Literature DB >> 17153383

Improving IMRT dose accuracy via deliverable Monte Carlo optimization for the treatment of head and neck cancer patients.

Nesrin Dogan1, Jeffery V Siebers, Paul J Keall, Fritz Lerma, Yan Wu, Mirek Fatyga, Jeffrey F Williamson, Rupert K Schmidt-Ullrich.   

Abstract

The purpose of this work is to investigate the effect of dose-calculation accuracy on head and neck (H&N) intensity modulated radiation therapy (IMRT) plans by determining the systematic dose-prediction and optimization-convergence errors (DPEs and OCEs), using a superposition/convolution (SC) algorithm. Ten patients with locally advanced H&N squamous cell carcinoma who were treated with simultaneous integrated boost IMRT were selected for this study. The targets consisted of gross target volume (GTV), clinical target volume (CTV), and nodal target volumes (CTV nodes). The critical structures included spinal cord, parotid glands, and brainstem. For all patients, three IMRT plans were created: A: an SC optimized plan (SCopt), B: an SCopt plan recalculated with Monte Carlo [MC(SCopt)], and C: an MC optimized plan (MCopt). For each structure, DPEs and OCEs were estimated as DPE(SC)=D(B)-D(A) and OCE(SC)=D(C)-D(B) where A, B, and C stand for the three different optimized plans as defined above. Deliverable optimization was used for all plans, that is, a leaf-sequencing step was incorporated into the optimization loop at each iteration. The range of DPE(SC) in the GTV D98 varied from -1.9% to -4.9%, while the OCE(SC) ranged from 0.9% to 7.0%. The DPE(SC) in the contralateral parotid D50 reached 8.2%, while the OCE(SC) in the contralateral parotid D50 varied from 0.91% to 6.99%. The DPE(SC) in cord D2 reached -3.0%, while the OCE(SC) reached to -7.0%. The magnitude of the DPE(SC) and OCE(SC) differences demonstrate the importance of using the most accurate available algorithm in the deliverable IMRT optimization process, especially for the estimation of normal structure doses.

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Year:  2006        PMID: 17153383     DOI: 10.1118/1.2357835

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  19 in total

1.  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

2.  Dose-mass inverse optimization for minimally moving thoracic lesions.

Authors:  I B Mihaylov; E G Moros
Journal:  Phys Med Biol       Date:  2015-04-24       Impact factor: 3.609

3.  Improving target dose coverage and organ-at-risk sparing in intensity-modulated radiotherapy of advanced laryngeal cancer by a simple optimization technique.

Authors:  J-Y Lu; L-L Wu; J-Y Zhang; J Zheng; M L-M Cheung; C-C Ma; L-X Xie; B-T Huang
Journal:  Br J Radiol       Date:  2014-12-12       Impact factor: 3.039

4.  A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model.

Authors:  Yuhe Wang; Thomas R Mazur; Olga Green; Yanle Hu; Hua Li; Vivian Rodriguez; H Omar Wooten; Deshan Yang; Tianyu Zhao; Sasa Mutic; H Harold Li
Journal:  Med Phys       Date:  2016-07       Impact factor: 4.071

5.  EGSnrc application for IMRT planning.

Authors:  Sitti Yani; Ilmi Rizkia; Mohamad Fahdillah Rhani; Mohammad Haekal; Freddy Haryanto
Journal:  Rep Pract Oncol Radiother       Date:  2020-01-22

6.  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

7.  CT-myelography for high-dose irradiation of spinal and paraspinal tumors with helical tomotherapy: revival of an old tool.

Authors:  Matthias Uhl; Florian Sterzing; Gregor Habl; Kai Schubert; Gabriele Sroka-Perez; Jürgen Debus; Klaus Herfarth
Journal:  Strahlenther Onkol       Date:  2011-06-27       Impact factor: 3.621

8.  Applying graphics processor units to Monte Carlo dose calculation in radiation therapy.

Authors:  M Bakhtiari; H Malhotra; M D Jones; V Chaudhary; J P Walters; D Nazareth
Journal:  J Med Phys       Date:  2010-04

9.  Evaluation of dose prediction errors and optimization convergence errors of deliverable-based head-and-neck IMRT plans computed with a superposition/convolution dose algorithm.

Authors:  I B Mihaylov; J V Siebers
Journal:  Med Phys       Date:  2008-08       Impact factor: 4.071

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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