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Related Experiment Videos

Bootstrap resampling: a powerful method of assessing confidence intervals for doses from experimental data.

G Iwi1, R K Millard, A M Palmer

  • 1Medical Physics Research Centre, Bristol Oncology Centre, UK.

Physics in Medicine and Biology
|May 8, 1999
PubMed
Summary

Bootstrap resampling is a reliable statistical method for estimating accuracy from experimental data. This approach calculates confidence intervals for radiation dosimetry, aiding in uncertainty and sensitivity analysis.

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Area of Science:

  • Biostatistics
  • Radiation Dosimetry
  • Medical Physics

Background:

  • Estimating the accuracy of quantities derived from experimental data is crucial in scientific research.
  • Traditional statistical methods may have limitations in assessing uncertainty for complex calculations.
  • Bootstrap resampling offers an empirically based alternative for evaluating statistical accuracy.

Purpose of the Study:

  • To introduce and illustrate the application of bootstrap resampling for estimating confidence intervals in biomedical contexts.
  • To demonstrate the utility of bootstrap resampling in radiation dosimetry for uncertainty and sensitivity analysis.
  • To provide practical examples of its use in calculating absorbed doses and related quantities.

Main Methods:

  • Bootstrap resampling involves generating numerous simulated datasets from existing measurements.

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  • Confidence intervals are obtained through direct numerical evaluation of derived quantities from these simulated datasets.
  • The method is exemplified using data from human subjects for thyroid and kidney dosimetry, and fetal dose estimation.

    • Main Results:

    • Accurate 95% confidence intervals were estimated for cumulated activity in the thyroid using 99mTc-sodium pertechnetate data.
    • Confidence limits for self-dose to the kidney were determined using 99mTc-DTPA uptake data.
    • Estimates of fetal doses following 99mTc-sodium pertechnetate administration during pregnancy were calculated.

    Conclusions:

    • Bootstrap resampling is a versatile and reliable method for estimating accuracy in quantities calculated from experimental data.
    • The method is particularly well-suited for radiation dosimetry, including uncertainty, reliability, and sensitivity analysis of biokinetic models.
    • Bootstrap resampling has broad applicability across various biomedical research areas beyond dosimetry.