Room: Karl Dean Ballroom A1
Purpose: To examine the efficacy of patient-specific collision modeling using novel wide-angle 3D cameras in a CT room.
Methods: Two pairs of wall-mounted 3D stereo cameras were utilized to capture the whole-body surfaces of an anthropomorphic phantom, and two human subjects immediately after CT simulation without shifting the subject to ensure setup consistent to that of treatment. The acquired surfaces were registered with the CT and then positioned on a computer-aided design model of a commercial linear accelerator system to create a detailed virtual geometrical collision model. The geometrical accuracy of the 3D cameras were validated by scanning a rigid cubical phantom with known dimensions. With the virtual model incorporating each obtained 3D surface, the minimum achievable source-to-target distances (STD) for treatments to the head, lung, abdomen, and pelvis were calculated for 1162 candidate beam angles evenly distributed throughout the 4Ï€ steradian. Minimum STD was also compared between the whole-body surface and CT body contour alone.
Results: Complete and visually accurate 3D surfaces were instantaneously acquired. Images of the reference cubical phantom showed under 2mm (<1.5%) discrepancy in all three dimensions. Acquired surfaces and the CT body contours showed good agreement. Large differences in number of beams deliverable with standard isocentric setup (STDâ‰¤100cm) and extended STD (STD>100cm) of up to 170 and 158 among all treatment sites between the phantom and liver patient surface due to the difference in positions, postures and body shapes. Comparison between full-body modeling and CT body contour alone also showed isocentrically deliverable beam angle difference of 118 and 157 for the cranial and liver patients, respectively. This result demonstrates the importance of individualized full-body patient collision modeling, particularly for treatments with non-coplanar geometries or largely off-centered isocenters.
Conclusion: the efficacy of and need for efficient full-body surface acquisition for patient-specific collision modeling have been demonstrated. â€ƒ
Funding Support, Disclosures, and Conflict of Interest: DE-SC0017687 DE-SC0017057 NIH R44CA183390 NIH R43CA183390 NIH R01CA188300 NIH R21CA144063 VisionRT