Statistical motion modeling of the thorax applied to respiratory gated FDG PET

Accurate attenuation correction in PET/CT relies upon an anatomically matched PET and CT. Respiratory motion introduces attenuation mismatch because the PET and CT scans are not necessarily temporally correlated. Acquiring a 4DCT scan in which each frame of the 4DCT is matched with a frame in a 4D gated PET is one strategy for obtaining temporally correlated PET and CT frames. In this paper we propose a statistical motion model as an alternative method to obtain correlated gated PET and CT frames. The model simulates the motion of all attenuating organs within the thorax. A PCA algorithm was used to extract components of motion from the gated CT scans of a cohort of 10 patients. The components were fitted to respiratory gated 4DPET frames to produce an artificial, yet realistic patient specific motion field. The first 5 components were fitted to large displacements in the 4DPET such that the model accounted for 95% of the movement in the most sensitive region of the PET camera. The fitted deformation field was then applied to the static spiral CT image to produce correlated frames. We propose this approach as the basis for a robust method of transforming a static spiral CT into correlated attenuation maps.