Assessment of Random Error in Phantom Dosimetry with the Use of Error Simulation in Statistical Software.

Objective. To investigate if software simulation is practical for quantifying random error (RE) in phantom dosimetry. Materials and Methods. We applied software error simulation to an existing dosimetry study. The specifications and the measurement values of this study were brought into the software...

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Publicado en:BioMed Research International Vol. 2015; pp. 1 - 6
Autores principales: Hoogeveen, R. C., Martens, E. P., van der Stelt, P. F., Berkhout, W. E. R.
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 12/31/2015
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 12/31/2015
      vid: 2015
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      pub: Wiley-Blackwell
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        10.1155/2015/596858
        113630269
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        atl: Assessment of Random Error in Phantom Dosimetry with the Use of Error Simulation in Statistical Software.
      aug:
        au:
          Hoogeveen, R. C.
          Martens, E. P.
          van der Stelt, P. F.
          Berkhout, W. E. R.
        affil: Department of Oral and Maxillofacial Radiology, Academic Center for Dentistry Amsterdam (ACTA), Gustav Mahlerlaan 3004, 1081 LA Amsterdam, Netherlands
      sug:
        subj:
          Random Error Evaluation
          Dosimetry
          Phantoms, Imaging
          Data Analysis Software
          Computer Simulation
          Algorithms
          Calibration
          Confidence Intervals
          Descriptive Statistics
          X-Rays
          Radiation Dosage
          Software Design
      ab: Objective. To investigate if software simulation is practical for quantifying random error (RE) in phantom dosimetry. Materials and Methods. We applied software error simulation to an existing dosimetry study. The specifications and the measurement values of this study were brought into the software (R version 3.0.2) together with the algorithm of the calculation of the effective dose (E). Four sources of RE were specified: (1) the calibration factor; (2) the background radiation correction; (3) the read-out process of the dosimeters; and (4) the fluctuation of the X-ray generator. Results. The amount of RE introduced by these sources was calculated on the basis of the experimental values and the mathematical rules of error propagation. The software repeated the calculations of E multiple times (n=10,000) while attributing the applicable RE to the experimental values. A distribution of E emerged as a confidence interval around an expected value. Conclusions. Credible confidence intervals around E in phantom dose studies can be calculated by using software modelling of the experiment. With credible confidence intervals, the statistical significance of differences between protocols can be substantiated or rejected. This modelling software can also be used for a power analysis when planning phantom dose experiments.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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