Toward robust adaptive radiation therapy strategies.

Area of Science:

• Medical Physics
• Radiation Oncology

Background:

• Fractionated radiation therapy requires precise dose delivery.
• Interfractional geometric variations can compromise treatment quality.
• Adaptive strategies aim to correct for these variations.

Purpose of the Study:

• To develop a framework for robust treatment planning and adaptive re-optimization.
• To maintain high treatment quality despite geometric variations.
• To identify patients who benefit most from adaptive fractionation.

Main Methods:

• Simulated treatments using stochastic minimax optimization on a 1D phantom.
• Three adaptive strategies investigated: updating error scenarios, adapting conservativeness, and recalculating margins.
• Simulations included anticipated and unpredictably larger errors.

Main Results:

• Robustly optimized plans ensure quality for anticipated errors.
• Adaptive strategies improve organ-at-risk protection.
• The first adaptive strategy (updating error scenarios) with weekly adaptation performed best for larger errors.

Conclusions:

• A framework for robust re-optimization and margin adaptation in response to geometric errors was presented.
• Robust adaptive strategies can identify candidates for individualized adaptive treatment.
• The simulated framework guides the development of optimally controlled robust adaptive therapy.