Literature DB >> 20061172

Determination of the optimal statistical uncertainty to perform electron-beam Monte Carlo absorbed dose estimation in the target volume.

A Isambert1, L Brualla, M Benkebil, D Lefkopoulos.   

Abstract

PURPOSE OF STUDY: Monte Carlo based treatment planning system are known to be more accurate than analytical methods for performing absorbed dose estimation, particularly in and near heterogeneities. However, the required computation time can still be an issue. The present study focused on the determination of the optimum statistical uncertainty in order to minimise computation time while keeping the reliability of the absorbed dose estimation in treatments planned with electron-beams.
MATERIALS AND METHODS: Three radiotherapy plans (medulloblastoma, breast and gynaecological) were used to investigate the influence of the statistical uncertainty of the absorbed dose on the target volume dose-volume histograms (spinal cord, intramammary nodes and pelvic lymph nodes, respectively).
RESULTS: The study of the dose-volume histograms showed that for statistical uncertainty levels (1 S.D.) above 2 to 3%, the standard deviation of the mean dose in the target volume calculated from the dose-volume histograms increases by at least 6%, reflecting the gradual flattening of the dose-volume histograms.
CONCLUSIONS: This work suggests that, in clinical context, Monte Carlo based absorbed dose estimations should be performed with a maximum statistical uncertainty of 2 to 3%. Copyright (c) 2009 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

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Year:  2010        PMID: 20061172     DOI: 10.1016/j.canrad.2009.09.007

Source DB:  PubMed          Journal:  Cancer Radiother        ISSN: 1278-3218            Impact factor:   1.018


  1 in total

Review 1.  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

  1 in total

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