4D medical image computing and visualization of lung tumor mobility in spatio-temporal CT image data.

Abstract

The development of 4D CT imaging has introduced the possibility of measuring breathing motion of tumors and inner organs. Conformal thoracic radiation therapy relies on a quantitative understanding of the position of lungs, lung tumors, and other organs during radiation delivery. Using 4D CT data sets, medical image computing and visualization methods were developed to visualize different aspects of lung and lung tumor mobility during the breathing cycle and to extract quantitative motion parameters. A non-linear registration method was applied to estimate the three-dimensional motion field and to compute 3D point trajectories. Specific visualization techniques were used to display the resulting motion field, the tumor's appearance probabilities during a breathing cycle as well as the volume covered by the moving tumor. Furthermore, trajectories of the tumor center-of-mass and organ specific landmarks were computed for the quantitative analysis of tumor and organ motion. The analysis of 4D data sets of seven patients showed that tumor mobility differs significantly between the patients depending on the individual breathing pattern and tumor location.