Literature DB >> 20148126

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

Jeffrey V Siebers1.   

Abstract

Monte Carlo (MC) is rarely used for IMRT plan optimization outside of research centres due to the extensive computational resources or long computation times required to complete the process. Time can be reduced by degrading the statistical precision of the MC dose calculation used within the optimization loop. However, this eventually introduces optimization convergence errors (OCEs). This study determines the statistical noise levels tolerated during MC-IMRT optimization under the condition that the optimized plan has OCEs <100 cGy (1.5% of the prescription dose) for MC-optimized IMRT treatment plans.Seven-field prostate IMRT treatment plans for 10 prostate patients are used in this study. Pre-optimization is performed for deliverable beams with a pencil-beam (PB) dose algorithm. Further deliverable-based optimization proceeds using: (1) MC-based optimization, where dose is recomputed with MC after each intensity update or (2) a once-corrected (OC) MC-hybrid optimization, where a MC dose computation defines beam-by-beam dose correction matrices that are used during a PB-based optimization. Optimizations are performed with nominal per beam MC statistical precisions of 2, 5, 8, 10, 15, and 20%. Following optimizer convergence, beams are re-computed with MC using 2% per beam nominal statistical precision and the 2 PTV and 10 OAR dose indices used in the optimization objective function are tallied. For both the MC-optimization and OC-optimization methods, statistical equivalence tests found that OCEs are less than 1.5% of the prescription dose for plans optimized with nominal statistical uncertainties of up to 10% per beam. The achieved statistical uncertainty in the patient for the 10% per beam simulations from the combination of the 7 beams is ~3% with respect to maximum dose for voxels with D>0.5D(max). The MC dose computation time for the OC-optimization is only 6.2 minutes on a single 3 Ghz processor with results clinically equivalent to high precision MC computations.

Entities:  

Year:  2008        PMID: 20148126      PMCID: PMC2818598          DOI: 10.1088/1742-6596/102/1/012020

Source DB:  PubMed          Journal:  J Phys Conf Ser        ISSN: 1742-6588


  22 in total

1.  Validation of Monte Carlo generated phase-space descriptions of medical linear accelerators.

Authors:  B Libby; J Siebers; R Mohan
Journal:  Med Phys       Date:  1999-08       Impact factor: 4.071

2.  The effect of dose calculation uncertainty on the evaluation of radiotherapy plans.

Authors:  P J Keall; J V Siebers; R Jeraj; R Mohan
Journal:  Med Phys       Date:  2000-03       Impact factor: 4.071

3.  Algorithms and functionality of an intensity modulated radiotherapy optimization system.

Authors:  Q Wu; R Mohan
Journal:  Med Phys       Date:  2000-04       Impact factor: 4.071

4.  Comparison of EGS4 and MCNP4b Monte Carlo codes for generation of photon phase space distributions for a Varian 2100C.

Authors:  J V Siebers; P J Keall; B Libby; R Mohan
Journal:  Phys Med Biol       Date:  1999-12       Impact factor: 3.609

5.  Removing the effect of statistical uncertainty on dose-volume histograms from Monte Carlo dose calculations.

Authors:  S B Jiang; T Pawlicki; C M Ma
Journal:  Phys Med Biol       Date:  2000-08       Impact factor: 3.609

6.  Incorporating multi-leaf collimator leaf sequencing into iterative IMRT optimization.

Authors:  Jeffrey V Siebers; Marc Lauterbach; Paul J Keall; Radhe Mohan
Journal:  Med Phys       Date:  2002-06       Impact factor: 4.071

7.  Effect of statistical uncertainties on Monte Carlo treatment planning.

Authors:  C-M Ma; J S Li; S B Jiang; T Pawlicki; W Xiong; L H Qin; J Yang
Journal:  Phys Med Biol       Date:  2005-02-17       Impact factor: 3.609

8.  Acceleration of dose calculations for intensity-modulated radiotherapy.

Authors:  J V Siebers; S Tong; M Lauterbach; Q Wu; R Mohan
Journal:  Med Phys       Date:  2001-06       Impact factor: 4.071

9.  Performance of a hybrid MC dose algorithm for IMRT optimization dose evaluation.

Authors:  Jeffrey V Siebers; Iwan Kawrakow; V Ramakrishnan
Journal:  Med Phys       Date:  2007-07       Impact factor: 4.071

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

Authors:  Nesrin Dogan; Jeffery V Siebers; Paul J Keall; Fritz Lerma; Yan Wu; Mirek Fatyga; Jeffrey F Williamson; Rupert K Schmidt-Ullrich
Journal:  Med Phys       Date:  2006-11       Impact factor: 4.071

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.