Purpose: A major barrier to implementing advanced proton therapy delivery techniques, such as proton arc/4pi delivery is the unknown characteristics of the collision zones, i.e., the combinations of couch and gantry angles that result in a mechanical collision between the gantry and couch or patient. This study aims to develop a collision model for the determination of patient-specific collision zones to enable safe and deliverable noncoplanar proton therapy treatment planning. Methods: The detailed geometric parameters of the treatment machine including the nozzle, the snout, and the size and the location of the range shifter were measured from an IBA Proteus ONE machine with the gantry rotation capability. The coordinate of the patient body and the treatment couch was obtained from the patient dicom RT structure. The patient body surface was aligned virtually to the treatment machine model with the gantry and the couch can be rotated to test for a potential collision. The combination of the feasible gantry and couch angles was searched in the whole 4pi space. A user interface of the collision model was developed using the MATLAB platform and evaluated on 3 head and neck (HN) patients, 3 brain patients, and 3 abdomen patients to identify the potential collision zones. Results: With the Drs2iso, distance from the surface of the range shifter to isocenter, to be 40cm, the collision zones were (50.3±7.3)%, (45.6±9.1)%, and (42.7±1)% within the 4pi space for HN, brain, and abdomen patients, respectively. Increasing the Drs2iso to be 50cm, the corresponding collision zones reduced to be (34.4±7)%, (29.9±7.9)%, and (26.4±1.4)%Conclusion: A collision model was developed to determine patient-specific collision zones that enable the safe application of arc/4pi delivery. Further improvement of the model accuracy would be needed by including details of the robotic couch base and other directions of couch movement.
Chen S, Zhao L, Zheng W, Qin A, Deraniyagala R, Ding X. Development of a collision model for advanced proton treatment planning and delivery. Med Phys. 2022 Jun; 49(6):E861.