SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement},
author = {Chamberlain, S and Roswell Park Cancer Institute, Buffalo, NY and French, S and Nazareth, D},
abstractNote = {Purpose: Adding kernels (small perturbations in leaf positions) to the existing apertures of VMAT control points may improve plan quality. We investigate the calculation of kernel doses using a parallelized Monte Carlo (MC) method. Methods: A clinical prostate VMAT DICOM plan was exported from Eclipse. An arbitrary control point and leaf were chosen, and a modified MLC file was created, corresponding to the leaf position offset by 0.5cm. The additional dose produced by this 0.5 cm × 0.5 cm kernel was calculated using the DOSXYZnrc component module of BEAMnrc. A range of particle history counts were run (varying from 3 × 10{sup 6} to 3 × 10{sup 7}); each job was split among 1, 10, or 100 parallel processes. A particle count of 3 × 10{sup 6} was established as the lower range because it provided the minimal accuracy level. Results: As expected, an increase in particle counts linearly increases run time. For the lowest particle count, the time varied from 30 hours for the single-processor run, to 0.30 hours for the 100-processor run. Conclusion: Parallel processing of MC calculations in the EGS framework significantly decreases time necessary for each kernel dose calculation. Particle counts lower than 1 × 10{sup 6} have too large of an error to output accurate dose for a Monte Carlo kernel calculation. Future work will investigate increasing the number of parallel processes and optimizing run times for multiple kernel calculations.},
doi = {10.1118/1.4955684},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}