S. Bryant, S. Xu, H. Bal, Y. Voronenko, V. Tur, J. Garcia, A. Da Silva, L. Shao, and G. Bal; RefleXion Medical, Inc., Hayward, CA
Purpose/Objective(s):Biology guided radiotherapy (BgRT) uses the real-time PET signal in conjunction with the linear accelerator (LINAC) to treat the target of interest. During treatment the limited time sampled (LTS) images are used to guide the radiation beam and deliver the prescribed dose to the target. In this work, we demonstrate the ability to simulate radiation treatment on volumes undergoing arbitrary motion trajectories.Materials/
Methods: We simulate BgRT delivery on a tumor following a programmed motion trajectory by utilizing the anatomically detailed xCAT digital phantom. This is done by using xCAT to generate high-quality PET images for a fixed set of tumor positions, each of which represents a static target in a different phase of motion. To mimic tumor motion during delivery, we generate a series of noisy LTS images from the PET images with the corresponding phase. This is done by forward-projecting the PET image, adding corrections to match our system, injecting noise to mimic LTS variability, and then back-projecting into PET space. To measure the efficacy of the simulated delivery, the dose is measured from both the patient point of view (PPOV), as well as the tumor point-of-view (TPOV), where the dose is translated into the frame of reference of the tumor, whose motion is known exactly. The TPOV dose measures the true radiation dose delivered to the tumor itself, rather than to the region the tumor moves through. Results: The BgRT protocol on medical technology company machines can be effectively simulated on artificial anatomical and motion data generated using the xCAT phantom. The dose delivered to the tumor itself can be measured in the TPOV, showing the radiation delivered to the actual tumor. Conclusion: Using this simulation process, we can test and refine novel radiotherapy techniques on different anatomical configurations undergoing arbitrary motion patterns without requesting additional patient data.
