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Selective robust optimization: A new intensity-modulated proton therapy optimization strategy.

Yupeng Li1, Perttu Niemela2, Li Liao3

  • 1Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and Department of Applied Research, Varian Medical Systems, Palo Alto, California 94304.

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This summary is machine-generated.

Selective robust optimization enhances proton therapy by improving target volume coverage and dose control. This new strategy aims to bridge the gap between research and clinical application for robust proton treatment planning.

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Intensity-modulated proton therapy (IMPT) planning requires robust strategies to account for uncertainties.
  • Translating research-level robust planning to clinical practice remains a challenge.

Purpose of the Study:

  • To develop and evaluate a novel robust optimization strategy for intensity-modulated proton therapy.
  • To enhance the clinical applicability of robust proton treatment planning.

Main Methods:

  • Extended a worst-case-based robust optimization algorithm for selective dose computation.
  • Applied selective robust optimization to lung and head and neck cancer cases, assuming static tumors for demonstration.

Main Results:

  • Achieved robust clinical target volume (CTV) coverage and improved nominal planning target volume coverage (95.8% vs. 84.6% in one lung case).
  • Reduced maximum dose in another lung case (113.6% vs. 131.3% with CTV-based robust optimization).
  • Demonstrated robust CTV coverage and improved isodose distribution control for a head and neck case.

Conclusions:

  • Selective robust optimization offers flexibility for clinical requirements while ensuring plan robustness.
  • This strategy facilitates the translation of robust proton treatment planning into clinical settings.