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Abstract #2730

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

Liam S. P. Lawrence1, Brige Chugh2,3, Ryan Oglesby4, and Angus Z. Lau1,5
1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada, 3Department of Physics, Toronto Metropolitan University, Toronto, ON, Canada, 4Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, Baltimore, MD, United States, 5Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada

Synopsis

Keywords: Phantoms, Phantoms, Real-time, adaptive radiotherapy

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.

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Keywords