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Predictive gamma passing rate by dose uncertainty potential accumulation model.

Eiji Shiba1,2, Akito Saito3, Makoto Furumi1

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|December 12, 2018
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Summary

This study developed a dose uncertainty accumulation model to predict gamma passing rates in intensity-modulated radiation therapy. The new method accurately estimates dose differences, offering a feasible alternative to current measurement-based verification for IMRT dose distributions.

Keywords:
complexity metricdose uncertaintygamma passing rate

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Radiotherapy Physics

Background:

  • Intensity-modulated radiation therapy (IMRT) uses numerous small fields, leading to accumulated dose uncertainties at field junctions.
  • Current IMRT dose verification practices do not fully account for the accumulation of dose uncertainties.
  • Accurate dose verification is critical for ensuring treatment efficacy and patient safety in IMRT.

Purpose of the Study:

  • To develop and validate a novel method for predicting the gamma passing rate (GPR) in IMRT.
  • To implement a dose uncertainty accumulation model to estimate potential dose variations.
  • To assess the feasibility of this predictive model as a replacement for conventional measurement-based IMRT dose verification.

Main Methods:

  • Utilized 33 intensity-modulated beams from head-and-neck cancer cases treated with step-and-shoot IMRT.
  • Developed in-house software to generate a dose uncertainty potential (DUP) distribution by accumulating weighted field shapes and applying Gaussian folding.
  • Predicted GPRs using DUP histograms and leave-one-out cross-validation, comparing predicted GPRs with measured GPRs for various tolerance levels (2%/2-mm, 3%/2-mm, 3%/3-mm).

Main Results:

  • Demonstrated a clear proportionality between the dose uncertainty potential (DUP) and the standard deviation of dose differences.
  • Achieved low standard deviations in the differences between measured and predicted GPRs (e.g., 1.7% for 3%/2-mm tolerance).
  • Established predictive GPR criteria corresponding to measured GPRs ≥ 90% with high confidence levels.

Conclusions:

  • The developed dose uncertainty accumulation model accurately predicts dose differences in IMRT.
  • The predicted gamma passing rates show good accuracy for planar dose distributions in head-and-neck IMRT.
  • This prediction method is a feasible and potentially more efficient substitute for current measurement-based IMRT dose verification techniques.