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Area of Science:

  • Radiation Oncology
  • Medical Physics
  • Computational Biology

Background:

  • Whole-breast radiation therapy (WBRT) requires precise beam setting for optimal efficacy and minimal toxicity.
  • Manual planning is time-consuming and may not fully leverage patient-specific anatomy.
  • Automated solutions are needed to improve efficiency and consistency in WBRT planning.

Purpose of the Study:

  • To develop an automated optimization program for generating patient-specific beam settings in WBRT.
  • To drive beam parameter selection using clinically oriented goals for improved treatment outcomes.
  • To significantly reduce the time required for treatment plan generation.

Main Methods:

  • A retrospective study of 40 patients utilizing planning images and contoured structures.
  • Development of a geometry-based goal function to minimize out-of-field target volume and ipsilateral lung dose.
  • Training and testing of the goal function weighting on distinct patient cohorts.
  • Utilizing an in-house automatic fluence optimization program for target coverage and dose homogeneity.

Main Results:

  • The program successfully generated beam parameters for all patients within 10-120 seconds.
  • Automatic plans demonstrated comparable target coverage (V95%) to manual plans (91.0% vs 88.5%).
  • Reduced ipsilateral lung dose (V20Gy) in automatic plans (15.2% vs 17.9%) with comparable heart sparing and conformity.

Conclusions:

  • An automated, goal-driven beam setting optimization program for WBRT has been successfully developed.
  • The program provides clinically relevant, patient-specific solutions significantly faster than manual methods.
  • This automated approach enhances efficiency and personalization in radiation therapy planning.