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A Method for Collision Avoidance in External Beam Radiation Therapy

I Buzurovic

I Buzurovic*, R Cormack, Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Boston, MA


SU-F-T-242 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: We proposed a method for collision avoidance (CA) in external beam radiation therapy (EBRT). The method encompasses the analysis of all positions of the moving components of the beam delivery system such as the treatment table and gantry, including patient specific information obtained from the CT images. This method eliminates the need for time-consuming dry-runs prior to the actual treatments.

Methods: The QA procedure for EBRT requires that the collision should be checked prior to treatment. We developed a system capable of a rigorous computer simulation of all moving components including positions of the couch and gantry during the delivery, position of the patients, and imaging equipment. By running this treatment simulation it is possible to quantify and graphically represent all positions and corresponding trajectories of all points of the moving parts during the treatment delivery. The development of the workflow for implementation of the CA includes several steps: a) derivation of combined dynamic equation of motion of the EBRT delivery systems, b) developing the simulation model capable of drawing the motion trajectories of the specific points, c) developing the interface between the model and the treatment plan parameters such as couch and gantry parameters for each field.

Results: The patient CT images were registered to the treatment couch so the patient dimensions were included into the simulation. The treatment field parameters were structured in the xml-file which was used as the input into the dynamic equations. The trajectories of the moving components were plotted on the same graph using the dynamic equations. If the trajectories intersect that was the signal that collision exists.

Conclusion: This CA method was proved to be effective in the simulation of treatment delivery. The proper implementation of this system can potentially improve the QA program and increase the efficacy in the clinical setup.

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