Using correlated sampson to accelerate CT-based Monte Carlo dose calculations for brachytherapy treatment planning

A. Sampson; Y. Le; D. Todor; J. Williamson

doi:10.1007/978-3-642-03474-9_88

Using correlated sampson to accelerate CT-based Monte Carlo dose calculations for brachytherapy treatment planning

A. Sampson, Y. Le, D. Todor, J. Williamson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

The aim of this study was to assess the impact on efficiency and accuracy of a correlated sampling Monte Carlo simulation code for evaluating clinical brachytherapy dose distributions, accounting for tissue-composition and applicator heterogeneities. This code was built upon an extensively benchmarked Monte Carlo code, PTRAN-CCG and a CT-like cross-section map derived from patient single-energy CT images. Differences between PTRAN-CCG and the correlated code, expressed relative to the statistical uncertainty were found to be normally distributed with a standard deviation of 1.00 and a mean of -0.109 indicating that the correlated and conventional Monte Carlo agree within statistical error. Correlated sampling increases efficiency by factors of 7.1, 9.1, and 10.4, for greater than 20%, 50% and 90% of D₉₀, respectively, for a 2×2×2 mm voxel grid.

Original language	English (US)
Title of host publication	World Congress on Medical Physics and Biomedical Engineering
Subtitle of host publication	Radiation Oncology
Publisher	Springer Verlag
Pages	311-314
Number of pages	4
Edition	1
ISBN (Print)	9783642034725
DOIs	https://doi.org/10.1007/978-3-642-03474-9_88
State	Published - 2009
Externally published	Yes
Event	World Congress on Medical Physics and Biomedical Engineering: Radiation Oncology - Munich, Germany Duration: Sep 7 2009 → Sep 12 2009

Publication series

Name	IFMBE Proceedings
Number	1
Volume	25
ISSN (Print)	1680-0737

Other

Other	World Congress on Medical Physics and Biomedical Engineering: Radiation Oncology
Country/Territory	Germany
City	Munich
Period	9/7/09 → 9/12/09

Keywords

Brachytherapy
Correlated sampling
Monte Carlo

ASJC Scopus subject areas

Bioengineering
Biomedical Engineering

Access to Document

10.1007/978-3-642-03474-9_88

Cite this

Sampson, A., Le, Y., Todor, D., & Williamson, J. (2009). Using correlated sampson to accelerate CT-based Monte Carlo dose calculations for brachytherapy treatment planning. In World Congress on Medical Physics and Biomedical Engineering: Radiation Oncology (1 ed., pp. 311-314). (IFMBE Proceedings; Vol. 25, No. 1). Springer Verlag. https://doi.org/10.1007/978-3-642-03474-9_88

Using correlated sampson to accelerate CT-based Monte Carlo dose calculations for brachytherapy treatment planning. / Sampson, A.; Le, Y.; Todor, D. et al.
World Congress on Medical Physics and Biomedical Engineering: Radiation Oncology. 1. ed. Springer Verlag, 2009. p. 311-314 (IFMBE Proceedings; Vol. 25, No. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sampson, A, Le, Y, Todor, D & Williamson, J 2009, Using correlated sampson to accelerate CT-based Monte Carlo dose calculations for brachytherapy treatment planning. in World Congress on Medical Physics and Biomedical Engineering: Radiation Oncology. 1 edn, IFMBE Proceedings, no. 1, vol. 25, Springer Verlag, pp. 311-314, World Congress on Medical Physics and Biomedical Engineering: Radiation Oncology, Munich, Germany, 9/7/09. https://doi.org/10.1007/978-3-642-03474-9_88

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abstract = "The aim of this study was to assess the impact on efficiency and accuracy of a correlated sampling Monte Carlo simulation code for evaluating clinical brachytherapy dose distributions, accounting for tissue-composition and applicator heterogeneities. This code was built upon an extensively benchmarked Monte Carlo code, PTRAN-CCG and a CT-like cross-section map derived from patient single-energy CT images. Differences between PTRAN-CCG and the correlated code, expressed relative to the statistical uncertainty were found to be normally distributed with a standard deviation of 1.00 and a mean of -0.109 indicating that the correlated and conventional Monte Carlo agree within statistical error. Correlated sampling increases efficiency by factors of 7.1, 9.1, and 10.4, for greater than 20%, 50% and 90% of D90, respectively, for a 2×2×2 mm voxel grid.",

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AB - The aim of this study was to assess the impact on efficiency and accuracy of a correlated sampling Monte Carlo simulation code for evaluating clinical brachytherapy dose distributions, accounting for tissue-composition and applicator heterogeneities. This code was built upon an extensively benchmarked Monte Carlo code, PTRAN-CCG and a CT-like cross-section map derived from patient single-energy CT images. Differences between PTRAN-CCG and the correlated code, expressed relative to the statistical uncertainty were found to be normally distributed with a standard deviation of 1.00 and a mean of -0.109 indicating that the correlated and conventional Monte Carlo agree within statistical error. Correlated sampling increases efficiency by factors of 7.1, 9.1, and 10.4, for greater than 20%, 50% and 90% of D90, respectively, for a 2×2×2 mm voxel grid.

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Using correlated sampson to accelerate CT-based Monte Carlo dose calculations for brachytherapy treatment planning

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