高精度重粒子線治療に向けた呼吸動態臓器の3次元動態定量化

A quantification technique of three-dimensional (3D) lung motion by means of tracking the anatomical features inside the lung using a set of sequential 3D-CT images (a 4D-CT image) is presented. Using lung CT images, lung volume modeling, lung vessel extraction and thinning are processed, and vessel bifurcations are derived as feature points. Such feature points are tracked in a series of 3D-CT images in which the lung is deformed. Consequently, 3D displacement vectors are obtained. The feature point tracking is carried out using point pattern matching with a probability relaxation method. The averaged error of the vectors is estimated to be ~0.2 mm for tentative lung CT images. Therefore, the accuracy is high enough for radiation therapy. This technique enables us to quantify the realistic 3D organ motion without any fiducial markers. It is applied to the quantification of tumor (target volume) deformation by gridding interpolation into all voxels. It is expected to be useful for dose estimation in mobile organs and 4D treatment planning for radiation therapy