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Setting Limits on Supersymmetry Using Simplified Models
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Correcting TG 119 confidence limits.

Vasant Kearney1, Timothy Solberg1, Shane Jensen2

  • 1Department of Radiation Oncology, University of California, San Francisco, CA, 94115, USA.

Medical Physics
|January 24, 2018
PubMed
Summary
This summary is machine-generated.

This study suggests using a gamma distribution instead of a Gaussian distribution for establishing confidence limits in intensity-modulated radiation therapy (IMRT) quality assurance (QA). The gamma distribution provides more accurate confidence limits for IMRT QA passing rates, improving clinical practice.

Keywords:
IMRTQA confidence limitsIMRTQA passing ratesTG 119TG 119 confidence limitsTG 119 passing rates

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Quality Assurance

Background:

  • Task Group 119 (TG-119) provides guidelines for intensity-modulated radiation therapy (IMRT) commissioning and patient-specific quality assurance (QA).
  • TG-119 uses 95% confidence limits (CLs) based on Gaussian distribution assumptions to identify systematic IMRT QA errors.
  • Gaussian distributions may not accurately represent IMRT QA data, potentially leading to inaccurate CLs.

Purpose of the Study:

  • To evaluate the suitability of the gamma distribution for establishing CLs in IMRT QA.
  • To compare the accuracy of CLs derived from gamma and Gaussian distributions.
  • To propose the gamma distribution as a replacement for the Gaussian model in TG-119 guidelines.

Main Methods:

  • Utilized the moments estimator (ME) for the gamma family to calculate CLs for Gamma (Γ) analysis failing rates.
  • Compared the root mean squared error and CL values between gamma and Gaussian distribution MEs.
  • Analyzed 302 IMRT plans to establish empirical 95% CLs as ground truth.

Main Results:

  • The gamma distribution underestimated the 95% CL by 0.09%.
  • The Gaussian distribution overestimated the 95% CL by 4.12%.
  • Empirical data showed a 91.83% passing rate with 3%/3 mm criteria.

Conclusions:

  • The gamma distribution is a more appropriate statistical model than the Gaussian distribution for establishing CLs in IMRT QA.
  • This mathematical approach is applicable across various IMRT planning and delivery systems.
  • Adopting the gamma distribution can enhance the accuracy of IMRT QA passing criteria.