Feasibility of robotic stereotactic body radiotherapy of lung tumors with kilovoltage x‐ray beams

Purpose Robotic Stereotactic body radiation therapy (SBRT) for lung tumors is treatment modality that, for cases of inoperable lung tumors, has shown excellent treatment outcomes. The typical photon energy when delivering this type of treatments is 6 MeV. In this work, using Monte Carlo simulation and realistic patient models we evaluate the characteristics of the absorbed dose distributions that result when x‐ray beams of peak spectral energy of 220 keV are used to irradiate lung tumors assuming a robotic SBRT delivery mode. Methods Both male and female patient models, based on voxelized phantoms, are used in our study. Two types of tumors are considered: centrally and peripherally located lung tumors. The Monte Carlo code PENELOPE was used to calculate absorbed dose distributions for each of the beams used in the treatments which were assumed circular with diameter ranging from 1 cm–3 cm. An optimization algorithm was then applied to determine the appropriate beam weight necessary to accomplish the treatment objectives. The feasibility of our proposed approach is determined based on the guidelines set by Radiation Therapy Oncology Group (RTOG) 0813 for central tumors and RTOG 0915 for peripheral tumors. Results While the dose to the skin and bony structures is higher for the kilovoltage treatment, they are within the safe limits established by both RTOG 0813 and 0915. Conversely, the maximum dose to distant structures, such as the heart wall and esophagus, are up to 10 Gy higher for some of the megavoltage treatments but, again, within the limits recommended by the aforementioned clinical protocols. Conclusions We have shown that robotic SBRT of lung tumors using kilovoltage beams is feasible and that, therefore, it may represent an attractive alternative to the use of more expensive megavoltage linear accelerators, particularly in developing countries, where the high cost of such equipment poses an increasing economic burden.