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The effect of interfraction prostate motion on IMRT plans: a dose-volume histogram analysis using a Gaussian error

James C L Chow1,2,3,4, Runqing Jiang5, Daniel Markel2

  • 1Department of Radiation Oncology, Princess Margaret Hospital, University Health Network, Toronto, ON, Canada.

Journal of Applied Clinical Medical Physics
|November 18, 2009
PubMed
Summary

The Gaussian error function model accurately analyzes prostate radiation therapy plans, revealing significant dose deviations with underestimated margins during interfraction motion. This model aids in evaluating treatment plans for prostate cancer patients.

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Interfraction prostate motion can significantly impact radiation therapy plan efficacy.
  • Accurate analysis of dose-volume histograms (DVHs) is crucial for optimizing treatment outcomes.
  • Existing methods may not fully capture the complexities of motion-induced DVH changes.

Purpose of the Study:

  • To apply and validate a Gaussian error function model for cumulative DVH (cDVH) analysis in prostate intensity-modulated radiation therapy (IMRT).
  • To assess the impact of interfraction prostate motion on cDVHs and evaluate treatment plan robustness.
  • To investigate the relationship between model parameters and prostate motion characteristics.

Main Methods:

  • Utilized a Gaussian error function model to analyze cDVHs for prostate IMRT plans.
  • Calculated and modeled cDVHs for clinical target volumes (CTVs) shifted in anterior-posterior directions.
  • Employed the Pinnacle3 treatment planning system for plan calculations.
  • Analyzed model parameters (a, b, c) in relation to prostate motion and volume.

Main Results:

  • The Gaussian error function model effectively evaluated cDVHs under interfraction prostate motion.
  • Underestimating CTV-planning target volume (PTV) margins led to significant cDVH deviations, especially posteriorly.
  • Model parameters demonstrated distinct behaviors related to motion direction, prostate size, and dose metrics.

Conclusions:

  • The Gaussian error function model is validated for analyzing prostate IMRT plans with interfraction motion.
  • The model provides a robust mathematical tool for evaluating treatment plan quality and robustness.
  • This approach enhances the clinical application of mathematical modeling in radiation oncology.