Characterization of deformable tumor models for real-time adaptive radiotherapy plan evaluation

Motivation: Real-time adaptive radiotherapy, which involves tracking a target during internal patient motion, may soon reach clinical implementation. Quality assurance methods will be needed, especially for deformable motion. Goal(s): Develop a method of characterizing the relationship between input and target shape for deformable tumor model phantoms. Approach: We acquired dynamic MRI and static CT of a deformable phantom subject to several input waveforms. We approximated the target as an ellipsoid and created a linear model to predict the ellipsoid parameters from the input. Results: The ellipsoid parameters of the target subject to a new waveform could be predicted to within a millimeter. Impact: We demonstrated a simple method to determine the relationship between input and target geometry for deformable tumor model phantoms. Patient-specific tumor motion can be recreated by inverting the input-target geometry relationship for quality assurance of real-time adaptive radiotherapy plans.