Fifty-seventh annual meeting of the American association of physicists in medicine
SU-F-BRD-11: A Virtual Simulator Designed for Collision Prevention in Proton Therapy
In proton therapy, collisions between patient and nozzle potentially occur in attaining minimal air gap due to the large nozzle structure. Thus, we developed software predicting the collisions of the nozzle and patient by simulating treatments.
3D modeling of a gantry inner-floor, nozzle and robotic-couch was done by using the SolidWorks based on the manufacturer's machine data. To obtain patient body information, a 3D-scanner was utilized to scan a patient right before CT scanning. From the acquired images, a 3D-image of the patient's body contour was reconstructed. The accuracy of the image was confirmed against the CT image for a humanoid phantom. The machine components and the virtual patient were combined on the treatment-room coordinate system, resulting in a virtual simulator. The simulator simulated the motion of its components such as rotation and translation of gantry, nozzle and couch, in real scale. Collision, if any, was examined both in static mode and dynamic mode. The static mode checks only at fixed positions of the machine's components while dynamic mode examines while one component is in motion. Collision was notified if any voxel of two components, for example a nozzle and a patient or couch, overlapped when calculating volume locations. The event and collision point are visualized and colliding volumes are reported.
All components were successfully assembled and the motions could be accurately controlled. The 3D-shape of a phantom agreed with CT images within a deviation of 2 mm. Collision situations can be simulated within minutes and the results are displayed and reported.
The developed software will be useful in improving patient safety and clinical efficiency for proton therapy.
This work was supported by the National Research Foundation of Korea funded by Ministry of Science, ICT & Future Planning (2012M3A9B6055201, 2013M2A2A7043507), and Samsung Medical Center grant (GFO1130081).