Robust radiation therapy optimization using simulated treatment courses for handling deformable organ motion.

Area of Science:

• Radiation Oncology
• Medical Physics
• Image-guided Therapy

Background:

• Interfraction organ motion significantly impacts radiation therapy accuracy.
• Conventional planning using planning target volume (PTV) may lead to suboptimal dose distribution.
• Robust optimization offers a potential solution to account for treatment uncertainties.

Purpose of the Study:

• To develop and evaluate a radiation therapy planning method using robust optimization on the clinical target volume (CTV).
• To compare this novel method against conventional planning based on PTV margins.
• To assess the impact on target coverage and organ-at-risk (OAR) doses in prostate cancer treatment.

Main Methods:

• Simulated treatment courses generated via deformable image registration to model interfraction motion.
• Robust optimization performed to ensure CTV coverage across all simulated scenarios.
• Comparison of robustly optimized plans with conventional PTV-based plans using clinical objectives for CTV and OARs.

Main Results:

• Robustly optimized plans showed a tendency to violate CTV overdosage goals less frequently than PTV plans.
• Significantly fewer violations of clinical goals for rectum, bladder, and anal canal observed with robust optimization.
• Robust optimization demonstrated potential for reduced dose to healthy tissues while maintaining target coverage.

Conclusions:

• Robust optimization, considering interfraction motion, can improve treatment plan quality in radiation therapy.
• This approach may reduce toxicity by sparing organs at risk.
• The method holds promise for minimizing the requirement for adaptive replanning during treatment courses.