Program Information
A Novel Tool for Treatment Planning and Simulation to Model and Prevent Treatment Collisions During External Beam Radiotherapy Using 3D Mapping
M Meltsner1*, L Padilla2 , (1) Philips , Fitchburg, WI, (2) Virginia Commonwealth University, Richmond, VA
Presentations
TH-EF-FS1-2 (Thursday, August 3, 2017) 1:00 PM - 3:00 PM Room: Four Seasons 1
Purpose: To provide a simulation and treatment planning tool for external beam radiotherapy with which collisions can be detected and avoided with various in-room devices to potentially optimize treatment trajectories.
Methods: The Varian (Palo Alto, CA) TrueBeam linac, On-Board-Imaging (OBI) arms, and couch were mapped as detailed mesh models using the Structure Sensor (Occipital, Inc.) 3D mapping device attached to an iPad. The models were imported into the Philips (Fitchburg, WI) Pinnacle3 TPS using the MBS (Model Based Segmentation) package. Surface images acquired with AlignRT (VisionRT, London, UK) during the treatment of two patients were used for testing. These were loaded into Pinnacle3 as meshes in their corresponding treatment isocenter position. This was done to complement the limited external anatomy range included in the planning CT. A custom spatial detection algorithm analyzed collisions and minimum distances between the patient models/couch base/tabletop and the gantry head/OBI arms at each treatment beam angle. For VMAT treatments, a sampling of 5 degrees was analyzed.
Results: For the two patients analyzed, no collisions were detected. However, in several configurations, a clearance of under 2 cm (minimum 1.6 cm) was found, which may signify issues during treatment delivery due to inherent setup uncertainties related to arm position, for example.
Conclusion: The described tool provides both a visual and quantitative analysis for collision detection. The reduction of these issues at the time of simulation or treatment planning has the potential for significant improvements in clinical workflow by reducing setup time and improving patient safety. Further, the need for re-simulation and/or re-planning after determining issues at the time of patient setup can be avoided. Future work will utilize this tool in applications of beam angle optimization, couch and support device density modeling for improved dose accuracy, and 4Pi optimization and trajectory planning.
Funding Support, Disclosures, and Conflict of Interest: The presenting author is an employee of Philips Healthcare. The funding for this project was provided by Philips Healthcare.
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