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Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
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ROE (Radiotherapy Outcomes Estimator): An open-source tool for optimizing radiotherapy prescriptions.

Aditi Iyer1, Aditya P Apte1, Ethan Bendau2

  • 1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States.

Computer Methods and Programs in Biomedicine
|October 20, 2023
PubMed
Summary

This study introduces ROE, an open-source software tool for personalized radiotherapy prescriptions. It helps determine optimal radiation doses by analyzing patient-specific dose-response curves for better treatment planning.

Keywords:
Normal tissue complication probabilityPrescription determinationRadiotherapy analysis softwareRadiotherapy outcome modelingTumor control probability

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Current radiotherapy prescriptions rely on population-wide guidelines from clinical trials.
  • There is a need for patient-specific approaches in radiation oncology.

Purpose of the Study:

  • To introduce ROE, an open-source software tool for personalized radiotherapy prescription.
  • To enable patient-specific dose determination using personalized dose-response curves.

Main Methods:

  • Developed ROE, a plugin for the Computational Environment for Radiotherapy Research.
  • ROE visualizes predicted tumor control and normal tissue complications as a function of prescription dose.
  • The tool is accessible in MATLAB, GNU Octave, and Python, offering a library of validated predictive models and batch-mode analysis.

Main Results:

  • ROE facilitates interactive exploration of dose-response relationships in radiotherapy planning.
  • The software quantifies risks and benefits of treatment protocols for improved patient awareness.
  • It aids in assessing dose escalation potential and estimating accrual rates for new protocols.

Conclusions:

  • ROE is a valuable open-source tool for interactive radiotherapy planning.
  • It enhances patient understanding of treatment risks and benefits.
  • The tool supports clinical decision-making for dose optimization and protocol evaluation.