Local image descriptor-based searching framework of usable similar cases in a radiation treatment planning database for stereotactic body radiotherapy

Radiation treatment planning (RTP) of the stereotactic body radiotherapy (SBRT) was more complex compared with conventional radiotherapy because of using a number of beam directions. We reported that similar planning cases could be helpful for determination of beam directions for treatment planners, who have less experiences of SBRT. The aim of this study was to develop a framework of searching for usable similar cases to an unplanned case in a RTP database based on a local image descriptor. This proposed framework consists of two steps searching and rearrangement. In the first step, the RTP database was searched for 10 cases most similar to object cases based on the shape similarity of two-dimensional lung region at the isocenter plane. In the second step, the 5 most similar cases were selected by using geometric features related to the location, size and shape of the planning target volume, lung and spinal cord. In the third step, the selected 5 cases were rearranged by use of the Euclidean distance of a local image descriptor, which is a similarity index based on the magnitudes and orientations of image gradients within a region of interest around an isocenter. It was assumed that the local image descriptor represents the information around lung tumors related to treatment planning. The cases, which were selected as cases most similar to test cases by the proposed method, were more resemble in terms of the tumor location than those selected by a conventional method. For evaluation of the proposed method, we applied a similar-cases-based beam arrangement method developed in the previous study to the similar cases selected by the proposed method based on a linear registration. The proposed method has the potential to suggest the superior beam-arrangements from the treatment point of view.