Literature DB >> 12361220

A method for photon beam Monte Carlo multileaf collimator particle transport.

Jeffrey V Siebers1, Paul J Keall, Jong Oh Kim, Radhe Mohan.   

Abstract

Monte Carlo (MC) algorithms are recognized as the most accurate methodology for patient dose assessment. For intensity-modulated radiation therapy (IMRT) delivered with dynamic multileaf collimators (DMLCs), accurate dose calculation, even with MC, is challenging. Accurate IMRT MC dose calculations require inclusion of the moving MLC in the MC simulation. Due to its complex geometry, full transport through the MLC can be time consuming. The aim of this work was to develop an MLC model for photon beam MC IMRT dose computations. The basis of the MC MLC model is that the complex MLC geometry can be separated into simple geometric regions, each of which readily lends itself to simplified radiation transport. For photons, only attenuation and first Compton scatter interactions are considered. The amount of attenuation material an individual particle encounters while traversing the entire MLC is determined by adding the individual amounts from each of the simplified geometric regions. Compton scatter is sampled based upon the total thickness traversed. Pair production and electron interactions (scattering and bremsstrahlung) within the MLC are ignored. The MLC model was tested for 6 MV and 18 MV photon beams by comparing it with measurements and MC simulations that incorporate the full physics and geometry for fields blocked by the MLC and with measurements for fields with the maximum possible tongue-and-groove and tongue-or-groove effects, for static test cases and for sliding windows of various widths. The MLC model predicts the field size dependence of the MLC leakage radiation within 0.1% of the open-field dose. The entrance dose and beam hardening behind a closed MLC are predicted within +/- 1% or 1 mm. Dose undulations due to differences in inter- and intra-leaf leakage are also correctly predicted. The MC MLC model predicts leaf-edge tongue-and-groove dose effect within +/- 1% or 1 mm for 95% of the points compared at 6 MV and 88% of the points compared at 18 MV. The dose through a static leaf tip is also predicted generally within +/- 1% or 1 mm. Tests with sliding windows of various widths confirm the accuracy of the MLC model for dynamic delivery and indicate that accounting for a slight leaf position error (0.008 cm for our MLC) will improve the accuracy of the model. The MLC model developed is applicable to both dynamic MLC and segmental MLC IMRT beam delivery and will be useful for patient IMRT dose calculations, pre-treatment verification of IMRT delivery and IMRT portal dose transmission dosimetry.

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Year:  2002        PMID: 12361220     DOI: 10.1088/0031-9155/47/17/312

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  23 in total

1.  Four-dimensional dosimetry validation and study in lung radiotherapy using deformable image registration and Monte Carlo techniques.

Authors:  Tzung-Chi Huang; Ji-An Liang; Thomas Dilling; Tung-Hsin Wu; Geoffrey Zhang
Journal:  Radiat Oncol       Date:  2010-05-29       Impact factor: 3.481

2.  Analytic IMRT dose calculations utilizing Monte Carlo to predict MLC fluence modulation.

Authors:  I B Mihaylov; F A Lerma; Y Wu; J V Siebers
Journal:  Med Phys       Date:  2006-04       Impact factor: 4.071

3.  Dosimetric impact of motion in free-breathing and gated lung radiotherapy: a 4D Monte Carlo study of intrafraction and interfraction effects.

Authors:  Joao Seco; Greg C Sharp; Ziji Wu; David Gierga; Florian Buettner; Harald Paganetti
Journal:  Med Phys       Date:  2008-01       Impact factor: 4.071

4.  Monte Carlo-based adaptive EPID dose kernel accounting for different field size responses of imagers.

Authors:  Song Wang; Joseph K Gardner; John J Gordon; Weidong Li; Luke Clews; Peter B Greer; Jeffrey V Siebers
Journal:  Med Phys       Date:  2009-08       Impact factor: 4.071

Review 5.  Monte Carlo systems used for treatment planning and dose verification.

Authors:  Lorenzo Brualla; Miguel Rodriguez; Antonio M Lallena
Journal:  Strahlenther Onkol       Date:  2016-11-25       Impact factor: 3.621

6.  Comparison of IMRT and VMAT plans with different energy levels using Monte-Carlo algorithm for prostate cancer.

Authors:  Cem Onal; Gungor Arslan; Cem Parlak; Serhat Sonmez
Journal:  Jpn J Radiol       Date:  2014-02-08       Impact factor: 2.374

7.  Commissioning of 6 MV medical linac for dynamic MLC-based IMRT on Monte Carlo code GEANT4.

Authors:  Hiroyuki Okamoto; Yukio Fujita; Kyoko Sakama; Hidetoshi Saitoh; Tatsuaki Kanai; Jun Itami; Toshiyuki Kohno
Journal:  Radiol Phys Technol       Date:  2014-02-08

8.  The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.

Authors:  Jeffrey V Siebers
Journal:  J Phys Conf Ser       Date:  2008-04-04

9.  Design and testing of a simulation framework for dosimetric motion studies integrating an anthropomorphic computational phantom into four-dimensional Monte Carlo.

Authors:  M Riboldi; G T Y Chen; G Baroni; H Paganetti; J Seco
Journal:  Technol Cancer Res Treat       Date:  2008-12

10.  Monte Carlo dose verification of prostate patients treated with simultaneous integrated boost intensity modulated radiation therapy.

Authors:  Nesrin Dogan; Ivaylo Mihaylov; Yan Wu; Paul J Keall; Jeffrey V Siebers; Michael P Hagan
Journal:  Radiat Oncol       Date:  2009-06-15       Impact factor: 3.481

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