Literature DB >> 12408475

A fluence-convolution method to calculate radiation therapy dose distributions that incorporate random set-up error.

W A Beckham1, P J Keall, J V Siebers.   

Abstract

The International Commission on Radiation Units and Measurements Report 62 (ICRU 1999) introduced the concept of expanding the clinical target volume (CTV) to form the planning target volume by a two-step process. The first step is adding a clinically definable internal margin, which produces an internal target volume that accounts for the size, shape and position of the CTV in relation to anatomical reference points. The second is the use of a set-up margin (SM) that incorporates the uncertainties of patient beam positioning, i.e. systematic and random set-up errors. We propose to replace the random set-up error component of the SM by explicitly incorporating the random set-up error into the dose-calculation model by convolving the incident photon beam fluence with a Gaussian set-up error kernel. This fluence-convolution method was implemented into a Monte Carlo (MC) based treatment-planning system. Also implemented for comparison purposes was a dose-matrix-convolution algorithm similar to that described by Leong (1987 Phys. Med. Biol. 32 327-34). Fluence and dose-matrix-convolution agree in homogeneous media. However, for the heterogeneous phantom calculations, discrepancies of up to 5% in the dose profiles were observed with a 0.4 cm set-up error value. Fluence-convolution mimics reality more closely, as dose perturbations at interfaces are correctly predicted (Wang et al 1999 Med. Phys. 26 2626-34, Sauer 1995 Med. Phys. 22 1685-90). Fluence-convolution effectively decouples the treatment beams from the patient. and more closely resembles the reality of particle fluence distributions for many individual beam-patient set-ups. However, dose-matrix-convolution reduces the random statistical noise in MC calculations. Fluence-convolution can easily be applied to convolution/superposition based dose-calculation algorithms.

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Year:  2002        PMID: 12408475     DOI: 10.1088/0031-9155/47/19/302

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


  19 in total

1.  Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning.

Authors:  Jan Unkelbach; Thomas Bortfeld; Benjamin C Martin; Martin Soukup
Journal:  Med Phys       Date:  2009-01       Impact factor: 4.071

2.  Coverage-based treatment planning: optimizing the IMRT PTV to meet a CTV coverage criterion.

Authors:  J J Gordon; J V Siebers
Journal:  Med Phys       Date:  2009-03       Impact factor: 4.071

3.  Evaluation of dosimetric margins in prostate IMRT treatment plans.

Authors:  J J Gordon; J V Siebers
Journal:  Med Phys       Date:  2008-02       Impact factor: 4.071

4.  A comparison of HDR brachytherapy and IMRT techniques for dose escalation in prostate cancer: a radiobiological modeling study.

Authors:  M Fatyga; J F Williamson; N Dogan; D Todor; J V Siebers; R George; I Barani; M Hagan
Journal:  Med Phys       Date:  2009-09       Impact factor: 4.071

Review 5.  Robustness Analysis for External Beam Radiation Therapy Treatment Plans: Describing Uncertainty Scenarios and Reporting Their Dosimetric Consequences.

Authors:  Adam D Yock; Radhe Mohan; Stella Flampouri; Walter Bosch; Paige A Taylor; David Gladstone; Siyong Kim; Jason Sohn; Robert Wallace; Ying Xiao; Jeff Buchsbaum
Journal:  Pract Radiat Oncol       Date:  2018-12-15

6.  Sensitivity of postplanning target and OAR coverage estimates to dosimetric margin distribution sampling parameters.

Authors:  Huijun Xu; J James Gordon; Jeffrey V Siebers
Journal:  Med Phys       Date:  2011-02       Impact factor: 4.071

7.  A simplified method of four-dimensional dose accumulation using the mean patient density representation.

Authors:  Carri K Glide-Hurst; Geoffrey D Hugo; Jian Liang; Di Yan
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

8.  Tumor trailing strategy for intensity-modulated radiation therapy of moving targets.

Authors:  Alexei Trofimov; Christian Vrancic; Timothy C Y Chan; Gregory C Sharp; Thomas Bortfeld
Journal:  Med Phys       Date:  2008-05       Impact factor: 4.071

9.  An evaluation of planning techniques for stereotactic body radiation therapy in lung tumors.

Authors:  Jianzhou Wu; Huiling Li; Raj Shekhar; Mohan Suntharalingam; Warren D'Souza
Journal:  Radiother Oncol       Date:  2008-03-24       Impact factor: 6.280

10.  Dose deformation-invariance in adaptive prostate radiation therapy: implication for treatment simulations.

Authors:  Manju Sharma; Elisabeth Weiss; Jeffrey V Siebers
Journal:  Radiother Oncol       Date:  2012-11-29       Impact factor: 6.280

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