SU‐E‐T‐591: Geometry‐Based Non‐Coplanar Beam Selection for Intensity Modulated Robotic Radiotherapy

Purpose: The MLC‐based CyberKnife system has been shown promising in treatment‐time reduction and plan‐quality improvement, comparing with the cone‐based models. The improved treatment efficiency can be attributed to the enhanced coverage of larger lesions and the capability of realizing high‐quality plans with less beams due to improved target conformity. The purpose of this study is to develop an efficient non‐coplanar beam selection program for CyberKnife‐based IMRT. Methods: The candidate beam‐set consists of 94 non‐coplanar beams, each defined by a vector connecting a CyberKnife node and a target point. The MLC leaves are configured to approximate a circle, whose radius R at 80cm SSD can be chosen such that the beam cross‐sections fully covers the PTV. We aim to choose an adequate number of beams that will cover as much body surface area as possible, considering the facts that to deliver a certain dose to the PTV, the larger the total covered surface area is, the lower the surface dose will be and that the more the beams are, the longer the treatment time will be. A beam‐selection program was developed based on the constraint on the body surface overlap. To evaluate its effectiveness, several IMRT plans with the selected beams for different treatment sites were generated using the Varian Eclipse treatment‐planning‐system. Results: Our program efficiently selected much less number of beams without compromising the desired surface coverage. For example, a set of 17 beams were selected for a pancreas case, covering 92.5% of the surface area covered by the 94 beams for R=5cm with 20% maximal overlap. The IMRT plans with the selected beams show superior quality with dramatically improved critical structure sparing, comparing with the clinically approved IMRT plans. Conclusion: One can efficiently select effective sets of non‐coplanar beams with our program, which allow the generation of high‐quality plans for MLC‐based robotic radiotherapy.